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Environmental processes, such as auditory and visual inputs, often follow power-law distributions with a time-dependent and constantly changing spectral exponent, β(t). However, it remains unclear how the brain's scale-free dynamics continuously respond to naturalistic inputs, such as by potentially alternating instead of static levels of the spectral exponent. Our fMRI study investigates the brain's dynamic, time-dependent spectral exponent, β(t), during movie-watching, and uses time-varying inter-subject correlation, ISC(t), to assess the extent to which input dynamics are reflected as shared brain activity across subjects in early sensory regions. Notably, we investigate the level of ISC particularly based on the modulation by time-dependent scale-free dynamics or β(t). We obtained three key findings: First, the brain's β(t) showed a distinct temporal structure in visual and auditory regions during naturalistic inputs compared to the resting-state, investigated in the 7 Tesla Human Connectome Project dataset. Second, β(t) and ISC(t) were positively correlated during naturalistic inputs. Third, grouping subjects based on the Rest-to-Movie standard deviation change of the time-dependent spectral exponent β(t) revealed that the brain's relative shift from intrinsic to stimulus-driven scale-free dynamics modulates the level of shared brain activity, or ISC(t), and thus the imprinting of inputs on brain activity. This modulation was further supported by the observation that the two groups displayed significantly different β(t)-ISC(t) correlations, where the group with a higher mean of ISC(t) during inputs also exhibited a higher β(t)-ISC(t) correlation in visual and auditory regions. In summary, our fMRI study underscores a positive relationship between time-dependent scale-free dynamics and ISC, where higher spectral exponents correspond to higher degrees of shared brain activity during ongoing audiovisual inputs.
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http://dx.doi.org/10.1016/j.neuroimage.2025.121255 | DOI Listing |
PLoS Comput Biol
September 2025
Faculty of Science, Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, the Netherlands.
Predictive coding (PC) proposes that our brains work as an inference machine, generating an internal model of the world and minimizing predictions errors (i.e., differences between external sensory evidence and internal prediction signals).
View Article and Find Full Text PDFBehav Res Methods
September 2025
Signal Processing Research Centre, Tampere University, Tampere, Finland.
Computational models of early language development involve implementing theories of learning as functional learning algorithms, exposing these models to realistic language input, and comparing learning outcomes to those in infants. While recent research has made major strides in developing more powerful learning models and evaluation protocols grounded in infant data, models are still predominantly trained with non-naturalistic input data, such as crowd-sourced read speech or text transcripts. This is due to the lack of suitable child-directed speech (CDS) corpora in terms of scale and quality.
View Article and Find Full Text PDFNeuroimage
August 2025
MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.
Action representation and the sharing of feature coding within the Action Observation Network (AON) remain debated, and our understanding of how the brain consistently encodes action features across sensory modalities under variable, naturalistic conditions is still limited. Here, we introduce a theoretically-based taxonomic model of action representation that categorizes action-related features into six conceptual domains: Space, Effector, Agent & Object, Social, Emotion, and Linguistic. We assessed the predictive power of this model on human brain activity by acquiring functional MRI (fMRI) data from participants exposed to audiovisual, visual-only, or auditory-only versions of the same naturalistic movie.
View Article and Find Full Text PDFIEEE Trans Affect Comput
July 2024
University of Virginia, Charlottesville, VA 22903 USA.
Interpersonal touch is an important channel of social emotional interaction. How these physical skin-to-skin touch expressions are processed in the peripheral nervous system is not well understood. From microneurography recordings in humans, we evaluated the capacity of six subtypes of cutaneous mechanoreceptive afferents to differentiate human-delivered social touch expressions.
View Article and Find Full Text PDFInfant Behav Dev
August 2025
Department of Psychology, University of Houston, United States.
Parents of autistic children often exhibit distinct interaction styles-such as increased gesturing and sustained focus on their child's face-compared to parents of neurotypical children, yet the mechanisms driving these behaviors remain unclear. This study examined how parental social scaffolding behaviors influence attention in toddlers at elevated likelihood of autism (i.e.
View Article and Find Full Text PDF