Vikaas Sohal
Associate professor
University of California, San Francisco
From this contributor
‘Outdated’ mouse model exposes key disruptions in autism brain
A mouse model based on exposure to an epilepsy drug offers a useful window into the brain circuits altered in autism.
‘Outdated’ mouse model exposes key disruptions in autism brain
Understanding contradictory connectivity reports in autism
Studies at the level of neural circuits are needed to better understand the importance of both increased and decreased connectivity between different regions in the autism brain, say John Rubenstein and Vikaas Sohal.
Understanding contradictory connectivity reports in autism
Targeting brain microcircuits may help treat autism
Understanding the function of neuronal circuits, specifically microcircuits in the prefrontal cortex and elsewhere in the brain, will play a major role in translating research findings into new autism treatments, says Vikaas Sohal.
Targeting brain microcircuits may help treat autism
Explore more from The Transmitter
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Sharing Africa’s brain data: Q&A with Amadi Ihunwo
These data are “virtually mandatory” to advance neuroscience, says Ihunwo, a co-investigator of the Brain Research International Data Governance & Exchange (BRIDGE) initiative, which seeks to develop a global framework for sharing, using and protecting neuroscience data.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
Cortical structures in infants linked to future language skills; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 19 May.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.
The BabyLM Challenge: In search of more efficient learning algorithms, researchers look to infants
A competition that trains language models on relatively small datasets of words, closer in size to what a child hears up to age 13, seeks solutions to some of the major challenges of today’s large language models.