scholarly journals Unveiling functions of the visual cortex using task-specific deep neural networks

2021 ◽  
Vol 17 (8) ◽  
pp. e1009267
Author(s):  
Kshitij Dwivedi ◽  
Michael F. Bonner ◽  
Radoslaw Martin Cichy ◽  
Gemma Roig
Keyword(s):  
Neural Networks ◽  
Visual Cortex ◽  
Deep Neural Networks ◽  
Scene Perception ◽  
Dorsal Stream ◽  
Brain Regions ◽  
Functional Mapping ◽  
Human Visual Cortex ◽  
Visual Tasks ◽  
Cortical Regions

The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We related human brain responses to scene images measured with functional MRI (fMRI) systematically to a diverse set of deep neural networks (DNNs) optimized to perform different scene perception tasks. We found a structured mapping between DNN tasks and brain regions along the ventral and dorsal visual streams. Low-level visual tasks mapped onto early brain regions, 3-dimensional scene perception tasks mapped onto the dorsal stream, and semantic tasks mapped onto the ventral stream. This mapping was of high fidelity, with more than 60% of the explainable variance in nine key regions being explained. Together, our results provide a novel functional mapping of the human visual cortex and demonstrate the power of the computational approach.

scholarly journals Unveiling functions of the visual cortex using task-specific deep neural networks

2020 ◽  
Author(s):  
Kshitij Dwivedi ◽  
Michael F. Bonner ◽  
Radoslaw Martin Cichy ◽  
Gemma Roig
Keyword(s):  
Neural Networks ◽  
Visual Cortex ◽  
Deep Neural Networks ◽  
Scene Perception ◽  
Dorsal Stream ◽  
Brain Regions ◽  
Functional Mapping ◽  
Human Visual Cortex ◽  
Visual Tasks ◽  
Cortical Regions

AbstractThe human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We related human brain responses to scene images measured with functional MRI (fMRI) systematically to a diverse set of deep neural networks (DNNs) optimized to perform different scene perception tasks. We found a structured mapping between DNN tasks and brain regions along the ventral and dorsal visual streams. Low-level visual tasks mapped onto early brain regions, 3-dimensional scene perception tasks mapped onto the dorsal stream, and semantic tasks mapped onto the ventral stream. This mapping was of high fidelity, with more than 60% of the explainable variance in nine key regions being explained. Together, our results provide a novel functional mapping of the human visual cortex and demonstrate the power of the computational approach.

scholarly journals Synthesizing images from deep neural networks to map the hierarchy of feature complexity in human visual cortex

2020 ◽  
Vol 20 (11) ◽  
pp. 556
Author(s):  
Jeffrey Wammes ◽  
Kailong Peng ◽  
Kenneth Norman ◽  
Nicholas Turk-Browne
Keyword(s):  
Neural Networks ◽  
Visual Cortex ◽  
Deep Neural Networks ◽  
Human Visual Cortex

scholarly journals Effects of task and attentional selection on responses in human visual cortex

2013 ◽  
Vol 109 (10) ◽  
pp. 2606-2617 ◽  
Author(s):  
Erik Runeson ◽  
Geoffrey M. Boynton ◽  
Scott O. Murray
Keyword(s):  
Visual Cortex ◽  
Physical Properties ◽  
Spatial Attention ◽  
Visual Stimulation ◽  
Color Discrimination ◽  
Attentional Processes ◽  
Human Visual Cortex ◽  
Visual Tasks ◽  
Modular Layout ◽  
Cortical Regions

Multiple visual tasks can be performed on the same visual input, with different tasks presumably engaging different neuronal populations. The modular layout of the visual system implies that specific cortical regions carry more information about certain stimulus attributes than others. Thus it is reasonable to assume that decisions during a task will be optimal if they are based on the responses of the most informative neuronal signals, which presumably originate in regions with the sharpest tuning for the relevant stimulus feature. Previous studies have supported this position. Here we present the results of two fMRI experiments that confirm these findings and expand on earlier investigations by addressing the effects of the physical properties of an attended stimulus on task-related modulations in human visual cortex. Specifically, we ask whether performing two-alternative forced choice speed- and color-discrimination tasks (and other attentional processes) can modulate neural activity independent of visual stimulation and whether the effect of spatial attention depends on which task is being performed. The results indicate that 1) when stimulation and spatial attention are constant, responses in V4 and MT+ depend on the task being performed and are independent of the tested physical properties of the selected stimulus, 2) this task-dependent modulation might require a stimulus—task-specific preparatory mechanisms alone are not sufficient to drive responses, and 3) independent of which task is being performed, spatial attention adds a baseline shift to responses in MT+ and V4 when a stimulus is present.

scholarly journals Disentangling Representations of Object Shape and Object Category in Human Visual Cortex: The Animate–Inanimate Distinction

2016 ◽  
Vol 28 (5) ◽  
pp. 680-692 ◽  
Author(s):  
Daria Proklova ◽  
Daniel Kaiser ◽  
Marius V. Peelen
Keyword(s):  
Visual Cortex ◽  
Activity Patterns ◽  
Temporal Cortex ◽  
Brain Regions ◽  
Visual Object ◽  
Object Category ◽  
Human Visual Cortex ◽  
Object Properties ◽  
Occipitotemporal Cortex ◽  
Visual Properties

Objects belonging to different categories evoke reliably different fMRI activity patterns in human occipitotemporal cortex, with the most prominent distinction being that between animate and inanimate objects. An unresolved question is whether these categorical distinctions reflect category-associated visual properties of objects or whether they genuinely reflect object category. Here, we addressed this question by measuring fMRI responses to animate and inanimate objects that were closely matched for shape and low-level visual features. Univariate contrasts revealed animate- and inanimate-preferring regions in ventral and lateral temporal cortex even for individually matched object pairs (e.g., snake–rope). Using representational similarity analysis, we mapped out brain regions in which the pairwise dissimilarity of multivoxel activity patterns (neural dissimilarity) was predicted by the objects' pairwise visual dissimilarity and/or their categorical dissimilarity. Visual dissimilarity was measured as the time it took participants to find a unique target among identical distractors in three visual search experiments, where we separately quantified overall dissimilarity, outline dissimilarity, and texture dissimilarity. All three visual dissimilarity structures predicted neural dissimilarity in regions of visual cortex. Interestingly, these analyses revealed several clusters in which categorical dissimilarity predicted neural dissimilarity after regressing out visual dissimilarity. Together, these results suggest that the animate–inanimate organization of human visual cortex is not fully explained by differences in the characteristic shape or texture properties of animals and inanimate objects. Instead, representations of visual object properties and object category may coexist in more anterior parts of the visual system.

scholarly journals Functional Mapping of the Human Visual Cortex with Intravoxel Incoherent Motion MRI

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0117706 ◽  
Author(s):  
Christian Federau ◽  
Kieran O’Brien ◽  
Adrien Birbaumer ◽  
Reto Meuli ◽  
Patric Hagmann ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Functional Mapping ◽  
Intravoxel Incoherent Motion ◽  
Human Visual Cortex ◽  
Motion Mri

Functional mapping of the human visual cortex by magnetic resonance imaging

Science ◽  
1991 ◽  
Vol 254 (5032) ◽  
pp. 716-719 ◽  
Author(s):  
J. Belliveau ◽  
D. Kennedy ◽  
R. McKinstry ◽  
B. Buchbinder ◽  
R. Weisskoff ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Visual Cortex ◽  
Magnetic Resonance ◽  
Functional Mapping ◽  
Resonance Imaging ◽  
Human Visual Cortex

scholarly journals Heritable functional architecture in human visual cortex

2020 ◽  
Author(s):  
Ivan Alvarez ◽  
Nonie J. Finlayson ◽  
Shwe Ei ◽  
Benjamin de Haas ◽  
John A. Greenwood ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Functional Organization ◽  
Spatial Location ◽  
Genetic Determination ◽  
Human Visual Cortex ◽  
Neuronal Populations ◽  
Visual Hierarchy ◽  
Retinotopic Organization ◽  
Cortical Regions ◽  
Genetically Determined

AbstractHow much of the functional organization of our visual system is inherited? Here we tested the heritability of retinotopic maps in human visual cortex using functional magnetic resonance imaging. We demonstrate that retinotopic organization shows a closer correspondence in monozygotic (MZ) compared to dizygotic (DZ) twin pairs, suggesting a partial genetic determination. Using population receptive field (pRF) analysis to examine the preferred spatial location and selectivity of these neuronal populations, we further demonstrate that across cortical regions V1-V3, map architecture was more similar in MZ than DZ twins. The heritability of spatial selectivity, as quantified by pRF size, increased across the visual hierarchy. Our findings are consistent with heritability in both the arrangement of areal boundaries and stimulus tuning properties of visual cortex. This could constitute a neural substrate for variations in a range of perceptual effects, which themselves have been found to be at least partially genetically determined.

Functional mapping of the human visual cortex at 4 and 1.5 tesla using deoxygenation contrast EPI

1993 ◽  
Vol 29 (2) ◽  
pp. 277-279 ◽  
Author(s):  
R. Turner ◽  
P. Jezzard ◽  
H. Wen ◽  
K. K. Kwong ◽  
D. Le Bihan ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Functional Mapping ◽  
Human Visual Cortex
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