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Psychophysiology|May 12, 2023
Deep learning on independent spatial EEG activity patterns delineates time windows relevant for response inhibitionNegin Gholamipourbarogh, Amirali Vahid, Moritz Mückschel, et al.
NPJ Dementia|December 8, 2025
Predicting future amyloid conversion: the role of baseline amyloid distribution, genetic and cognitive resilienceAmirali Vahid, Jafar Zamani, S M Hadi Hosseini
Frontiers in Human Neuroscience|March 8, 2019
The Intensity of Early Attentional Processing, but Not Conflict Monitoring, Determines the Size of Subliminal Response ConflictsWiebke Bensmann, Amirali Vahid, Christian Beste, et al.
Frontiers in Human Neuroscience|November 22, 2018
On the Neurophysiological Mechanisms Underlying the Adaptability to Varying Cognitive Control DemandsNicolas Zink, Ann-Kathrin Stock, Amirali Vahid, et al.
Neuroimage. Reports|June 26, 2025
On the relative importance of attention and response selection processes for multi-component behavior - Evidence from EEG-based deep learningAmirali Vahid, Ann-Kathrin Stock, Moritz Mückschel, et al.
Journal of Clinical Medicine|July 24, 2019
Deep Learning Based on Event-Related EEG Differentiates Children with ADHD from Healthy ControlsAmirali Vahid, Annet Bluschke, Veit Roessner, et al.
Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association|March 14, 2026
Multivariate patterns of plasma biomarkers predict region-specific Alzheimer's pathology and cognitive decline across independent cohortsJafar Zamani, Amirali Vahid, Edward N Wilson, et al.
Scientific Reports|November 4, 2018
Machine learning provides novel neurophysiological features that predict performance to inhibit automated responsesAmirali Vahid, Moritz Mückschel, Andres Neuhaus, et al.
Communications Biology|March 11, 2020
Applying deep learning to single-trial EEG data provides evidence for complementary theories on action controlAmirali Vahid, Moritz Mückschel, Sebastian Stober, et al.
Communications Biology|February 22, 2022
Conditional generative adversarial networks applied to EEG data can inform about the inter-relation of antagonistic behaviors on a neural levelAmirali Vahid, Moritz Mückschel, Sebastian Stober, et al.
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