Neural decoding of EEG signals with machine learning: a systematic review

M Saeidi, W Karwowski, FV Farahani, K Fiok, R Taiar… - Brain Sciences, 2021 - mdpi.com
Electroencephalography (EEG) is a non-invasive technique used to record the brain's
evoked and induced electrical activity from the scalp. Artificial intelligence, particularly …

Applying deep learning to single-trial EEG data provides evidence for complementary theories on action control

A Vahid, M Mückschel, S Stober, AK Stock… - Communications …, 2020 - nature.com
Efficient action control is indispensable for goal-directed behaviour. Different theories have
stressed the importance of either attention or response selection sub-processes for action …

Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses

A Vahid, M Mückschel, A Neuhaus, AK Stock… - Scientific reports, 2018 - nature.com
Neurophysiological features like event-related potentials (ERPs) have long been used to
identify different cognitive sub-processes that may contribute to task performance. It has …

The psychophysiology of action: A multidisciplinary endeavor for integrating action and cognition

S Hoffmann, U Borges, L Bröker, S Laborde… - Frontiers in …, 2018 - frontiersin.org
There is a vast amount of literature concerning the integration of action and cognition.
Although this broad research area is of great interest for many disciplines like sports …

The neural stability of perception–motor representations affects action outcomes and behavioral adaptation

S Yu, M Mückschel, S Hoffmann, A Bluschke… - …, 2023 - Wiley Online Library
Actions can fail–even though this is well known, little is known about what distinguishes
neurophysiological processes preceding errors and correct actions. In this study, relying on …

Learning experience reverses catecholaminergic effects on adaptive behavior

M Mückschel, E Eggert, A Prochnow… - International Journal of …, 2020 - academic.oup.com
Background Catecholamines are important for cognitive control and the ability to adapt
behavior (eg, after response errors). A prominent drug that modulates the catecholaminergic …

A neuronal theta band signature of error monitoring during integration of facial expression cues

C Dias, D Costa, T Sousa, J Castelhano, V Figueiredo… - PeerJ, 2022 - peerj.com
Error monitoring is the metacognitive process by which we are able to detect and signal our
errors once a response has been made. Monitoring when the outcome of our actions …

A neuro-based method for detecting context-dependent erroneous robot action

S Ehrlich, G Cheng - 2016 IEEE-RAS 16th International …, 2016 - ieeexplore.ieee.org
Validating appropriateness and naturalness of human-robot interaction (HRI) is commonly
performed by taking subjective measures from human interaction partners, eg questionnaire …

A condition-independent framework for the classification of error-related brain activity

I Kakkos, EM Ventouras, PA Asvestas… - Medical & Biological …, 2020 - Springer
The cognitive processing and detection of errors is important in the adaptation of the
behavioral and learning processes. This brain activity is often reflected as distinct patterns of …

Algorithmic Bias in BERT for Response Accuracy Prediction: A Case Study for Investigating Population Validity

G Gorgun, SN Yildirim‐Erbasli - Journal of Educational …, 2024 - Wiley Online Library
Pretrained large language models (LLMs) have gained popularity in recent years due to
their high performance in various educational tasks such as learner modeling, automated …