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Anne Churchland

4 accepted papers

2025

Shared-AE: Automatic Identification of Shared Subspaces in High-dimensional Neural and Behavioral Activity

ICLR 2025poster

Understanding the relationship between behavior and neural activity is crucial for understanding brain function. An effective method is to learn embeddings for interconnected modalities. For simple behavioral tasks, neural features can be learned based on labels. However, complex behaviors, such as…

2021

Decentralized Motion Inference and Registration of Neuropixel Data

ICASSP 2021accepted

Multi-electrode arrays such as "Neuropixels" probes enable the study of neuronal voltage signals at high temporal and single-cell spatial resolution. However, in vivo recordings from these devices often experience some shifting of the probe (due e.g. to animal movement), resulting in poorly localize…

Cited by 0SourceScholar
2019

BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos

NeurIPS 2019poster

A fundamental goal of systems neuroscience is to understand the relationship between neural activity and behavior. Behavior has traditionally been characterized by low-dimensional, task-related variables such as movement speed or response times. More recently, there has been a growing interest in au…

2017

OnACID: Online Analysis of Calcium Imaging Data in Real Time

NeurIPS 2017poster

Optical imaging methods using calcium indicators are critical for monitoring the activity of large neuronal populations in vivo. Imaging experiments typically generate a large amount of data that needs to be processed to extract the activity of the imaged neuronal sources. While deriving such proces…

Cited by 85SourcePDFScholar