scholarly journals Characterization of Feedback Neurons in the High-Level Visual Cortical Areas That Project Directly to the Primary Visual Cortex in the Cat

2021 ◽  
Vol 14 ◽  
Author(s):  
Huijun Pan ◽  
Shen Zhang ◽  
Deng Pan ◽  
Zheng Ye ◽  
Hao Yu ◽  
...  
Keyword(s):  
Information Processing ◽  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Higher Order ◽  
Top Down ◽  
Cortical Areas ◽  
Area 21A ◽  
High Level ◽  
Visual Cortical

Previous studies indicate that top-down influence plays a critical role in visual information processing and perceptual detection. However, the substrate that carries top-down influence remains poorly understood. Using a combined technique of retrograde neuronal tracing and immunofluorescent double labeling, we characterized the distribution and cell type of feedback neurons in cat’s high-level visual cortical areas that send direct connections to the primary visual cortex (V1: area 17). Our results showed: (1) the high-level visual cortex of area 21a at the ventral stream and PMLS area at the dorsal stream have a similar proportion of feedback neurons back projecting to the V1 area, (2) the distribution of feedback neurons in the higher-order visual area 21a and PMLS was significantly denser than in the intermediate visual cortex of area 19 and 18, (3) feedback neurons in all observed high-level visual cortex were found in layer II–III, IV, V, and VI, with a higher proportion in layer II–III, V, and VI than in layer IV, and (4) most feedback neurons were CaMKII-positive excitatory neurons, and few of them were identified as inhibitory GABAergic neurons. These results may argue against the segregation of ventral and dorsal streams during visual information processing, and support “reverse hierarchy theory” or interactive model proposing that recurrent connections between V1 and higher-order visual areas constitute the functional circuits that mediate visual perception. Also, the corticocortical feedback neurons from high-level visual cortical areas to the V1 area are mostly excitatory in nature.

A collicular visual cortex: Neocortical space for an ancient midbrain visual structure

Science ◽  
2019 ◽  
Vol 363 (6422) ◽  
pp. 64-69 ◽  
Author(s):  
Riccardo Beltramo ◽  
Massimo Scanziani
Keyword(s):  
Cerebral Cortex ◽  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Cortical Area ◽  
Moving Objects ◽  
Visual Responses ◽  
Visual Cortical Area ◽  
Postrhinal Cortex ◽  
Visual Cortical

Visual responses in the cerebral cortex are believed to rely on the geniculate input to the primary visual cortex (V1). Indeed, V1 lesions substantially reduce visual responses throughout the cortex. Visual information enters the cortex also through the superior colliculus (SC), but the function of this input on visual responses in the cortex is less clear. SC lesions affect cortical visual responses less than V1 lesions, and no visual cortical area appears to entirely rely on SC inputs. We show that visual responses in a mouse lateral visual cortical area called the postrhinal cortex are independent of V1 and are abolished upon silencing of the SC. This area outperforms V1 in discriminating moving objects. We thus identify a collicular primary visual cortex that is independent of the geniculo-cortical pathway and is capable of motion discrimination.

scholarly journals Biological variation in the sizes, shapes and locations of visual cortical areas in the mouse

2018 ◽  
Author(s):  
Jack Waters ◽  
Eric Lee ◽  
Nathalie Gaudreault ◽  
Fiona Griffin ◽  
Jerome Lecoq ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Biological Variation ◽  
Measurement Noise ◽  
Cortical Areas ◽  
Retinotopic Maps ◽  
Visual Areas ◽  
Visual Cortical ◽  
Cortical Visual Areas ◽  
Processing Of Visual Information

ABSTRACTVisual cortex is organized into discrete sub-regions or areas that are arranged into a hierarchy and serve different functions in the processing of visual information. In our previous work, we noted that retinotopic maps of cortical visual areas differed between mice, but did not quantify these differences or determine the relative contributions of biological variation and measurement noise. Here we quantify the biological variation in the size, shape and locations of 11 visual areas in the mouse. We find that there is substantial biological variation in the sizes of visual areas, with some visual areas varying in size by two-fold across the population of mice.

scholarly journals Generative perspective of the primary visual cortex

2021 ◽  
Author(s):  
Zedong Bi
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Power Law ◽  
Computational Models ◽  
Higher Order ◽  
Top Down ◽  
Complex Cells ◽  
Shape Morphing ◽  
Neural Representations ◽  
Learning Principles

According to analysis-by-synthesis theories of perception, the primary visual cortex (V1) reconstructs visual stimuli through top-down pathway, and higher-order cortex reconstructs V1 activity. Experiments also found that neural representations are generated in a top-down cascade during visual imagination. What code does V1 provide higher-order cortex to reconstruct or simulate to improve perception or imaginative creativity? What unsupervised learning principles shape V1 for reconstructing stimuli so that V1 activity eigenspectrum is power-law with close-to-1 exponent? Using computational models, we reveal that reconstructing the activities of V1 complex cells facilitate higher-order cortex to form representations smooth to shape morphing of stimuli, improving perception and creativity. Power-law eigenspectrum with close-to-1 exponent results from the constraints of sparseness and temporal slowness when V1 is reconstructing stimuli, at a sparseness strength that best whitens V1 code and makes the exponent most insensitive to slowness strength. Our results provide fresh insights into V1 computation.

scholarly journals A new framework for understanding vision from the perspective of the primary visual cortex

2019 ◽  
Author(s):  
Li Zhaoping
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Saliency Map ◽  
Foveal Vision ◽  
Additional Information ◽  
Cortical Areas ◽  
Foveal Region ◽  
Analysis By Synthesis ◽  
Visual Cortical ◽  
New Framework

Visual attention selects only a tiny fraction of visual input informationfor further processing. Selection starts in the primary visual cortex (V1), which creates abottom-up saliency map to guide the fovea to selected visual locations via gaze shifts.This motivates a new framework that views visionas consisting of encoding, selection, and decoding stages, placingselection on center stage. It suggests a massive loss of non-selectedinformation from V1 downstream along the visual pathway.Hence, feedback from downstream visual cortical areas to V1 for better decoding (recognition),through analysis-by-synthesis, should query for additional information and be mainly directed atthe foveal region. Accordingly, non-foveal vision is not only poorer in spatial resolution,but also more susceptible to many illusions.

scholarly journals Pulvinar Modulates Contrast Responses in the Visual Cortex as a Function of Cortical Hierarchy

2019 ◽  
Vol 30 (3) ◽  
pp. 1068-1086 ◽  
Author(s):  
Bruno Oliveira Ferreira de Souza ◽  
Nelson Cortes ◽  
Christian Casanova
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Theoretical Data ◽  
Visual Neurons ◽  
Cortical Areas ◽  
Cortical Hierarchy ◽  
Area 21A ◽  
Contrast Response Function ◽  
Contrast Response ◽  
The Impact

Abstract The pulvinar is the largest extrageniculate visual nucleus in mammals. Given its extensive reciprocal connectivity with the visual cortex, it allows the cortico-thalamocortical transfer of visual information. Nonetheless, knowledge of the nature of the pulvinar inputs to the cortex remains elusive. We investigated the impact of silencing the pulvinar on the contrast response function of neurons in 2 distinct hierarchical cortical areas in the cat (areas 17 and 21a). Pulvinar inactivation altered the response gain in both areas, but with larger changes observed in area 21a. A theoretical model was proposed, simulating the pulvinar contribution to cortical contrast responses by modifying the excitation-inhibition balanced state of neurons across the cortical hierarchy. Our experimental and theoretical data showed that the pulvinar exerts a greater modulatory influence on neuronal activity in area 21a than in the primary visual cortex, indicating that the pulvinar impact on cortical visual neurons varies along the cortical hierarchy.

scholarly journals Effects of individuation and grouping on face representations in the visual cortex

2018 ◽  
Author(s):  
Hyehyeon Kim ◽  
Gayoung Kim ◽  
Sue-Hyun Lee
Keyword(s):  
Information Processing ◽  
Visual Cortex ◽  
Face Perception ◽  
Response Patterns ◽  
Top Down ◽  
Identity Recognition ◽  
Face Area ◽  
The Face ◽  
Early Visual Cortex ◽  
High Level

AbstractTop-down signals can influence our visual perception by providing guidance on information processing. Especially, top-down control between two basic frameworks, “Individuation” and “grouping”, is critical for information processing during face perception. Individuation of faces supports identity recognition while grouping subserves higher category level face perception such as race or gender. However, it still remains elusive how top-down dependent control between individuation and grouping affects cortical representations during face perception. Here we performed an fMRI experiment to investigate whether representations across early and high-level visual areas can be altered by top-down control between individuation and grouping process during face perception. Focusing on neural response patterns across the early visual cortex (EVC) and the face-selective area (the fusiform face area (FFA)), we found that the discriminability of individual faces from the response patterns was strong in the FFA but weak in the EVC during the individuation task whereas the EVC but not the FFA showed significant face discrimination during the grouping tasks. Thus, these findings suggest that the representation of face information across the early and high-level visual cortex is flexible depending on the top-down control of the perceptual framework between individuation and grouping.

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