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Li P, Garg AK, Zhang LA, Rashid MS, Callaway EM. Cone opponent functional domains in primary visual cortex combine signals for color appearance mechanisms. Nat Commun 2022; 13:6344. [PMID: 36284139 PMCID: PMC9596481 DOI: 10.1038/s41467-022-34020-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 10/11/2022] [Indexed: 12/25/2022] Open
Abstract
Studies of color perception have led to mechanistic models of how cone-opponent signals from retinal ganglion cells are integrated to generate color appearance. But it is unknown how this hypothesized integration occurs in the brain. Here we show that cone-opponent signals transmitted from retina to primary visual cortex (V1) are integrated through highly organized circuits within V1 to implement the color opponent interactions required for color appearance. Combining intrinsic signal optical imaging (ISI) and 2-photon calcium imaging (2PCI) at single cell resolution, we demonstrate cone-opponent functional domains (COFDs) that combine L/M cone-opponent and S/L + M cone-opponent signals following the rules predicted from psychophysical studies of color perception. These give rise to an orderly organization of hue preferences of the neurons within the COFDs and the generation of hue "pinwheels". Thus, spatially organized neural circuits mediate an orderly transition from cone-opponency to color appearance that begins in V1.
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Affiliation(s)
- Peichao Li
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, 1369 West Wenyi Road, 311121, Hangzhou, China
| | - Anupam K Garg
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, 92093, USA
- Wilmer Eye Institute, Johns Hopkins University, 600N Wolfe Street, Baltimore, MD, 21287, USA
| | - Li A Zhang
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA
| | | | - Edward M Callaway
- The Salk Institute for Biological Studies, La Jolla, CA, 92037, USA.
- Neurosciences Graduate Program, University of California, San Diego, La Jolla, CA, 92093, USA.
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Scholl B, Wilson DE, Jaepel J, Fitzpatrick D. Functional Logic of Layer 2/3 Inhibitory Connectivity in the Ferret Visual Cortex. Neuron 2019; 104:451-457.e3. [PMID: 31495646 DOI: 10.1016/j.neuron.2019.08.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2018] [Revised: 05/29/2019] [Accepted: 08/01/2019] [Indexed: 10/26/2022]
Abstract
Understanding how cortical inhibition shapes circuit function requires identifying the connectivity rules relating the response properties of inhibitory interneurons and their postsynaptic targets. Here we explore the orientation tuning of layer 2/3 inhibitory inputs in the ferret visual cortex using a combination of in vivo axon imaging, functional input mapping, and physiology. Inhibitory boutons exhibit robust orientation-tuned responses with preferences that can differ significantly from the cortical column in which they reside. Inhibitory input fields measured with patterned optogenetic stimulation and intracellular recordings revealed that these inputs originate from a wide range of orientation domains, inconsistent with a model of co-tuned inhibition and excitation. Intracellular synaptic conductance measurements confirm that individual neurons can depart from a co-tuned regime. Our results argue against a simple rule for the arrangement of inhibitory inputs supplied by layer 2/3 circuits and suggest that heterogeneity in presynaptic inhibitory networks contributes to neural response properties.
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Affiliation(s)
- Benjamin Scholl
- Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA.
| | | | - Juliane Jaepel
- Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
| | - David Fitzpatrick
- Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL 33458, USA
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Differential tuning of excitation and inhibition shapes direction selectivity in ferret visual cortex. Nature 2018; 560:97-101. [PMID: 30046106 PMCID: PMC6946183 DOI: 10.1038/s41586-018-0354-1] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2017] [Accepted: 06/08/2018] [Indexed: 11/12/2022]
Abstract
To encode specific sensory inputs, cortical neurons must generate selective responses for distinct stimulus features. In principle, a variety of factors contribute to a cortical neuron’s response selectivity: the tuning and strength of excitatory1–3 and inhibitory synaptic inputs4–6, dendritic nonlinearities7–9, and spike threshold10,11. Here we employ a combination of techniques including in vivo whole-cell recording, synaptic and cellular resolution in vivo two photon calcium imaging, and GABAergic-selective optogenetic manipulation to dissect the factors contributing to direction selective responses of layer 2/3 neurons in ferret visual cortex (V1). Two-photon calcium imaging of dendritic spines12,13 revealed that each neuron receives a mixture of excitatory synaptic inputs selective for the somatic preferred or null direction of motion. The relative number of preferred- and null-tuned excitatory inputs predicted a neuron’s somatic direction preference, but failed to account for the degree of direction selectivity. In contrast, in vivo whole-cell patch clamp recordings revealed a striking degree of direction selectivity in subthreshold responses that was significantly correlated with spiking direction selectivity. Subthreshold direction selectivity was predicted by the magnitude and variance of the response to the null direction of motion, and several lines of evidence including conductance measurements demonstrate that differential tuning of excitation and inhibition suppresses responses to the null direction of motion. Consistent with this idea, optogenetic inactivation of GABAergic neurons in layer 2/3 reduced direction selectivity by enhancing responses to the null direction. Furthermore, using a new technique to optogenetically map connections of inhibitory neurons in layer 2/3 in vivo, we find that layer 2/3 inhibitory neurons make long-range, intercolumnar projections to excitatory neurons that prefer the opposite direction of motion. We conclude that intracortical inhibition exerts a major influence on the degree of direction selectivity in layer 2/3 of ferret V1 by suppressing responses to the null direction of motion.
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Ribot J, Romagnoni A, Milleret C, Bennequin D, Touboul J. Pinwheel-dipole configuration in cat early visual cortex. Neuroimage 2015; 128:63-73. [PMID: 26707892 DOI: 10.1016/j.neuroimage.2015.12.022] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Revised: 12/02/2015] [Accepted: 12/14/2015] [Indexed: 11/16/2022] Open
Abstract
In the early visual cortex, information is processed within functional maps whose layouts are thought to underlie visual perception. However, the precise organization of these functional maps as well as their interrelationships remain unsettled. Here, we show that spatial frequency representation in cat early visual cortex exhibits singularities around which the map organizes like an electric dipole potential. These singularities are precisely co-located with singularities of the orientation map: the pinwheel centers. To show this, we used high resolution intrinsic optical imaging in cat areas 17 and 18. First, we show that a majority of pinwheel centers exhibit in their neighborhood both semi-global maximum and minimum in the spatial frequency map (i.e. extreme values of the spatial frequency in a hypercolumn). This contradicts pioneering studies suggesting that pinwheel centers are placed at the locus of a single spatial frequency extremum. Based on an analogy with electromagnetism, we proposed a mathematical model for a dipolar structure, accurately fitting optical imaging data. We conclude that a majority of orientation pinwheel centers form spatial frequency dipoles in cat early visual cortex. Given the functional specificities of neurons at singularities in the visual cortex, it is argued that the dipolar organization of spatial frequency around pinwheel centers could be fundamental for visual processing.
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Affiliation(s)
- Jérôme Ribot
- Mathematical Neuroscience Team, CIRB - Collège de France (CNRS UMR 7241, INSERM U1050, UPMC ED 158, MEMOLIFE PSL), 11 Place Marcelin Berthelot, 75005 Paris, France.
| | - Alberto Romagnoni
- Mathematical Neuroscience Team, CIRB - Collège de France (CNRS UMR 7241, INSERM U1050, UPMC ED 158, MEMOLIFE PSL), 11 Place Marcelin Berthelot, 75005 Paris, France
| | - Chantal Milleret
- Brain Rhythms and Neural Coding of Memory, CIRB - Collège de France (CNRS UMR 7241, INSERM U1050, UPMC ED 158, MEMOLIFE PSL), 11 Place Marcelin Berthelot, 75005 Paris, France
| | - Daniel Bennequin
- Géométrie et dynamique, Université Paris Diderot (Paris VII), Paris, France
| | - Jonathan Touboul
- Mathematical Neuroscience Team, CIRB - Collège de France (CNRS UMR 7241, INSERM U1050, UPMC ED 158, MEMOLIFE PSL), 11 Place Marcelin Berthelot, 75005 Paris, France; INRIA Mycenae Team, Paris-Rocquencourt, France
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Purushothaman G, Chen X, Yampolsky D, Casagrande VA. Neural mechanisms of coarse-to-fine discrimination in the visual cortex. J Neurophysiol 2014; 112:2822-33. [PMID: 25210162 DOI: 10.1152/jn.00612.2013] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier.
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Affiliation(s)
- Gopathy Purushothaman
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee; and
| | - Xin Chen
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee; and
| | - Dmitry Yampolsky
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee; and
| | - Vivien A Casagrande
- Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee; and Departments of Psychology, Ophthalmology, and Visual Sciences, Vanderbilt University, Nashville, Tennessee
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Purushothaman G, Casagrande VA. A Generalized ideal observer model for decoding sensory neural responses. Front Psychol 2013; 4:617. [PMID: 24137135 PMCID: PMC3786228 DOI: 10.3389/fpsyg.2013.00617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2012] [Accepted: 02/04/2013] [Indexed: 11/13/2022] Open
Abstract
We show that many ideal observer models used to decode neural activity can be generalized to a conceptually and analytically simple form. This enables us to study the statistical properties of this class of ideal observer models in a unified manner. We consider in detail the problem of estimating the performance of this class of models. We formulate the problem de novo by deriving two equivalent expressions for the performance and introducing the corresponding estimators. We obtain a lower bound on the number of observations (N) required for the estimate of the model performance to lie within a specified confidence interval at a specified confidence level. We show that these estimators are unbiased and consistent, with variance approaching zero at the rate of 1/N. We find that the maximum likelihood estimator for the model performance is not guaranteed to be the minimum variance estimator even for some simple parametric forms (e.g., exponential) of the underlying probability distributions. We discuss the application of these results for designing and interpreting neurophysiological experiments that employ specific instances of this ideal observer model.
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Affiliation(s)
- Gopathy Purushothaman
- Department of Cell and Developmental Biology, Vanderbilt University Medical SchoolNashville, TN, USA
| | - Vivien A. Casagrande
- Department of Cell and Developmental Biology, Vanderbilt University Medical SchoolNashville, TN, USA
- Departments of Psychology and Ophthalmalogy and Visual Sciences, Vanderbilt UniversityNashville, TN, USA
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Bednar JA. Building a mechanistic model of the development and function of the primary visual cortex. ACTA ACUST UNITED AC 2012; 106:194-211. [PMID: 22343520 DOI: 10.1016/j.jphysparis.2011.12.001] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2011] [Accepted: 12/16/2011] [Indexed: 10/28/2022]
Abstract
Researchers have used a very wide range of different experimental and theoretical approaches to help understand mammalian visual systems. These approaches tend to have quite different assumptions, strengths, and weaknesses. Computational models of the visual cortex, in particular, have typically implemented either a proposed circuit for part of the visual cortex of the adult, assuming a very specific wiring pattern based on findings from adults, or else attempted to explain the long-term development of a visual cortex region from an initially undifferentiated starting point. Previous models of adult V1 have been able to account for many of the measured properties of V1 neurons, while not explaining how these properties arise or why neurons have those properties in particular. Previous developmental models have been able to reproduce the overall organization of specific feature maps in V1, such as orientation maps, but are generally formulated at an abstract level that does not allow testing with real images or analysis of detailed neural properties relevant for visual function. In this review of results from a large set of new, integrative models developed from shared principles and a set of shared software components, I show how these models now represent a single, consistent explanation for a wide body of experimental evidence, and form a compact hypothesis for much of the development and behavior of neurons in the visual cortex. The models are the first developmental models with wiring consistent with V1, the first to have realistic behavior with respect to visual contrast, and the first to include all of the demonstrated visual feature dimensions. The goal is to have a comprehensive explanation for why V1 is wired as it is in the adult, and how that circuitry leads to the observed behavior of the neurons during visual tasks.
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Affiliation(s)
- James A Bednar
- Institute for Adaptive and Neural Computation, The University of Edinburgh, 10 Crichton St., EH8 9AB Edinburgh, UK.
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