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.

scholarly journals Re-thinking the functional organization of human visual cortex

2012 ◽  
Vol 12 (9) ◽  
pp. 817-817
Author(s):  
K. Weiner ◽  
K. Grill-Spector
Keyword(s):  
Visual Cortex ◽  
Functional Organization ◽  
Human Visual Cortex

scholarly journals Functional organization of human visual cortex in occipital polymicrogyria

2007 ◽  
Vol 28 (12) ◽  
pp. 1302-1312 ◽  
Author(s):  
Serge O. Dumoulin ◽  
Jeffrey D. Jirsch ◽  
Andrea Bernasconi
Keyword(s):  
Visual Cortex ◽  
Functional Organization ◽  
Human Visual Cortex

Mapping of functional organization in human visual cortex: Electrical cortical stimulation

Neurology ◽  
2000 ◽  
Vol 54 (4) ◽  
pp. 849-854 ◽  
Author(s):  
H. W. Lee ◽  
S. B. Hong ◽  
D. W. Seo ◽  
W. S. Tae ◽  
S. C. Hong
Keyword(s):  
Visual Cortex ◽  
Functional Organization ◽  
Cortical Stimulation ◽  
Human Visual Cortex

scholarly journals Human intracranial recordings link suppressed transients rather than 'filling-in' to perceptual continuity across blinks

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Tal Golan ◽  
Ido Davidesco ◽  
Meir Meshulam ◽  
David M Groppe ◽  
Pierre Mégevand ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Neural Correlates ◽  
Activity Level ◽  
Human Visual Cortex ◽  
Eye Blinks ◽  
Visual Activity ◽  
Visual Hierarchy ◽  
Video Frames ◽  
Visual Areas ◽  
Intracranial Recordings

We hardly notice our eye blinks, yet an externally generated retinal interruption of a similar duration is perceptually salient. We examined the neural correlates of this perceptual distinction using intracranially measured ECoG signals from the human visual cortex in 14 patients. In early visual areas (V1 and V2), the disappearance of the stimulus due to either invisible blinks or salient blank video frames ('gaps') led to a similar drop in activity level, followed by a positive overshoot beyond baseline, triggered by stimulus reappearance. Ascending the visual hierarchy, the reappearance-related overshoot gradually subsided for blinks but not for gaps. By contrast, the disappearance-related drop did not follow the perceptual distinction – it was actually slightly more pronounced for blinks than for gaps. These findings suggest that blinks' limited visibility compared with gaps is correlated with suppression of blink-related visual activity transients, rather than with "filling-in" of the occluded content during blinks.

scholarly journals Coherent representations of subjective spatial position in primary visual cortex and hippocampus

2017 ◽  
Author(s):  
Aman B. Saleem ◽  
E. Mika Diamanti ◽  
Julien Fournier ◽  
Kenneth D. Harris ◽  
Matteo Carandini
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Spatial Location ◽  
Visual Responses ◽  
V1 Neurons ◽  
Neuronal Populations ◽  
Subjective Estimate ◽  
Ca1 Region ◽  
Navigational Systems

A major role of vision is to guide navigation, and navigation is strongly driven by vision1-4. Indeed, the brain’s visual and navigational systems are known to interact5, 6, and signals related to position in the environment have been suggested to appear as early as in visual cortex6, 7. To establish the nature of these signals we recorded in primary visual cortex (V1) and in the CA1 region of the hippocampus while mice traversed a corridor in virtual reality. The corridor contained identical visual landmarks in two positions, so that a purely visual neuron would respond similarly in those positions. Most V1 neurons, however, responded solely or more strongly to the landmarks in one position. This modulation of visual responses by spatial location was not explained by factors such as running speed. To assess whether the modulation is related to navigational signals and to the animal’s subjective estimate of position, we trained the mice to lick for a water reward upon reaching a reward zone in the corridor. Neuronal populations in both CA1 and V1 encoded the animal’s position along the corridor, and the errors in their representations were correlated. Moreover, both representations reflected the animal’s subjective estimate of position, inferred from the animal’s licks, better than its actual position. Indeed, when animals licked in a given location – whether correct or incorrect – neural populations in both V1 and CA1 placed the animal in the reward zone. We conclude that visual responses in V1 are tightly controlled by navigational signals, which are coherent with those encoded in hippocampus, and reflect the animal’s subjective position in the environment. The presence of such navigational signals as early as in a primary sensory area suggests that these signals permeate sensory processing in the cortex.

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 The Normalization Model Captures the Effects of Object-based Attention in the Human Visual Cortex

2021 ◽  
Author(s):  
Narges Doostani ◽  
Gholam-Ali Hossein-Zadeh ◽  
Maryam Vaziri-Pashkam
Keyword(s):  
Visual Cortex ◽  
Human Brain ◽  
Human Visual Cortex ◽  
Visual Hierarchy ◽  
Primate Brain ◽  
Object Based

Here, we report that normalization model can capture the effects of object-based attention across the visual hierarchy in the human brain. We used superimposed pairs of objects and asked participants to attend to different targets. Modeling voxel responses, we demonstrated that the normalization model outperforms other models in predicting voxel responses in the presence of attention. Our results propose normalization as a canonical computation operating in the primate brain.

scholarly journals Perception and memory have distinct spatial tuning properties in human visual cortex

2019 ◽  
Author(s):  
Serra E. Favila ◽  
Brice A. Kuhl ◽  
Jonathan Winawer
Keyword(s):  
Visual Cortex ◽  
Memory Retrieval ◽  
Poor Performance ◽  
Long Term Memory ◽  
Human Visual Cortex ◽  
Visual Areas ◽  
The Hierarchical Structure ◽  
Retinotopic Organization ◽  
Insight Into

AbstractReactivation of earlier perceptual activity is thought to underlie long-term memory recall. Despite evidence for this view, it is unknown whether mnemonic activity exhibits the same tuning properties as feedforward perceptual activity. Here, we leveraged population receptive field models to parameterize fMRI activity in human visual cortex during spatial memory retrieval. Though retinotopic organization was present during both perception and memory, large systematic differences in tuning were also evident. Notably, whereas there was a three-fold decline in spatial precision from early to late visual areas during perception, this property was entirely abolished during memory retrieval. This difference could not be explained by reduced signal-to-noise or poor performance on memory trials. Instead, by simulating top-down activity in a network model of cortex, we demonstrate that this property is well-explained by the hierarchical structure of the visual system. Our results provide insight into the computational constraints governing memory reactivation in sensory cortex.

scholarly journals Predicting brain function from anatomy using geometric deep learning

2020 ◽  
Author(s):  
Fernanda L. Ribeiro ◽  
Steffen Bollmann ◽  
Alexander M. Puckett
Keyword(s):  
Deep Learning ◽  
Visual Cortex ◽  
Brain Function ◽  
Functional Organization ◽  
Human Vision ◽  
Complex Biological System ◽  
Actual Structure ◽  
Hierarchical Processing ◽  
Human Visual Cortex ◽  
And Function

AbstractWhether it be in a single neuron or a more complex biological system like the human brain, form and function are often directly related. The functional organization of human visual cortex, for instance, is tightly coupled with the underlying anatomy. This is seen in properties such as cortical magnification (i.e., there is more cortex dedicated to processing foveal vs. peripheral information) as well as in the presence, placement, and connectivity of multiple visual areas – which is critical for the hierarchical processing underpinning the rich experience of human vision. Here we developed a geometric deep learning model capable of exploiting the actual structure of the cortex to learn the complex relationship between brain function and anatomy in human visual cortex. We show that our neural network was not only able to predict the functional organization throughout the visual cortical hierarchy, but that it was also able to predict nuanced variations across individuals. Although we demonstrate its utility for modeling the relationship between structure and function in human visual cortex, geometric deep learning is flexible and well-suited for a range of other applications involving data structured in non-Euclidean spaces.

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