Matthew A. Smith, PhD

Title/Position
Adjunct Professor, Neuroscience
Professor, Biomedical Engineering, Carnegie Mellon University

    Education & Training

  • PhD, New York University, 2003
Research Interests

Understanding the brain's mechanisms for interpreting visual inputs, processing them, making decisions and eventually generating motor outputs, using a host of backgrounds, from computational approaches to electrophysiology.

In sighted individuals, vision is the foundation of perception and an important contributor to decision-making, planning, and memory. Yet the neuronal basis of how we construct internal representations of external visual scenes remains largely unknown. Research in the Smith laboratory is aimed at understanding how groups of neurons interact to construct our visual perception of the visual world and then access that perception in service of cognition and motor outputs. We do this with a host of methods, combining computational and experimental approaches to understand the brain and its functions in both normal and disease states. A particular focus of the work in the Smith lab involves bridging across scales and methodologies in neural engineering approaches, leveraging the information provided by each. This involves combining local signals from single neurons with more global signals such as electroencephalography at the scalp or near-infrared imaging of blood oxygenation in the brain.

Recent Publications

BR Cowley, PL Stan, JW Pillow*, MA Smith* [* equal contribution] (2026) Compact deep neural network models of visual cortex. Nature (Journal Link)

H Bong, V Ventura, EA Yttri, MA Smith, RE Kass (2026) Cross-population amplitude coupling in high-dimensional oscillatory neural time series. Front Comput Neurosci, volume 20 (Journal Link)

ME McDonnell*, A Umakantha*, RC Williamson*, MA Smith†, BM Yu† (2026) Interactions across hemispheres in prefrontal cortex reflect global cognitive processing. Nature Communications, 17: 5088 (Journal Link) [*,† equal contribution]

R Johnston, MA Smith (2026) Brain-wide arousal signals are segregated from movement planning in the superior colliculus. eLife 13:RP99278 (Journal Link)

J Soldado-Magraner, Y Minai, BM Yu*, MA Smith* (2025) Robustness of working memory to prefrontal cortex microstimulation. Journal of Neuroscience 30 May 2025, e2197242025; (Journal Link) [* equal contribution]

Y Minai, J Soldado-Magraner, MA Smith, BM Yu (2025) OMiSO: Adaptive optimization of state-dependent brain stimulation to shape neural population states. Advances in Neural Information Processing Systems, 38 (arXiv link)

MA Smith, SP Arun (2025) Carl R. Olson (1944-2024). Neuron 113 (6), 806-807 (Journal Link)

Y Minai, J Soldado-Magraner, MA Smith, BM Yu (2024) MiSO: Optimizing brain stimulation to create neural activity states. Advances in Neural Information Processing Systems, 37: 24126–24149 (Journal Link)

PL Stan, MA Smith (2024) Recent visual experience reshapes V4 neuronal activity and improves perceptual performance. Journal of Neuroscience 9 October 2024, 44 (41) e1764232024 (Journal Link)

S Wu, C Huang, AC Snyder, MA Smith*, B Doiron*, BM Yu* (2024) Automated customization of large-scale spiking network models to neuronal population activity. Nature Computational Science, 4, 690–705 (Journal Link) [* equal contribution]

K Yu, S Schmitt, Y Ni, EC Crane, MA Smith, B He (2024) Transcranial focused ultrasound remotely modulates extrastriate visual cortex by stimulating frontal eye field with subregion specificity. Journal of Neural Engineering, 21 (6): 066018 (Journal Link)