Reza Abbasi-Asl, PhD

Assistant Professor

Neurology

+1 415 476-3199

We are a research team at the University of California, San Francisco where we investigate the role of advanced computational tools in understanding brain functions and its related disorders. More specifically, our research program revolves around the development of interpretable machine learning tools to (1) integrate multi-modal data collected from the brain (and body) in both microscopic and macroscopic resolutions, (2) predict functions of biological systems in different resolutions, and (3) determine the functional differences across neurological disorders. We are a part of the Neuroscape Center and Cognitive Neuroscience division at UCSF and our team is supported through funding from NIH National Institute of Mental Health, NIH National Institute of Aging, Weill Neurohub, Sandler Program for Breakthrough in Biomedical Research, UCSF Innovation Ventures, and Google.

Publications

Robustness tests for biomedical foundation models should tailor to specifications.

npj Digital Medicine

Xian RP, Baker NR, David T, Cui Q, Holmgren AJ, Bauer S, Sushil M, Abbasi-Asl R

Imaging joy with generalized slice dithered enhanced resolution and SWAT reconstruction: 3T high spatial-temporal resolution fMRI.

Frontiers in neuroimaging

Townsend JD, Muller AM, Naeem Z, Beckett A, Kalisetti B, Abbasi-Asl R, Liao C, Vu AT

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies.

bioRxiv : the preprint server for biology

Wagner-Carena J, Kate S, Riordan T, Abbasi-Asl R, Aman J, Amster A, Bodor AL, Brittain D, Buchanan JA, Buice MA, Bumbarger DJ, Collman F, da Costa NM, Denman DJ, de Vries S, Joyce E, Kapner D, King CW, Larkin JD, Lecoq J, Mahalingam G, Millman D, Mölter J, Morrison C, Reid RC, Schneider-Mizell CM, Daniel S, Suckow S, Takasaki KT, Takeno M, Torres R, Vumbaco D, Waters J, Wyrick DG, Yin W, Zhuang J, Mihalas S, Berteau S

Motor learning leverages coordinated low-frequency cortico-basal ganglia activity to optimize motor preparation in humans with Parkinson's disease.

Frontiers in neuroscience

Presbrey KN, Wozny TA, Louie KH, Little S, Starr PA, Abbasi-Asl R, Wang DD

Data-driven fine-grained region discovery in the mouse brain with transformers.

bioRxiv : the preprint server for biology

Lee AJ, Yao S, Lusk N, Ng L, Kunst M, Zeng H, Tasic B, Abbasi-Asl R

Compression-enabled interpretability of voxelwise encoding models.

PLoS computational biology

Kamali F, Suratgar AA, Menhaj M, Abbasi-Asl R

Deep brain stimulation-entrained gamma oscillations in chronic home recordings in Parkinson's disease.

Brain stimulation

Olaru M, Hahn A, Shcherbakova M, Little S, Neumann WJ, Abbasi-Asl R, Starr PA

Unsupervised pattern identification in spatial gene expression atlas reveals mouse brain regions beyond established ontology.

Proceedings of the National Academy of Sciences of the United States of America

Cahill R, Wang Y, Xian RP, Lee AJ, Zeng H, Yu B, Tasic B, Abbasi-Asl R

Structurally-constrained encoding framework using a multi-voxel reduced-rank latent model for human natural vision.

Journal of neural engineering

Ranjbar A, Suratgar AA, Menhaj MB, Abbasi-Asl R

Interpretable video-based tracking and quantification of parkinsonism clinical motor states.

NPJ Parkinson's disease

Deng D, Ostrem JL, Nguyen V, Cummins DD, Sun J, Pathak A, Little S, Abbasi-Asl R

Motor network gamma oscillations in chronic home recordings predict dyskinesia in Parkinson's disease.

Brain : a journal of neurology

Olaru M, Cernera S, Hahn A, Wozny TA, Anso J, de Hemptinne C, Little S, Neumann WJ, Abbasi-Asl R, Starr PA

Interpretable prototype discovery in deep learning based time series classification

Integrated Systems: Innovations and Applications, Springer book chapter

Gaurav Ghosal, R. Abbasi-Asl

Journal of Vision

Reconstructing visual experience from a large-scale biologically realistic model of mouse primary visual cortex

R. Abbasi-Asl, Y. Chi, H. Yang, K. Dai, A. Arkhipov

Neurology

Diurnal Step Count Patterns in Progressive Multiple Sclerosis

D. Navani, V. Block, B. Cree, R. Abbasi-Asl

The entropic heart: Tracking the psychedelic state via heart rate dynamics

bioRxiv preprint

F. E. Rosas, P. A. M. Mediano, C. Timmermann, A. I Luppi, D. Candia-Rivera, R. Abbasi-Asl, A. Gazzaley, M. L. Kringelbach, S. D. Muthukumaraswamy, D. Bor, S. Garfinkel, R. Carhart-Harris

Machine Learning for Uncovering Biological Insights in Spatial Transcriptomics Data.

arxiv

Lee AJ, Cahill R, Abbasi-Asl R

Editorial: Functional microcircuits in the brain and in artificial intelligent systems.

Frontiers in computational neuroscience

Lee JH, Choe Y, Ardid S, Abbasi-Asl R, McCarthy M, Hu B

Robust Image Registration via Empirical Mode Decomposition

arXiv:1711.04247

Reza Abbasi-Asl, Aboozar Ghaffari, Emad Fatemizadeh

Journal of Vision

A large-scale standardized survey of neural receptive fields in an entire column in mouse V1

R. Abbasi-Asl, A. Muslim, J. Larkin, K. Takasaki, D. Millman, D. Denman, J. Lecoq, A, Arkhipov, N. W Gouwens, J. Waters, R C. Reid, S. EJ de Vries

Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification

arxiv

Gaurav R Ghosal, Reza Abbasi-Asl

Structural Compression of Convolutional Neural Networks with Applications in Interpretability.

Frontiers in big data

Abbasi-Asl R, Yu B

Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex.

Neuron

Billeh YN, Cai B, Gratiy SL, Dai K, Iyer R, Gouwens NW, Abbasi-Asl R, Jia X, Siegle JH, Olsen SR, Koch C, Mihalas S, Arkhipov A

Superficial bound of the depth limit of 2-photon imaging in mouse brain.

eNeuro

Takasaki K, Abbasi-Asl R, Waters J

Definitions, methods, and applications in interpretable machine learning.

Proceedings of the National Academy of Sciences of the United States of America

Murdoch WJ, Singh C, Kumbier K, Abbasi-Asl R, Yu B

3-Photon Calcium Imaging of Deep Cortical Layers for Functional Connectomics

Optics and the Brain

Kevin Takasaki, Josh Larkin, Reza Abbasi-Asl, Dan Denman, Dan Millman, Saskia de Vries, Marc Takeno, Nuno M da Costa, R Clay Reid, Jack Waters

Brain-Computer Interface in Virtual Reality

9th International IEEE EMBS Conference on Neural Engineering (NER)

R. Abbasi-Asl, M. Keshavarzi, D. Y. Chan

Visual physiology of the layer 4 cortical circuit in silico.

PLoS computational biology

Arkhipov A, Gouwens NW, Billeh YN, Gratiy S, Iyer R, Wei Z, Xu Z, Abbasi-Asl R, Berg J, Buice M, Cain N, da Costa N, de Vries S, Denman D, Durand S, Feng D, Jarsky T, Lecoq J, Lee B, Li L, Mihalas S, Ocker GK, Olsen SR, Reid RC, Soler-Llavina G, Sorensen SA, Wang Q, Waters J, Scanziani M, Koch C

Publications

Robustness tests for biomedical foundation models should tailor to specifications.

Imaging joy with generalized slice dithered enhanced resolution and SWAT reconstruction: 3T high spatial-temporal resolution fMRI.

Hebb's Vision: The Structural Underpinnings of Hebbian Assemblies.

Motor learning leverages coordinated low-frequency cortico-basal ganglia activity to optimize motor preparation in humans with Parkinson's disease.

Data-driven fine-grained region discovery in the mouse brain with transformers.

Compression-enabled interpretability of voxelwise encoding models.

Deep brain stimulation-entrained gamma oscillations in chronic home recordings in Parkinson's disease.

Unsupervised pattern identification in spatial gene expression atlas reveals mouse brain regions beyond established ontology.

Structurally-constrained encoding framework using a multi-voxel reduced-rank latent model for human natural vision.

Interpretable video-based tracking and quantification of parkinsonism clinical motor states.

Motor network gamma oscillations in chronic home recordings predict dyskinesia in Parkinson's disease.

Interpretable prototype discovery in deep learning based time series classification

Journal of Vision

Neurology

The entropic heart: Tracking the psychedelic state via heart rate dynamics

Machine Learning for Uncovering Biological Insights in Spatial Transcriptomics Data.

Editorial: Functional microcircuits in the brain and in artificial intelligent systems.

Robust Image Registration via Empirical Mode Decomposition

Journal of Vision

Multi-Modal Prototype Learning for Interpretable Multivariable Time Series Classification

Structural Compression of Convolutional Neural Networks with Applications in Interpretability.

Systematic Integration of Structural and Functional Data into Multi-scale Models of Mouse Primary Visual Cortex.

Superficial bound of the depth limit of 2-photon imaging in mouse brain.

Definitions, methods, and applications in interpretable machine learning.

3-Photon Calcium Imaging of Deep Cortical Layers for Functional Connectomics

Brain-Computer Interface in Virtual Reality

Visual physiology of the layer 4 cortical circuit in silico.

The DeepTune framework for modeling and characterizing neurons in visual cortex area V4

Interpreting Convolutional Neural Networks Through Compression

Do retinal ganglion cells project natural scenes to their principal subspace and whiten them?

Automatic b-spline image registration using histogram-based landmark extraction

Estimation of muscle force with emg signals using hammerstein-wiener model

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Publications

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