The roles of supervised machine learning in systems neuroscience
Over the last several years, the use of machine learning (ML) in neuroscience has been
rapidly increasing. Here, we review ML's contributions, both realized and potential, across …
rapidly increasing. Here, we review ML's contributions, both realized and potential, across …
Modeling statistical dependencies in multi-region spike train data
Neural computations underlying cognition and behavior rely on the coordination of neural
activity across multiple brain areas. Understanding how brain areas interact to process …
activity across multiple brain areas. Understanding how brain areas interact to process …
Long-term stability of single neuron activity in the motor system
How an established behavior is retained and consistently produced by a nervous system in
constant flux remains a mystery. One possible solution to ensure long-term stability in motor …
constant flux remains a mystery. One possible solution to ensure long-term stability in motor …
Circumstantial evidence and explanatory models for synapses in large-scale spike recordings
IH Stevenson - arXiv preprint arXiv:2304.09699, 2023 - arxiv.org
Whether, when, and how causal interactions between neurons can be meaningfully studied
from observations of neural activity alone are vital questions in neural data analysis. Here …
from observations of neural activity alone are vital questions in neural data analysis. Here …
Network modeling of dynamic brain interactions predicts emergence of neural information that supports human cognitive behavior
RD Mill, JL Hamilton, EC Winfield, N Lalta… - PLoS …, 2022 - journals.plos.org
How cognitive task behavior is generated by brain network interactions is a central question
in neuroscience. Answering this question calls for the development of novel analysis tools …
in neuroscience. Answering this question calls for the development of novel analysis tools …
The Hybrid Drive: a chronic implant device combining tetrode arrays with silicon probes for layer-resolved ensemble electrophysiology in freely moving mice
M Guardamagna, R Eichler, R Pedrosa… - Journal of Neural …, 2022 - iopscience.iop.org
Objective. Understanding the function of brain cortices requires simultaneous investigation
at multiple spatial and temporal scales and to link neural activity to an animal's behavior. A …
at multiple spatial and temporal scales and to link neural activity to an animal's behavior. A …
Detecting rhythmic spiking through the power spectra of point process model residuals
Objective. Oscillations figure prominently as neurological disease hallmarks and
neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to …
neuromodulation targets. To detect oscillations in a neuron's spiking, one might attempt to …
Linear-nonlinear cascades capture synaptic dynamics
J Rossbroich, D Trotter, J Beninger… - PLoS computational …, 2021 - journals.plos.org
Short-term synaptic dynamics differ markedly across connections and strongly regulate how
action potentials communicate information. To model the range of synaptic dynamics …
action potentials communicate information. To model the range of synaptic dynamics …
Modeling the short-term dynamics of in vivo excitatory spike transmission
Information transmission in neural networks is influenced by both short-term synaptic
plasticity (STP) as well as nonsynaptic factors, such as after-hyperpolarization currents and …
plasticity (STP) as well as nonsynaptic factors, such as after-hyperpolarization currents and …
A convolutional neural network for estimating synaptic connectivity from spike trains
The recent increase in reliable, simultaneous high channel count extracellular recordings is
exciting for physiologists and theoreticians because it offers the possibility of reconstructing …
exciting for physiologists and theoreticians because it offers the possibility of reconstructing …