Skip to main content

Research Repository

Advanced Search

All Outputs (4)

Bayesian Mapping of the Striatal Microcircuit Reveals Robust Asymmetries in the Probabilities and Distances of Connections (2021)
Journal Article
Cinotti, F., & Humphries, M. D. (2022). Bayesian Mapping of the Striatal Microcircuit Reveals Robust Asymmetries in the Probabilities and Distances of Connections. Journal of Neuroscience, 42(8), 1417-1435. https://doi.org/10.1523/JNEUROSCI.1487-21.2021

The striatum’s complex microcircuit is made by connections within and between its D1- and D2-receptor expressing projection neurons and at least five species of interneuron. Precise knowledge of this circuit is likely essential to understanding stria... Read More about Bayesian Mapping of the Striatal Microcircuit Reveals Robust Asymmetries in the Probabilities and Distances of Connections.

Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia (2021)
Journal Article
Humphries, M. D., & Gurney, K. (2021). Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia. Biological Cybernetics, 115(4), 323-329. https://doi.org/10.1007/s00422-021-00887-5

How does your brain decide what you will do next? Over the past few decades compelling evidence has emerged that the basal ganglia, a collection of nuclei in the fore- and mid-brain of all vertebrates, are vital to action selection. Gurney, Prescott,... Read More about Making decisions in the dark basement of the brain: A look back at the GPR model of action selection and the basal ganglia.

Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models (2021)
Journal Article
Humphries, M. D., Caballero, J. A., Evans, M., Maggi, S., & Singh, A. (2021). Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models. PLoS ONE, 16(7), Article e0254057. https://doi.org/10.1371/journal.pone.0254057

Discovering low-dimensional structure in real-world networks requires a suitable null model that defines the absence of meaningful structure. Here we introduce a spectral approach for detecting a network's low-dimensional structure, and the nodes tha... Read More about Spectral estimation for detecting low-dimensional structure in networks using arbitrary null models.

Strong and weak principles of neural dimension reduction (2021)
Journal Article
Humphries, M. D. (2021). Strong and weak principles of neural dimension reduction. Neurons, Behavior, Data Analysis, and Theory, 5(2), https://doi.org/10.51628/001c.24619

If spikes are the medium, what is the message? Answering that question is driving the development of large-scale, single neuron resolution recordings from behaving animals, on the scale of thousands of neurons. But these data are inherently high-dime... Read More about Strong and weak principles of neural dimension reduction.