sottoscrivi

Accedi

A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity

A neurophysiologically interpretable deep neural network predicts complex  movement components from brain activity

Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions

Why is everyone talking about brain state?: Trends in Neurosciences

Key Findings

Predicting Human Behavior with Diffusion Models - Sapien Labs, Neuroscience

Deep Learning Methods for EEG Neural Classification

A neurophysiologically interpretable deep neural network predicts complex movement components from brain activity

Eeg Decoding Papers With Code

A deep learning approach with event-related spectral EEG data in attentional deficit hyperactivity disorder

From brain to movement: Wearables-based motion intention prediction across the human nervous system - ScienceDirect

Many but not all deep neural network audio models capture brain responses and exhibit correspondence between model stages and brain regions

Weak self-supervised learning for seizure forecasting: a feasibility study

Topological data analysis for revealing dynamic brain reconfiguration in MEG data [PeerJ]

From brain to movement: Wearables-based motion intention prediction across the human nervous system - ScienceDirect

Approaches to revealing the neural basis of muscle synergies: a review and a critique

Frontiers Multimodal intelligent logistics robot combining 3D CNN, LSTM, and visual SLAM for path planning and control