Dataset Information

A Large Video Set of Natural Human Actions for Visual and Cognitive Neuroscience Studies and Its Validation with fMRI.

ABSTRACT: The investigation of the perception of others' actions and underlying neural mechanisms has been hampered by the lack of a comprehensive stimulus set covering the human behavioral repertoire. To fill this void, we present a video set showing 100 human actions recorded in natural settings, covering the human repertoire except for emotion-driven (e.g., sexual) actions and those involving implements (e.g., tools). We validated the set using fMRI and showed that observation of the 100 actions activated the well-established action observation network. We also quantified the videos' low-level visual features (luminance, optic flow, and edges). Thus, this comprehensive video set is a valuable resource for perceptual and neuronal studies.

SUBMITTER: Urgen BA

PROVIDER: S-EPMC9856703 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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A Large Video Set of Natural Human Actions for Visual and Cognitive Neuroscience Studies and Its Validation with fMRI.

Urgen Burcu A BA Nizamoğlu Hilal H Eroğlu Aslı A Orban Guy A GA

Brain sciences 20221229 1

The investigation of the perception of others' actions and underlying neural mechanisms has been hampered by the lack of a comprehensive stimulus set covering the human behavioral repertoire. To fill this void, we present a video set showing 100 human actions recorded in natural settings, covering the human repertoire except for emotion-driven (e.g., sexual) actions and those involving implements (e.g., tools). We validated the set using fMRI and showed that observation of the 100 actions activa ...[more]

PMID: 36672043

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Project description:Functional magnetic resonance imaging (fMRI) has revolutionized human brain research. But there exists a fundamental mismatch between the rapid time course of neural events and the sluggish nature of the fMRI blood oxygen level-dependent (BOLD) signal, which presents special challenges for cognitive neuroscience research. This limitation in the temporal resolution of fMRI puts constraints on the information about brain function that can be obtained with fMRI and also presents methodological challenges. Most notably, when using fMRI to measure neural events occurring closely in time, the BOLD signals may temporally overlap one another. This overlap problem may be exacerbated in complex experimental paradigms (stimuli and tasks) that are designed to manipulate and isolate specific cognitive-neural processes involved in perception, cognition, and action. Optimization strategies to deconvolve overlapping BOLD signals have proven effective in providing separate estimates of BOLD signals from temporally overlapping brain activity, but there remains reduced efficacy of such approaches in many cases. For example, when stimulus events necessarily follow a non-random order, like in trial-by-trial cued attention or working memory paradigms. Our goal is to provide guidance to improve the efficiency with which the underlying responses evoked by one event type can be detected, estimated, and distinguished from other events in designs common in cognitive neuroscience research. We pursue this goal using simulations that model the nonlinear and transient properties of fMRI signals, and which use more realistic models of noise. Our simulations manipulated: (i) Inter-Stimulus-Interval (ISI), (ii) proportion of so-called null events, and (iii) nonlinearities in the BOLD signal due to both cognitive and design parameters. We offer a theoretical framework along with a python toolbox called deconvolve to provide guidance on the optimal design parameters that will be of particular utility when using non-random, alternating event sequences in experimental designs. In addition, though, we also highlight the challenges and limitations in simultaneously optimizing both detection and estimation efficiency of BOLD signals in these common, but complex, cognitive neuroscience designs.

Dataset Information

A Large Video Set of Natural Human Actions for Visual and Cognitive Neuroscience Studies and Its Validation with fMRI.

Publications

A Large Video Set of Natural Human Actions for Visual and Cognitive Neuroscience Studies and Its Validation with fMRI.

Similar Datasets

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