Five exceptional graduate students from across the University of California have been named the inaugural UC Noyce Graduate Student Fellows, launching a new program designed to support the next genera...

UCSB associate professor of computer science Michael Beyeler and his colleagues used a deep-learning model to design patterns of electrical stimulation for electrodes temporarily implanted in the visual cortex — the region at the back of the brain that processes visual information — of a blind participant.

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Visual systems evolved to extract behaviorally relevant information while animals move through and interact with their world. Such ecological vision differs fundamentally from standard laboratory paradigms in many key aspects, making this a much harder problem for the brain to solve, and for the neuroscientist to study. However, emerging technologies and experimental approaches have enabled investigation of visual computations under these ecological conditions. These approaches are particularly powerful in the mouse, combining well-developed genetic tools, high-throughput recordings, and quantifiable ethological tasks. Here we review computations that are engaged in ecological contexts, including active sensing, motion processing, scene analysis, distance estimation, and spatial perception. We delineate experimental approaches that engage these computations and synthesize current understanding of their neural implementations based on mouse research. These studies reveal how ecological vision engages distinct processing strategies and novel neural circuitry, while highlighting the vast territory that remains unexplored in understanding real-world visual computation.

Workshop at IEEE ISMAR 2026

Every time you lift a finger, your brain generates a small electrical signal that travels down the spinal cord, branches out through peripheral nerves, and arrives at a muscle with a specific instruct...

We review computations that are engaged in ecological contexts, including active sensing, motion processing, scene analysis, distance estimation, and spatial perception.

We propose a systematic, quantitative approach to detect and characterize unsafe stimulation patterns in ML-driven neurostimulation systems.

Human-aligned deep learning models exhibit behaviors consistent with human values, such as robustness, fairness, and honesty. Transferring these behavioral properties to models trained on different ta...

Can your AI visually navigate better than a mouse?

Can your AI visually navigate better than a mouse?

School officials defend software as bulwark against ransomware, but professors fear potential surveillance of their devices

Visual robustness under real-world conditions remains a critical bottleneck for modern reinforcement learning agents. In contrast, biological systems such as mice show remarkable resilience to environ...

UC researchers and the patients they work with are showing the world what's possible when the human mind and advanced computers meet.

Discover cutting-edge research, events, and insights in bionic vision and sight restoration.

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Oct 2-5 2025University of Minnesota, Twin Cities, MN

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