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Denagamage S, Morton MP, Hudson NV, Nandy AS. Widespread receptive field remapping in early primate visual cortex. Cell Rep 2024; 43:114557. [PMID: 39058592 PMCID: PMC11484688 DOI: 10.1016/j.celrep.2024.114557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 04/24/2024] [Accepted: 07/13/2024] [Indexed: 07/28/2024] Open
Abstract
Predictive remapping of receptive fields (RFs) is thought to be one of the critical mechanisms for enforcing perceptual stability during eye movements. While RF remapping has been observed in several cortical areas, its role in early visual cortex and its consequences on the tuning properties of neurons have been poorly understood. Here, we track remapping RFs in hundreds of neurons from visual area V2 while subjects perform a cued saccade task. We find that remapping is widespread in area V2 across neurons from all recorded cortical layers and cell types. Furthermore, our results suggest that remapping RFs not only maintain but also transiently enhance their feature selectivity due to untuned suppression. Taken together, these findings shed light on the dynamics and prevalence of remapping in the early visual cortex, forcing us to revise current models of perceptual stability during saccadic eye movements.
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Affiliation(s)
- Sachira Denagamage
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06510, USA.
| | - Mitchell P Morton
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06510, USA
| | - Nyomi V Hudson
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Anirvan S Nandy
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06510, USA; Kavli Institute for Neuroscience, Yale University, New Haven, CT 06510, USA; Wu Tsai Institute, Yale University, New Haven, CT 06510, USA; Department of Psychology, Yale University, New Haven, CT 06510, USA.
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Weng G, Akbarian A, Clark K, Noudoost B, Nategh N. Neural correlates of perisaccadic visual mislocalization in extrastriate cortex. Nat Commun 2024; 15:6335. [PMID: 39068199 PMCID: PMC11283495 DOI: 10.1038/s41467-024-50545-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 07/10/2024] [Indexed: 07/30/2024] Open
Abstract
When interacting with the visual world using saccadic eye movements (saccades), the perceived location of visual stimuli becomes biased, a phenomenon called perisaccadic mislocalization. However, the neural mechanism underlying this altered visuospatial perception and its potential link to other perisaccadic perceptual phenomena have not been established. Using the electrophysiological recording of extrastriate areas in four male macaque monkeys, combined with a computational model, we were able to quantify spatial bias around the saccade target (ST) based on the perisaccadic dynamics of extrastriate spatiotemporal sensitivity captured by a statistical model. This approach could predict the perisaccadic spatial bias around the ST, consistent with behavioral data, and revealed the precise neuronal response components underlying representational bias. These findings also establish the crucial role of increased sensitivity near the ST for neurons with receptive fields far from the ST in driving the ST spatial bias. Moreover, we showed that, by allocating more resources for visual target representation, visual areas enhance their representation of the ST location, even at the expense of transient distortions in spatial representation. This potential neural basis for perisaccadic ST representation also supports a general role for extrastriate neurons in creating the perception of stimulus location.
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Affiliation(s)
- Geyu Weng
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Amir Akbarian
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Kelsey Clark
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Behrad Noudoost
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, USA.
| | - Neda Nategh
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, USA.
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA.
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Xiao W, Sharma S, Kreiman G, Livingstone MS. Feature-selective responses in macaque visual cortex follow eye movements during natural vision. Nat Neurosci 2024; 27:1157-1166. [PMID: 38684892 PMCID: PMC11156562 DOI: 10.1038/s41593-024-01631-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 03/26/2024] [Indexed: 05/02/2024]
Abstract
In natural vision, primates actively move their eyes several times per second via saccades. It remains unclear whether, during this active looking, visual neurons exhibit classical retinotopic properties, anticipate gaze shifts or mirror the stable quality of perception, especially in complex natural scenes. Here, we let 13 monkeys freely view thousands of natural images across 4.6 million fixations, recorded 883 h of neuronal responses in six areas spanning primary visual to anterior inferior temporal cortex and analyzed spatial, temporal and featural selectivity in these responses. Face neurons tracked their receptive field contents, indicated by category-selective responses. Self-consistency analysis showed that general feature-selective responses also followed eye movements and remained gaze-dependent over seconds of viewing the same image. Computational models of feature-selective responses located retinotopic receptive fields during free viewing. We found limited evidence for feature-selective predictive remapping and no viewing-history integration. Thus, ventral visual neurons represent the world in a predominantly eye-centered reference frame during natural vision.
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Affiliation(s)
- Will Xiao
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
| | - Saloni Sharma
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Gabriel Kreiman
- Department of Ophthalmology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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Weng G, Clark K, Akbarian A, Noudoost B, Nategh N. Time-varying generalized linear models: characterizing and decoding neuronal dynamics in higher visual areas. Front Comput Neurosci 2024; 18:1273053. [PMID: 38348287 PMCID: PMC10859875 DOI: 10.3389/fncom.2024.1273053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 01/09/2024] [Indexed: 02/15/2024] Open
Abstract
To create a behaviorally relevant representation of the visual world, neurons in higher visual areas exhibit dynamic response changes to account for the time-varying interactions between external (e.g., visual input) and internal (e.g., reward value) factors. The resulting high-dimensional representational space poses challenges for precisely quantifying individual factors' contributions to the representation and readout of sensory information during a behavior. The widely used point process generalized linear model (GLM) approach provides a powerful framework for a quantitative description of neuronal processing as a function of various sensory and non-sensory inputs (encoding) as well as linking particular response components to particular behaviors (decoding), at the level of single trials and individual neurons. However, most existing variations of GLMs assume the neural systems to be time-invariant, making them inadequate for modeling nonstationary characteristics of neuronal sensitivity in higher visual areas. In this review, we summarize some of the existing GLM variations, with a focus on time-varying extensions. We highlight their applications to understanding neural representations in higher visual areas and decoding transient neuronal sensitivity as well as linking physiology to behavior through manipulation of model components. This time-varying class of statistical models provide valuable insights into the neural basis of various visual behaviors in higher visual areas and hold significant potential for uncovering the fundamental computational principles that govern neuronal processing underlying various behaviors in different regions of the brain.
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Affiliation(s)
- Geyu Weng
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
| | - Kelsey Clark
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
| | - Amir Akbarian
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
| | - Behrad Noudoost
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
| | - Neda Nategh
- Department of Ophthalmology and Visual Sciences, University of Utah, Salt Lake City, UT, United States
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, United States
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Weng G, Akbarian A, Clark K, Noudoost B, Nategh N. Neural correlates of perisaccadic visual mislocalization in extrastriate cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565871. [PMID: 37986765 PMCID: PMC10659380 DOI: 10.1101/2023.11.06.565871] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
When interacting with the visual world using saccadic eye movements (saccades), the perceived location of visual stimuli becomes biased, a phenomenon called perisaccadic mislocalization, which is indeed an exemplar of the brain's dynamic representation of the visual world. However, the neural mechanism underlying this altered visuospatial perception and its potential link to other perisaccadic perceptual phenomena have not been established. Using a combined experimental and computational approach, we were able to quantify spatial bias around the saccade target (ST) based on the perisaccadic dynamics of extrastriate spatiotemporal sensitivity captured by statistical models. This approach could predict the perisaccadic spatial bias around the ST, consistent with the psychophysical studies, and revealed the precise neuronal response components underlying representational bias. These findings also established the crucial role of response remapping toward ST representation for neurons with receptive fields far from the ST in driving the ST spatial bias. Moreover, we showed that, by allocating more resources for visual target representation, visual areas enhance their representation of the ST location, even at the expense of transient distortions in spatial representation. This potential neural basis for perisaccadic ST representation, also supports a general role for extrastriate neurons in creating the perception of stimulus location.
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Affiliation(s)
- Geyu Weng
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Ophthalmology and V7isual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Amir Akbarian
- Department of Ophthalmology and V7isual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Kelsey Clark
- Department of Ophthalmology and V7isual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Behrad Noudoost
- Department of Ophthalmology and V7isual Sciences, University of Utah, Salt Lake City, UT, USA
| | - Neda Nategh
- Department of Ophthalmology and V7isual Sciences, University of Utah, Salt Lake City, UT, USA
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
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