AIMC Topic: Evoked Potentials

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A TrAdaBoost Method for Detecting Multiple Subjects' N200 and P300 Potentials Based on Cross-Validation and an Adaptive Threshold.

International journal of neural systems
Traditional training methods need to collect a large amount of data for every subject to train a subject-specific classifier, which causes subjects fatigue and training burden. This study proposes a novel training method, TrAdaBoost based on cross-va...

EEG Signals Classification Using Machine Learning for The Identification and Diagnosis of Schizophrenia.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents the design of a machine learning-based classifier for the differentiation between Schizophrenia patients and healthy controls using features extracted from electroencephalograph(EEG) signals based on event related potential(ERP). ...

3D Convolutional Neural Networks for Event-Related Potential detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Deep learning techniques have recently been successful in the classification of brain evoked responses for multiple applications, including brain-machine interface. Single-trial detection in the electroencephalogram (EEG) of brain evoked responses, l...

Classification of TMS evoked potentials using ERP time signatures and SVM versus deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Modeling transcranial magnetic stimulation (TMS) evoked potentials (TEP) begins with classification of stereotypical single-pulse TMS responses in order to select validation targets for generative dynamical models. Several dimensionality reduction te...

Extremely Reduced Data Sets Indicate Optimal Stimulation Parameters for Classification in Brain-Computer Interfaces.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The time between the onset of subsequent auditory or visual stimuli - also known as stimulus onset asynchrony (SOA) - determines many of the event-related potential characteristics of the resulting evoked brain signals. Specifically, the SOA value in...

The Decision Decoding ToolBOX (DDTBOX) - A Multivariate Pattern Analysis Toolbox for Event-Related Potentials.

Neuroinformatics
In recent years, neuroimaging research in cognitive neuroscience has increasingly used multivariate pattern analysis (MVPA) to investigate higher cognitive functions. Here we present DDTBOX, an open-source MVPA toolbox for electroencephalography (EEG...

Application of a brain-computer interface for person authentication using EEG responses to photo stimuli.

Journal of integrative neuroscience
In this paper, a personal authentication system that can effectively identify individuals by generating unique electroencephalogram signal features in response to self-face and non-self-face photos is presented. To achieve performance stability, a se...

Convolutional Neural Network for Target Face Detection using Single-trial EEG Signal.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Face recognition plays an import role in our daily lives. However, computer face recognition performance degrades dramatically with the presence of variations in illumination, head pose and occlusion. In contrast, the human brain can recognize target...

The combined use of virtual reality and EEG to study language processing in naturalistic environments.

Behavior research methods
When we comprehend language, we often do this in rich settings where we can use many cues to understand what someone is saying. However, it has traditionally been difficult to design experiments with rich three-dimensional contexts that resemble our ...

A Hybrid Network for ERP Detection and Analysis Based on Restricted Boltzmann Machine.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Detecting and Please provide the correct one analyzing the event-related potential (ERP) remains an important problem in neuroscience. Due to the low signal-to-noise ratio and complex spatio-temporal patterns of ERP signals, conventional methods usua...