scholarly journals The role of human ventral visual cortex in motion perception

Brain ◽  
2013 ◽  
Vol 136 (9) ◽  
pp. 2784-2798 ◽  
Author(s):  
Sharon Gilaie-Dotan ◽  
Ayse P. Saygin ◽  
Lauren J. Lorenzi ◽  
Ryan Egan ◽  
Geraint Rees ◽  
...  
eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Ingo Marquardt ◽  
Peter De Weerd ◽  
Marian Schneider ◽  
Omer Faruk Gulban ◽  
Dimo Ivanov ◽  
...  

Human visual surface perception has neural correlates in early visual cortex, but the role of feedback during surface segmentation in human early visual cortex remains unknown. Feedback projections preferentially enter superficial and deep anatomical layers, which provides a hypothesis for the cortical depth distribution of fMRI activity related to feedback. Using ultra-high field fMRI, we report a depth distribution of activation in line with feedback during the (illusory) perception of surface motion. Our results fit with a signal re-entering in superficial depths of V1, followed by a feedforward sweep of the re-entered information through V2 and V3. The magnitude and sign of the BOLD response strongly depended on the presence of texture in the background, and was additionally modulated by the presence of illusory motion perception compatible with feedback. In summary, the present study demonstrates the potential of depth-resolved fMRI in tackling biomechanical questions on perception.


2005 ◽  
Vol 21 (4) ◽  
pp. 1107-1115 ◽  
Author(s):  
Dave Saint-Amour ◽  
Vincent Walsh ◽  
Jean-Paul Guillemot ◽  
Maryse Lassonde ◽  
Franco Lepore

2019 ◽  
Vol 5 (1) ◽  
pp. 247-268 ◽  
Author(s):  
Peter Thier ◽  
Akshay Markanday

The cerebellar cortex is a crystal-like structure consisting of an almost endless repetition of a canonical microcircuit that applies the same computational principle to different inputs. The output of this transformation is broadcasted to extracerebellar structures by way of the deep cerebellar nuclei. Visually guided eye movements are accommodated by different parts of the cerebellum. This review primarily discusses the role of the oculomotor part of the vermal cerebellum [the oculomotor vermis (OMV)] in the control of visually guided saccades and smooth-pursuit eye movements. Both types of eye movements require the mapping of retinal information onto motor vectors, a transformation that is optimized by the OMV, considering information on past performance. Unlike the role of the OMV in the guidance of eye movements, the contribution of the adjoining vermal cortex to visual motion perception is nonmotor and involves a cerebellar influence on information processing in the cerebral cortex.


2008 ◽  
Vol 20 (7) ◽  
pp. 1847-1872 ◽  
Author(s):  
Mark C. W. van Rossum ◽  
Matthijs A. A. van der Meer ◽  
Dengke Xiao ◽  
Mike W. Oram

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.


2007 ◽  
Vol 47 (7) ◽  
pp. 887-898 ◽  
Author(s):  
Deborah Giaschi ◽  
Amy Zwicker ◽  
Simon Au Young ◽  
Bruce Bjornson

2017 ◽  
Vol 37 (28) ◽  
pp. 6628-6637 ◽  
Author(s):  
Nisha S. Pulimood ◽  
Wandilson dos Santos Rodrigues ◽  
Devon A. Atkinson ◽  
Sandra M. Mooney ◽  
Alexandre E. Medina

1998 ◽  
Vol 31 ◽  
pp. S324
Author(s):  
Nobuko Mataga ◽  
Brian G. Condie ◽  
Sayaka Fujishima ◽  
Takao K. Hensch

2018 ◽  
Vol 2018 ◽  
pp. 1-6
Author(s):  
B. L. Mayer ◽  
L. H. A. Monteiro

A Newman-Watts graph is formed by including random links in a regular lattice. Here, the emergence of synchronization in coupled Newman-Watts graphs is studied. The whole neural network is considered as a toy model of mammalian visual pathways. It is composed by four coupled graphs, in which a coupled pair represents the lateral geniculate nucleus and the visual cortex of a cerebral hemisphere. The hemispheres communicate with each other through a coupling between the graphs representing the visual cortices. This coupling makes the role of the corpus callosum. The state transition of neurons, supposed to be the nodes of the graphs, occurs in discrete time and it follows a set of deterministic rules. From periodic stimuli coming from the retina, the neuronal activity of the whole network is numerically computed. The goal is to find out how the values of the parameters related to the network topology affect the synchronization among the four graphs.


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