STRONG
Imported from OpenNeuro ds004849
- Participants
- 1
- Channels
- 64 (10-10)
- Citations
- 2
- HED
- v8.1.0
- Size
- 78.9 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
100 results for "naturalistic stimulation" · page 9 of 10 · ranked by relevance
Imported from OpenNeuro ds004849
…Brain Stimulation, in press. Real-time and offline analysis code can be…
[ recordings from 50 healthy control participants performing a reinforcement learning task under two mood conditions: sad mood manipulation (n=25) and neutral mood manipulation (n=25). The task included training and testing phases adapted from established reinforcement learning paradigms. Data were collected between 2019-2021 at the Cognitive Rhythms and Computation Lab at the University of New Mexico to investigate the effects of mood state on learning and decision-making processes.
A multiclass electroencephalography dataset of inner speech commands acquired from ten subjects using a 136-channel system. The dataset includes three experimental paradigms: inner speech, pronounced speech, and visualized conditions, with four directional commands (up, down, right, left) totaling 5,640 trials. This resource addresses the scarcity of publicly available EEG datasets for inner speech recognition and supports the development of brain-computer interface technologies and investigation of neural mechanisms underlying inner speech. Ethics approval: Comité Asesor de Ética y Seguridad en el Trabajo Experimental (CEySTE), CCT-CONICET, Santa Fe.
…The data set involves the use of direct electrical stimulation to examine…
Imported from OpenNeuro ds006126
This dataset comprises EEG recordings and behavioral responses from participants viewing scene images and rating their aesthetic properties (beauty, complexity, interestingness) and contextual appropriateness for reading or social activities. The study investigates neural correlates of environmental perception and aesthetic judgment, with extracted behavioral data and complete stimulus set provided for reproducibility and further analysis.
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.
Imported from OpenNeuro ds002578