30 results for "facial expressions" · page 2 of 3 · ranked by relevance
…The EEG files contain 63 head channels, ECG, EOG, facial EMG and…
This dataset investigates brain signal-based emotion recognition through magnetoencephalography (MEG) recordings collected while participants viewed validated emotional video stimuli. It comprises three components: a large-scale online behavioral survey of 500 participants rating 40 video clips, head digitization data for co-registration, and MEG neural recordings from 23 participants viewing the same stimuli. Emotional states were assessed using Self-Assessment Manikin ratings, discrete emotion categories (PrEmo), and temporal highlight annotations, providing multi-faceted ground truth for affective neuroscience research.
…A root-level `/stimuli` folder containing the facial cut-outs (JPG) of…
This dataset contains EEG recordings used to derive auditory brainstem responses (ABRs) to continuous, naturally uttered speech under varying levels of speech masking. Data were collected from 25 normal-hearing adult participants presented with click trains and 'peaky speech' stimuli from one to five simultaneously presented talkers at different signal-to-noise ratios. The study aims to characterize how masking affects subcortical neural encoding of speech in human listeners, building on prior methods for deriving speech-ABRs.
…The dataset does not contain: * Personal identifying information * Facial images * Structural MRI…
This dataset comprises multi-subject, multimodal neuroimaging data (structural MRI, fMRI, MEG, and EEG) collected during a face processing task, in which participants viewed famous, unfamiliar, and scrambled faces presented under initial, immediate repeat, and delayed repeat conditions. It is a BIDS-formatted subset of the original Wakeman & Henson (2015) dataset, designed to support research on multimodal integration of brain imaging data and studies of face recognition and repetition effects.
…time (TE) of 5.1ms. Facial structures were removed from T1-weighted…
The Brain, Body, and Behaviour Dataset (Experiment 4) is a multimodal neurophysiological dataset comprising simultaneous recordings of EEG, eye-tracking, cardiac, respiratory, and electrooculographic signals from 43 subjects across two sessions. Participants watched three educational videos (Stim-04, Stim-05, Stim-06) under two attention conditions. In Session 1 (attentive condition), participants viewed the videos and answered comprehension questions afterward. In Session 2 (distracted condition), participants viewed the same three videos in the same order while performing a concurrent backward counting task, with no comprehension testing. This derivative dataset supports investigation of neural and behavioral correlates of attention, learning, and cognitive load during naturalistic video viewing.
…via dcm2niix (v1.0.20220505). Facial features were removed from anatomical images…
This dataset comprises multimodal physiological recordings from 23 healthy adult participants collected during naturalistic smartphone interaction and standardized video viewing conditions. Simultaneous EEG (64-channel), eye-tracking, photoplethysmography (PPG), and galvanic skin response (GSR) data were acquired, synchronized via hardware TTL pulses. The dataset supports research into physiological and neural correlates of smartphone use and passive video viewing.