Rate My Professor Mark Humphries

Mark Humphries is Chair in Computational Neuroscience in the School of Psychology, Faculty of Science, at the University of Nottingham. He completed his PhD and postdoctoral training at the University of Sheffield. Following this, he held a three-year fellowship at the École Normale Supérieure in Paris and a prestigious seven-year Senior Research Fellowship from the UK Medical Research Council. In his current role, he leads the Humphries Lab, a neural data lab supported by the Medical Research Council, BBSRC, and Innovate UK.

Humphries is a systems neuroscientist who employs computational and statistical models to study brain function, rather than animal models. His research interrogates how the joint activity of many neurons encodes the past, present, and future to guide behaviour. The lab develops data analysis techniques for recordings of hundreds or thousands of neurons across tasks, circuits, species, and phyla, and creates theoretical and computational models explaining this joint activity from underlying neural circuits. Key focus areas include the basal ganglia, brainstem, sensory and prefrontal cortex, and invertebrate locomotion systems, with recurrent interest in dopamine's role. Humphries has pioneered the use of network theory tools to analyze large-scale neural recordings, including unsupervised detection of cell assemblies and tracking correlated activity dynamics over time and learning. Notable publications include 'Dynamical networks: finding, measuring, and tracking neural population activity using network science' (Network Neuroscience, 2017), 'A spiral attractor network drives rhythmic locomotion' (eLife, 2017, with Bruno and Frost), 'Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program' (Neuron, 2015), 'Insights into Parkinson's disease from computational models of the basal ganglia' (Journal of Neurology, Neurosurgery, and Psychiatry, 2018, with Obeso and Dreyer), and 'An ensemble code in medial prefrontal cortex links prior events to outcomes during learning' (Nature Communications, 2018, with Maggi and Peyrache). He authored the popular science book 'The Spike: An Epic Journey Through the Brain in 2.1 Seconds' (Princeton University Press, 2021). His scholarship has amassed over 6,400 citations, with an h-index of 30. Humphries contributes to public discourse through essays on The Spike blog, columns for The Transmitter, and podcast discussions on neural data science and Parkinson's modeling. He has released open-source code for neural analysis techniques.