What mechanisms underlie flexible inter-areal communication in the cortex? We consider four mechanisms for temporal coordination and their contributions to communication: (1) Oscillatory synchronization (communication-through-coherence); (2) communication-through-resonance; (3) non-linear integration; and (4) linear signal transmission (coherence-through-communication). We discuss major challenges for communication-through-coherence based on layer- and cell-type-specific analyses of spike phase-locking, heterogeneity of dynamics across networks and states, and computational models for selective communication. We argue that resonance and non-linear integration are viable alternative mechanisms that facilitate computation and selective communication in recurrent networks. Finally, we consider communication in relation to cortical hierarchy and critically examine the hypothesis that feedforward and feedback communication use fast (gamma) and slow (alpha/beta) frequencies, respectively. Instead, we propose that feedforward propagation of prediction errors relies on the non-linear amplification of aperiodic transients, whereas gamma and beta rhythms represent rhythmic equilibrium states that facilitate sustained and efficient information encoding and amplification of short-range feedback via resonance.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.neuron.2023.03.015 | DOI Listing |
Heliyon
January 2025
Department of Mechanical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran.
Background: The development of heat transfer devices used for heat conversion and recovery in several industrial and residential applications has long focused on improving heat transfer between two parallel plates. Numerous articles have examined the relevance of enhancing thermal performance for the system's performance and economics. Heat transport is improved by increasing the Reynolds number as the turbulent effects grow.
View Article and Find Full Text PDFHum Brain Mapp
January 2025
Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico.
Premature infants, born before 37 weeks of gestation can have alterations in neurodevelopment and cognition, even when no anatomical lesions are evident. Resting-state functional neuroimaging of naturally sleeping babies has shown altered connectivity patterns, but there is limited evidence on the developmental trajectories of functional organization in preterm neonates. By using a large dataset from the developing Human Connectome Project, we explored the differences in graph theory properties between at-term (n = 332) and preterm (n = 115) neonates at term-equivalent age, considering the age subgroups proposed by the World Health Organization for premature birth.
View Article and Find Full Text PDFGenome-wide association studies (GWAS) have identified genetic variants robustly associated with asthma. A potential near-term clinical application is to calculate polygenic risk score (PRS) to improve disease risk prediction. The value of PRS, as part of numerous multi-source variables used to define asthma, remains unclear.
View Article and Find Full Text PDFPhysiol Meas
January 2025
Department of Electrical and Electronic Engineering (DIEE), University of Cagliari, Via Marengo, Cagliari, Sardegna, 09123, ITALY.
Heart rate variability (HRV) analysis during sleep plays a key role for understanding autonomic nervous system function and assessing cardiovascular health. The UNICA Sleep HRV analysis (UNICA-HRV) tool is a novel, open-source MATLAB tool designed to fill the gap in current HRV analysis tools. In particular, the integration of ECG and HRV data with hypnogram information, which illustrates the progression through the different sleep stages, ease the computation of HRV metrics in polysomnographic recordings.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China.
Microbiome-metabolome association analysis is critical to reveal the key pairs of gut microbiota and metabolites for discovery of the microbial biomarkers in chronic diseases. However, the characteristics of microbiome data, such as zero inflation, over dispersion, may impair the confidence of association analysis between microbiome and metabolome data. The objectives of this study are to evaluate the strengths and weaknesses of existing statistical methods and to develop a computational framework tailored to the unique characteristics of microbiome data.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!