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Distinguished Speaker Series | Jack Gallant, PhD

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https://ucihealth.zoom.us/j/94483669170?pwd=WUd1clg2aUM1bnpPVHd3MlkwTUN1Zz09
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The Center for Translational Vision Research Distinguished Speaker Series, also known as "Friday Seminars" showcases innovative research across the world. The seminar series has now been expanded to include lectures by experts on topics ranging from Ophthalmology, Genetics, Biochemistry, Neurobiology, Imaging, Computational Sciences to Novel Ophthalmic Treatments.

All talks are hybrid. You can join us in person at

The Susan & Henry Samueli College of Health Sciences 

Sue Gross Auditorium.

You can also join us by zoom. Zoom link and information are on your right and in the calendar links above.

October 18, 2024 | Jack Gallant, PhD

A biologically plausible hierarchical convolutional energy model explains V4 responses during natural vision.

 

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Jack Gallant, PhD
Jack Gallant, PhD
  • Professor, Department of Neuroscience, Co-director of the Brain Imaging Center (BIC), University of California, Berkeley

New preprint! Model connectivity: leveraging the power of encoding models to overcome the limitations of functional connectivity (Meschke et al., in review). Functional connectivity (FC) is the most popular method for recovering functional networks of brain areas with fMRI. However, because FC is defined as temporal correlations in brain activity, FC networks are inevitably confounded by noise and their function cannot be determined directly from FC. To overcome these limitations, we have developed model connectivity (MC). MC is defined as similarities in encoding model weights, which quantify reliable functional activity in terms of interpretable stimulus- or task-related features. In this paper we compare these two methods directly in a language comprehension dataset. We confirm the confounds of FC, and we show that MC does not suffer from these confounds. MC recovers more spatially localized networks and it reveals their functional assignment. MC is powerful tool for recovering the functional networks that support complex cognitive processes.