Ph.D.
Massachusetts Institute of Technology
2012
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Faculty
Faculty
Dominique Pritchett
Associate Professor, Director of Graduate Studies
Department/Office
- Biology
School/College
- College of Arts & Sciences
Biography
Dominique Pritchett, Ph.D. is an Associate Professor of Biology at Howard University, Director of Graduate Studies, and Co-Director of the Neurodegeneration Computational Fellows (NDCF) Program funded by the Chan Zuckerberg Initiative. His research integrates systems neuroscience, whole-brain imaging, electrophysiology, and AI/ML to investigate how cerebellar circuits coordinate distributed brain-wide activity to support cognitive and motor functions. His lab uses larval zebrafish light-sheet calcium imaging and multi-electrode recordings in mouse models to examine network dynamics, gamma oscillations, and learning mechanisms, with a particular focus on how molecular perturbations (e.g., Grin2A mutations, anesthesia) alter circuit function. He also leads NSF- and Army-funded projects developing AI/ML pipelines for neural data, including CNNs, LSTMs, and state-space models such as Mamba-SSM.
Dr. Pritchett is deeply invested in computational training and workforce development. He teaches Animal Physiology and Neuroscience with a core lab component introducing biology majors to Python coding and machine learning. He leads an NSF-funded seminar on AI for image processing that connects students to summer research experiences in computational neuroscience. As Co-Director of the NDCF post-baccalaureate program, he prepares trainees to apply bioinformatics and AI approaches to neurodegeneration research in collaboration with Howard University Hospital and Columbia University. He is also developing Stanford and Army partnerships to build high-bandwidth, real-time, closed-loop neural interfacing capacity and advance AI-driven analysis of large-scale neural datasets.
Dr. Pritchett has a strong record of collaboration across disciplines and institutions, partnering with colleagues at NIH/NINDS, Janelia Research Campus, Brookhaven National Lab, Stanford, and the Howard CS and Math departments. His work bridges molecular mechanisms, circuit computation, and network-level coordination to reveal how the brain learns and adapts. Through research, teaching, grant development, and program leadership, he is shaping a new generation of neuroscientists fluent in both experimental biology and computational science.
Education & Expertise
Education
B.S.
Virginia State University
2004
Expertise
Circuit Mechanisms of Learning and Memory
Cerebellar coordination
Optogenetics/chemogenetics
Sensorimotor and cognitive integration
Network state analysis
AI/ML pipelines for neuroscience
Academics
Academics
Animal Physiology (BIOL 341)
Neurobiology (BIOL444)
Research
Research
Specialty
Learning and MemoryGroup Information
Dominique Pritchett, Ph.D. is an Associate Professor of Biology at Howard University, Director of Graduate Studies, and Co-Director of the Neurodegeneration Computational Fellows (NDCF) Program funded by the Chan Zuckerberg Initiative. His research integrates systems neuroscience, whole-brain imaging, electrophysiology, and AI/ML to investigate how cerebellar circuits coordinate distributed brain-wide activity to support cognitive and motor functions. His lab uses larval zebrafish light-sheet calcium imaging and multi-electrode recordings in mouse models to examine network dynamics, gamma oscillations, and learning mechanisms, with a particular focus on how molecular perturbations (e.g., Grin2A mutations, anesthesia) alter circuit function. He also leads NSF- and Army-funded projects developing AI/ML pipelines for neural data, including CNNs, LSTMs, and state-space models such as Mamba-SSM.
Dr. Pritchett is deeply invested in computational training and workforce development. He teaches Animal Physiology and Neuroscience with a core lab component introducing biology majors to Python coding and machine learning. He leads an NSF-funded seminar on AI for image processing that connects students to summer research experiences in computational neuroscience. As Co-Director of the NDCF post-baccalaureate program, he prepares trainees to apply bioinformatics and AI approaches to neurodegeneration research in collaboration with Howard University Hospital and Columbia University. He is also developing Stanford and Army partnerships to build high-bandwidth, real-time, closed-loop neural interfacing capacity and advance AI-driven analysis of large-scale neural datasets.
Dr. Pritchett has a strong record of collaboration across disciplines and institutions, partnering with colleagues at NIH/NINDS, Janelia Research Campus, Brookhaven National Lab, Stanford, and the Howard CS and Math departments. His work bridges molecular mechanisms, circuit computation, and network-level coordination to reveal how the brain learns and adapts. Through research, teaching, grant development, and program leadership, he is shaping a new generation of neuroscientists fluent in both experimental biology and computational science.
Google Scholar: https://scholar.google.com/citations?user=NTM94R4AAAAJ&hl=en
Research Gate: https://www.researchgate.net/profile/Dominique_Pritchett
Publications and Presentations
Publications and Presentations
Locomotor activity modulates associative learning in mouse cerebellum
Albergaria C, Silva NT, Pritchett DL, Carey MR. (2017). Locomotor activity modulates associative learning in mouse cerebellum. Nat Neurosci. 2018 May 21(5). doi: 10.1038/s41593-018-0129-x
For things needing your attention: the role of neocortical gamma in sensory perception
Pritchett DL, Siegle JH, Deister CA, Moore CI. (2015). For things needing your attention: the role of neocortical gamma in sensory perception. Curr. Opin Neurobiol. 31, 254 - 263.
Attention drives synchronization of alpha and beta rhythms between right inferior frontal and primary sensory neocortex
Sacchet MD, LaPlante RA, Wan Q, Pritchett DL, Lee AK, Hämäläinen M, Moore CI, Kerr CE, Jones SR. (2015). Attention drives synchronization of alpha and beta rhythms between right inferior frontal and primary sensory neocortex. J Neurosci. 35(5), 2074-2082.
Gamma-range synchronization of fast-spiking interneurons can enhance detection of tactile stimuli
Siegle JH*, Pritchett DL*, Moore CI. (2014). Gamma-range synchronization of fast-spiking interneurons can enhance detection of tactile stimuli. Nat Neurosci. 17(10), 1371-1379.
A matter of trial and error for motor learning
Pritchett DL, Carey MR. (2014). A matter of trial and error for motor learning. Trends Neurosci. 37(9), 465-466.
The flexDrive: an ultra-light implant for optical control and highly parallel chronic recording of neuronal ensembles
Voigts J, Siegle JH, Pritchett DL, Moore CI. (2013). The flexDrive: an ultra-light implant for optical control and highly parallel chronic recording of neuronal ensembles in freely moving mice. Frontiers in System Neuroscience. 13, 7-8.
Dynamics of dynamics within a single data acquisition session: variation in neocortical alpha oscillations in human MEG.
Wan Q, Kerr C, Pritchett D, Hämäläinen M, Moore C, Jones S. (2011). Dynamics of dynamics within a single data acquisition session: variation in neocortical alpha oscillations in human MEG. Plos One. 6(9), e24941.
Effects of mindfulness meditation training on anticipatory alpha modulation in primary somatosensory cortex
Kerr CE, Jones SR, Wan Q, Pritchett DL, Wasserman RH, Wexler A, Villanueva JJ, Shaw JR, Lazar SW, Kaptchuk TJ, Littenberg R, Hämäläinen MS, Moore CI. (2011). Effects of mindfulness meditation training on anticipatory alpha modulation in primary somatosensory cortex. Brain Res Bull. 85(3-4), 96-103.
Local dynamic gain modulation drives enhanced efficacy and efficiency of signal transmission.
Knoblich U, Siegle JH, Pritchett DL, Moore CI. (2011). What do we gain from gamma? Local dynamic gain modulation drives enhanced efficacy and efficiency of signal transmission. Front. Hum. Neurosci. 4, 185.
Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory cortex
Jones SR, Kerr CE, Wan Q, Pritchett DL, Hämäläinen M, Moore CI. (2010). Cued spatial attention drives functionally relevant modulation of the mu rhythm in primary somatosensory cortex. J. Neurosci. 30(41) 13760 - 13765.
Transformations in oscillatory activity and evoked responses in primary somatosensory
Ziegler DA, Pritchett DL, Hosseini-Varnamkhasti P, Corkin S, Hämäläinen M, Moore CI, Jones SR. (2010). Transformations in oscillatory activity and evoked responses in primary somatosensory cortex in middle age: a combined computational neural modeling and MEG study. Neuroimage. 52(3) 897 - 912.
Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm
Jones SR, Pritchett DL, Sikora MA, Stufflebeam SM, Hämäläinen M, Moore CI. (2009). Quantitative analysis and biophysically realistic neural modeling of the MEG mu rhythm: rhythmogenesis and modulation of sensory-evoked responses. J. Neurophysiol. 102(6), 3554-3572.
Neural correlates of tactile detection: a combined magnetoencephalography and biophysically
Jones SR, Pritchett DL, Stufflebeam SM, Hämäläinen M, Moore CI. (2007). Neural correlates of tactile detection: a combined magnetoencephalography and biophysically based computational modeling study. J. Neurosci. 27(40), 10751 - 10764.