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8 results

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Sensory predictions are embedded in cortical motor activity

Jonathan A Michaels, Mehrdad Kashefi, Jack Zheng et al. · COSYNE 2023

…Delayed sensory feedback is generally too slow to allow accurate state estimation during responses to external forces, so the nervous system may solve this problem by using prior information to make rapid sensory predictions during feedback control. However, it is unknown how flexibly these priors can be set nor how neural activity underlies these fundamental abilities. To answer this, we designed a reaching task in which subjects (human or m

ePoster · Neuroscience

…circuit, reciprocal feedback connections produce a compressed thalamic representation of the computations performed in the prefrontal cortex. In inspiration, we use a neural network with a separate latent task representation and introduce a simple algorithm that uses optimization to rapidly infer and generate representations

ePoster · Computational Neuroscience

Sensory feedback can drive adaptation in motor cortex and facilitate generalization

Barbara Feulner, Matthew G. Perich, Lee E. Miller et al. · COSYNE 2022

Experimental and computational studies suggest that motor cortex acts as a feedback controller, allowing for ‘on-the-fly’ movement corrections in response to afferent sensory feedback. However, it remains unclear whether feedback control relates to longer-term learning, and how this would be implemented in neural circuitry. Here, we tackled these questions by testing how a recurrent neural network (RNN) can use feedback to control its own output, and whether this process can enable learning. We built an RNN that received feedback signaling the error between its intended and observed output. An

ePoster · Computational Neuroscience

Credit Assignment in Neural Networks through Deep Feedback Control

Alexander Meulemans · Institute of Neuroinformatics, University of Zürich and ETH Zürich

…Here, we introduce Deep Feedback Control (DFC), a new learning method that uses a feedback controller to drive a deep neural network to match a desired output target and whose con

Thu, Sep 30, 2021 · 13:00 UTC

Seminar · Machine Learning

…Ca2+ has long been hypothesized as a feedback control signal, the source of Ca2+ and the molecular machinery enabling network-wide homeostatic responses remain largely unknown. I will present our hypothesis and framework on identifying homeostatic regulators i

Thu, Jun 3, 2021 · 15:00 UTC

Seminar · Neuroscience

…has enabled new insights into motor control and learning. In this talk, I’ll first present an example study where sensory-motor loop manipulations in BMI allowed us to probe feed-forward and feedback control mechanisms in ways that are not possible in the natural motor system. This study shed light on sensorimotor processing, and in turn led to state-of

Fri, Oct 9, 2020 · 15:00 UTC

Seminar · Neuroscience

Animals rely on an internal sense of body position and movement to effectively control motor behaviour. This sense of proprioception is mediated by diverse populations of internal mechanosensory neurons distributed throughout the body. My lab is trying to understand how proprioceptive stimuli are detected by sensory neurons, integrated and transformed in central circuits, and used to guide motor output. We approach these questions using genetic tools, in vivo two-photon imaging, and patch-clamp electrophysiology in Drosophila. We recently found that the axons of fly leg proprioceptors are o

Wed, May 13, 2020 · 06:00 UTC

Seminar · Neuroscience