All Outputs (16)

The computational bottleneck of basal ganglia output (and what to do about it) (2024)
Journal Article
Humphries, M. D. (in press). The computational bottleneck of basal ganglia output (and what to do about it). eNeuro,

What the basal ganglia do is an oft-asked question; answers range from the selection of actions to the specification of movement to the estimation of time. Here I argue that \emph{how} the basal ganglia do what they do is a less-asked but equally imp... Read More about The computational bottleneck of basal ganglia output (and what to do about it).

Motor cortex latent dynamics encode spatial and temporal arm movement parameters independently. (2024)
Journal Article
Colins Rodriguez, A., Perich, M. G., Miller, L., & Humphries, M. D. (2024). Motor cortex latent dynamics encode spatial and temporal arm movement parameters independently. Journal of Neuroscience, 44(35), Article e1777232024. https://doi.org/10.1523/JNEUROSCI.1777-23.2024

The fluid movement of an arm requires multiple spatiotemporal parameters to be set independently. Recent studies have argued that arm movements are generated by the collective dynamics of neurons in motor cortex. An untested prediction of this hypoth... Read More about Motor cortex latent dynamics encode spatial and temporal arm movement parameters independently..

Activity Subspaces in Medial Prefrontal Cortex Distinguish States of the World (2022)
Journal Article
Maggi, S., & Humphries, M. D. (2022). Activity Subspaces in Medial Prefrontal Cortex Distinguish States of the World. Journal of Neuroscience, 42(20), 4131-4146. https://doi.org/10.1523/JNEUROSCI.1412-21.2022

Medial prefrontal cortex (mPfC) activity represents information about the state of the world, including present behavior, such as decisions, and the immediate past, such as short-term memory. Unknown is whether information about different states of t... Read More about Activity Subspaces in Medial Prefrontal Cortex Distinguish States of the World.

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.

Maladaptive striatal plasticity and abnormal reward‐learning in cervical dystonia (2019)
Journal Article
Gilbertson, T., Humphries, M., & Steele, J. D. (2019). Maladaptive striatal plasticity and abnormal reward‐learning in cervical dystonia. European Journal of Neuroscience, 50(7), 3191-3204. https://doi.org/10.1111/ejn.14414

In monogenetic generalized forms of dystonia, in vitro neurophysiological recordings have demonstrated direct evidence for abnormal plasticity at the level of the cortico‐striatal synapse. It is unclear whether similar abnormalities contribute to the... Read More about Maladaptive striatal plasticity and abnormal reward‐learning in cervical dystonia.

Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues during Active Tactile Decision Making (2019)
Journal Article
Campagner, D., Evans, M. H., Chlebikova, K., Colins-Rodriguez, A., Loft, M. S., Fox, S., …Petersen, R. S. (2019). Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues during Active Tactile Decision Making. Journal of Neuroscience, 39(20), 3921-3933. https://doi.org/10.1523/jneurosci.2217-18.2019

Perceptual decision making is an active process where animals move their sense organs to extract task-relevant information. To investigate how the brain translates sensory input into decisions during active sensation, we developed a mouse active touc... Read More about Prediction of Choice from Competing Mechanosensory and Choice-Memory Cues during Active Tactile Decision Making.

Medial prefrontal cortex population activity is plastic irrespective of learning (2019)
Journal Article
Singh, A., Peyrache, A., & Humphries, M. D. (2019). Medial prefrontal cortex population activity is plastic irrespective of learning. Journal of Neuroscience, 39(18), 3470-3483. https://doi.org/10.1523/JNEUROSCI.1370-17.2019

The prefrontal cortex is thought to learn the relationships between actions and their outcomes. But little is known about what changes to population activity in prefrontal cortex are specific to learning these relationships. Here we characterise the... Read More about Medial prefrontal cortex population activity is plastic irrespective of learning.

An ensemble code in medial prefrontal cortex links prior events to outcomes during learning (2018)
Journal Article
Maggi, S., Peyrache, A., & Humphries, M. D. (2018). An ensemble code in medial prefrontal cortex links prior events to outcomes during learning. Nature Communications, 9(1), Article 2204. https://doi.org/10.1038/s41467-018-04638-2

The prefrontal cortex is implicated in learning the rules of an environment through trial and error. But it is unclear how such learning is related to the prefrontal cortex’s role in short-term memory. Here we ask if the encoding of short-term memory... Read More about An ensemble code in medial prefrontal cortex links prior events to outcomes during learning.

Insights into Parkinson’s disease from computational models of the basal ganglia (2018)
Journal Article
Humphries, M. D., Obeso, J. A., & Dreyer, J. K. (2018). Insights into Parkinson’s disease from computational models of the basal ganglia. Journal of Neurology, Neurosurgery and Psychiatry, https://doi.org/10.1136/jnnp-2017-315922

Movement disorders arise from the complex interplay of multiple changes to neural circuits. Successful treatments for these disorders could interact with these complex changes in myriad ways, and as a consequence their mechanisms of action and their... Read More about Insights into Parkinson’s disease from computational models of the basal ganglia.

A probabilistic, distributed, recursive mechanism for decision-making in the brain (2018)
Journal Article
Caballero, J. A., Humphries, M. D., & Gurney, K. N. (2018). A probabilistic, distributed, recursive mechanism for decision-making in the brain. PLoS Computational Biology, 14(4), Article e1006033. https://doi.org/10.1371/journal.pcbi.1006033

Decision formation recruits many brain regions, but the procedure they jointly execute is unknown. Here we characterize its essential composition, using as a framework a novel recursive Bayesian algorithm that makes decisions based on spike-trains wi... Read More about A probabilistic, distributed, recursive mechanism for decision-making in the brain.

A spiral attractor network drives rhythmic locomotion (2017)
Journal Article
Bruno, A. M., Frost, W. N., & Humphries, M. D. (2017). A spiral attractor network drives rhythmic locomotion. eLife, 6, Article e27342. https://doi.org/10.7554/elife.27342

The joint activity of neural populations is high dimensional and complex. One strategy for reaching a tractable understanding of circuit function is to seek the simplest dynamical system that can account for the population activity. By imaging Aplysi... Read More about A spiral attractor network drives rhythmic locomotion.

Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program (2015)
Journal Article
Bruno, A., Frost, W., & Humphries, M. (2015). Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program. Neuron, 86(1), 304-318. https://doi.org/10.1016/j.neuron.2015.03.005

The neural substrates of motor programs are only well understood for small, dedicated circuits. Here we investigate how a motor program is constructed within a large network. We imaged populations of neurons in the Aplysia pedal ganglion during execu... Read More about Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program.

A new framework for cortico-striatal plasticity: behavioural theory meets In vitro data at the reinforcement-action interface (2015)
Journal Article
Gurney, K. N., Humphries, M. D., & Redgrave, P. (2015). A new framework for cortico-striatal plasticity: behavioural theory meets In vitro data at the reinforcement-action interface. PLoS Biology, 13(1), Article e1002034. https://doi.org/10.1371/journal.pbio.1002034

Operant learning requires that reinforcement signals interact with action representations at a suitable neural interface. Much evidence suggests that this occurs when phasic dopamine, acting as a reinforcement prediction error, gates plasticity at co... Read More about A new framework for cortico-striatal plasticity: behavioural theory meets In vitro data at the reinforcement-action interface.