Given a directed graph of nodes and edges connecting them, a common problem is to find the shortest path between any two nodes. Here we show that the shortest path distances can be found by a simple matrix inversion: if the edges are given by the adjacency matrix Aij, then with a suitably small value of γ, the shortest path distances are Dij = ceil(logγ[(I-γA)\u207b¹]ij).We derive several graph-theoretic bounds on the value of γ and explore its useful range with numerics on different graph types. Even when the distance function is not globally accurate across the entire graph, it still works locally to instruct pursuit of the shortest path. In this mode, it also extends to weighted graphs with positive edge weights. For a wide range of dense graphs, this distance function is computationally faster than the best available alternative. Finally, we show that this method leads naturally to a neural network solution of the all-pairs-shortest-path problem.
", "doi": "10.1162/neco_a_01716", "issn": "0899-7667", "publisher": "MIT Press", "publication": "Neural Computation", "publication_date": "2024-12", "series_number": "12", "volume": "36", "issue": "12", "pages": "2710-2733" }, { "id": "authors:8y0gr-dwq36", "collection": "authors", "collection_id": "8y0gr-dwq36", "cite_using_url": "https://authors.library.caltech.edu/records/8y0gr-dwq36", "type": "article", "title": "Endotaxis: A neuromorphic algorithm for mapping, goal-learning, navigation, and patrolling", "author": [ { "family_name": "Zhang", "given_name": "Tony", "orcid": "0000-0002-5198-499X", "clpid": "Zhang-Tony" }, { "family_name": "Rosenberg", "given_name": "Matthew", "clpid": "Rosenberg-Matthew" }, { "family_name": "Jing", "given_name": "Zeyu", "orcid": "0000-0002-4741-4177", "clpid": "Jing-Zeyu" }, { "family_name": "Perona", "given_name": "Pietro", "orcid": "0000-0002-7583-5809", "clpid": "Perona-P" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "An animal entering a new environment typically faces three challenges: explore the space for resources, memorize their locations, and navigate towards those targets as needed. Here we propose a neural algorithm that can solve all these problems and operates reliably in diverse and complex environments. At its core, the mechanism makes use of a behavioral module common to all motile animals, namely the ability to follow an odor to its source. We show how the brain can learn to generate internal “virtual odors” that guide the animal to any location of interest. This endotaxis algorithm can be implemented with a simple 3-layer neural circuit using only biologically realistic structures and learning rules. Several neural components of this scheme are found in brains from insects to humans. Nature may have evolved a general mechanism for search and navigation on the ancient backbone of chemotaxis.
\nPublished by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article's title, journal citation, and DOI. Open access publication funded by the Max Planck Society.
", "doi": "10.1103/physrevresearch.5.043205", "issn": "2643-1564", "publisher": "American Physical Society", "publication": "Physical Review Research", "publication_date": "2023-12", "series_number": "4", "volume": "5", "issue": "4", "pages": "043205" }, { "id": "authors:0wd1r-y8426", "collection": "authors", "collection_id": "0wd1r-y8426", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20230510-345799900.1", "type": "article", "title": "Functional cell types in the mouse superior colliculus", "author": [ { "family_name": "Li", "given_name": "Ya-tang", "orcid": "0000-0003-2763-1534", "clpid": "Li-Ya-tang" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "The superior colliculus (SC) represents a major visual processing station in the mammalian brain that receives input from many types of retinal ganglion cells (RGCs). How many parallel channels exist in the SC, and what information does each encode? Here, we recorded from mouse superficial SC neurons under a battery of visual stimuli including those used for classification of RGCs. An unsupervised clustering algorithm identified 24 functional types based on their visual responses. They fall into two groups: one that responds similarly to RGCs and another with more diverse and specialized stimulus selectivity. The second group is dominant at greater depths, consistent with a vertical progression of signal processing in the SC. Cells of the same functional type tend to cluster near each other in anatomical space. Compared to the retina, the visual representation in the SC has lower dimensionality, consistent with a sifting process along the visual pathway.", "doi": "10.7554/elife.82367", "pmcid": "PMC10121220", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2023-04-19", "volume": "12", "pages": "Art. No. e82367" }, { "id": "authors:pm0hw-3cn95", "collection": "authors", "collection_id": "pm0hw-3cn95", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20220607-425325000", "type": "article", "title": "Learning, fast and slow", "author": [ { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Animals can learn efficiently from a single experience and change their future behavior in response. However, in other instances, animals learn very slowly, requiring thousands of experiences. Here, I survey tasks involving fast and slow learning and consider some hypotheses for what differentiates the underlying neural mechanisms. It has been proposed that fast learning relies on neural representations that favor efficient Hebbian modification of synapses. These efficient representations may be encoded in the genome, resulting in a repertoire of fast learning that differs across species. Alternatively, the required neural representations may be acquired from experience through a slow process of unsupervised learning from the environment.", "doi": "10.1016/j.conb.2022.102555", "issn": "0959-4388", "publisher": "Elsevier", "publication": "Current Opinion in Neurobiology", "publication_date": "2022-08", "volume": "75", "pages": "Art. No. 102555" }, { "id": "authors:zwfrv-rbn84", "collection": "authors", "collection_id": "zwfrv-rbn84", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20191126-145230904", "type": "article", "title": "Electrode pooling can boost the yield of extracellular recordings with switchable silicon probes", "author": [ { "family_name": "Lee", "given_name": "Kyu Hyun", "orcid": "0000-0001-6483-9444", "clpid": "Lee-Kyu-Hyun" }, { "family_name": "Ni", "given_name": "Yu-Li", "orcid": "0000-0003-1600-9854", "clpid": "Ni-Yu-Li" }, { "family_name": "Colonell", "given_name": "Jennifer", "clpid": "Colonell-Jennifer" }, { "family_name": "Karsh", "given_name": "Bill", "clpid": "Karsh-Bill" }, { "family_name": "Putzeys", "given_name": "Jan", "orcid": "0000-0001-8834-5852", "clpid": "Putzeys-Jan" }, { "family_name": "Pachitariu", "given_name": "Marius", "orcid": "0000-0001-7106-814X", "clpid": "Pachitariu-Marius" }, { "family_name": "Harris", "given_name": "Timothy D.", "orcid": "0000-0002-6289-4439", "clpid": "Harris-Timothy-D" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "State-of-the-art silicon probes for electrical recording from neurons have thousands of recording sites. However, due to volume limitations there are typically many fewer wires carrying signals off the probe, which restricts the number of channels that can be recorded simultaneously. To overcome this fundamental constraint, we propose a method called electrode pooling that uses a single wire to serve many recording sites through a set of controllable switches. Here we present the framework behind this method and an experimental strategy to support it. We then demonstrate its feasibility by implementing electrode pooling on the Neuropixels 1.0 electrode array and characterizing its effect on signal and noise. Finally we use simulations to explore the conditions under which electrode pooling saves wires without compromising the content of the recordings. We make recommendations on the design of future devices to take advantage of this strategy.", "doi": "10.1038/s41467-021-25443-4", "issn": "2041-1723", "publisher": "Nature Publishing Group", "publication": "Nature Communications", "publication_date": "2021-09-02", "volume": "12", "pages": "Art. No. 5245" }, { "id": "authors:85fpv-smk36", "collection": "authors", "collection_id": "85fpv-smk36", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210119-130811113", "type": "article", "title": "Mice in a labyrinth show rapid learning, sudden insight, and efficient exploration", "author": [ { "family_name": "Rosenberg", "given_name": "Matthew", "clpid": "Rosenberg-Matthew" }, { "family_name": "Zhang", "given_name": "Tony", "orcid": "0000-0002-5198-499X", "clpid": "Zhang-Tony" }, { "family_name": "Perona", "given_name": "Pietro", "orcid": "0000-0002-7583-5809", "clpid": "Perona-P" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Animals learn certain complex tasks remarkably fast, sometimes after a single experience. What behavioral algorithms support this efficiency? Many contemporary studies based on two-alternative-forced-choice (2AFC) tasks observe only slow or incomplete learning. As an alternative, we study the unconstrained behavior of mice in a complex labyrinth and measure the dynamics of learning and the behaviors that enable it. A mouse in the labyrinth makes ~2000 navigation decisions per hour. The animal explores the maze, quickly discovers the location of a reward, and executes correct 10-bit choices after only 10 reward experiences \u2014 a learning rate 1000-fold higher than in 2AFC experiments. Many mice improve discontinuously from one minute to the next, suggesting moments of sudden insight about the structure of the labyrinth. The underlying search algorithm does not require a global memory of places visited and is largely explained by purely local turning rules.", "doi": "10.7554/eLife.66175", "pmcid": "PMC8294850", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2021-07-01", "volume": "10", "pages": "Art. No. e66175" }, { "id": "authors:dkw5a-pk181", "collection": "authors", "collection_id": "dkw5a-pk181", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20210225-132711583", "type": "article", "title": "Learning by Turning: Neural Architecture Aware Optimisation", "author": [ { "family_name": "Liu", "given_name": "Yang", "clpid": "Liu-Yang-Abacus" }, { "family_name": "Bernstein", "given_name": "Jeremy", "orcid": "0000-0001-9110-7476", "clpid": "Bernstein-Jeremy-D" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Yue", "given_name": "Yisong", "orcid": "0000-0001-9127-1989", "clpid": "Yue-Yisong" } ], "abstract": "Descent methods for deep networks are notoriously capricious: they require careful tuning of step size, momentum and weight decay, and which method will work best on a new benchmark is a priori unclear. To address this problem, this paper conducts a combined study of neural architecture and optimisation, leading to a new optimiser called Nero: the neuronal rotator. Nero trains reliably without momentum or weight decay, works in situations where Adam and SGD fail, and requires little to no learning rate tuning. Also, Nero's memory footprint is square root that of Adam or LAMB. Nero combines two ideas: (1) projected gradient descent over the space of balanced networks; (2) neuron-specific updates, where the step size sets the angle through which each neuron's hyperplane turns. The paper concludes by discussing how this geometric connection between architecture and optimisation may impact theories of generalisation in deep learning.", "doi": "10.48550/arXiv.2102.07227", "issn": "2640-3498", "publisher": "ML Research Press", "publication": "Proceedings of Machine Learning Research", "publication_date": "2021-07", "volume": "139", "pages": "6748-6758" }, { "id": "authors:pkq4n-ytp93", "collection": "authors", "collection_id": "pkq4n-ytp93", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20191031-141639740", "type": "article", "title": "Functional Architecture of Motion Direction in the Mouse Superior Colliculus", "author": [ { "family_name": "Li", "given_name": "Ya-tang", "orcid": "0000-0003-2763-1534", "clpid": "Li-Ya-tang" }, { "family_name": "Turan", "given_name": "Zeynep", "clpid": "Turan-Zeynep" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Motion vision is important in guiding animal behavior. Both the retina and the visual cortex process object motion in largely unbiased fashion: all directions are represented at all locations in the visual field. We investigate motion processing in the superior colliculus of the awake mouse by optically recording neural responses across both hemispheres. Within the retinotopic map, one finds large regions of \u223c500 \u03bcm size where neurons prefer the same direction of motion. This preference is maintained in depth to \u223c350 \u03bcm. The scale of these patches, \u223c30 degrees of visual angle, is much coarser than the animal's visual resolution (\u223c2 degrees). A global map of motion direction shows approximate symmetry between the left and right hemispheres and a net bias for upward-nasal motion in the upper visual field.", "doi": "10.1016/j.cub.2020.06.023", "pmcid": "PMC8221388", "issn": "0960-9822", "publisher": "Cell Press", "publication": "Current Biology", "publication_date": "2020-09-07", "series_number": "17", "volume": "30", "issue": "17", "pages": "3304-3315" }, { "id": "authors:wtr1r-4ds33", "collection": "authors", "collection_id": "wtr1r-4ds33", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20200420-134619006", "type": "article", "title": "The sifting of visual information in the superior colliculus", "author": [ { "family_name": "Lee", "given_name": "Kyu Hyung", "clpid": "Lee-Kyu-Hyung" }, { "family_name": "Tran", "given_name": "Alvita", "clpid": "Tran-Alvita" }, { "family_name": "Turan", "given_name": "Zeynep", "clpid": "Turan-Z" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Much of the early visual system is devoted to sifting the visual scene for the few bits of behaviorally relevant information. In the visual cortex of mammals, a hierarchical system of brain areas leads eventually to the selective encoding of important features, like faces and objects. Here, we report that a similar process occurs in the other major visual pathway, the superior colliculus. We investigate the visual response properties of collicular neurons in the awake mouse with large-scale electrophysiology. Compared to the superficial collicular layers, neuronal responses in the deeper layers become more selective for behaviorally relevant stimuli; more invariant to location of stimuli in the visual field; and more suppressed by repeated occurrence of a stimulus in the same location. The memory of familiar stimuli persists in complete absence of the visual cortex. Models of these neural computations lead to specific predictions for neural circuitry in the superior colliculus.", "doi": "10.7554/elife.50678", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2020-04-14", "volume": "9", "pages": "Art. No. e50678" }, { "id": "authors:k0ce8-q3067", "collection": "authors", "collection_id": "k0ce8-q3067", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20191118-080725855", "type": "article", "title": "Functional diversity among sensory neurons from efficient coding principles", "author": [ { "family_name": "Gjorgjieva", "given_name": "Julijana", "orcid": "0000-0001-7118-4079", "clpid": "Gjorgjieva-J" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Sompolinsky", "given_name": "Haim", "clpid": "Sompolinsky-H" } ], "abstract": "In many sensory systems the neural signal is coded by the coordinated response of heterogeneous populations of neurons. What computational benefit does this diversity confer on information processing? We derive an efficient coding framework assuming that neurons have evolved to communicate signals optimally given natural stimulus statistics and metabolic constraints. Incorporating nonlinearities and realistic noise, we study optimal population coding of the same sensory variable using two measures: maximizing the mutual information between stimuli and responses, and minimizing the error incurred by the optimal linear decoder of responses. Our theory is applied to a commonly observed splitting of sensory neurons into ON and OFF that signal stimulus increases or decreases, and to populations of monotonically increasing responses of the same type, ON. Depending on the optimality measure, we make different predictions about how to optimally split a population into ON and OFF, and how to allocate the firing thresholds of individual neurons given realistic stimulus distributions and noise, which accord with certain biases observed experimentally.", "doi": "10.1371/journal.pcbi.1007476", "pmcid": "PMC6890262", "issn": "1553-7358", "publisher": "Public Library of Science", "publication": "PLOS Computational Biology", "publication_date": "2019-11-14", "series_number": "11", "volume": "15", "issue": "11", "pages": "Art. No. e1007476" }, { "id": "authors:2ftqt-zd927", "collection": "authors", "collection_id": "2ftqt-zd927", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20181030-140944700", "type": "article", "title": "Augmented Reality Powers a Cognitive Assistant for the Blind", "author": [ { "family_name": "Liu", "given_name": "Yang", "orcid": "0000-0002-8155-9134", "clpid": "Liu-Yang" }, { "family_name": "Stiles", "given_name": "Noelle R. B.", "orcid": "0000-0002-7352-5815", "clpid": "Stiles-N-R-B" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "To restore vision for the blind, several prosthetic approaches have been explored that convey raw images to the brain. So far, these schemes all suffer from a lack of bandwidth. An alternate approach would restore vision at the cognitive level, bypassing the need to convey sensory data. A wearable computer captures video and other data, extracts important scene knowledge, and conveys that to the user in compact form. Here, we implement an intuitive user interface for such a device using augmented reality: each object in the environment has a voice and communicates with the user on command. With minimal training, this system supports many aspects of visual cognition: obstacle avoidance, scene understanding, formation and recall of spatial memories, navigation. Blind subjects can traverse an unfamiliar multi-story building on their first attempt. To spur further development in this domain, we developed an open-source environment for standardized benchmarking of visual assistive devices.", "doi": "10.7554/eLife.37841.001", "pmcid": "PMC6257813", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2018-11-28", "volume": "7", "pages": "Art. No. e37841" }, { "id": "authors:0ma3g-zry11", "collection": "authors", "collection_id": "0ma3g-zry11", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170807-132930354", "type": "article", "title": "Four alpha ganglion cell types in mouse retina: Function, structure, and molecular signatures", "author": [ { "family_name": "Barnes", "given_name": "Steven", "clpid": "Barnes-S" }, { "family_name": "Krieger", "given_name": "Brenna", "clpid": "Krieger-B" }, { "family_name": "Qiao", "given_name": "Mu", "orcid": "0000-0001-7309-4237", "clpid": "Qiao-Mu" }, { "family_name": "Rousso", "given_name": "David L.", "clpid": "Rousso-D-L" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "The retina communicates with the brain using \u226530 parallel channels, each carried by axons of distinct types of retinal ganglion cells. In every mammalian retina one finds so-called \"alpha\" ganglion cells (\u03b1RGCs), identified by their large cell bodies, stout axons, wide and mono-stratified dendritic fields, and high levels of neurofilament protein. In the mouse, three \u03b1RGC types have been described based on responses to light steps: On-sustained, Off-sustained, and Off-transient. Here we employed a transgenic mouse line that labels \u03b1RGCs in the live retina, allowing systematic targeted recordings. We characterize the three known types and identify a fourth, with On-transient responses. All four \u03b1RGC types share basic aspects of visual signaling, including a large receptive field center, a weak antagonistic surround, and absence of any direction selectivity. They also share a distinctive waveform of the action potential, faster than that of other RGC types. Morphologically, they differ in the level of dendritic stratification within the IPL, which accounts for their response properties. Molecularly, each type has a distinct signature. A comparison across mammals suggests a common theme, in which four large-bodied ganglion cell types split the visual signal into four channels arranged symmetrically with respect to polarity and kinetics.", "doi": "10.1371/journal.pone.0180091", "pmcid": "PMC5533432", "issn": "1932-6203", "publisher": "Public Library of Science", "publication": "PLOS ONE", "publication_date": "2017-07-28", "series_number": "7", "volume": "12", "issue": "7", "pages": "Art. No. e0180091" }, { "id": "authors:1g4b3-nw108", "collection": "authors", "collection_id": "1g4b3-nw108", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170117-132604622", "type": "article", "title": "Neural Circuit Inference from Function to Structure", "author": [ { "family_name": "Real", "given_name": "Esteban", "clpid": "Real-E" }, { "family_name": "Asari", "given_name": "Hiroki", "clpid": "Asari-Hiroki" }, { "family_name": "Gollisch", "given_name": "Tim", "clpid": "Gollisch-T" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Advances in technology are opening new windows on the structural connectivity and functional dynamics of brain circuits. Quantitative frameworks are needed that integrate these data from anatomy and physiology. Here, we present a modeling approach that creates such a link. The goal is to infer the structure of a neural circuit from sparse neural recordings, using partial knowledge of its anatomy as a regularizing constraint. We recorded visual responses from the output neurons of the retina, the ganglion cells. We then generated a systematic sequence of circuit models that represents retinal neurons and connections and fitted them to the experimental data. The optimal models faithfully recapitulated the ganglion cell outputs. More importantly, they made predictions about dynamics and connectivity among unobserved neurons internal to the circuit, and these were subsequently confirmed by experiment. This circuit inference framework promises to facilitate the integration and understanding of big data in neuroscience.", "doi": "10.1016/j.cub.2016.11.040", "issn": "0960-9822", "publisher": "Cell Press", "publication": "Current Biology", "publication_date": "2017-01-23", "series_number": "2", "volume": "27", "issue": "2", "pages": "189-198" }, { "id": "authors:msp84-d8463", "collection": "authors", "collection_id": "msp84-d8463", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160822-141245894", "type": "article", "title": "Physical limits to magnetogenetics", "author": [ { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "This is an analysis of how magnetic fields affect biological molecules and cells. It was prompted by a series of prominent reports regarding magnetism in biological systems. The first claims to have identified a protein complex that acts like a compass needle to guide magnetic orientation in animals (Qin et al., 2016). Two other articles report magnetic control of membrane conductance by attaching ferritin to an ion channel protein and then tugging the ferritin or heating it with a magnetic field (Stanley et al., 2015; Wheeler et al., 2016). Here I argue that these claims conflict with basic laws of physics. The discrepancies are large: from 5 to 10 log units. If the reported phenomena do in fact occur, they must have causes entirely different from the ones proposed by the authors. The paramagnetic nature of protein complexes is found to seriously limit their utility for engineering magnetically sensitive cells.", "doi": "10.7554/eLife.17210", "pmcid": "PMC5016093", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2016-08-16", "volume": "5", "pages": "Art. No. 17210" }, { "id": "authors:7pc1r-9ng53", "collection": "authors", "collection_id": "7pc1r-9ng53", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20160714-081242660", "type": "article", "title": "Reconstruction of genetically identified neurons imaged by serial-section electron microscopy", "author": [ { "family_name": "Joesch", "given_name": "Maximilian", "clpid": "Joesch-M" }, { "family_name": "Mankus", "given_name": "David", "clpid": "Mankus-D" }, { "family_name": "Yamagata", "given_name": "Masahito", "clpid": "Yamagata-M" }, { "family_name": "Shahbazi", "given_name": "Ali", "clpid": "Shahbazi-A" }, { "family_name": "Shalek", "given_name": "Richard", "clpid": "Shalek-R" }, { "family_name": "Suissa-Peleg", "given_name": "Adi", "clpid": "Suissa-Peleg-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Lichtman", "given_name": "Jeff W.", "clpid": "Lichtman-J-W" }, { "family_name": "Scheirer", "given_name": "Walter J", "clpid": "Scheirer-W-J" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" } ], "abstract": "Resolving patterns of synaptic connectivity in neural circuits currently requires serial section electron microscopy. However, complete circuit reconstruction is prohibitively slow and may not be necessary for many purposes such as comparing neuronal structure and connectivity among multiple animals. Here, we present an alternative strategy, targeted reconstruction of specific neuronal types. We used viral vectors to deliver peroxidase derivatives, which catalyze production of an electron-dense tracer, to genetically identified neurons, and developed a protocol that enhances the electron-density of the labeled cells and while retaining quality of the ultrastructure. The high contrast of the marked neurons enabled two innovations that dramatically speed data acquisition: targeted high-resolution reimaging of regions selected from rapidly-acquired lower resolution reconstruction, and an unsupervised segmentation algorithm. This pipeline reduces imaging and reconstruction times by at least two orders of magnitude, facilitating directed inquiry of circuit motifs.", "doi": "10.7554/eLife.15015", "pmcid": "PMC4959841", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2016-07-07", "volume": "5", "pages": "Art. NO. e15015" }, { "id": "authors:7hj7a-7ng44", "collection": "authors", "collection_id": "7hj7a-7ng44", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20151223-110847966", "type": "article", "title": "A neuronal circuit for colour vision based on rod\u2013cone opponency", "author": [ { "family_name": "Joesch", "given_name": "Maximilian", "clpid": "Joesch-M" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "In bright light, cone-photoreceptors are active and colour vision derives from a comparison of signals in cones with different visual pigments. This comparison begins in the retina, where certain retinal ganglion cells have 'colour-opponent' visual responses\u2014excited by light of one colour and suppressed by another colour. In dim light, rod-photoreceptors are active, but colour vision is impossible because they all use the same visual pigment. Instead, the rod signals are thought to splice into retinal circuits at various points, in synergy with the cone signals. Here we report a new circuit for colour vision that challenges these expectations. A genetically identified type of mouse retinal ganglion cell called JAMB (J-RGC), was found to have colour-opponent responses, OFF to ultraviolet (UV) light and ON to green light. Although the mouse retina contains a green-sensitive cone, the ON response instead originates in rods. Rods and cones both contribute to the response over several decades of light intensity. Remarkably, the rod signal in this circuit is antagonistic to that from cones. For rodents, this UV-green channel may play a role in social communication, as suggested by spectral measurements from the environment. In the human retina, all of the components for this circuit exist as well, and its function can explain certain experiences of colour in dim lights, such as a 'blue shift' in twilight. The discovery of this genetically defined pathway will enable new targeted studies of colour processing in the brain.", "doi": "10.1038/nature17158", "issn": "0028-0836", "publisher": "Nature Publishing Group", "publication": "Nature", "publication_date": "2016-04-14", "series_number": "7598", "volume": "532", "issue": "7598", "pages": "236-239" }, { "id": "authors:sbtd2-xt236", "collection": "authors", "collection_id": "sbtd2-xt236", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20151201-102717877", "type": "article", "title": "Neurodata Without Borders: Creating a Common Data Format for Neurophysiology", "author": [ { "family_name": "Teeters", "given_name": "Jeffery L.", "clpid": "Teeters-J-L" }, { "family_name": "Godfrey", "given_name": "Keith", "clpid": "Godfrey-K" }, { "family_name": "Young", "given_name": "Rob", "clpid": "Young-R" }, { "family_name": "Dang", "given_name": "Chinh", "clpid": "Dang-C" }, { "family_name": "Friedsam", "given_name": "Claudia", "clpid": "Friedsam-C" }, { "family_name": "Wark", "given_name": "Barry", "clpid": "Wark-B" }, { "family_name": "Asari", "given_name": "Hiroki", "clpid": "Asari-H" }, { "family_name": "Peron", "given_name": "Simon", "clpid": "Peron-S" }, { "family_name": "Li", "given_name": "Nuo", "clpid": "Li-Nuo" }, { "family_name": "Peyrache", "given_name": "Adrien", "clpid": "Peyrache-A" }, { "family_name": "Denisov", "given_name": "Gennady", "clpid": "Denisov-G" }, { "family_name": "Siegle", "given_name": "Joshua H.", "clpid": "Siegle-J-H" }, { "family_name": "Olsen", "given_name": "Shawn R.", "clpid": "Olsen-S-R" }, { "family_name": "Martin", "given_name": "Christopher", "orcid": "0000-0002-8078-8859", "clpid": "Martin-Christopher-Kavli" }, { "family_name": "Chun", "given_name": "Miyoung", "clpid": "Chun-Miyoung" }, { "family_name": "Tripathy", "given_name": "Shreejoy", "clpid": "Tripathy-S" }, { "family_name": "Blanche", "given_name": "Timothy J.", "clpid": "Blanche-T-J" }, { "family_name": "Harris", "given_name": "Kenneth", "clpid": "Harris-K" }, { "family_name": "Buzs\u00e1ki", "given_name": "Gy\u00f6rgy", "clpid": "Buzs\u00e1ki-G" }, { "family_name": "Koch", "given_name": "Christof", "orcid": "0000-0001-6482-8067", "clpid": "Koch-C" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Svoboda", "given_name": "Karel", "clpid": "Svoboda-K" }, { "family_name": "Sommer", "given_name": "Friedrich T.", "clpid": "Sommer-F-T" } ], "abstract": "The Neurodata Without Borders (NWB) initiative promotes data standardization in neuroscience to increase research reproducibility and opportunities. In the first NWB pilot project, neurophysiologists and software developers produced a common data format for recordings and metadata of cellular electrophysiology and optical imaging experiments. The format specification, application programming interfaces, and sample datasets have been released.", "doi": "10.1016/j.neuron.2015.10.025", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2015-11-18", "series_number": "4", "volume": "88", "issue": "4", "pages": "629-634" }, { "id": "authors:18scf-1be84", "collection": "authors", "collection_id": "18scf-1be84", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20150707-114340163", "type": "article", "title": "On the dimensionality of odor space", "author": [ { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "There is great interest in understanding human olfactory experience from a principled and quantitative standpoint. The comparison is often made to color vision, where a solid framework with a three-dimensional perceptual space enabled a rigorous search for the underlying neural pathways, and the technological development of lifelike color display devices. A recent, highly publicized report claims that humans can discriminate at least 1 trillion odors, which exceeds by many orders of magnitude the known capabilities of color discrimination. This claim is wrong. I show that the failure lies in the mathematical method used to infer the size of odor space from a limited experimental sample. Further analysis focuses on establishing how many dimensions the perceptual odor space has. I explore the dimensionality of physical, neural, and perceptual spaces, drawing on results from bacteria to humans, and propose some experimental approaches to better estimate the number of discriminable odors.", "doi": "10.7554/eLife.07865", "pmcid": "PMC4491593", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2015-07-07", "pages": "Art. No. e07865" }, { "id": "authors:yv8jn-vp450", "collection": "authors", "collection_id": "yv8jn-vp450", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20141118-102008104", "type": "article", "title": "Orientation columns in the mouse superior colliculus", "author": [ { "family_name": "Feinberg", "given_name": "Evan H.", "clpid": "Feinberg-E-H" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "More than twenty types of retinal ganglion cells conduct visual information from the eye to the rest of the brain. Each retinal ganglion cell type tessellates the retina in a regular mosaic, so that every point in visual space is processed for visual primitives such as contrast and motion. This information flows to two principal brain centres: the visual cortex and the superior colliculus. The superior colliculus plays an evolutionarily conserved role in visual behaviours, but its functional architecture is poorly understood. Here we report on population recordings of visual responses from neurons in the mouse superior colliculus. Many neurons respond preferentially to lines of a certain orientation or movement axis. We show that cells with similar orientation preferences form large patches that span the vertical thickness of the retinorecipient layers. This organization is strikingly different from the randomly interspersed orientation preferences in the mouse's visual cortex; instead, it resembles the orientation columns observed in the visual cortices of large mammals. Notably, adjacent superior colliculus orientation columns have only limited receptive field overlap. This is in contrast to the organization of visual cortex, where each point in the visual field activates neurons with all preferred orientations. Instead, the superior colliculus favours specific contour orientations within ~30\u00b0 regions of the visual field, a finding with implications for behavioural responses mediated by this brain centre.", "doi": "10.1038/nature14103", "issn": "0028-0836", "publisher": "Nature Publishing Group", "publication": "Nature", "publication_date": "2015-03-12", "series_number": "7542", "volume": "519", "issue": "7542", "pages": "229-232" }, { "id": "authors:av68f-p9n77", "collection": "authors", "collection_id": "av68f-p9n77", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20150325-100540825", "type": "article", "title": "Ventromedial hypothalamic neurons control a defensive emotion state", "author": [ { "family_name": "Kunwar", "given_name": "Prabhat S.", "clpid": "Kunwar-P-S" }, { "family_name": "Zelikowsky", "given_name": "Moriel", "clpid": "Zelikowski-M" }, { "family_name": "Remedios", "given_name": "Ryan", "clpid": "Remedios-R" }, { "family_name": "Cai", "given_name": "Haijiang", "clpid": "Cai-Haijiang" }, { "family_name": "Yilmaz", "given_name": "Melis", "clpid": "Yilmaz-M" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Anderson", "given_name": "David J.", "orcid": "0000-0001-6175-3872", "clpid": "Anderson-D-J" } ], "abstract": "Defensive behaviors reflect underlying emotion states, such as fear. The hypothalamus plays a role in such behaviors, but prevailing textbook views depict it as an effector of upstream emotion centers, such as the amygdala, rather than as an emotion center itself. We used optogenetic manipulations to probe the function of a specific hypothalamic cell type that mediates innate defensive responses. These neurons are sufficient to drive multiple defensive actions, and required for defensive behaviors in diverse contexts. The behavioral consequences of activating these neurons, moreover, exhibit properties characteristic of emotion states in general, including scalability, (negative) valence, generalization and persistence. Importantly, these neurons can also condition learned defensive behavior, further refuting long-standing claims that the hypothalamus is unable to support emotional learning and therefore is not an emotion center. These data indicate that the hypothalamus plays an integral role to instantiate emotion states, and is not simply a passive effector of upstream emotion centers.", "doi": "10.7554/eLife.06633", "pmcid": "PMC4379496", "issn": "2050-084X", "publisher": "eLife Sciences Publications", "publication": "eLife", "publication_date": "2015-03-06", "volume": "4", "pages": "Art. No. e06633" }, { "id": "authors:h1qyg-dt397", "collection": "authors", "collection_id": "h1qyg-dt397", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20140911-151331633", "type": "article", "title": "Benefits of Pathway Splitting in Sensory Coding", "author": [ { "family_name": "Gjorgjieva", "given_name": "Julijana", "orcid": "0000-0001-7118-4079", "clpid": "Gjorgjieva-J" }, { "family_name": "Sompolinsky", "given_name": "Haim", "clpid": "Sompolinsky-H" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "In many sensory systems, the neural signal splits into multiple parallel pathways. For example, in the mammalian retina, \u223c20 types of retinal ganglion cells transmit information about the visual scene to the brain. The purpose of this profuse and early pathway splitting remains unknown. We examine a common instance of splitting into ON and OFF neurons excited by increments and decrements of light intensity in the visual scene, respectively. We test the hypothesis that pathway splitting enables more efficient encoding of sensory stimuli. Specifically, we compare a model system with an ON and an OFF neuron to one with two ON neurons. Surprisingly, the optimal ON\u2013OFF system transmits the same information as the optimal ON\u2013ON system, if one constrains the maximal firing rate of the neurons. However, the ON\u2013OFF system uses fewer spikes on average to transmit this information. This superiority of the ON\u2013OFF system is also observed when the two systems are optimized while constraining their mean firing rate. The efficiency gain for the ON\u2013OFF split is comparable with that derived from decorrelation, a well known processing strategy of early sensory systems. The gain can be orders of magnitude larger when the ecologically important stimuli are rare but large events of either polarity. The ON\u2013OFF system also provides a better code for extracting information by a linear downstream decoder. The results suggest that the evolution of ON\u2013OFF diversification in sensory systems may be driven by the benefits of lowering average metabolic cost, especially in a world in which the relevant stimuli are sparse.", "doi": "10.1523/JNEUROSCI.1032-14.2014", "pmcid": "PMC4152610", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2014-09-03", "series_number": "36", "volume": "34", "issue": "36", "pages": "12127-12144" }, { "id": "authors:qx078-fk246", "collection": "authors", "collection_id": "qx078-fk246", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20140320-111914365", "type": "article", "title": "The Projective Field of Retinal Bipolar Cells and Its Modulation by Visual Context", "author": [ { "family_name": "Asari", "given_name": "Hiroki", "clpid": "Asari-Hiroki" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "The receptive field of a sensory neuron spells out all the receptor inputs it receives. To understand a neuron's role in the circuit, one also needs to know its projective field, namely the outputs it sends to all downstream cells. Here we present the projective fields of the primary excitatory neurons in a sensory circuit. We stimulated single bipolar cells of the salamander retina and recorded simultaneously from a population of ganglion cells. Individual bipolar cell signals diverge through polysynaptic pathways into ganglion cells of many different types and over surprisingly large distance. However, the strength and polarity of the projection depend on the cell types involved. Furthermore, visual stimulation strongly modulates the bipolar cell projective field, in opposite direction for different cell types. In this way, the context from distant parts of the visual field can control the routing of signals in the inner retina.", "doi": "10.1016/j.neuron.2013.11.029", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2014-02-05", "series_number": "3", "volume": "81", "issue": "3", "pages": "641-652" }, { "id": "authors:jfwjh-c3b32", "collection": "authors", "collection_id": "jfwjh-c3b32", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-092056680", "type": "article", "title": "Dynamical Adaptation in Photoreceptors", "author": [ { "family_name": "Clark", "given_name": "Damon A.", "clpid": "Clark-D-A" }, { "family_name": "Benichou", "given_name": "Raphael", "clpid": "Benichou-R" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "da Silveira", "given_name": "Rava Azeredo", "clpid": "da-Silveira-R-A" } ], "abstract": "Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over \u223c 300 ms\u2014i. e., over the time scale of the response itself\u2014and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant.", "doi": "10.1371/journal.pcbi.1003289", "pmcid": "PMC3828139", "issn": "1553-7358", "publisher": "Public Library of Science", "publication": "PLOS Computational Biology", "publication_date": "2013-11", "series_number": "11", "volume": "9", "issue": "11", "pages": "Art. No. e1003289" }, { "id": "authors:q05zd-xc516", "collection": "authors", "collection_id": "q05zd-xc516", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20131202-102453212", "type": "article", "title": "Nonlinear Dynamics Support a Linear Population Code in a Retinal Target-Tracking Circuit", "author": [ { "family_name": "Leonardo", "given_name": "Anthony", "clpid": "Leonardo-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "A basic task faced by the visual system of many organisms is to accurately track the position of moving prey. The retina is the first stage\nin the processing of such stimuli; the nature of the transformation here, from photons to spike trains, constrains not only the ultimate\nfidelity of the tracking signal but also the ease with which it can be extracted by other brain regions. Herewedemonstrate that a population\nof fast-OFF ganglion cells in the salamander retina, whose dynamics are governed by a nonlinear circuit, serve to compute the future\nposition of the target over hundreds of milliseconds. The extrapolated position of the target is not found by stimulus reconstruction but\nis instead computed by a weighted sum of ganglion cell outputs, the population vector average (PVA). The magnitude of PVA extrapolation\nvaries systematically with target size, speed, and acceleration, such that large targets are tracked most accurately at high speeds,\nand small targets at low speeds, just as is seen in the motion of real prey. Tracking precision reaches the resolution of single photoreceptors,\nand the PVA algorithm performs more robustly than several alternative algorithms. If the salamander brain uses the fast-OFF cell\ncircuit for target extrapolation as we suggest, the circuit dynamics should leave a microstructure on the behavior that may be measured\nin future experiments. Our analysis highlights the utility of simple computations that, while not globally optimal, are efficiently implemented\nand have close to optimal performance over a limited but ethologically relevant range of stimuli.", "doi": "10.1523/JNEUROSCI.2257-13.2013", "pmcid": "PMC3807026", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2013-10-23", "series_number": "43", "volume": "33", "issue": "43", "pages": "16971-16982" }, { "id": "authors:17gmh-c2z94", "collection": "authors", "collection_id": "17gmh-c2z94", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20131010-112717303", "type": "article", "title": "Rapid Innate Defensive Responses of Mice to Looming Visual Stimuli", "author": [ { "family_name": "Yilmaz", "given_name": "Melis", "clpid": "Yilmaz-M" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Much of brain science is concerned with understanding the neural circuits that underlie specific behaviors. While the mouse has become a favorite experimental subject, the behaviors of this species are still poorly explored. For example, the mouse retina, like that of other mammals, contains \u223c20 different circuits that compute distinct features of the visual scene [1 and 2]. By comparison, only a handful of innate visual behaviors are known in this species\u2014the pupil reflex [3], phototaxis [4], the optomotor response [5], and the cliff response [6]\u2014two of which are simple reflexes that require little visual processing. We explored the behavior of mice under a visual display that simulates an approaching object, which causes defensive reactions in some other species [7 and 8]. We show that mice respond to this stimulus either by initiating escape within a second or by freezing for an extended period. The probability of these defensive behaviors is strongly dependent on the parameters of the visual stimulus. Directed experiments identify candidate retinal circuits underlying the behavior and lead the way into detailed study of these neural pathways. This response is a new addition to the repertoire of innate defensive behaviors in the mouse that allows the detection and avoidance of aerial predators.", "doi": "10.1016/j.cub.2013.08.015", "pmcid": "PMC3809337", "issn": "0960-9822", "publisher": "Cell Press", "publication": "Current Biology", "publication_date": "2013-10-21", "series_number": "20", "volume": "23", "issue": "20", "pages": "2011-2015" }, { "id": "authors:t3yv8-r0a68", "collection": "authors", "collection_id": "t3yv8-r0a68", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20131224-092551420", "type": "article", "title": "Rats maintain a binocular field centered on the horizon", "author": [ { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Cox", "given_name": "David", "clpid": "Cox-D-J" } ], "abstract": "In this letter, we attempt to correct a potentially serious misperception arising\nfrom the paper \"Rats maintain an overhead binocular field at the expense of\nconstant fusion\". While the authors repeatedly emphasize that the animal's\nbinocular field is overhead, the authors' own data show that the truth is quite\ndifferent, even orthogonal: the binocular field is in fact centered dead-ahead in\nfront of the animal, tapering to a sliver both above and below the animal. We\npredict that this paper will be widely cited for something that it does not\ndemonstrate, a concern that is borne out by the paper's earliest citation.", "doi": "10.12688/f1000research.2-176.v1", "pmcid": "PMC3790602", "issn": "2046-1402", "publisher": "F1000 Research Ltd.", "publication": "F1000Research", "publication_date": "2013-08-16", "series_number": "2", "volume": "2013", "issue": "2", "pages": "Art. No. 176" }, { "id": "authors:ry7y4-b9x46", "collection": "authors", "collection_id": "ry7y4-b9x46", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-103352974", "type": "article", "title": "Computing Complex Visual Features with Retinal Spike Times", "author": [ { "family_name": "G\u00fctig", "given_name": "Robert", "clpid": "G\u00fctig-R" }, { "family_name": "Gollisch", "given_name": "Tim", "clpid": "Gollisch-T" }, { "family_name": "Sompolinsky", "given_name": "Haim", "clpid": "Sompolinsky-H" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Neurons in sensory systems can represent information not only by their firing rate, but also by the precise timing of individual spikes. For example, certain retinal ganglion cells, first identified in the salamander, encode the spatial structure of a new image by their first-spike latencies. Here we explore how this temporal code can be used by downstream neural circuits for computing complex features of the image that are not available from the signals of individual ganglion cells. To this end, we feed the experimentally observed spike trains from a population of retinal ganglion cells to an integrate-and-fire model of post-synaptic integration. The synaptic weights of this integration are tuned according to the recently introduced tempotron learning rule. We find that this model neuron can perform complex visual detection tasks in a single synaptic stage that would require multiple stages for neurons operating instead on neural spike counts. Furthermore, the model computes rapidly, using only a single spike per afferent, and can signal its decision in turn by just a single spike. Extending these analyses to large ensembles of simulated retinal signals, we show that the model can detect the orientation of a visual pattern independent of its phase, an operation thought to be one of the primitives in early visual processing. We analyze how these computations work and compare the performance of this model to other schemes for reading out spike-timing information. These results demonstrate that the retina formats spatial information into temporal spike sequences in a way that favors computation in the time domain. Moreover, complex image analysis can be achieved already by a simple integrate-and-fire model neuron, emphasizing the power and plausibility of rapid neural computing with spike times.", "doi": "10.1371/journal.pone.0053063", "pmcid": "PMC3534662", "issn": "1932-6203", "publisher": "Public Library of Science", "publication": "PLoS ONE", "publication_date": "2013-01-02", "series_number": "1", "volume": "8", "issue": "1", "pages": "Art. No. e53063" }, { "id": "authors:y91gw-ydf27", "collection": "authors", "collection_id": "y91gw-ydf27", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20121129-134641275", "type": "article", "title": "Divergence of visual channels in the inner retina", "author": [ { "family_name": "Asari", "given_name": "Hiroki", "clpid": "Asari-Hiroki" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Bipolar cells form parallel channels that carry visual signals from the outer to the inner retina. Each type of bipolar cell is thought to carry a distinct visual message to select types of amacrine cells and ganglion cells. However, the number of ganglion cell types exceeds that of the bipolar cells providing their input, suggesting that bipolar cell signals diversify on transmission to ganglion cells. We explored in the salamander retina how signals from individual bipolar cells feed into multiple ganglion cells and found that each bipolar cell was able to evoke distinct responses among ganglion cells, differing in kinetics, adaptation and rectification properties. This signal divergence resulted primarily from interactions with amacrine cells that allowed each bipolar cell to send distinct signals to its target ganglion cells. Our findings indicate that individual bipolar cell\u2013ganglion cell connections have distinct transfer functions. This expands the number of visual channels in the inner retina and enhances the computational power and feature selectivity of early visual processing.", "doi": "10.1038/nn.3241", "pmcid": "PMC3717330", "issn": "1097-6256", "publisher": "Nature Publishing Group", "publication": "Nature Neuroscience", "publication_date": "2012-11", "series_number": "11", "volume": "15", "issue": "11", "pages": "1581-1589" }, { "id": "authors:bqddp-kwa16", "collection": "authors", "collection_id": "bqddp-kwa16", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-135114672", "type": "article", "title": "The most numerous ganglion cell type of the mouse retina is a selective feature detector", "author": [ { "family_name": "Zhang", "given_name": "Yifeng", "clpid": "Zhang-Yifeng" }, { "family_name": "Kim", "given_name": "In-Jung", "clpid": "Kim-In-Jung" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "The retina reports the visual scene to the brain through many parallel channels, each carried by a distinct population of retinal ganglion cells. Among these, the population with the smallest and densest receptive fields encodes the neural image with highest resolution. In human retina, and those of cat and macaque, these high-resolution ganglion cells act as generic pixel encoders: They serve to represent many different visual inputs and convey a neural image of the scene downstream for further processing. Here we identify and analyze high-resolution ganglion cells in the mouse retina, using a transgenic line in which these cells, called \"W3\", are labeled fluorescently. Counter to the expectation, these ganglion cells do not participate in encoding generic visual scenes, but remain silent during most common visual stimuli. A detailed study of their response properties showed that W3 cells pool rectified excitation from both On and Off bipolar cells, which makes them sensitive to local motion. However, they also receive unusually strong lateral inhibition, both pre- and postsynaptically, triggered by distant motion. As a result, the W3 cell can detect small moving objects down to the receptive field size of bipolar cells, but only if the background is featureless or stationary\u2014an unusual condition. A survey of naturalistic stimuli shows that W3 cells may serve as alarm neurons for overhead predators.", "doi": "10.1073/pnas.1211547109", "pmcid": "PMC3437843", "issn": "0027-8424", "publisher": "National Academy of Sciences", "publication": "Proceedings of the National Academy of Sciences of the United States of America", "publication_date": "2012-09-04", "series_number": "36", "volume": "109", "issue": "36", "pages": "E2391-E2398" }, { "id": "authors:1qk7e-zdk31", "collection": "authors", "collection_id": "1qk7e-zdk31", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-082056107", "type": "article", "title": "Decorrelation and efficient coding by retinal ganglion cells", "author": [ { "family_name": "Pitkow", "given_name": "Xaq", "clpid": "Pitkow-X" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "An influential theory of visual processing asserts that retinal center-surround receptive fields remove spatial correlations in the visual world, producing ganglion cell spike trains that are less redundant than the corresponding image pixels. For bright, high-contrast images, this decorrelation would enhance coding efficiency in optic nerve fibers of limited capacity. We tested the central prediction of the theory and found that the spike trains of retinal ganglion cells were indeed decorrelated compared with the visual input. However, most of the decorrelation was accomplished not by the receptive fields, but by nonlinear processing in the retina. We found that a steep response threshold enhanced efficient coding by noisy spike trains and that the effect of this nonlinearity was near optimal in both salamander and macaque retina. These results offer an explanation for the sparseness of retinal spike trains and highlight the importance of treating the full nonlinear character of neural codes.", "doi": "10.1038/nn.3064", "pmcid": "PMC3725273", "issn": "1097-6256", "publisher": "Nature Publishing Group", "publication": "Nature Neuroscience", "publication_date": "2012-04", "series_number": "4", "volume": "15", "issue": "4", "pages": "628-635" }, { "id": "authors:yb6wh-4h691", "collection": "authors", "collection_id": "yb6wh-4h691", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-082004518", "type": "article", "title": "Age-Related Alterations in Neurons of the Mouse Retina", "author": [ { "family_name": "Samuel", "given_name": "Melanie A.", "clpid": "Samuel-M-A" }, { "family_name": "Zhang", "given_name": "Yifeng", "clpid": "Zhang-Yifeng" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" } ], "abstract": "The behavioral consequences of age-related alterations in neural function are well documented, but less is known about their cellular bases. To characterize such changes, we analyzed 14 molecularly identified subsets of mouse retinal projection neurons (retinal ganglion cells or RGCs) and interneurons (amacrine, bipolar, and horizontal cells). The retina thinned but expanded with age, maintaining its volume. There was minimal decline in the number of RGCs, interneurons, or photoreceptors, but the diameter of RGC dendritic arbors decreased with age. Together, the increased retinal area and the decreased dendritic area may lead to gaps in RGC coverage of the visual field. Axonal arbors of RGCs in the superior colliculus also atrophied with age, suggesting that the relay of visual information to central targets may decline over time. On the other hand, the laminar restriction of RGC dendrites and the interneuronal processes that synapse on them were not detectably disturbed, and RGC subtypes exhibited distinct electrophysiological responses to complex visual stimuli. Other neuronal types aged in different ways: amacrine cell arbors did not remodel detectably, whereas horizontal cell processes sprouted into the photoreceptor layer. Bipolar cells showed arbor-specific alterations: their dendrites sprouted but their axons remained stable. In summary, retinal neurons exhibited numerous age-related quantitative alterations (decreased areas of dendritic and axonal arbors and decreased density of cells and synapses), whereas their qualitative features (molecular identity, laminar specificity, and feature detection) were largely preserved. Together, these data reveal selective age-related alterations in neural circuitry, some of which could underlie declines in visual acuity.", "doi": "10.1523/JNEUROSCI.3580-11.2011", "pmcid": "PMC3238393", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2011-11-02", "series_number": "44", "volume": "31", "issue": "44", "pages": "16033-16044" }, { "id": "authors:5a3se-5bb26", "collection": "authors", "collection_id": "5a3se-5bb26", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-073927798", "type": "article", "title": "The Projective Field of a Retinal Amacrine Cell", "author": [ { "family_name": "de Vries", "given_name": "Saskia E. J.", "clpid": "de-Vries-S-E-J" }, { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "In sensory systems, neurons are generally characterized by their receptive field, namely the sensitivity to activity patterns at the input of the circuit. To assess the role of the neuron in the system, one must also know its projective field, namely the spatiotemporal effects the neuron exerts on all of the outputs of the circuit. We studied both the receptive and projective fields of an amacrine interneuron in the salamander retina. This amacrine type has a sustained OFF response with a small receptive field, but its output projects over a much larger region. Unlike other amacrine cells, this type is remarkably promiscuous and affects nearly every ganglion cell within reach of its dendrites. Its activity modulates the sensitivity of visual responses in ganglion cells but leaves their kinetics unchanged. The projective field displays a center-surround structure: depolarizing a single amacrine suppresses the visual sensitivity of ganglion cells nearby and enhances it at greater distances. This change in sign is seen even within the receptive field of one ganglion cell; thus, the modulation occurs presynaptically on bipolar cell terminals, most likely via GABAB receptors. Such an antagonistic projective field could contribute to the mechanisms of the retina for predictive coding.", "doi": "10.1523/JNEUROSCI.5662-10.2011", "pmcid": "PMC3130123", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2011-06-08", "series_number": "23", "volume": "31", "issue": "23", "pages": "8595-8604" }, { "id": "authors:dedw5-ahe56", "collection": "authors", "collection_id": "dedw5-ahe56", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-063019589", "type": "article", "title": "Retinal Ganglion Cells with Distinct Directional Preferences Differ in Molecular Identity, Structure, and Central Projections", "author": [ { "family_name": "Kay", "given_name": "Jeremy N.", "clpid": "Kay-J-N" }, { "family_name": "De la Huerta", "given_name": "Irina", "clpid": "De-la-Huerta-I" }, { "family_name": "Kim", "given_name": "In-Jung", "clpid": "Kim-In-Jung" }, { "family_name": "Zhang", "given_name": "Yifeng", "clpid": "Zhang-Yifeng" }, { "family_name": "Yamagata", "given_name": "Masahito", "clpid": "Yamagata-Masahito" }, { "family_name": "Chu", "given_name": "Monica W.", "clpid": "Chu-Monica-W" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" } ], "abstract": "The retina contains ganglion cells (RGCs) that respond selectively to objects moving in particular directions. Individual members of a group of ON-OFF direction-selective RGCs (ooDSGCs) detect stimuli moving in one of four directions: ventral, dorsal, nasal, or temporal. Despite this physiological diversity, little is known about subtype-specific differences in structure, molecular identity, and projections. To seek such differences, we characterized mouse transgenic lines that selectively mark ooDSGCs preferring ventral or nasal motion as well as a line that marks both ventral- and dorsal-preferring subsets. We then used the lines to identify cell surface molecules, including Cadherin 6, CollagenXXV\u03b11, and Matrix metalloprotease 17, that are selectively expressed by distinct subsets of ooDSGCs. We also identify a neuropeptide, CART (cocaine- and amphetamine-regulated transcript), that distinguishes all ooDSGCs from other RGCs. Together, this panel of endogenous and transgenic markers distinguishes the four ooDSGC subsets. Patterns of molecular diversification occur before eye opening and are therefore experience independent. They may help to explain how the four subsets obtain distinct inputs. We also demonstrate differences among subsets in their dendritic patterns within the retina and their axonal projections to the brain. Differences in projections indicate that information about motion in different directions is sent to different destinations.", "doi": "10.1523/JNEUROSCI.0907-11.2011", "pmcid": "PMC3108146", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2011-05-25", "series_number": "21", "volume": "31", "issue": "21", "pages": "7753-7762" }, { "id": "authors:cgg6d-tq552", "collection": "authors", "collection_id": "cgg6d-tq552", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20110303-161530587", "type": "article", "title": "A wireless multi-channel neural amplifier for freely moving animals", "author": [ { "family_name": "Szuts", "given_name": "Tobi A.", "clpid": "Szuts-T-A" }, { "family_name": "Fadeyev", "given_name": "Vitaliy", "clpid": "Fadeyev-V" }, { "family_name": "Kachiguine", "given_name": "Sergei", "clpid": "Kachiguine-S" }, { "family_name": "Sher", "given_name": "Alexander", "clpid": "Sher-A" }, { "family_name": "Grivich", "given_name": "Matthew V.", "clpid": "Grivich-M-V" }, { "family_name": "Agroch\u00e3o", "given_name": "Margarida", "clpid": "Agroch\u00e3o-M" }, { "family_name": "Hottowy", "given_name": "Pawel", "clpid": "Hottowy-P" }, { "family_name": "Dabrowski", "given_name": "Wladyslaw", "clpid": "Dabrowski-W" }, { "family_name": "Lubenov", "given_name": "Evgueniy V.", "orcid": "0000-0002-1099-944X", "clpid": "Lubenov-E-V" }, { "family_name": "Siapas", "given_name": "Athanassios G.", "orcid": "0000-0001-8837-678X", "clpid": "Siapas-A-G" }, { "family_name": "Uchida", "given_name": "Naoshige", "clpid": "Uchida-Naoshige" }, { "family_name": "Litke", "given_name": "Alan M.", "clpid": "Litke-A-M" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Conventional neural recording systems restrict behavioral experiments to a flat indoor environment compatible with the cable that tethers the subject to recording instruments. To overcome these constraints, we developed a wireless multi-channel system for recording neural signals from rats. The device takes up to 64 voltage signals from implanted electrodes, samples each at 20 kHz, time-division multiplexes them into one signal and transmits that output by radio frequency to a receiver up to 60 m away. The system introduces <4 \u03bcV of electrode-referred noise, comparable to wired recording systems, and outperforms existing rodent telemetry systems in channel count, weight and transmission range. This allows effective recording of brain signals in freely behaving animals. We report measurements of neural population activity taken outdoors and in tunnels. Neural firing in the visual cortex was relatively sparse, correlated even across large distances and was strongly influenced by locomotor activity.", "doi": "10.1038/nn.2730", "issn": "1097-6256", "publisher": "Nature Publishing Group", "publication": "Nature Neuroscience", "publication_date": "2011-02", "series_number": "2", "volume": "14", "issue": "2", "pages": "263-269" }, { "id": "authors:acqe1-ycr80", "collection": "authors", "collection_id": "acqe1-ycr80", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-134032704", "type": "article", "title": "Bayesian model of dynamic image stabilization in the visual system", "author": [ { "family_name": "Burak", "given_name": "Yoram", "clpid": "Burak-Y" }, { "family_name": "Rokni", "given_name": "Uri", "clpid": "Rokni-U" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Sompolinsky", "given_name": "Haim", "clpid": "Sompolinsky-H" } ], "abstract": "Humans can resolve the fine details of visual stimuli although the image projected on the retina is constantly drifting relative to the photoreceptor array. Here we demonstrate that the brain must take this drift into account when performing high acuity visual tasks. Further, we propose a decoding strategy for interpreting the spikes emitted by the retina, which takes into account the ambiguity caused by retinal noise and the unknown trajectory of the projected image on the retina. A main difficulty, addressed in our proposal, is the exponentially large number of possible stimuli, which renders the ideal Bayesian solution to the problem computationally intractable. In contrast, the strategy that we propose suggests a realistic implementation in the visual cortex. The implementation involves two populations of cells, one that tracks the position of the image and another that represents a stabilized estimate of the image itself. Spikes from the retina are dynamically routed to the two populations and are interpreted in a probabilistic manner. We consider the architecture of neural circuitry that could implement this strategy and its performance under measured statistics of human fixational eye motion. A salient prediction is that in high acuity tasks, fixed features within the visual scene are beneficial because they provide information about the drifting position of the image. Therefore, complete elimination of peripheral features in the visual scene should degrade performance on high acuity tasks involving very small stimuli.", "doi": "10.1073/pnas.1006076107", "pmcid": "PMC2984143", "issn": "0027-8424", "publisher": "National Academy of Sciences", "publication": "Proceedings of the National Academy of Sciences of the United States of America", "publication_date": "2010-11-09", "series_number": "45", "volume": "107", "issue": "45", "pages": "19525-19530" }, { "id": "authors:pp314-r3991", "collection": "authors", "collection_id": "pp314-r3991", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-081115721", "type": "article", "title": "Eye Smarter than Scientists Believed: Neural Computations in Circuits of the Retina", "author": [ { "family_name": "Gollisch", "given_name": "Tim", "clpid": "Gollisch-T" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "We rely on our visual system to cope with the vast barrage of incoming light patterns and to extract features from the scene that are relevant to our well-being. The necessary reduction of visual information already begins in the eye. In this review, we summarize recent progress in understanding the computations performed in the vertebrate retina and how they are implemented by the neural circuitry. A new picture emerges from these findings that helps resolve a vexing paradox between the retina's structure and function. Whereas the conventional wisdom treats the eye as a simple prefilter for visual images, it now appears that the retina solves a diverse set of specific tasks and provides the results explicitly to downstream brain areas.", "doi": "10.1016/j.neuron.2009.12.009", "pmcid": "PMC3717333", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2010-01-28", "series_number": "2", "volume": "65", "issue": "2", "pages": "150-164" }, { "id": "authors:aw4n6-tbm58", "collection": "authors", "collection_id": "aw4n6-tbm58", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-065327156", "type": "article", "title": "Laminar Restriction of Retinal Ganglion Cell Dendrites and Axons: Subtype-Specific Developmental Patterns Revealed with Transgenic Markers", "author": [ { "family_name": "Kim", "given_name": "In-Jung", "clpid": "Kim-In-Jung" }, { "family_name": "Zhang", "given_name": "Yifeng", "clpid": "Zhang-Yifeng" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" } ], "abstract": "Retinal ganglion cells (RGCs), which transfer information from the eye to the brain, are heterogeneous in structure and function, but developmental studies have generally treated them as a single group. Here, we investigate the development of RGC axonal and dendritic arbors using four mouse transgenic lines in which nonoverlapping subsets of RGCs are indelibly labeled with a fluorescent protein. Each subset has a distinct functional signature, size, and morphology. Dendrites of each subset are restricted to specific sublaminae within the inner plexiform layer in adulthood, but acquire their restriction in different ways: one subset has lamina-restricted dendrites from an early postnatal stage, a second remodels an initially diffuse pattern, and two others develop stepwise. Axons of each subset arborize in discrete laminar zones within the lateral geniculate nucleus or superior colliculus, demonstrating previously unrecognized subdivisions of retinorecipient layers. As is the case for dendrites, lamina-restricted axonal projections of RGC subsets develop in different ways. For example, while axons of two RGC subsets arborize in definite zones of the superior colliculus from an early postnatal stage, axons of another subset initially occupy a deep layer, then translocate to a narrow subpial zone. Together, these results show that RGC subsets use a variety of strategies to construct lamina-restricted dendritic and axonal arbors. Taking account of these subtype-specific features will facilitate identification of the molecules and cells that regulate arbor formation.", "doi": "10.1523/JNEUROSCI.4779-09.2010", "pmcid": "PMC2822471", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2010-01-27", "series_number": "4", "volume": "30", "issue": "4", "pages": "1452-1462" }, { "id": "authors:f6b4y-p7d54", "collection": "authors", "collection_id": "f6b4y-p7d54", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20090605-114631504", "type": "article", "title": "Neural encoding of rapidly fluctuating odors", "author": [ { "family_name": "Geffen", "given_name": "Maria N.", "clpid": "Geffen-M-N" }, { "family_name": "Broome", "given_name": "Bede M.", "clpid": "Broome-B-M" }, { "family_name": "Laurent", "given_name": "Gilles", "orcid": "0000-0002-2296-114X", "clpid": "Laurent-G" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Olfactory processing in the insect antennal lobe is a highly dynamic process, yet it has been studied primarily with static step stimuli. To approximate the rapid odor fluctuations encountered in nature, we presented flickering \"white-noise\" odor stimuli to the antenna of the locust and recorded spike trains from antennal lobe projection neurons (PNs). The responses varied greatly across PNs and across odors for the same PN. Surprisingly, this diversity across the population was highly constrained, and most responses were captured by a quantitative model with just 3 parameters. Individual PNs were found to communicate odor information at rates up to ~4 bits/s. A small group of PNs was sufficient to provide an accurate representation of the dynamic odor time course, whose quality was maximal for fluctuations of frequency ~0.8 Hz. We develop a simple model for the encoding of dynamic odor stimuli that accounts for many prior observations on the population response.", "doi": "10.1016/j.neuron.2009.01.021", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2009-02-26", "series_number": "4", "volume": "61", "issue": "4", "pages": "570-586" }, { "id": "authors:c0mmc-xcn33", "collection": "authors", "collection_id": "c0mmc-xcn33", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-072611037", "type": "article", "title": "Precision and diversity in an odor map on the olfactory bulb", "author": [ { "family_name": "Soucy", "given_name": "Edward R.", "orcid": "0000-0002-1187-5596", "clpid": "Soucy-E-R" }, { "family_name": "Albeanu", "given_name": "Dinu F.", "clpid": "Albeanu-D-F" }, { "family_name": "Fantana", "given_name": "Antoniu L.", "clpid": "Fantana-A-L" }, { "family_name": "Murthy", "given_name": "Venkatesh N.", "clpid": "Murthy-V-N" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "We explored the map of odor space created by glomeruli on the olfactory bulb of both rat and mouse. Identified glomeruli could be matched across animals by their response profile to hundreds of odors. Their layout in different individuals varied by only ~ 1 glomerular spacing, corresponding to a precision of 1 part in 1,000. Across species, mouse and rat share many glomeruli with apparently identical odor tuning, arranged in a similar layout. In mapping the position of a glomerulus to its odor tuning, we found only a coarse relationship with a precision of ~ 5 spacings. No chemotopic order was apparent on a finer scale and nearby glomeruli were almost as diverse in their odor sensitivity as distant ones. This local diversity of sensory tuning stands in marked distinction from other brain maps. Given the reliable placement of the glomeruli, it represents a feature, not a flaw, of the olfactory bulb.", "doi": "10.1038/nn.2262", "issn": "1097-6256", "publisher": "Nature Publishing Group", "publication": "Nature Neuroscience", "publication_date": "2009-02", "series_number": "2", "volume": "12", "issue": "2", "pages": "210-220" }, { "id": "authors:z11ny-w1936", "collection": "authors", "collection_id": "z11ny-w1936", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-141850023", "type": "article", "title": "\u03b3-Protocadherins regulate neuronal survival but are dispensable for circuit formation in retina", "author": [ { "family_name": "Lefebvre", "given_name": "Julie L.", "clpid": "Lefebvre-J-L" }, { "family_name": "Zhang", "given_name": "Yifeng", "clpid": "Zhang-Yifeng" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Wang", "given_name": "Xiaozhong", "clpid": "Wang-Xiaozhong" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" } ], "abstract": "Twenty-two tandemly arranged protocadherin-\u03b3 (Pcdh-\u03b3) genes encode transmembrane proteins with distinct cadherin-related extracellular domains and a common intracellular domain. Genetic studies have implicated Pcdh-\u03b3 genes in the regulation of neuronal survival and synapse formation. Because mice lacking the Pcdh-\u03b3 cluster die perinatally, we generated conditional mutants to analyze roles of Pcdh-\u03b3 genes in the development and function of neural circuits. Retina-specific deletion of Pcdh-\u03b3s led to accentuation of naturally occurring death of interneurons and retinal ganglion cells (RGCs) during the first two postnatal weeks. Nonetheless, many neuronal subtypes formed lamina-specific arbors. Blocking apoptosis by deletion of the pro-apoptotic gene Bax showed that even neurons destined to die formed qualitatively and quantitatively appropriate connections. Moreover, electrophysiological analysis indicated that processing of visual information was largely normal in the absence of Pcdh-\u03b3 genes. These results suggest that Pcdh-\u03b3 genes are dispensable for elaboration of specific connections in retina, but play a primary role in sculpting neuronal populations to appropriate sizes or proportions during the period of naturally occurring cell death.", "doi": "10.1242/dev.027912", "pmcid": "PMC2644426", "issn": "0950-1991", "publisher": "Company of Biologists", "publication": "Development", "publication_date": "2008-12-15", "series_number": "24", "volume": "135", "issue": "24", "pages": "4141-4151" }, { "id": "authors:54dj2-f9024", "collection": "authors", "collection_id": "54dj2-f9024", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-143539566", "type": "article", "title": "Modeling convergent ON and OFF pathways in the early visual system", "author": [ { "family_name": "Gollisch", "given_name": "Tim", "clpid": "Gollisch-T" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "For understanding the computation and function of single neurons in sensory systems, one needs to investigate how sensory stimuli are related to a neuron's response and which biological mechanisms underlie this relationship. Mathematical models of the stimulus\u2013response relationship have proved very useful in approaching these issues in a systematic, quantitative way. A starting point for many such analyses has been provided by phenomenological \"linear\u2013nonlinear\" (LN) models, which comprise a linear filter followed by a static nonlinear transformation. The linear filter is often associated with the neuron's receptive field. However, the structure of the receptive field is generally a result of inputs from many presynaptic neurons, which may form parallel signal processing pathways. In the retina, for example, certain ganglion cells receive excitatory inputs from ON-type as well as OFF-type bipolar cells. Recent experiments have shown that the convergence of these pathways leads to intriguing response characteristics that cannot be captured by a single linear filter. One approach to adjust the LN model to the biological circuit structure is to use multiple parallel filters that capture ON and OFF bipolar inputs. Here, we review these new developments in modeling neuronal responses in the early visual system and provide details about one particular technique for obtaining the required sets of parallel filters from experimental data.", "doi": "10.1007/s00422-008-0252-y", "pmcid": "PMC2784078", "issn": "0340-1200", "publisher": "Springer", "publication": "Biological Cybernetics", "publication_date": "2008-11", "series_number": "4-5", "volume": "99", "issue": "4-5", "pages": "263-278" }, { "id": "authors:359cn-5jq07", "collection": "authors", "collection_id": "359cn-5jq07", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-080226964", "type": "article", "title": "Rat Olfactory Bulb Mitral Cells Receive Sparse Glomerular Inputs", "author": [ { "family_name": "Fantana", "given_name": "Antoniu L.", "clpid": "Fantana-A-L" }, { "family_name": "Soucy", "given_name": "Edward R.", "orcid": "0000-0002-1187-5596", "clpid": "Soucy-E-R" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Center-surround receptive fields are a fundamental unit of brain organization. It has been proposed that olfactory bulb mitral cells exhibit this functional circuitry, with excitation from one glomerulus and inhibition from a broad field of glomeruli within reach of the lateral dendrites. We investigated this hypothesis using a combination of in vivo intrinsic imaging, single-unit recording, and a large panel of odors. Assuming a broad inhibitory field, a mitral cell would be influenced by >100 contiguous glomeruli and should respond to many odors. Instead, the observed response rate was an order of magnitude lower. A quantitative model indicates that mitral cell responses can be explained by just a handful of glomeruli. These glomeruli are spatially dispersed on the bulb and represent a broad range of odor sensitivities. We conclude that mitral cells do not have center-surround receptive fields. Instead, each mitral cell performs a specific computation combining a small and diverse set of glomerular inputs.", "doi": "10.1016/j.neuron.2008.07.039", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2008-09-11", "series_number": "5", "volume": "59", "issue": "5", "pages": "802-814" }, { "id": "authors:z5729-j1f98", "collection": "authors", "collection_id": "z5729-j1f98", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-071558162", "type": "article", "title": "A Retinal Circuit That Computes Object Motion", "author": [ { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "\u00d6lveczky", "given_name": "Bence P.", "clpid": "\u00d6lveczky-B-P" }, { "family_name": "Manu", "given_name": "Mihai", "clpid": "Manu-M" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Certain ganglion cells in the retina respond sensitively to differential motion between the receptive field center and surround, as produced by an object moving over the background, but are strongly suppressed by global image motion, as produced by the observer's head or eye movements. We investigated the circuit basis for this object motion sensitive (OMS) response by recording intracellularly from all classes of retinal interneurons while simultaneously recording the spiking output of many ganglion cells. Fast, transient bipolar cells respond linearly to motion in the receptive field center. The synaptic output from their terminals is rectified and then pooled by the OMS ganglion cell. A type of polyaxonal amacrine cell is driven by motion in the surround, again via pooling of rectified inputs, but from a different set of bipolar cell terminals. By direct intracellular current injection, we found that these polyaxonal amacrine cells selectively suppress the synaptic input of OMS ganglion cells. A quantitative model of these circuit elements and their interactions explains how an important visual computation is accomplished by retinal neurons and synapses.", "doi": "10.1523/JNEUROSCI.4206-07.2008", "issn": "0270-6474", "publisher": "Society for Neuroscience", "publication": "Journal of Neuroscience", "publication_date": "2008-07-02", "series_number": "27", "volume": "28", "issue": "27", "pages": "6807-6817" }, { "id": "authors:khzqm-d3g71", "collection": "authors", "collection_id": "khzqm-d3g71", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-101751665", "type": "article", "title": "LED Arrays as Cost Effective and Efficient Light Sources for Widefield Microscopy", "author": [ { "family_name": "Albeanu", "given_name": "Dinu F.", "clpid": "Albeanu-D-F" }, { "family_name": "Soucy", "given_name": "Edward", "orcid": "0000-0002-1187-5596", "clpid": "Soucy-E-R" }, { "family_name": "Sato", "given_name": "Tomokazu F.", "clpid": "Sato-T-F" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Murthy", "given_name": "Venkatesh N.", "clpid": "Murthy-V-N" } ], "abstract": "New developments in fluorophores as well as in detection methods have fueled the rapid growth of optical imaging in the life sciences. Commercial widefield microscopes generally use arc lamps, excitation/emission filters and shutters for fluorescence imaging. These components can be expensive, difficult to maintain and preclude stable illumination. Here, we describe methods to construct inexpensive and easy-to-use light sources for optical microscopy using light-emitting diodes (LEDs). We also provide examples of its applicability to biological fluorescence imaging.", "doi": "10.1371/journal.pone.0002146", "pmcid": "PMC2361193", "issn": "1932-6203", "publisher": "Public Library of Science", "publication": "PLoS ONE", "publication_date": "2008-05-14", "series_number": "5", "volume": "3", "issue": "5", "pages": "Art. No. e2146" }, { "id": "authors:ga0vx-et608", "collection": "authors", "collection_id": "ga0vx-et608", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-094857083", "type": "article", "title": "Molecular identification of a retinal cell type that responds to upward motion", "author": [ { "family_name": "Kim", "given_name": "In-Jung", "clpid": "Kim-In-Jung" }, { "family_name": "Zhang", "given_name": "Yifeng", "clpid": "Zhang-Yifeng" }, { "family_name": "Yamagata", "given_name": "Masahito", "clpid": "Yamagata-Masahito" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Sanes", "given_name": "Joshua R.", "clpid": "Sanes-J-R" } ], "abstract": "The retina contains complex circuits of neurons that extract salient information from visual inputs. Signals from photoreceptors are processed by retinal interneurons, integrated by retinal ganglion cells (RGCs) and sent to the brain by RGC axons. Distinct types of RGC respond to different visual features, such as increases or decreases in light intensity (ON and OFF cells, respectively), colour or moving objects1, 2, 3, 4, 5. Thus, RGCs comprise a set of parallel pathways from the eye to the brain. The identification of molecular markers for RGC subsets will facilitate attempts to correlate their structure with their function, assess their synaptic inputs and targets, and study their diversification. Here we show, by means of a transgenic marking method, that junctional adhesion molecule B (JAM-B) marks a previously unrecognized class of OFF RGCs in mice. These cells have asymmetric dendritic arbors aligned in a dorsal-to-ventral direction across the retina. Their receptive fields are also asymmetric and respond selectively to stimuli moving in a soma-to-dendrite direction; because the lens reverses the image of the world on the retina, these cells detect upward motion in the visual field. Thus, JAM-B identifies a unique population of RGCs in which structure corresponds remarkably to function.", "doi": "10.1038/nature06739", "issn": "0028-0836", "publisher": "Nature Publishing Group", "publication": "Nature", "publication_date": "2008-03-27", "series_number": "7186", "volume": "452", "issue": "7186", "pages": "478-482" }, { "id": "authors:sa23b-wj235", "collection": "authors", "collection_id": "sa23b-wj235", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-064514516", "type": "article", "title": "Rapid Neural Coding in the Retina with Relative Spike Latencies", "author": [ { "family_name": "Gollisch", "given_name": "Tim", "clpid": "Gollisch-T" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Natural vision is a highly dynamic process. Frequent body, head, and eye movements constantly bring new images onto the retina for brief periods, challenging our understanding of the neural code for vision. We report that certain retinal ganglion cells encode the spatial structure of a briefly presented image in the relative timing of their first spikes. This code is found to be largely invariant to stimulus contrast and robust to noisy fluctuations in response latencies. Mechanistically, the observed response characteristics result from different kinetics in two retinal pathways (\"ON\" and \"OFF\") that converge onto ganglion cells. This mechanism allows the retina to rapidly and reliably transmit new spatial information with the very first spikes emitted by a neural population.", "doi": "10.1126/science.1149639", "issn": "0036-8075", "publisher": "American Association for the Advancement of Science", "publication": "Science", "publication_date": "2008-02-22", "series_number": "5866", "volume": "319", "issue": "5866", "pages": "1108-1111" }, { "id": "authors:bpxdj-75n40", "collection": "authors", "collection_id": "bpxdj-75n40", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-083802627", "type": "article", "title": "A Neural Computation for Visual Acuity in the Presence of Eye Movements", "author": [ { "family_name": "Burr", "given_name": "David", "clpid": "Burr-D" }, { "family_name": "Pitkow", "given_name": "Xaq", "clpid": "Pitkow-X" }, { "family_name": "Sompolinsky", "given_name": "Haim", "clpid": "Sompolinsky-H" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Humans can distinguish visual stimuli that differ by features the size of only a few photoreceptors. This is possible despite the incessant image motion due to fixational eye movements, which can be many times larger than the features to be distinguished. To perform well, the brain must identify the retinal firing patterns induced by the stimulus while discounting similar patterns caused by spontaneous retinal activity. This is a challenge since the trajectory of the eye movements, and consequently, the stimulus position, are unknown. We derive a decision rule for using retinal spike trains to discriminate between two stimuli, given that their retinal image moves with an unknown random walk trajectory. This algorithm dynamically estimates the probability of the stimulus at different retinal locations, and uses this to modulate the influence of retinal spikes acquired later. Applied to a simple orientation-discrimination task, the algorithm performance is consistent with human acuity, whereas naive strategies that neglect eye movements perform much worse. We then show how a simple, biologically plausible neural network could implement this algorithm using a local, activity-dependent gain and lateral interactions approximately matched to the statistics of eye movements. Finally, we discuss evidence that such a network could be operating in the primary visual cortex.", "doi": "10.1371/journal.pbio.0050331", "pmcid": "PMC2222970", "issn": "1545-7885", "publisher": "Public Library of Science", "publication": "PLoS Biology", "publication_date": "2007-12-27", "series_number": "12", "volume": "5", "issue": "12", "pages": "Art. No. e331" }, { "id": "authors:9kwym-t3p88", "collection": "authors", "collection_id": "9kwym-t3p88", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-073838107", "type": "article", "title": "Retinal Adaptation to Object Motion", "author": [ { "family_name": "\u00d6lveczky", "given_name": "Bence P.", "clpid": "\u00d6lveczky-B-P" }, { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Due to fixational eye movements, the image on the retina is always in motion, even when one views a stationary scene. When an object moves within the scene, the corresponding patch of retina experiences a different motion trajectory than the surrounding region. Certain retinal ganglion cells respond selectively to this condition, when the motion in the cell's receptive field center is different from that in the surround. Here we show that this response is strongest at the very onset of differential motion, followed by gradual adaptation with a time course of several seconds. Different subregions of a ganglion cell's receptive field can adapt independently. The circuitry responsible for differential motion adaptation lies in the inner retina. Several candidate mechanisms were tested, and the adaptation most likely results from synaptic depression at the synapse from bipolar to ganglion cell. Similar circuit mechanisms may act more generally to emphasize novel features of a visual stimulus.", "doi": "10.1016/j.neuron.2007.09.030", "pmcid": "PMC2117331", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2007-11-21", "series_number": "4", "volume": "56", "issue": "4", "pages": "689-700" }, { "id": "authors:hay5f-h3631", "collection": "authors", "collection_id": "hay5f-h3631", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-140543270", "type": "article", "title": "Local Retinal Circuits of Melanopsin-Containing Ganglion Cells Identified by Transsynaptic Viral Tracing", "author": [ { "family_name": "Viney", "given_name": "Tim James", "clpid": "Viney-T-J" }, { "family_name": "Balint", "given_name": "Kamill", "clpid": "Balint-K" }, { "family_name": "Hillier", "given_name": "Daniel", "clpid": "Hillier-D" }, { "family_name": "Siegert", "given_name": "Sandra", "clpid": "Siegert-S" }, { "family_name": "Boldogkoi", "given_name": "Zsolt", "clpid": "Boldogkoi-Z" }, { "family_name": "Enquist", "given_name": "Lynn W.", "clpid": "Enquist-L-W" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Cepko", "given_name": "Constance L.", "clpid": "Cepko-C-L" }, { "family_name": "Roska", "given_name": "Botond", "clpid": "Roska-B" } ], "abstract": "Intrinsically photosensitive melanopsin-containing retinal ganglion cells (ipRGCs) control important physiological processes, including the circadian rhythm, the pupillary reflex, and the suppression of locomotor behavior (reviewed in [1]). ipRGCs are also activated by classical photoreceptors, the rods and cones, through local retinal circuits 2 ; 3. ipRGCs can be transsynaptically labeled through the pupillary-reflex circuit with the derivatives of the Bartha strain of the alphaherpesvirus pseudorabies virus(PRV) 4 ; 5 that express GFP 6; 7; 8; 9; 10; 11 ; 12. Bartha-strain derivatives spread only in the retrograde direction [13]. There is evidence that infected cells function normally for a while during GFP expression [7]. Here we combine transsynaptic PRV labeling, two-photon laser microscopy, and electrophysiological techniques to trace the local circuit of different ipRGC subtypes in the mouse retina and record light-evoked activity from the transsynaptically labeled ganglion cells. First, we show that ipRGCs are connected by monostratified amacrine cells that provide strong inhibition from classical-photoreceptor-driven circuits. Second, we show evidence that dopaminergic interplexiform cells are synaptically connected to ipRGCs. The latter finding provides a circuitry link between light\u2013dark adaptation and ipRGC function.", "doi": "10.1016/j.cub.2007.04.058", "issn": "0960-9822", "publisher": "Cell Press", "publication": "Current Biology", "publication_date": "2007-06-05", "series_number": "11", "volume": "17", "issue": "11", "pages": "981-988" }, { "id": "authors:3ma24-1jm96", "collection": "authors", "collection_id": "3ma24-1jm96", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-082620129", "type": "article", "title": "Retinal Ganglion Cells Can Rapidly Change Polarity from Off to On", "author": [ { "family_name": "Geffen", "given_name": "Maria Neimark", "clpid": "Geffen-M-N" }, { "family_name": "de Vries", "given_name": "Saskia E. J", "clpid": "de-Vries-S-E-J" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Retinal ganglion cells are commonly classified as On-center or Off-center depending on whether they are excited predominantly by brightening or dimming within the receptive field. Here we report that many ganglion cells in the salamander retina can switch from one response type to the other, depending on stimulus events far from the receptive field. Specifically, a shift of the peripheral image\u2014as produced by a rapid eye movement\u2014causes a brief transition in visual sensitivity from Off-type to On-type for approximately 100 ms. We show that these ganglion cells receive inputs from both On and Off bipolar cells, and the Off inputs are normally dominant. The peripheral shift strongly modulates the strength of these two inputs in opposite directions, facilitating the On pathway and suppressing the Off pathway. Furthermore, we identify certain wide-field amacrine cells that contribute to this modulation. Depolarizing such an amacrine cell affects nearby ganglion cells in the same way as the peripheral image shift, facilitating the On inputs and suppressing the Off inputs. This study illustrates how inhibitory interneurons can rapidly gate the flow of information within a circuit, dramatically altering the behavior of the principal neurons in the course of a computation.", "doi": "10.1371/journal.pbio.0050065", "pmcid": "PMC1808116", "issn": "1545-7885", "publisher": "Public Library of Science", "publication": "PLoS Biology", "publication_date": "2007-03-06", "series_number": "3", "volume": "5", "issue": "3", "pages": "Art. No. e65" }, { "id": "authors:hcttx-t0a72", "collection": "authors", "collection_id": "hcttx-t0a72", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-093657286", "type": "article", "title": "Dynamic predictive coding by the retina", "author": [ { "family_name": "Hosoya", "given_name": "Toshihiko", "clpid": "Hosoya-Toshihiko" }, { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Retinal ganglion cells convey the visual image from the eye to the brain. They generally encode local differences in space and changes in time rather than the raw image intensity. This can be seen as a strategy of predictive coding, adapted through evolution to the average image statistics of the natural environment. Yet animals encounter many environments with visual statistics different from the average scene. Here we show that when this happens, the retina adjusts its processing dynamically. The spatio-temporal receptive fields of retinal ganglion cells change after a few seconds in a new environment. The changes are adaptive, in that the new receptive field improves predictive coding under the new image statistics. We show that a network model with plastic synapses can account for the large variety of observed adaptations.", "doi": "10.1038/nature03689", "issn": "0028-0836", "publisher": "Nature Publishing Group", "publication": "Nature", "publication_date": "2005-07-07", "series_number": "7047", "volume": "436", "issue": "7047", "pages": "71-77" }, { "id": "authors:9xhs6-v3q44", "collection": "authors", "collection_id": "9xhs6-v3q44", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-073120186", "type": "article", "title": "Retina versus Cortex: Contrast Adaptation in Parallel Visual Pathways", "author": [ { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Human vision adapts to the contrast of patterns by changing its sensitivity, but the origins of this perceptual adaptation have been disputed. In this issue of Neuron, Solomon et al. show that contrast adaptation in the primate arises mostly in the retina for the magnocellular pathway and mostly in the cortex for the parvocellular pathway. It appears that adaptation arises most strongly at sites that pool over many inputs.", "doi": "10.1016/S0896-6273(04)00187-4", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2004-04-08", "series_number": "1", "volume": "42", "issue": "1", "pages": "5-7" }, { "id": "authors:zqns6-b8s02", "collection": "authors", "collection_id": "zqns6-b8s02", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-113339851", "type": "article", "title": "Genetically engineered mice with an additional class of cone photoreceptors: Implications for the evolution of color vision", "author": [ { "family_name": "Smallwood", "given_name": "Philip M.", "clpid": "Smallwood-P-M" }, { "family_name": "\u00d6lveczky", "given_name": "Bence P.", "clpid": "\u00d6lveczky-B-P" }, { "family_name": "Williams", "given_name": "Gary L.", "clpid": "Williams-G-L" }, { "family_name": "Jacobs", "given_name": "Gerald H.", "clpid": "Jacobs-G-H" }, { "family_name": "Reese", "given_name": "Benjamin E.", "clpid": "Reese-B-E" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Nathans", "given_name": "Jeremy", "clpid": "Nathans-J" } ], "abstract": "Among eutherian mammals, only primates possess trichromatic color vision. In Old World primates, trichromacy was made possible by a visual pigment gene duplication. In most New World primates, trichromacy is based on polymorphic variation in a single X-linked gene that produces, by random X inactivation, a patchy mosaic of spectrally distinct cone photoreceptors in heterozygous females. In the present work, we have modeled the latter strategy in a nonprimate by replacing the X-linked mouse green pigment gene with one encoding the human red pigment. In the mouse retina, the human red pigment seems to function normally, and heterozygous female mice express the human red and mouse green pigments at levels that vary between animals. Multielectrode array recordings from heterozygous female retinas reveal significant variation in the chromatic sensitivities of retinal ganglion cells. The data are consistent with a model in which these retinal ganglion cells draw their inputs indiscriminately from a coarse-grained mosaic of red and green cones. These observations support the ideas that (i) chromatic signals could arise from stochastic variation in inputs drawn nonselectively from red and green cones and (ii) tissue mosaicism due to X chromosome inactivation could be one mechanism for driving the evolution of CNS diversity.", "doi": "10.1073/pnas.1934712100", "pmcid": "PMC208822", "issn": "0027-8424", "publisher": "National Academy of Sciences", "publication": "Proceedings of the National Academy of Sciences of the United States of America", "publication_date": "2003-09-30", "series_number": "20", "volume": "100", "issue": "20", "pages": "11706-11711" }, { "id": "authors:njcny-aq569", "collection": "authors", "collection_id": "njcny-aq569", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-152615141", "type": "article", "title": "Segregation of object and background motion in the retina", "author": [ { "family_name": "\u00d6lveczky", "given_name": "Bence P.", "clpid": "\u00d6lveczky-B-P" }, { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "An important task in vision is to detect objects moving within a stationary scene. During normal viewing this is complicated by the presence of eye movements that continually scan the image across the retina, even during fixation. To detect moving objects, the brain must distinguish local motion within the scene from the global retinal image drift due to fixational eye movements. We have found that this process begins in the retina: a subset of retinal ganglion cells responds to motion in the receptive field centre, but only if the wider surround moves with a different trajectory. This selectivity for differential motion is independent of direction, and can be explained by a model of retinal circuitry that invokes pooling over nonlinear interneurons. The suppression by global image motion is probably mediated by polyaxonal, wide-field amacrine cells with transient responses. We show how a population of ganglion cells selective for differential motion can rapidly flag moving objects, and even segregate multiple moving objects.", "doi": "10.1038/nature01652", "issn": "0028-0836", "publisher": "Nature Publishing Group", "publication": "Nature", "publication_date": "2003-05-22", "series_number": "6938", "volume": "423", "issue": "6938", "pages": "401-408" }, { "id": "authors:b8hqx-bxp74", "collection": "authors", "collection_id": "b8hqx-bxp74", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-132335746", "type": "article", "title": "Multineuronal Firing Patterns in the Signal from Eye to Brain", "author": [ { "family_name": "Schnitzer", "given_name": "Mark J.", "clpid": "Schnitzer-M-J" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "Population codes in the brain have generally been characterized by recording responses from one neuron at a time. This approach will miss codes that rely on concerted patterns of action potentials from many cells. Here we analyze visual signaling in populations of ganglion cells recorded from the isolated salamander retina. These neurons tend to fire synchronously far more frequently than expected by chance. We present an efficient algorithm to identify what groups of cells cooperate in this way. Such groups can include up to seven or more neurons and may account for more than 50% of all the spikes recorded from the retina. These firing patterns represent specific messages about the visual stimulus that differ significantly from what one would derive by single-cell analysis.", "doi": "10.1016/S0896-6273(03)00004-7", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2003-02-06", "series_number": "3", "volume": "37", "issue": "3", "pages": "499-511" }, { "id": "authors:zr676-gs486", "collection": "authors", "collection_id": "zr676-gs486", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170404-131413153", "type": "article", "title": "Fast and Slow Contrast Adaptation in Retinal Circuitry", "author": [ { "family_name": "Baccus", "given_name": "Stephen A.", "clpid": "Baccus-S-A" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" } ], "abstract": "The visual system adapts to the magnitude of intensity fluctuations, and this process begins in the retina. Following the switch from a low-contrast environment to one of high contrast, ganglion cell sensitivity declines in two distinct phases: a fast change occurs in <0.1 s, and a slow decrease over \u223c10 s. To examine where these modulations arise, we recorded intracellularly from every major cell type in the salamander retina. Certain bipolar and amacrine cells, and all ganglion cells, adapted to contrast. Generally, these neurons showed both fast and slow adaptation. Fast effects of a contrast increase included accelerated kinetics, decreased sensitivity, and a depolarization of the baseline membrane potential. Slow adaptation did not affect kinetics, but produced a gradual hyperpolarization. This hyperpolarization can account for slow adaptation in the spiking output of ganglion cells.", "doi": "10.1016/S0896-6273(02)01050-4", "issn": "0896-6273", "publisher": "Elsevier", "publication": "Neuron", "publication_date": "2002-12-05", "series_number": "5", "volume": "36", "issue": "5", "pages": "909-919" }, { "id": "authors:3cpz3-k3714", "collection": "authors", "collection_id": "3cpz3-k3714", "cite_using_url": "https://resolver.caltech.edu/CaltechAUTHORS:20170405-070334559", "type": "article", "title": "Loss of Sex Discrimination and Male-Male Aggression in Mice Deficient for TRP2", "author": [ { "family_name": "Stowers", "given_name": "Lisa", "clpid": "Stowers-L" }, { "family_name": "Holy", "given_name": "Timothy E.", "clpid": "Holy-T-E" }, { "family_name": "Meister", "given_name": "Markus", "orcid": "0000-0003-2136-6506", "clpid": "Meister-M" }, { "family_name": "Dulac", "given_name": "Catherine", "clpid": "Dulac-C" }, { "family_name": "Koentges", "given_name": "Georgy", "clpid": "Koentges-G" } ], "abstract": "The mouse vomeronasal organ (VNO) is thought to mediate social behaviors and neuroendocrine changes elicited by pheromonal cues. The molecular mechanisms underlying the sensory response to pheromones and the behavioral repertoire induced through the VNO are not fully characterized. Using the tools of mouse genetics and multielectrode recording, we demonstrate that the sensory activation of VNO neurons requires TRP2, a putative ion channel of the transient receptor potential family that is expressed exclusively in these neurons. Moreover, we show that male mice deficient in TRP2 expression fail to display male-male aggression, and they initiate sexual and courtship behaviors toward both males and females. Our study suggests that, in the mouse, sensory activation of the VNO is essential for sex discrimination of conspecifics and thus ensures gender-specific behavior.", "doi": "10.1126/science.1069259", "issn": "0036-8075", "publisher": "American Association for the Advancement of Science", "publication": "Science", "publication_date": "2002-02-22", "series_number": "5559", "volume": "295", "issue": "5559", "pages": "1493-1500" } ]