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

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.

2021 ◽  
Vol 17 (8) ◽  
pp. e1009267
Author(s):  
Kshitij Dwivedi ◽  
Michael F. Bonner ◽  
Radoslaw Martin Cichy ◽  
Gemma Roig

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.


2020 ◽  
Author(s):  
Kshitij Dwivedi ◽  
Michael F. Bonner ◽  
Radoslaw Martin Cichy ◽  
Gemma Roig

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.


2008 ◽  
Vol 28 (40) ◽  
pp. 10056-10061 ◽  
Author(s):  
S. L. Bressler ◽  
W. Tang ◽  
C. M. Sylvester ◽  
G. L. Shulman ◽  
M. Corbetta

2009 ◽  
Vol 98 (2) ◽  
pp. 85-89 ◽  
Author(s):  
M. S. Vafaee ◽  
S. Marrett ◽  
E. Meyer ◽  
A. C. Evans ◽  
A. Gjedde

Sign in / Sign up

Export Citation Format

Share Document