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Navigating everyday environments requires that the brain perform information processing at multiple different timescales. For example, while watching a movie we use sensory information from every video frame to construct the current movie scene, which itself is continuously integrated into the narrative arc of the film. This critical function is supported by sensory inputs propagating from dynamic sensory cortices to association cortices, where neural activity remains more stable over time. The hierarchical organization of cortex is therefore reflected in a gradient of neural timescales. While this propagation of inputs up the cortical hierarchy is facilitated by both rhythmic (oscillatory) and non-rhythmic (aperiodic) neural activity, traditional measures of oscillations are often confounded by the influence of aperiodic signals. The reverse is also true: traditional measures of aperiodic neural timescales are influenced by oscillations. This makes it difficult to distinguish between oscillatory and timescale effects in cognition. Here, we analyzed electroencephalography (EEG) data from participants performing a cognitive control task that manipulated the amount of task-relevant contextual information, called task abstraction. Critically, we separated aperiodic neural timescales from the confounding influence of oscillatory power. We hypothesized that neural timescales would increase during the task, and more so in high-abstraction conditions. We found that task abstraction dilated the aperiodic neural timescale, as estimated from the autocorrelation function, over prefrontal cortical regions. Our findings suggests that neural timescales are a dynamic feature of the cerebral cortex that change to meet task demands.
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http://dx.doi.org/10.1101/2025.04.21.649913 | DOI Listing |
J Neurosci
September 2025
Wallace H Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, USA.
Layer 6 corticothalamic (L6CT) neurons project to both cortex and thalamus, inducing multiple effects including the modulation of cortical and thalamic firing, and the emergence of high gamma oscillations in the cortical local field potential (LFP). We hypothesize that the high gamma oscillations driven by L6CT neuron activation reflect the dynamic engagement of intracortical and cortico-thalamo-cortical circuits. To test this, we optogenetically activated L6CT neurons in NTSR1-cre mice (both male and female) expressing channelrhodopsin-2 in L6CT neurons.
View Article and Find Full Text PDFPhys Chem Chem Phys
September 2025
Department of Chemistry, Malaviya National Institute of Technology Jaipur, Jaipur, 302017, India.
One of the most important puzzles in atmospheric chemistry is the long-lifetime of HO˙ in spite of its low-stabilization energy. In the present work, we have estimated the lifetime of HO˙ using classical dynamics simulations by coupling an available neural-network analytical potential energy surface with a chemical dynamics program. The simulation results clearly indicate that at room temperature, the lifetime of HO˙ can exceed 1 μs under collision-free conditions.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, 5735 S. Ellis Ave., SCL 123, Chicago, Illinois 60637, USA.
Molecular dynamics simulations are essential for studying complex molecular systems, but their high computational cost limits scalability. Coarse-grained (CG) models reduce this cost by simplifying the system, yet traditional approaches often fail to maintain dynamic consistency, compromising their reliability in kinetics-driven processes. Here, we introduce an adversarial training framework that aligns CG trajectory ensembles with all-atom (AA) reference dynamics, ensuring both thermodynamic and kinetic fidelity.
View Article and Find Full Text PDFThe human mind constructs and updates models of events during comprehension. Event models are multidimensional, multi-timescale, and structured. They enable prediction, shape memory formation, and facilitate action control.
View Article and Find Full Text PDFCurr Biol
August 2025
Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada.
Humans and other primates are capable of learning to recognize new visual stimuli throughout their lifetimes. Most theoretical models assume that such learning occurs through the adjustment of the large number of synaptic weights connecting the visual cortex to downstream decision-making areas. While this approach to learning can optimize performance on behavioral tasks, it can also be costly in terms of time and energy.
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