5 papers
Learning Behaviorally Relevant Dynamics in Multimodal Neural Recordings
Parastoo Azizeddin, Eray Erturk, Maryam M. Shanechi
Multimodal neural data can enable a more complete understanding of brain dynamics underlying behavior. Modalities such as spiking activity, local field potentials (LFPs), and behav…
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…
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…
Beyond Sensor Data: Foundation Models of Behavioral Data from Wearables Improve Health Predictions
Eray Erturk, Fahad Kamran, Salar Abbaspourazad +6
Wearable devices record physiological and behavioral signals that can improve health predictions. While foundation models are increasingly used for such predictions, they have been…