Upcoming Events
Past Events
3:00 PM Ramyzy Al-Mulla Lab: Smear (Psych)
3:15 PM Hylen James Lab: Smear (Psych)
3:30 PM Alanna Sowles Lab: Huxtable (Human Phys)
3:45 PM Will Gaston Lab: Wollman (Human Phys)
Abstract- The superior colliculus (SC) is an evolutionarily conserved structure that receives direct retinal input in all vertebrates. It was the most sophisticated visual center until the neocortex evolved in mammals. Even in mice and tree shrews, mammalian species that are increasingly used in vision research, the vast majority of retinal ganglion cells project to the SC, making it a prominent visual structure in these animals. In this talk, I will review our recent functional studies of the mouse SC and describe our current efforts in linking functional properties to genetically identified cell types in both mice and tree shrews.
Dr. Daniel Lashof is a Senior Fellow at the World Resources Institute and previously served
as Director of WRl's programmatic work in the United States.
For more than three decades, Dr. Lashof has worked to promote solutions to climate change. Before the World Resources Institute, Dan was the Chief Operating Officer of NextGen Policy Center and previously served as the Director of the Climate and Clean Air Program at the Natural Resources Defense Council.
His focus is developing federal and state regulations to place enforceable limits on carbon dioxide and other heat-trapping pollutants, responsibly scale up carbon dioxide removal, and properly account for the impact of land use in climate and fuels policies. He has participated in scientific assessments of global warming through the Intergovernmental Panel on Climate Change and has monitored international climate negotiations since their inception. He has testified at numerous Congressional and California legislative hearings
and posts articles regularly on WRI Insights.
Dr. Lashof earned his Bachelor's degree in Physics and Mathematics at Harvard and his
Doctorate from the Energy and Resources Group at the University of California, Berkeley.
Abstract: Sensory systems continuously adapt their responses based on the statistics of the environment. The response changes induced by adaptation have been characterized in detail at the single-neuron level and in trial-averaged populations. However, it remains unclear how adaptation modifies aspects of representations that relate more directly to stimulus perception. To address this question, we recorded from a population of neurons in mouse V1 while presenting stimulus sequences sampled from different statistical distributions. Surprisingly, discriminability increased between more frequent stimuli, even as responses to those stimuli decreased—an effect we reproduced in artificial networks trained to reconstruct stimuli under metabolic constraints. Furthermore, we found that the average population response follows a power law of stimulus probability with an exponent invariant across environments. Our efficient coding framework reproduced this power law and explained its invariance. These results suggest that the observed adaptation-induced changes in neural representations reflect a common trade-off between representational fidelity and metabolic cost, consistent with efficient coding.