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The goals of our joint US/UK interdisciplinary effort are to investigate and model the neural mechanisms underlying multisensory processing and decision making and to design closed-loop adaptive algorithms for optimized exploitation of multisensory data for brain-computer communication.  We are motivated by the observation that in performing many tasks, such as flying an airplane, an operator has to make decisions in time-pressured and stressful conditions based on a multiplicity of multisensory information presented in cluttered and distracting environments. We envision a closed-loop brain-computer interface (BCI) architecture for enhancing decision accuracy. Our effort consists of both computational and experimental components. The computational component of our effort spans Bayesian inference, stochastic control, adaptive signal processing, and machine learning. The experimental component of our effort validates our computational models and algorithms using state-of-the-art neurophysiology.

Principal Investigator: Maryam Shanechi (USC) shanechi at usc dot edu

Funding Agencies: US Army Research Office (ARO) and UK Ministry of Defense (MOD)

Program Managers: Hamid Krim (ARO), Cliff Wang (ARO), Frederick Gregory (ARO), Bhopinder K Madahar (MoD), Alec Banks (MoD)


Bighamian R., Wong Y., Pesaran B., Shanechi M. M., “Sparse model-based estimation of functional dependence in high-dimensional field and spike multiscale networks”, Journal of Neural Engineering, May 2019 (link).

M Angjelichinoski, T Banerjee, J Choi, B Pesaran, V Tarokh, “Minimax-optimal decoding of movement goals from local field potentials using complex spectral features”, arXiv preprint arXiv:1901.10397, 2019 (link)

F Najafi, G F Elsayed, R Cao, E Pnevmatikakis, P E. Latham, J P Cunningham, A K Churchland, “Excitatory and inhibitory subnetworks are equally selective during decision-making and emerge simultaneously during learning”, bioRxiv 354340; doi:, 2019 (link)

Pesaran B, Vinck M, Einevoll GT, Sirota A, Fries P, Siegel M, Truccolo W, Schroeder CE, Srinivasan R., “Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation”, Nat Neurosci, 21(7): 903-919, Jul. 2018 (link).

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Our third annual meeting will be held at the University of Essex Dec. 3-4, 2019. The meeting of our US-UK BARI program will also be held at Essex on Dec. 2, 2019.


The joint meeting for two international MURI and BARI initiatives led by Maryam Shanechi is highlighted here.


We held a joint meeting for our MURI and BARI programs at USC with over 60 international experts from academia and government labs in US and UK. Led by Maryam Shanechi, MURI started in 2016 to develop brain-machine interfaces (BMIs) for enhanced decision accuracy and BARI was just kicked off to develop human-AI teams for joint decision making, funded by US DoD and UK MoD. Read more here.


Our second annual meeting will be held at USC Feb. 12-14, 2019. This meeting will be held jointly with the kick-off meeting of our new US-UK BARI program announced here.


Our first annual meeting will be held at UCL on Feb. 21-22, 2018. Tentative agenda is here.


We held our joint US/UK MURI kick-off meeting at USC with participation from academia, DoD labs, and UK MoD. Our program is now officially launched.


Our project is highlighted in USC news. Read more: USC news here , Viterbi news here, Press release here.


We are awarded a joint US/UK multidisciplinary MURI grant to lead a multi-institutional collaboration that aims to build brain-machine interfaces for enhanced decision accuracy.

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We are grateful for the support from the US ARO and from the UK MoD.
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