Publications

Cross-Subject Modeling for Widefield Calcium Imaging via Atlas-Aligned Spatiotemporal Tokenization

Mohammad Hosseini, Eray Erturk, Saba Hashemi, Maryam M. Shanechi

Jul

Preferential dynamic modeling with forward-backward smoothing

Sani O. G., Jha T., Hosseini S. M., Shanechi M. M.

Multimodal LLMs can learn to read brain signals: a vision–language model for unified multi-task EEG decoding

Azizeddin P., Sharafi O., Shanechi M. M.

Learning behaviorally relevant dynamics in multimodal neural recordings

Azizeddin P., Erturk E., Shanechi M. M.

iMINDBench: iEEG multi-institution neural decoding benchmark

Chau G., Hashemi S., Gwon Y., Patel E., DeWitt J., Wang C., Zahorodnii A., Talukder S. J., Han D. D., Chung C. K., Shanechi M. M., Yue Y.

Prioritized nonlinear modeling of shared dynamics across neural populations

Jha T., Song D., Shanechi M. M.

Aug

Unsupervised learning of multiscale switching dynamical system models from multimodal neural data

Kim D., Song C. Y., Hsieh H., Shanechi M. M.

23 (2), 026039, Apr

BaRISTA: Brain Scale Informed Spatiotemporal Representation of Human Intracranial Neural Activity

Lucine L. Oganesian, Saba Hashemi, Maryam M. Shanechi

Dec

Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data

Sayed Mohammad Hosseini, Maryam Shanechi

Dynamical modeling of nonlinear latent factors in multiscale neural activity with real-time inference

Eray Erturk, Maryam M. Shanechi

Dec

BRAID: Input-driven Nonlinear Dynamical Modeling of Neural-Behavioral Data

Parsa Vahidi, Omid G. Sani, Maryam M. Shanechi

Cross-modal representational knowledge distillation for enhanced spike-informed LFP modeling

Erturk E., Hashemi S., Shanechi M. M.

Dec

Prioritized learning of cross-population neural dynamics

Jha T., Sani O., Pesaran B., Shanechi M. M.

Aug

Preferential subspace identification (PSID) with forward-backward smoothing

Sani O., Shanechi M. M.

Probabilistic geometric principal component analysis with application to neural data

Hsieh, H., Shanechi M. M.

Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks

Omid G. Sani, Bijan Pesaran, Maryam M. Shanechi

Sep

Dynamical flexible inference of nonlinear latent factors and structures in neural population activity

Hamidreza Abbaspourazad, Eray Erturk, Bijan Pesaran, Maryam M. Shanechi

8 (1), 85–108, Jan

Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior

Parsa Vahidi, Omid G. Sani, Maryam M. Shanechi

121 (7), e2212887121, Feb

Spectral learning of shared dynamics between generalized-linear processes

Oganesian, L., Sani, O. G., Shanechi M. M.

Dec

Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation

Herron J., Kullmann A., Denison T., Goodman W. K., Gunduz A., Neumann W-J., Provenza N. R., Shanechi M. M., Sheth S. A., Starr P. A., Widge A. S.

Dec

An application-based taxonomy for brain–computer interfaces

Robinson J. T., Norman S. L., Angle M. R., Constandinou T. G., Denison T., Donoghue J. P., Field R. M., Forsland A., Kouider S., Millan Jd. R., Michaels J. A., Orsborn A. L., Pandarinath C., Pruszynski J. A., Rozell C. J., Shah N. P., Shanechi M. M., Shoaran M., Sheth S. A., Stavisky S. D., Trautmann E., Vachicouras N., Xie C.

Dec

Brain-computer interfaces for neuropsychiatric disorders

Oganesian, L., Shanechi M. M.

Jun

Event detection and classification from multimodal time series with application to neural data

Sadras N., Pesaran B., Shanechi M. M.

21 (2), 026049, May

Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

Ahmadipour P., Sani O. G., Pesaran B., Shanechi M. M.

21 (2), 026001, Mar

Unsupervised learning of stationary and switching dynamical system models from Poisson observations

Song C. Y., Shanechi M. M.

20 (6), 066029, Dec

Post-stimulus encoding of decision confidence in EEG: toward a brain-computer interface for decision making

Sadras N., Sani O. G., Ahmadipour P., Shanechi M. M.

20 (5), 056012, Sep

First-in-human prediction of chronic pain state using intracranial neural biomarkers

Shirvalkar P., Prosky J., Chin G., Ahmadipour P., Sani O. G., Desai M., Manning A., Dawes H., Shanechi M. M., Starr P., Chang E. F.

26, 1090–1099, May

Modeling and Inference Methods for Switching Regime-Dependent Dynamical Systems with Multiscale Neural Observations

Song C., Hsieh, H., Pesaran B., Shanechi M. M.

Oct

Modeling multiscale causal interactions between spiking and field potential signals during behavior

Wang C., Pesaran B., Shanechi M.M.

Jan

Modelling and prediction of the dynamic responses of large-scale brain networks during direct electrical stimulation

Yuxiao Yang, Shaoyu Qiao, Omid G. Sani, J. Isaac Sedillo, Breonna Ferrentino, Bijan Pesaran, Maryam M. Shanechi

Feb

Sensory feedback can give rise to neural rotations

Sani, O. G., Shanechi, M. M.

Dec

Multiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior

Abbaspourazad H., Choudhary M., Wong Y.T., Pesaran B., Shanechi M. M.

Jan

Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification

Omid G. Sani, Hamidreza Abbaspourazad, Yan T. Wong, Bijan Pesaran, Maryam M. Shanechi

Nov

Adaptive latent state modeling of brain network dynamics with real-time learning rate optimization

Yang Y., Ahmadipour P., Shanechi M. M .

Nov

Adaptive tracking of human ECoG network dynamics

Ahmadipour P., Yang Y., Chang E. F., Shanechi M. M.

Aug

Multiscale low-dimensional neural dynamics explain naturalistic 3D movements

Abbaspourazad H., Choudhary M., Wong Y. T., Pesaran B., Shanechi M. M.

Feb. 27–Mar. 1, Denver, CO

Modeling behaviorally relevant neural dynamics with a novel preferential subspace identification (PSID)

Sani O., Pesaran B., Shanechi M. M.

Feb. 27–Mar. 1, Denver, CO

Modeling large-scale brain network dynamics in response to electrical stimulation

Yang Y., Qiao S., Sani O., Sedillo I., Ferrentino B., Pesaran B., Shanechi M. M.

Feb. 27–Mar. 1, Denver, CO

Brain-machine interfaces from motor to mood

Shanechi M. M.

Sep

A point-process matched filter for event detection and decoding from population spike trains

Sadras N., Pesaran B., Shanechi M. M.

Aug

Dynamic network modeling and dimensionality reduction for human ECoG activity

Yang Y.*, Sani O. G.*, Chang E. F., Shanechi M. M.

May

Sparse model-based estimation of functional dependence in high-dimensional field and spike multiscale networks

Bighamian R., Wong Y., Pesaran B., Shanechi M. M.

May

A Multiscale Dynamical Modeling and Identification Framework for Spike-Field Activity

Abbaspourazad H., Hsieh H., Shanechi M. M.

Apr

Estimating Multiscale Direct Causality Graphs in Neural Spike-Field Networks

Wang C., Shanechi M. M.

Mar

Developing a personalized closed-loop controller of medically-induced coma in a rodent model

Yang Y., Guidera J., Vlasov K., Pei J., Brown E.N., Solt K., Shanechi M. M.

Mar

Decoder for switching state-space models with spike-field observations

Song C., Hsieh H., Shanechi M. M.

20–23 Mar., San Francisco, CA

Investigating the effect of forgetting factor on tracking non-stationary neural dynamics

Ahmadipouranari P., Yang Y., Shanechi M. M.

20–23 Mar., San Francisco, CA

Mood variations decoded from multi-site intracranial human brain activity

Omid G. Sani, Yuxiao Yang, Morgan B. Lee, Heather E. Dawes, Edward F. Chang, Maryam M. Shanechi

Sep

Direct Electrical Stimulation of Lateral Orbitofrontal Cortex Acutely Improves Mood in Individuals with Symptoms of Depression

Rao V.R., Sellers K.K., Wallace D.L., Lee M.B, Bijanzadeh M, Sani O.G., Yang Y, Shanechi M.M., Dawes H.E., Chang E.F.

Nov

Multiscale Modeling and Decoding Algorithms for Spike-Field Activity

Hsieh H, Wong Y, Pesaran B, Shanechi M.M.

Oct

A control-theoretic system identification framework and a real-time closed-loop clinical simulation testbed for electrical brain stimulation

Yang Y., Connolly A. T., Shanechi M. M .

15:066007, Sep

Optimizing the Learning Rate for Adaptive Estimation of Neural Encoding Models

Hsieh H., Shanechi M. M.

14(5): e1006168, May

Identifying Multiscale Hidden States to Decode Behavior

Abbaspourazad H., Wong Y., Pesaran B., Shanechi M. M.

Honolulu, HI

Estimation of Functional Dependence in High-Dimensional Spike-Field Activity

Bighamian R., Shanechi M. M.

Honolulu, HI

Decoding Spike Trains from Neurons with Spatio-Temporal Receptive Fields

Sadras, N., Shanechi M. M.

Honolulu, HI

An Information-Theoretic Measure of Multiscale Causality for Spike-Field Activity

Wang C., Shanechi M.M.

Honolulu, HI

Multiscale modeling and decoding of spike-field activity during a naturalistic reach-to-grasp task

Hsieh, H., Wong Y.T., Pesaran B., Shanechi M. M.

1–4 Mar., Denver, CO

A novel framework for dynamic modeling of brain-network response to electrical stimulation

Yang Y., Sani O., Sellers K.K., Chang E. F., Shanechi M. M.

1–4 Mar., Denver, CO

Decoding mood state from multisite ECoG activity in human subjects

Sani O., Yang Y., Lee M., Dawes H., Chang E. F., Shanechi M. M.

1–4 Mar., Denver, CO

Brain-machine interfaces

Shanechi M. M.

Ed. S. Sarma, Ed. Z. Chen, Springer International Publishing

Rapid control and feedback rates enhance neuroprosthetic control

Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Dangi S, Carmena J.M.

8:13825, Jan

Brain-machine interface control algorithms

Shanechi M.M.

25(10):1725 – 1734

Multiscale modeling of dependencies between spikes and fields

Abbaspourazad H., Shanechi M. M.

29–31 Oct., Pacific Grove, CA

Dynamic tracking of non-stationarity in human ECoG activity

Yang Y., Chang E.F., Shanechi M.M.

Jeju Island, Korea

Multiscale decoding for reliable brain-machine interface performance over time

Hsieh H., Wong Y.T., Pesaran B., Shanechi M.M.

Jeju Island, Korea

An unsupervised learning algorithm for multiscale neural activity

Abbaspourazad H., Shanechi M.M.

Jeju Island, Korea

Multiscale decoding of spike-field activity to improve brain-machine interface robustness and longevity

Hsieh, H., Wong Y.T., Pesaran B., Shanechi M. M.

Society for Neuroscience (SFN), 11–15 Nov., Washington, DC

Learning the dependencies between spikes and fields in multiscale modeling

Abbaspourazad H., Shanechi M. M.

Society for Neuroscience (SFN), 11–15 Nov., Washington, DC

Modeling dynamic brain network responses to electrical stimulation

Yang Y., Sellers K.K., Chang E. F., Shanechi M. M.

Society for Neuroscience (SFN), 11–15 Nov., Washington, DC

Real-time decoding of mood from human large-scale ECoG activity

Sani O., Yang Y., Chang E. F., Shanechi M. M.

Society for Neuroscience (SFN), 11–15 Nov., Washington, DC

An adaptive and generalizable closed-loop system for control of medically-induced coma and other states of anesthesia

Yang Y., Shanechi M.M.

13(6):066019, Nov

Robust brain-machine interface design using optimal feedback control modeling and adaptive point process filtering

Shanechi M.M., Orsborn A.L., Carmena J.M.

12(4): e1004730, Apr

Time-Efficient Identification of Input-Output Brain Dynamics

Yang Y., Shanechi M.M.

Orlando, FL

Multiscale Brain-Machine Interface Decoders

Hsieh H., Shanechi M.M

Orlando, FL

A new modeling framework for multiscale neural activity underlying behavior

Abbaspourazad H., Shanechi M.M.

San Diego, CA

Adaptive multiscale brain-machine interface decoders

Hsieh, H., Shanechi M.M.

San Diego, CA

Adaptive identification of high-dimensional brain network dynamics to track non-stationarity and plasticity

Yang Y., Shanechi M.M.

San Diego, CA

A framework for identification of brain network dynamics using a novel binary noise modulated electrical stimulation pattern

Yang Y., Shanechi M.M.

Milan, Italy

Optimal calibration of the learning rate in closed-loop adaptive brain-machine interfaces

Hsieh H., Shanechi M.M

Milan, Italy

A generalizable adaptive brain-machine interface architecture for closed-loop control of anesthesia

Yang Y., Shanechi M.M.

Milan, Italy

Modeling brain network dynamics underlying mood disorders

Connolly A., Yang Y., Chang E.F., Shanechi M.M.

Chicago, Il

A novel binary noise modulated electrical stimulation pattern for identification of brain network dynamics

Yang Y., Connolly A., Shanechi M.M.

Chicago, Il

A general framework for optimal selection of the learning rate in closed-loop brain-machine interfaces

Hsieh, H., Shanechi M.M.

Chicago, Il

Rapid sensorimotor control and feedback rates enhance neuroprosthetic control

Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Dangi S, Carmena J.M.

Chicago, Il

An adaptive and robust brain-machine interface architecture for closed-loop control of anesthesia

Yang Y., Shanechi M.M.

Honolulu, HI

Closed-loop decoder adaptation shapes neural plasticity for skillful neuroprosthetic control

Orsborn A. L., Mooreman H. G., Overduin S. A., Shanechi M. M., Dimitrov D. F., Carmena J. M.

82(6), Jun

Continuous closed-loop decoder adaptation with a recursive maximum likelihood algorithm allows for rapid performance acquisition in brain-machine interfaces

Dangi S., Gowda S., Moorman H.G., Orsborn A.L., So K., Shanechi M. M., Carmena J.M.

26:9, Sep

A cortical-spinal prosthesis for targeted limb movement in paralyzed primate avatars

Shanechi M. M., Hu R., Williams, Z.M.

5:3237, Feb

An adaptive brain-machine interface algorithm for control of burst suppression in medical coma

Yang Y., Shanechi M.M.

Chicago, Il

High-performance brain-machine interface enabled by an adaptive optimal feedback-controlled point process decoder

Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Carmena J.M.

Chicago, Il

A design of neural decoder by reducing discrepancy between manual control and brain control

Chang Y. H., Chen M., Shanechi M. M., Carmena J. M., Tomlin C.

Strasbourg, France

Spike-by-spike control using an adaptive optimal feedback-controlled point process decoder improves BMI performance

Shanechi M.M., Orsborn A.L., Moorman H., Gowda S., Dangi S., Carmena J.M.

Washington DC

Control of burst-suppression in a rodent model of medical coma using a brain-machine interface

Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N.

Montreal, Canada

A brain-machine interface for control of medically-induced coma

Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N.

9(10), Oct

A real-time brain-machine interface combining motor target and trajectory intent using an optimal feedback control design

Shanechi M. M., Williams Z. M., Wornell G. W., Hu R. C., Powers M., Brown E. N.

8 (4), Apr

Optimal feedback-controlled point process decoder for adaptation and assisted training in brain-machine interfaces

Shanechi M. M., Carmena J. M.

San Diego, CA

Proficient BMI control enabled by closed-loop adaptation of an optimal feedback-controlled point process decoder

Shanechi M. M., Orsborn A., Gowda S., Carmena J. M.

San Diego, CA

A brain-machine interface for control of burst suppression in medical coma

Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N.

Osaka, Japan

A brain-machine interface for control of medically-induced coma

Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N.

Salt Lake City

A brain-machine interface for control of medically-induced coma

Shanechi M. M., Chemali J., Liberman M., Solt K., Brown E. N.

San Diego, CA

Neural population partitioning and a concurrent brain-machine interface for sequential motor function

Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M.

15 (12), Dec

Feedback-controlled parallel point process filter for estimation of goal-directed movements from neural signals

Shanechi M. M., Wornell G. W., Williams Z. M., Brown E. N.

Oct

A concurrent brain-machine interface for enhanced motor function

Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M.

Salt Lake City, USA

A real-time concurrent brain-machine interface for performing sequential movements

Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M.

Society for Neuroscience (SFN), Washington, USA

A brain-machine interface combining target and trajectory information using optimal feedback control

Shanechi M. M., Hu R., Powers M., Wornell G. W., Brown E. N., Williams Z. M.

Salt Lake City, USA

Real-time brain-machine interface architectures: neural decoding from plan to movement

Shanechi M. M.

PhD Dissertation, MIT, April

Comparison of practical feedback algorithms for multiuser MIMO

Shanechi M. M., Porat R., Erez U.

58 (8), Aug

A parallel point-process filter for estimation of goal-directed movements from neural signals

Shanechi M. M., Wornell G. W., Williams Z. M., Brown E. N.

Dallas, USA

Combining plan and peri-movement activities improves the performance of brain-machine interfaces

Shanechi M. M., Williams Z. M., Wornell G. W., Brown E. N.

Society for Neuroscience (SFN), San Diego, USA

A real-time brain-machine interface combining plan and peri-movement activities

Shanechi M. M., Williams Z. M., Wornell G. W., Brown E. N.

Santorini, Greece

Comparison of practical feedback algorithms for multiuser MIMO

Shanechi M. M., Porat R., Erez U.

Barcelona, Spain

Rateless codes for MIMO channels

Shanechi M. M., Erez U., Wornell G. W.

New Orleans, USA

Time-invariant rateless codes for MIMO channels

Shanechi M. M., Erez U., Wornell G. W.

Toronto, Canada

Universal coding for parallel Gaussian channels

Shanechi M. M., Erez U., Wornell G. W.

Zurich, Switzerland

On the importance of phase in human speech recognition

Shi G., Shanechi M. M., Aarabi, P.

14 (5), Sep

Phase-based speech processing

Aarabi P., Shi G., Shanechi M. M., Rabi S.

World Scientific

Post recognition speech localization

Mavandadi S., Aarabi P., Mohajer K., Shanechi M. M.

8 (2), Jun

Structural analysis of multisensor arrays for speech separation applications

Shanechi M. M., Aarabi P.

Orlando, USA