DeepAI AI Chat
Log In Sign Up

Robust and highly adaptable brain-computer interface with convolutional net architecture based on a generative model of neuromagnetic measurements

05/28/2018
by   Ivan Zubarev, et al.
0

Deep Neural Networks have been applied very successfully in image recognition and natural language processing. Recently these powerful methods have received attention also in the brain-computer interface (BCI) community. Here, we introduce a convolutional neural network (CNN) architecture optimized for classification of brain states from non-invasive magnetoencephalographic (MEG) measurements. The model structure is motivated by a state-of-the-art generative model of the MEG signal and is thus readily interpretable in neurophysiological terms. We demonstrate that the proposed model is highly accurate in decoding event-related responses as well as modulations of oscillatory brain activity, and is robust with respect to inter-individual differences. Importantly, the model generalizes well across users: when trained on data pooled from previous users, it can successfully perform on new users. Thus, the time-consuming BCI calibration can be omitted. Moreover, the model can be incrementally updated, resulting in +8.9 +17.0 BCIs and basic neuroscience research.

READ FULL TEXT

page 1

page 2

page 3

page 4

03/12/2021

Hippocampal formation-inspired probabilistic generative model

We constructed a hippocampal formation (HPF)-inspired probabilistic gene...
08/25/2022

Decoding speech from non-invasive brain recordings

Decoding language from brain activity is a long-awaited goal in both hea...
03/05/2020

A Neuro-AI Interface for Evaluating Generative Adversarial Networks

Generative adversarial networks (GANs) are increasingly attracting atten...
01/26/2023

DBGDGM: Dynamic Brain Graph Deep Generative Model

Graphs are a natural representation of brain activity derived from funct...
08/17/2022

EEG-BBNet: a Hybrid Framework for Brain Biometric using Graph Connectivity

Brain biometrics based on electroencephalography (EEG) have been used in...
04/30/2019

Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks

Neural coding is one of the central questions in systems neuroscience fo...
11/25/2020

Convolutional Neural Networks for cytoarchitectonic brain mapping at large scale

Human brain atlases provide spatial reference systems for data character...