10 papers
Constitution-Guided Watermarking
Toluwani Aremu, Samuele Poppi, Nils Lukas
Regulation such as the EU AI Act requires providers of language models to mark generated text in a machine-readable way. Watermarking meets this requirement by embedding a secret-k…
iMINDBench: iEEG Multi-Institution Neural Decoding Benchmark
Geeling Chau, Saba Hashemi, Yonghyeon Gwon +9
Intracranial electroencephalography (iEEG) is widely used to record electrical activity directly from electrodes inside the human brain, making it an attractive modality for neural…
Cross-Subject Modeling for Widefield Calcium Imaging via Atlas-Aligned Spatiotemporal Tokenization
Mohammad Hosseini, Eray Erturk, Saba Hashemi +1
Large-scale, multi-subject widefield calcium imaging provides unprecedented access to brain-wide cortical dynamics. However, the high dimensionality, complex spatiotemporal structu…
Nonlinear Dynamical Modeling of Human Intracranial Brain Activity with Flexible Inference
Kiarash Vaziri, Lucine L. Oganesian, HyeongChan Jo +4
Dynamical modeling of multisite human intracranial neural recordings is essential for developing neurotechnologies such as brain-computer interfaces (BCIs). Linear dynamical models…
Unsupervised learning of multiscale switching dynamical system models from multimodal neural data
DongKyu Kim, Han-Lin Hsieh, Maryam M. Shanechi
Neural population activity often exhibits regime-dependent non-stationarity in the form of switching dynamics. Learning accurate switching dynamical system models can reveal how be…
Dynamical modeling of nonlinear latent factors in multiscale neural activity with real-time inference
Eray Erturk, Maryam M. Shanechi
Real-time decoding of target variables from multiple simultaneously recorded neural time-series modalities, such as discrete spiking activity and continuous field potentials, is im…
Cross-Modal Representational Knowledge Distillation for Enhanced Spike-Informed LFP Modeling
Eray Erturk, Saba Hashemi, Maryam M. Shanechi
Local field potentials (LFPs) can be routinely recorded alongside spiking activity in intracortical neural experiments, measure a larger complementary spatiotemporal scale of brain…
BaRISTA: Brain Scale Informed Spatiotemporal Representation of Human Intracranial Neural Activity
Lucine L. Oganesian, Saba Hashemi, Maryam M. Shanechi
Intracranial recordings have opened a unique opportunity to simultaneously measure activity across multiregional networks in the human brain. Recent works have focused on developin…
Dynamical Modeling of Behaviorally Relevant Spatiotemporal Patterns in Neural Imaging Data
Mohammad Hosseini, Maryam M. Shanechi
High-dimensional imaging of neural activity, such as widefield calcium and functional ultrasound imaging, provide a rich source of information for understanding the relationship be…
Probabilistic Geometric Principal Component Analysis with application to neural data
Han-Lin Hsieh, Maryam M. Shanechi
Dimensionality reduction is critical across various domains of science including neuroscience. Probabilistic Principal Component Analysis (PPCA) is a prominent dimensionality reduc…