4 papers
A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks
Georgios Mentzelopoulos, Ioannis Asmanis, Konrad P. Kording +3
Brain-computer interfaces (BCIs) promise to enable vital functions, such as speech and prosthetic control, for individuals with neuromotor impairments. Central to their success are…
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
Philippe Brouillard, Chandler Squires, Jonas Wahl +4
Causal discovery aims to automatically uncover causal relationships from data, a capability with significant potential across many scientific disciplines. However, its real-world a…
Homogenized Neural Activity and Connectivity Data
Quilee Simeon, Anshul Kashyap, Konrad P Kording +1
There is renewed interest in modeling and understanding the nervous system of the nematode (), as this small model system pro…
Neural decoding from stereotactic EEG: accounting for electrode variability across subjects
Georgios Mentzelopoulos, Evangelos Chatzipantazis, Ashwin G. Ramayya +5
Deep learning based neural decoding from stereotactic electroencephalography (sEEG) would likely benefit from scaling up both dataset and model size. To achieve this, combining dat…