65 results for "connectome" · page 3 of 7 · ranked by relevance
This dataset contains MEG data collected as part of the FLUX pipeline project, a standardized analysis and preprocessing pipeline for magnetoencephalography (MEG) research. The dataset was reorganized into BIDS format from an original OpenNeuro dataset to support reproducible MEG analysis workflows across multiple research sites.
PsiConnect is a large-scale multimodal neuroimaging study investigating context-dependent neural and subjective effects of psilocybin in 62 participants. The dataset combines functional, structural, and diffusion-weighted MRI with concurrent EEG acquired before and after psilocybin administration (19 mg), incorporating resting-state and naturalistic conditions (guided meditation, music listening, movie watching). Half the cohort completed an 8-week meditation training program, enabling investigation of interactions between meditation, psilocybin, and brain function. Comprehensive behavioral and self-report measures were collected acutely and longitudinally up to one year post-administration.
This dataset comprises simultaneous EEG and fNIRS recordings from 12 participants performing semantic imagery tasks involving silent naming and sensory-based imagination of animals and tools. Participants engaged in visual, auditory, and tactile perception tasks while neural activity was captured using a 64-channel BioSemi EEG system and a NIRx fNIRS imaging system with integrated optodes. The multimodal neuroimaging data supports research in semantic decoding and brain-computer interface applications.
This dataset comprises simultaneous EEG and fMRI recordings from 10 subjects performing motor imagery and neurofeedback tasks. Participants completed six runs including motor localization, pre- and post-neurofeedback motor imagery, and three neurofeedback conditions (bimodal EEG-fMRI, unimodal EEG, and unimodal fMRI). The dataset provides both raw and preprocessed EEG data (64 channels at 5 kHz), structural and functional MRI data (3T Siemens, 2×2×4 mm³ resolution), and computed neurofeedback scores, enabling multi-modal neuroimaging data integration studies.
This dataset contains electroencephalogram (EEG) recordings from 15 university students (8 males, 7 females; aged 21-23 years) collected to investigate brain connectivity during learning processes involving generative AI. Participants performed essay-writing tasks under varying AI interaction conditions, enabling assessment of cognitive states such as creativity, memory, and critical thinking.
This open multimodal dataset combines intracranial electroencephalography (iEEG) and functional magnetic resonance imaging (fMRI) recordings from patients during naturalistic audiovisual film stimulation. The dataset includes simultaneous electrocorticography and fMRI data collected during a short film presentation, providing a unique resource for investigating neural responses to complex naturalistic stimuli across multiple recording modalities and spatial scales.
FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.
This dataset presents multimodal simultaneous fMRI/EEG data collected from participants performing an auditory category learning task, alongside resting-state fMRI scans. Each dataset includes 63-channel EEG with additional ECG, EOG, facial EMG, and skin conductance recordings, a physiological file capturing respiration and finger-pulse signals, and structural MRI (T1-weighted and PD-weighted UTE) scans for anatomical reference and electrode localization. Collected at the Combinatorial NeuroImaging core facility of the Leibniz Institute for Neurobiology, the data support research into multi-dimensional auditory category learning and its neural correlates.
This dataset comprises concurrent deep-brain electrical stimulation and whole-brain functional MRI data from 26 patients with medically refractory epilepsy. Patients underwent intracranial electrode implantation for clinical purposes, with one or multiple electrode contacts stimulated during fMRI acquisition using block design protocols. The resource includes anatomical imaging (T1, T2), resting-state fMRI, electrical stimulation-fMRI (es-fMRI) scans, field maps, electrode coordinates, and stimulation parameters, along with preprocessed derivatives.
This dataset comprises simultaneous EEG-fMRI recordings from 24 healthy adults performing a sustained attention task (GradCPT) and a resting-state task with intermittent multi-dimensional experience sampling, collected across two sessions per participant. It includes behavioral responses, experience sampling ratings across 13 dimensions of thought, and mental health survey data, enabling study of the neural correlates of attentional fluctuations, mind-wandering, and the reliability of EEG-fMRI relationships across sessions.