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Dr
Emory University and Georgia Tech
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Schedule
Wednesday, June 12, 2024
2:00 PM Europe/London
Domain
NeuroscienceHost
NeuroAI UCL
Duration
70 minutes
Large-scale recordings of neural activity are providing new opportunities to study network-level dynamics with unprecedented detail. However, the sheer volume of data and its dynamical complexity are major barriers to uncovering and interpreting these dynamics. I will present latent factor analysis via dynamical systems, a sequential autoencoding approach that enables inference of dynamics from neuronal population spiking activity on single trials and millisecond timescales. I will also discuss recent adaptations of the method to uncover dynamics from neural activity recorded via 2P Calcium imaging. Finally, time permitting, I will mention recent efforts to improve the interpretability of deep-learning based dynamical systems models.
Chethan Pandarinath
Dr
Emory University and Georgia Tech
neuro
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