Overview
Bidirectional Brain Computer Interfaces
Brain-computer interfaces (BCI) aim to treat disability due to loss of neural function, such as blindness and paralysis, by interfacing with the remaining functional neural circuit. Recent advances in high-resolution and large-scale implantable hardware devices have now enabled us to investigate large neural populations at cellular resolution, resulting in a wealth of basic neuroscientific data across brain regions, species, and tasks.
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Our goal is to build a computational toolbox for reading-out and writing-in into neural circuits, in real-time and at cellular-resolution.
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Some questions we want to answer:
How are flexible, high-degrees of freedom movements such as finger movements, limb movements and speech represented in the brain?
Can we use intracortical array recordings in human participants with paralysis to enable full-body movement in virtual reality?
How do we reproduce rich spatio-temporal natural activity patterns using electrical stimulation?
How do we use existing experimental data to develop the next-generation of low-power, large-scale and high-density implantable BCIs?
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We aim to make progress towards these questions by collaborating with hardware groups, basic neuroscientists and clinicians, both at the Rice University and the Texas Medical Center.
Team
News
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May 8th, 2025: Siyuan Tao was awarded third place in the poster presentation competition at the InterfaceNeuro Conference held at Georgia Tech.
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January 20, 2025: Our manuscript entitled "A high-performance brain–computer interface for finger decoding and quadcopter game control in an individual with paralysis" was published in Nature Medicine. ​
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Check out some of the articles covering this publication: Michigan News, Nature News, New Scientist, SER, DroneXL, News Medical, singularityhub, BBC Radio 5 live (Jan. 20, 2025)
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Nick Ramsey and Mariska J. Vansteensel present a thoughtful analysis of ours and related BCI work in their article entitled: "The Expanding Repertoire of brain-computer Interfaces"
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January 1, 2025: Lab officially opens.
Join us!
We are actively seeking talented postdocs and graduate students to join our research team. If you're interested, please email us: bhaishahster[at]gmail.com.
Postdoctoral Scholars
We are looking for 1-3 postdoctoral scholars to lead research in high-degrees of freedom motor decoding, encompassing whole-body movement and speech. The specific project will be determined based on mutual interests. Potential options include:
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Setting up a BCI rig and collaborating with clinical partners at the Texas Medical Center to initiate a human BCI trial.
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Real-time, closed-loop decoding of speech and whole-body movements in virtual reality.
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Investigating how the human brain composes simple movements into complex simultaneous and rapid sequential movements.
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Identifying the neural representation and dynamics in multiple brain regions to understand how high-level thoughts are transformed into low-level movements.
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Perturbing neural activity using precise, cellular-resolution electrical stimulation.
Postdoctoral scholars will play a crucial role in shaping our scientific direction and fostering a rigorous and collaborative lab culture.
Ideal candidates will have:
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A strong quantitative background.
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A PhD in Electrical Engineering, Computer Science, Mechanical Engineering, Neuroscience, or Statistics.
Research Engineer
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We are seeking a research engineer to build and maintain a BCI system for collecting experimental data from human participants with intra-cortical neural implants. This role is central to our human BCI projects and involves real-time neural signal processing, task visualization, and neural decoding. The research engineer will also help develop and maintain other technical infrastructure, such as robotic hands or digital interfaces.
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Research engineers will:
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Be co-authors on academic publications using the developed infrastructure.
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Have the opportunity to lead scientific projects if interested.
Ideal candidates will have:
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A BA/BS/BTech in a technical or engineering field.
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Experience in building embedded/real-time systems, signal processing, writing well-documented code, and working in collaborative teams is highly desirable.
Graduate Students
We are seeking up to 3 graduate students for all the projects outlined above. Email us if you are an admitted student or planning to apply to a PhD program at Rice.
Publications
​Preprints
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N. P. Shah, M. S. Willsey, N. Hahn, F. Kamdar, D. T. Avansino, C. Fan, L. R. Hochberg, F. Willett, Jaimie M. Henderson A flexible intracortical brain-computer interface for typing using finger movements. bioRxiv April 2024. [paper]
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N. P. Shah, D. Avansino, F. Kamdar, C. Nicolas, A. Kapitonava, C. Vargas-Irwin, L. R. Hochberg, C. Pandarinath, K. Shenoy, F. R Willett, J. Henderson Pseudo-linear Summation explains Neural Geometry of Multi-finger Movements in Human Premotor Cortex. bioRxiv, October 2023 [Paper]
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Journal papers
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M. S. Willsey, N. P. Shah, D. T. Avansino, N. V. Hahn, R. M. Jamiolkowski, F. B. Kamdar, L. R. Hochberg, F. R. Willett, J. M. Henderson. A real-time, high-performance brain-computer interface for finger decoding and quadcopter control. Nature Medicine January 2025. [pPaper]
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N. P. Shah*, A.J. Phillips*, S. Madugula, A. Lotlikar, A. R. Gogliettino, M. Hays, L. Grosberg, J. Brown, A. Dusi, P. Tandon, P. Hottowy, W. Dabrowski, A. Sher, A. M. Litke, S. Mitra, E.J. Chichilnisky. Precise control of neural activity using dynamically optimized electrical stimulation. eLife, November 2025 [Paper] (* indicates equal contribution)
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M. Zaidi, G. Aggarwal, N. P. Shah, O. Karniol-Tambour, G. Goetz, S. Madugula, A. R. Gogliettino, E. G. Wu, A. Kling, N. Brackbill, A. Sher, A. M. Litke, E.J. Chichilnisky. Inferring retinal ganglion cell light response properties from intrinsic electrical features. Journal of Neural Engineering. August 2023. [Paper]
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P. Yan, A. Akhoundi, N. P. Shah, P. Tandon, D. G. Muratore, E.J.Chichilnisky, Boris Murmann. Data Compression versus Signal Fidelity Tradeoff in Wired-OR Analog-to-Digital Compressive Arrays for Neural Recording. IEEE TBioCAS. July, 2023. [Paper]
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S. Madugula, R. Vilkhu, N. P. Shah, L. Grosberg, A. Kling, A. Gogliettino, H. Nguyen, P. Hottowy, A. Sher, A. Litke, E.J. Chichilnisky. Inference of Electrical Stimulation Sensitivity from Recorded Activity of Primate Retinal Ganglion Cells. Journal of Neuroscience. June 2023. [Paper]
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S. Madugula, A. R. Gogliettino, M. Zaidi, G. Aggarwal, A. Kling, N. P. Shah, R. Vilkhu, M. Hays, H. Nguyan, V. Fan, E. G. Wu, P. Hottowy, A. Sher, A. M. Litke, R. A. Silva, E. J. Chichilnisky. Focal Electrical Stimulation of Human Retinal Ganglion Cells for Vision Restoration. Journal of Neural Engineering. December 2022. [Paper]
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N. P Shah, N. Brackbill, R. Samarakoon, C. Rhoades, A. Kling, A. Sher, A. Litke, Y. Singer, J. Shlens, E.J. Chichilnisky. Individual Variability in the Neural Code of the Retina. Neuron, February 2022. [Paper]
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N. P. Shah, E.J. Chichilnisky. Computational Challenges and Opportunities for a Bidirectional Artificial Retina. Journal of Neural Engineering, October 2020. [Paper]
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P. Tandon, N. Bhaskar, N. P. Shah, S. Madugula, L.E. Grosberg, V.H. Fan, P. Hottowy, A. Sher, A.M. Litke, E.J. Chichilnisky, S. Mitra. Automatic Identification and Avoidance of Axon Bundle Activation for Epiretinal Prosthesis. IEEE Trasactions on Neural Systems and Rehabilitation Engineering 2021. [Paper]
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N. Brackbill, C. Rhoades, A. Kling, N. P. Shah, A. Sher, A. M. Litke, E.J. Chichilnisky. Reconstruction of natural images from responses of primate retinal ganglion cells. eLife November 2020. [Paper]
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N. P Shah, N. Brackbill, C. Rhoades, A. Kling, G. Goetz, A. Litke, A. Sher, E. P. Simoncelli, E.J. Chichilnisky. Inference of nonlinear receptive field subunits with spike-triggered clustering. eLife:9:e45743 March, 2020. [Paper][Code]
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C. Rhoades, N. P Shah, M. Manookin, N. Brackbill, A. Kling, G. Goetz, A. Sher, A. Litke, E.J. Chichilnisky. Unusual Physiological Properties of Smooth Monostratified Ganglion Cell Types in Primate Retina. Neuron, June 2019. [Paper]
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Conference papers
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N. P. Shah, M. S. Willsey, N. Hahn, F. Kamdar, D. Avansino, Krishna Shenoy*, Jaimie Henderson*. A brain-computer typing interface using finger movements. IEEE NER, April 2023 [Paper]
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P. Vasireddy, A. Gogliettino, J. Brown, R. Vilkhu, S. Madugula, A.J. Phillips, S. Mitra, P. Hottowy, A. Sher, A. Litke, N. P. Shah, E.J. Chichilnisky. Efficient Modeling and Calibration of Multi-Electrode Stimuli for Epiretinal Implants. IEEE NER, April 2023 [Paper] (Oral presentation)
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A. Lotlikar, N. P. Shah, A. Gogliettino, R. Vilkhu, S. Madugula, L. Grosberg, P. Hottowy, A. Sher, A. Litke, E.J. Chichilnisky, Subhasish Mitra. Partitioned Temporal Dithering for Efficient Epiretinal Electrical Stimulation. IEEE NER, April 2023 [Paper]
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AJ Phillips, N. P Shah, M. Hays, S. Madugula, J. Brown, P. Hottowy, A. Sher, A. Litke, EJ Chichilnisky Spatially Multiplexed Electrical Stimulation to Reproduce the Neural Code in the Primate Retina. IEEE NER, April 2023
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Pumiao Yan, N. P. Shah, Dante G. Muratore, Pulkit Tandon, E.J. Chichilnisky, Boris Murmann. Data Compression versus Signal Fidelity Tradeoff in Wired-OR ADC Arrays for Neural Recording. IEEE Biomedical Circuits and Systems Conference, October 2022 [Paper]
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N. P. Shah, S. Madugula, P. Hottowy, A. Sher, A. Litke, L. Paninski, E.J. Chichilnisky. Efficient Characterization of Electrically Evoked Responses for Neural Interfaces. NeurIPS, December 2019 [Paper] [Code]
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N. P. Shah, S. Madugula, L. Grosberg, G. Mena, P. Tandon, P. Hottowy, A. Sher, A. Litke, S. Mitra, E.J. Chichilnisky Optimization of Electrical Stimulation for a High-Fidelity Artificial Retina. IEEE NER, March 2019 [Paper]}(Invited for Plenary talk})
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N. P. Shah, S. Madugula, E.J. Chichilnisky, Y. Singer, J. Shlens. Learning a neural response metric for retinal prosthesis. ICLR, April 2018 [Paper]
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N. P. Shah, F. Alexandre. Reinforcement learning and dimensionality reduction: A model in computational neuroscience. IJCNN, July 2011[Paper]