Building population models for large-scale neural recordings: opportunities and pitfalls

02/03/2021
by   Cole Hurwitz, et al.
0

Modern extracellular recording technologies now enable simultaneous recording from large numbers of neurons. This has driven the development of new statistical models for analyzing and interpreting neural population activity. Here we provide a broad overview of recent developments in this area. We compare and contrast different approaches, highlight strengths and limitations, and discuss biological and mechanistic insights that these methods provide. While still an area of active development, there are already a number of powerful models for interpreting large scale neural recordings even in complex experimental settings.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/05/2023

Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures

Modern neural recording techniques allow neuroscientists to obtain spiki...
research
02/14/2023

Detecting human and non-human vocal productions in large scale audio recordings

We propose an automatic data processing pipeline to extract vocal produc...
research
05/29/2019

Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference

Extracellular recordings using modern, dense probes provide detailed foo...
research
03/11/2020

Model Order Reduction in Neuroscience

The human brain contains approximately 10^9 neurons, each with approxima...
research
02/04/2022

Identifying stimulus-driven neural activity patterns in multi-patient intracranial recordings

Identifying stimulus-driven neural activity patterns is critical for stu...
research
08/31/2021

Bubblewrap: Online tiling and real-time flow prediction on neural manifolds

While most classic studies of function in experimental neuroscience have...

Please sign up or login with your details

Forgot password? Click here to reset