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Publications

2019

A. K. Ramdas, R. F. Barber, M. J. Wainwright, M. I. Jordan, et al. A unified treatment of multiple testing with prior knowledge using the p-filter. The Annals of Statistics, 47(5):2790-2821, 2019.

H. Abbaspourazad, Y. Wong, B. Pesaran, and M. M. Shanechi. Dynamical characteristics of simultaneously-recorded spike and lfp activities underlying 3d reach-to-grasp. In Annual Meeting, Society for Neuroscience (SFN), 2019.

H. Abbaspourazad, H.-L. Hsieh, and M. M. Shanechi. A multiscale dynamical modeling and identification framework for spike-field activity. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2019.

P. Ahmadipour, Y. Yang, and M. M. Shanechi. Investigating the effect of forgetting factor on tracking non-stationary neural dynamics. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pages 291-294. IEEE, 2019.

C. Y. Song and M. M. Shanechi. Decoder for switching state-space models with spike-field observations. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pages 199-202. IEEE, 2019.

M. Angjelichinoski, T. Banerjee, J. Choi, B. Pesaran, and V. Tarokh. Minimax-optimal decoding of movement goals from local field potentials using complex spectral features. Journal of neural engineering, 16(4):046001, 2019.

T. Banerjee, S. Allsop, K. M. Tye, D. Ba, and V. Tarokh. Sequential detection of regime changes in neural data. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pages 139-142. IEEE, 2019.

S. Bhattacharyya, D. Valeriani, C. Cinel, L. Citi, and R. Poli. Target detection in video feeds with selected dyads and groups assisted by collaborative brain-computer interfaces. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pages 159-162. IEEE, 2019.

R. Bighamian, Y. T. Wong, B. Pesaran, and M. M. Shanechi. Sparse model-based estimation of functional dependence in high-dimensional field and spike multiscale networks. Journal of neural engineering, 2019.

J. Choi, E. A. Voinas, A. Orsborn, B. Ferrentino, and B. Pesaran. A projector-scope for spatiotemporal control of macaque cortex. In 2019 9th International IEEE EMBS Conference on Neural Engineering (NER). IEEE, 2019.

C. Cinel, D. Valeriani, and R. Poli. Neurotechnologies for human cognitive augmentation: Current state of the art and future prospects. Frontiers in human neuroscience, 13, 2019.

G. Denevi, C. Ciliberto, R. Grazzi, and M. Pontil. Learning-to-learn stochastic gradient descent with biased regularization. arXiv preprint arXiv:1903.10399, 2019.

A. Dubey, D. A. Markowitz, and B. Pesaran. Beta activity (15-30 hz) modulates the choice probability in a visual selection task. In Annual Meeting, Society for Neuroscience (SFN), 2019.

H.-L. Hsieh, B. Pesaran, and M. M. Shanechi. The topology and geometry of motor cortical dynamics underlying 3d movements. In Annual Meeting, Society for Neuroscience (SFN), 2019.

G. Luise, D. Stamos, M. Pontil, and C. Ciliberto. Leveraging low-rank relations between surrogate tasks in structured prediction. arXiv preprint arXiv:1903.00667, 2019.

F. Najafi, G. F. Elsayed, R. Cao, E. Pnevmatikakis, P. E. Latham, J. Cunningham, and A. K. Churchland. Excitatory and inhibitory subnetworks are equally selective during decision-making and emerge simultaneously during learning. bioRxiv, page 354340, 2019.

P. Ahmadipour, Y. Yang, and M. M. Shanechi. Adaptive modeling of neural network dynamics with optimized learning rate. In Annual Meeting, Society for Neuroscience (SFN), 2019.

R. M. Nair, O. G. Sani, N. Sadras, C. Song, P. Ahmadipouranari, D. Valeriani, C. Cinel, L. Citi, R. Poli, and M. M. Shanechi. Decoding human confidence from neural signals. In Annual Meeting, Society for Neuroscience (SFN), 2019.

S. Sabharwal-Siddiqi, A. Dubey, J. Choi, J. Haggerty, S. Qiao, E. A. Voinas, and B. Pesaran. Virtual reality system for the immersive display of visual and audiovisual objects. In Annual Meeting, Society for Neuroscience (SFN), 2019.

N. Sadras, B. Pesaran, and M. M. Shanechi. Estimating event times from spike trains with a point process matched filter. In Annual Meeting, Society for Neuroscience (SFN), 2019.

N. Sadras, B. Pesaran, and M. M. Shanechi. A point-process matched filter for event detection and decoding from population spike trains. Journal of neural engineering (in press), 2019.

O. G. Sani, B. Pesaran, and M. M. Shanechi. A new preferential subspace identification (psid) algorithm for learning dynamic neural encoding models with behavior-related latent states. In Annual Meeting, Society for Neuroscience (SFN), 2019.

M. M. Shanechi. Brain-machine interfaces from motor to mood: toward functional restoration and scientific discovery. Nature Neuroscience [Invited Article] (in revision), 2019.

R. A. Shewcraft, H. L. Dean, M. A. Hagan, M. M. Fabiszak, Y. T. Wong, and B. Pesaran. Coherent neuronal dynamics driven by optogenetic stimulation in the primate brain. bioRxiv, page 437970, 2019.

C. Y. Song, H.-L. Hsieh, and M. M. Shanechi. Decoder for switching state space models with spike-field observations. In Annual Meeting, Society for Neuroscience (SFN), 2019.

B. Tolooshams, A. H. Song, S. Temereanca, and D. Ba. Deep exponential-family auto-encoders. In Advances in Neural Information Processing Systems (Submitted), 2019.

B. Tolooshams, S. Dey, and D. Ba. Deep residual auto-encoders for expectation maximization-based dictionary learning. IEEE Transactions on Neural Networks and Learning Systems (Submitted), 2019.

D. Valeriani and R. Poli. Cyborg groups enhance face recognition in crowded environments. PloS one, 14(3):e0212935, 2019.

C. Wang and M. M. Shanechi. Estimating multiscale direct causality graphs in neural spike-field networks. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(5):857-866, 2019.

C. Wang, B. Pesaran, and M. M. Shanechi. Multiscale spike-field network causality identification during a motor task. In Annual Meeting, Society for Neuroscience (SFN), 2019.

Y. Yang, S. Qiao, B. Pesaran, and M. M. Shanechi. Accurate prediction of large-scale lfp network dynamics in response to electrical stimulation. In Annual Meeting, Society for Neuroscience (SFN), 2019.

Y. Yang, Q. Shaoyu, O. G. Sani, I. J. Sedillo, B. Ferrentino, B. Pesaran, and M. M. Shanechi. Model-based prediction of large-scale brain network dynamic response to direct electrical stimulation. Nature Biomedical Engineering (in review), 2019.

S. Musall, M. T. Kaufman, A. L. Juayinett, S. Gluf, and A. K. Churchland. Single-trial neural dynamics are dominated by richly varied movements. Nature Neuroscience (in press), 2019.

S. Musall, A. Urai, D. Sussillo, and A. Churchland. Harnessing behavioral diversity to understand circuits for cognition. arXiv preprint arXiv:1906.09622, 2019.

S. Pisupati, L. Chartarifsky-Lynn, A. Khanal, and A. K. Churchland. Lapses in perceptual decisions reflect exploration. bioRxiv, 2019.

L. Chua, M. I. Jordan, and R. Muller. High sensitivity, low power, seizure detection classifier with unsupervised online learning. In IEEE Biomedical Circuits and Systems Conference (BioCAS) (submitted to), 2019.

A. Ramdas, J. Chen, M. J. Wainwright, and M. I. Jordan. A sequential algorithm for false discovery rate control on directed acyclic graphs. Biometrika, 106(1):69-86, 2019.

J. Zazo, B. Tolooshams, and D. Ba. Convolutional dictionary learning in hierarchical networks. In International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019.

S. Bhattacharyya, C. Cinel, L. Citi, D. Valeriani, and R. Poli. Walking improves the performance of a brainā€? computer interface for group decisionā€?making. In 2nd Neuroadaptive Technology Conference, Liverpool, UK, 2019.

S. Bhattacharyya, D. Valeriani, C. Cinel, L. Citi, and R. Poli. Collaborative brain-computer interfaces to enhance group decisions in an outpost surveillance task. 2019.

R. Wang, C. Ciliberto, P. Amadori, and Y. Demiris. Random expert distillation: Imitation learning via expert policy support estimation. 2019.

W. von Rosenberg, M.-O. Hoting, and D. P. Mandic. A physiology based model of heart rate variability. Biomedical Engineering Letters, pages 1-10, 2019.

2018

H. Abbaspourazad, Y. Wong, B. Pesaran, and M. M. Shanechi. Identifying multiscale hidden states to decode behavior. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 3778-3781. IEEE, 2018.

H. Abbaspourazad, Y. T. Wong, B. Pesaran, and M. M. Shanechi. Identifying multiscale hidden neural dynamics to decode movemen. In Annual Meeting, Society for Neuroscience (SFN), 2018.

T. Adjei, J. Xue, and D. P. Mandic. The female heart: sex differences in the dynamics of ecg in response to stress. Frontiers in physiology, 9, 2018.

D. Ba. Deeply-sparse signal representations (DS2P). arXiv preprint arXiv:1807.01958, 2018.

T. Banerjee, J. Choi, B. Pesaran, D. Ba, and V. Tarokh. Classification of local field potentials using gaussian sequence model. In 2018 IEEE Statistical Signal Processing Workshop (SSP), pages 683-687. IEEE, 2018.

T. Banerjee, J. Choi, B. Pesaran, D. Ba, and V. Tarokh. Wavelet shrinkage and thresholding based robust classification for brain-computer interface. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 836-840. IEEE, 2018.

R. Bighamian and M. M. Shanechi. Estimation of functional dependence in high-dimensional spike-field activity. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 2635-2638. IEEE, 2018.

R. Bighamian and M. M. Shanechi. Modeling functional dependencies in high-dimensional spike-field activity. In Annual Meeting, Society for Neuroscience (SFN), 2018.

J. Choi, V. Goncharov, J. Kleinbart, A. Orsborn, and B. Pesaran. Monkey-mimms: Towards automated cellular resolution large-scale two-photon microscopy in the awake macaque monkey. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 3013-3016. IEEE, 2018.

G. Denevi, C. Ciliberto, D. Stamos, and M. Pontil. Incremental learning-to-learn with statistical guarantees. arXiv preprint arXiv:1803.08089, 2018.

G. Denevi, C. Ciliberto, D. Stamos, and M. Pontil. Learning to learn around a common mean. In Advances in Neural Information Processing Systems, pages 10169-10179, 2018.

D. J. Hawellek, K. A. Brown, and B. Pesaran. Deliberation and enaction during adaptive economic choice. bioRxiv, page 445346, 2018.

A. Hemakom, V. Goverdovsky, and D. P. Mandic. Ear-eeg for detecting inter-brain synchronisation in continuous cooperative multi-person scenarios. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 911-915. IEEE, 2018.

H.-L. Hsieh, Y. T. Wong, B. Pesaran, and M. M. Shanechi. Multiscale modeling and decoding of spike-field activity. In Computational and Systems Neuroscience (Cosyne), 2018.

H.-L. Hsieh, Y. T. Wong, B. Pesaran, and M. M. Shanechi. Multiscale modeling and decoding algorithms for spike-field activity. Journal of neural engineering, 2018.

H.-L. Hsieh and M. M. Shanechi. Optimizing the learning rate for adaptive estimation of neural encoding models. PLoS computational biology, 14(5):e1006168, 2018.

S. Kanna, W. von Rosenberg, V. Goverdovsky, A. G. Constantinides, and D. P. Mandic. Bringing wearable sensors into the classroom: A participatory approach [sp education]. IEEE Signal Processing Magazine, 35(3):110-130, 2018.

G. Luise, A. Rudi, M. Pontil, and C. Ciliberto. Differential properties of sinkhorn approximation for learning with wasserstein distance. In Advances in Neural Information Processing Systems, pages 5859-5870, 2018.

N. Malem-Shinitski, Y. Zhang, D. T. Gray, S. N. Burke, A. C. Smith, C. A. Barnes, and D. Ba. A separable two-dimensional random field model of binary response data from multi-day behavioral experiments. Journal of neuroscience methods, 307:175-187, 2018.

F. Najafi, G. F. Elsayed, E. Pnevmatikakis, J. Cunningham, and A. K. Churchland. Inhibitory and excitatory populations in parietal cortex are equally selective for decision outcome in both novices and experts. bioRxiv, page 354340, 2018.

T. Nakamura, Y. D. Alqurashi, M. J. Morrell, and D. P. Mandic. Automatic detection of drowsiness using in-ear eeg. In 2018 International Joint Conference on Neural Networks (IJCNN), pages 1-6. IEEE, 2018.

P. Normahani, N. Makwana, W. von Rosenberg, S. Syed, D. P. Mandic, V. Goverdovsky, N. J. Standfield, and U. Jaffer. Self-assessment of surgical ward crisis management using video replay augmented with stress biofeedback. Patient safety in surgery, 12(1):6, 2018.

B. Pesaran, M. Vinck, G. T. Einevoll, A. Sirota, P. Fries, M. Siegel, W. Truccolo, C. E. Schroeder, and R. Srinivasan. Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation. Nature neuroscience, 21(7):903, 2018.

A. Ramdas, T. Zrnic, M. Wainwright, and M. Jordan. Saffron: an adaptive algorithm for online control of the false discovery rate. arXiv preprint arXiv:1802.09098, 2018.

N. Sadras and M. M. Shanechi. Decoding spike trains from neurons with spatio-temporal receptive fields. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 2012-2015. IEEE, 2018.

B. Tolooshams, S. Dey, and D. Ba. Scalable convolutional dictionary learning with constrained recurrent sparse auto-encoders. In 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), pages 1-6. IEEE, 2018.

D. Valeriani, S. Bhattacharyya, C. Cinel, L. Citi, and R. Poli. Augmenting group decision making accuracy in a realistic environment using collaborative brain-computer interfaces based on error-related potentials. 7th International BCI Meeting 2018 (Asilomar, CA), 2018.

C. Wang and M. M. Shanechi. An information-theoretic measure of multiscale causality for spike-field activity. In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 2631-2634. IEEE, 2018.

C. Wang and M. M. Shanechi. Learning causal graphs in spike-field multiscale network encoding models. In Annual Meeting, Society for Neuroscience (SFN), 2018.

Y. Zhang, N. Malem-Shinitski, S. A. Allsop, K. M. Tye, and D. Ba. Estimating a separably markov random field from binary observations. Neural computation, 30(4):1046-1079, 2018.

O. G. Sani and M. M. Shanechi. Learning dynamic neural encoding models with behaviorally-relevant latent states. In Annual Meeting, Society for Neuroscience (SFN), 2018.

F. Najafi and A. K. Churchland. Perceptual decision-making: A field in the midst of a transformation. Neuron, 100(2):453-462, oct 2018.

T. Zrnic, A. Ramdas, and M. I. Jordan. Asynchronous online testing of multiple hypotheses. arXiv preprint arXiv:1812.05068, 2018.

T. Nakamura, Y. D. Alqurashi, M. J. Morrell, and D. P. Mandic. Automatic detection of drowsiness using in-ear eeg. In 2018 International Joint Conference on Neural Networks (IJCNN), pages 1-6. IEEE, 2018.

2017

H. Abbaspourazad, H.-L. Hsieh, and M. M. Shanechi. Multiscale modeling of dependencies between spikes and fields. In 2017 51st Asilomar Conference on Signals, Systems, and Computers, pages 719-723. IEEE, 2017.

H. Abbaspourazad and M. M. Shanechi. An unsupervised learning algorithm for multiscale neural activity. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 201-204. IEEE, 2017.

T. Adjei, W. Von Rosenberg, V. Goverdovsky, K. Powezka, U. Jaffer, and D. P. Mandic. Pain prediction from ecg in vascular surgery. IEEE journal of translational engineering in health and medicine, 5:1-10, 2017.

C. Ciliberto, A. Rudi, L. Rosasco, and M. Pontil. Consistent multitask learning with nonlinear output relations. In Advances in Neural Information Processing Systems, pages 1986-1996, 2017.

C. Ciliberto, D. Stamos, and M. Pontil. Reexamining low rank matrix factorization for trace norm regularization. arXiv preprint arXiv:1706.08934, 2017.

T. Georgiou and Y. Demiris. Adaptive user modelling in car racing games using behavioural and physiological data. User Modeling and User-Adapted Interaction, 27(2):267-311, 2017.

V. Goverdovsky, W. von Rosenberg, T. Nakamura, D. Looney, D. J. Sharp, C. Papavassiliou, M. J. Morrell, and D. P. Mandic. Hearables: Multimodal physiological in-ear sensing. Scientific reports, 7(1):6948, 2017.

A. Hemakom, K. Powezka, V. Goverdovsky, U. Jaffer, and D. P. Mandic. Quantifying team cooperation through intrinsic multi-scale measures: respiratory and cardiac synchronization in choir singers and surgical teams. Royal Society open science, 4(12):170853, 2017.

H.-L. Hsieh, Y. T. Wong, B. Pesaran, and M. M. Shanechi. Multiscale decoding for reliable brain-machine interface performance over time. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 197-200. IEEE, 2017.

H.-L. Hsieh, Y. T. Wong, B. Pesaran, and M. M. Shanechi. Multiscale decoding of spike-field activity to improve brain-machine interface robustness and longevity. In Annual Meeting, Society for Neuroscience (SFN), 2017.

S. L. Kappel, D. Looney, D. P. Mandic, and P. Kidmose. Physiological artifacts in scalp eeg and ear-eeg. Biomedical engineering online, 16(1):103, 2017.

L. Lei and M. Jordan. Less than a single pass: Stochastically controlled stochastic gradient. In Artificial Intelligence and Statistics, pages 148-156, 2017.

F. Najafi, G. F. Elsayed, E. A. Pnevmatikakis, J. P. Cunningham, and A. K. Churchland. Single-trial decision can be predicted from population activity of excitatory and inhibitor neurons. In Annual Meeting, COSYNE, 2017.

T. Nakamura, V. Goverdovsky, and D. P. Mandic. In-ear eeg biometrics for feasible and readily collectable real-world person authentication. IEEE Transactions on Information Forensics and Security, 13(3):648-661, 2017.

M. Rabinovich, A. Ramdas, M. I. Jordan, and M. J. Wainwright. Optimal rates and tradeoffs in multiple testing. arXiv preprint arXiv:1705.05391, 2017.

A. Ramdas, J. Chen, M. J. Wainwright, and M. I. Jordan. Dagger: A sequential algorithm for fdr control on dags. arXiv preprint arXiv:1709.10250, 2017.

A. Ramdas, F. Yang, M. J. Wainwright, and M. I. Jordan. Online control of the false discovery rate with decaying memory. In Advances In Neural Information Processing Systems, pages 5650-5659, 2017.

A. Ramdas, J. Chen, M. J. Wainwright, and M. I. Jordan. Qute: Decentralized multiple testing on sensor networks with false discovery rate control. In 2017 IEEE 56th Annual Conference on Decision and Control (CDC), pages 6415-6421. IEEE, 2017.

H. Abbaspourazad and M. M. Shanechi. Learning the dependencies between spikes and fields in multiscale modeling. In Annual Meeting, Society for Neuroscience (SFN), 2017.

H. Abbaspourazad, H.-L. Hsieh, and M. M. Shanechi. Multiscale modeling of high-dimensional neural activity. In Asilomar conference on signals, systems and computers, 2017.

Y. Tonoyan, T. Chanwimalueang, D. P. Mandic, and M. M. Van Hulle. Discrimination of emotional states from scalp-and intracranial eeg using multiscale rényi entropy. PloS one, 12(11):e0186916, 2017.

D. Valeriani, C. Cinel, and R. Poli. Augmenting group performance in target-face recognition via collaborative brain-computer interfaces for surveillance applications. In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), pages 415-418. IEEE, 2017.

D. Valeriani, C. Cinel, and R. Poli. A collaborative bci trained to aid group decisions in a visual search task works well with similar tasks. In 1st Biannual Neuroadaptive Technology Conference (NAT’17), pages 77-78, 2017.

D. Valeriani, C. Cinel, and R. Poli. Group augmentation in realistic visual-search decisions via a hybrid brain-computer interface. Scientific reports, 7(1):7772, 2017.

W. von Rosenberg, T. Chanwimalueang, V. Goverdovsky, N. S. Peters, C. Papavassiliou, and D. P. Mandic. Hearables: Feasibility of recording cardiac rhythms from head and in-ear locations. Royal Society Open Science, 4(11):171214, 2017.

W. von Rosenberg, T. Chanwimalueang, T. Adjei, U. Jaffer, V. Goverdovsky, and D. P. Mandic. Resolving ambiguities in the lf/hf ratio: Lf-hf scatter plots for the categorization of mental and physical stress from hrv. Frontiers in physiology, 8:360, 2017.

2016

H.-L. Hsieh and M. M. Shanechi. Adaptive multiscale brain-machine interface decoders. In Annual Meeting, Society for Neuroscience (SFN), 2016.

H.-L. Hsieh and M. M. Shanechi. Multiscale brain-machine interface decoders. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 6361-6364. IEEE, 2016.

H. Abbaspourazad and M. M. Shanechi. A new modeling framework for multiscale neural activity underlying behavior. In Annual Meeting, Society for Neuroscience (SFN), 2016.

M. M. Shanechi. Brain-machine interface control algorithms. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(10):1725-1734, 2016.

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