4 papers
Spatially Masked Regression Reveals Local and Distributed Predictability in Electrophysiological Recordings
Maryam Ostadsharif Memar, Nima Dehghani
Neural recordings are often interpreted as local measurements, yet the signal at any one sensor can also reflect structured activity distributed across the broader network. This ra…
Hierarchical Stochastic Differential Equation Models for Latent Manifold Learning in Neural Time Series
Pedram Rajaei, Maryam Ostadsharif Memar, Navid Ziaei +2
The manifold hypothesis suggests that high-dimensional neural time series lie on a low-dimensional manifold shaped by simpler underlying dynamics. To uncover this structure, latent…
A Combined Channel Approach for Decoding Intracranial EEG Signals: Enhancing Accuracy through Spatial Information Integration
Maryam Ostadsharif Memar, Navid Ziaei, Behzad Nazari
Intracranial EEG (iEEG) recording, characterized by high spatial and temporal resolution and superior signal-to-noise ratio (SNR), enables the development of precise brain-computer…
RISE-iEEG: Robust to Inter-Subject Electrodes Implantation Variability iEEG Classifier
Maryam Ostadsharif Memar, Navid Ziaei, Behzad Nazari +1
Intracranial electroencephalography (iEEG) is increasingly used for clinical and brain-computer interface applications due to its high spatial and temporal resolution. However, int…