Biology subjects

Gong, Z.-Q.

Publications and source records attributed to Gong, Z.-Q..

6 recordsLinked to original sources

bioRxiv2026

The emergent mental operation of the learning brain

How does the learning brain give rise to emergent mental operations that enable skill internalization and generalization? Using five-year longitudinal tracking of children acquiring abacus-based mental calculation, we reveal how sustained practice progressively reconfigures whole-brain states. Learning induces nonlinear transitions from stable baseline configurations through a transient exploratory phase toward restabilized associative brain networks. This hierarchical remodeling cascades from perceptual systems to action and default networks, mediated by adaptive neural variability and selective connectivity reweighting, with the salience-parietal memory network acting as a dynamic relay. These brain-state transitions accompany an ordered cognitive transfer cascade, emerging within arithmetic and extending to visuospatial and executive functions. Our findings are reproducible and provide a systems-level account of how ecological learning sculpts large-scale networks to enable complex skill acquisition.

neuroscience↗

bioRxiv2026

Reliability and validity of multi-band multi-echo fMRI

Precision mapping of individual differences in human brain spontaneous activity is critical for characterizing brain function and guiding clinical translation. Multi-echo resting-state functional MRI (ME-rfMRI) has the potential to provide more reliable mapping of inter-individual differences in intrinsic brain function than conventional single-echo rfMRI (SE-rfMRI). However, the psychometric benefits of ME-rfMRI for mapping individual differences in spontaneous brain activity (SBA) have not been systematically investigated, which is fundamental for understanding the human brain in health and disease. To quantify the psychometric performance of ME-rfMRI in precisely mapping inter-individual variations in SBA, we employed a psychometric design. We scanned 27 healthy adults with both ME-rfMRI and SE-rfMRI to assess short-term (minutes) test-retest reliability, as well as validity across eyes-open (EO) and eyes-closed (EC) resting states. Our results demonstrate that ME-rfMRI improves reliability relative to SE-rfMRI by 10.8% for amplitude of low-frequency fluctuation (ALFF), 4.4% for regional homogeneity (ReHo), and 8.0% for voxel-mirrored homotopic connectivity (VMHC) in cortical regions, and by 12.5% for ALFF, 8.3% for ReHo, and 4.0% for VMHC in subcortical regions. This enhancement is achieved by increasing inter-individual variability while reducing intra-individual variability. Notably, ME-rfMRI accentuates inter-individual variability in the unimodal cortex and clearly delineates two parallel systems with distinct variability patterns within the motor cortex. Concurrently, ME-rfMRI increases effect sizes (4%-8%) for detecting individual differences between EO and EC resting states. Interestingly, ME-rfMRI reveals differential effects of eye closure on two intertwined systems in the primary motor and sensory cortices, extending previous findings. Computational simulations indicate that, compared to SE-rfMRI, ME-rfMRI facilitates experimental designs with reduced costs (i.e., 4%-11% smaller sample sizes) for precise mapping of individual differences. These findings establish, for the first time, the psychometric performance of ME-rfMRI measurements, supporting its potential utility in personalized neuroscience applications, including neurodevelopment and brain disorders.

neuroscience↗

bioRxiv2025

Frequency-specific maturation of cortical organization and social-cognitive links from childhood to adolescence

The human brain unfolds its functional architecture over multiple timescales during childhood and adolescence, yet we know little about how these developmental trajectories vary between individuals. Slow brain signals at different frequencies are thought to support distinct functional processes, but their contribution to shaping large-scale cortical organization across development remains unclear. Here, we map the maturation of cortical organization by decomposing spontaneous slow brain activity into multiple frequency bands in participants aged 6-19 years. We identify a reproducible three-stage progression - child-like, transitional, and adult-like configurations - whose timing depends on frequency: faster dynamics mature earliest, intermediate frequencies develop gradually, and lower-frequency dynamics reorganize abruptly around puberty. Individual cognitive and social traits modulate these trajectories: children with higher social anxiety or higher IQ reach adult-like configurations earlier in specific frequency bands, whereas lower-IQ children show generalized delays. These results reveal that cortical organization matures along multiple, frequency-specific timescales and that intellectual and socio-emotional factors shape its pace. Our multi-frequency framework provides a new perspective on hierarchical brain development and may inform biomarkers for atypical neurodevelopment.

neuroscience↗

bioRxiv2024

Activating Cognitive Processes in Human Cortex at Multiple Low-Frequency Bands

Neural oscillations are fundamental for brain function, governing various cognitive processes. While electrophysiological studies have characterized the frequency properties of these oscillations, their spatial resolution is limited. In contrast, functional magnetic resonance imaging (fMRI) provides high spatial resolution but was initially restricted to a narrow frequency range. This study aims to bridge the gap by investigating the role of blood-oxygen-level-dependent (BOLD) oscillations across multiple frequency bands in cognitive processes using high temporal resolution task-fMRI data. Our findings reveal that different frequency bands are associated with distinct functional processes. Specifically, the slow-1 to slow-3 bands primarily contribute to local sensory information processing, while the slow-4 band is crucial for various fundamental cognitive functions, including somatic motor function and social cognitive function. The slow-5 band is involved in cognitive processes requiring higher memory load, integrated cognitive processing, and attention maintenance. Through multiband activation analysis, this study underscores the importance of analyzing a broad frequency range to capture the full spectrum of brain function. These findings highlight the diverse roles of different frequency bands in brain activity, shedding light on the underlying mechanisms of cognitive processes. This research enhances our understanding of the neural mechanisms underlying cognitive processes and has significant implications for cognitive neuroscience and clinical applications.

neuroscience↗

bioRxiv2023

A longitudinal resource for population neuroscience of school-age children and adolescents in China

During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013-2022), a ten-year pilot stage of the lifespan CCNP (2013-2032), is an ongoing project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0-17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the "Chinese Data-sharing Warehouse for In-vivo Imaging Brain" in the Chinese Color Nest Project (CCNP) - Lifespan Brain-Mind Development Data Community (https://www.scidb.cn/en/c/ccnp) at the Science Data Bank. Design TypesO_LIAccelerated longitudinal design C_LIO_LIBrain-mind development C_LIO_LIPopulation imaging C_LIO_LIBrain chart C_LIO_LIRepeated measure C_LI MeasurementsO_LIPsychological behaviours C_LIO_LIBiophysical and physical measures C_LIO_LIIntelligence quotient measure C_LIO_LINeuroimaging C_LI Sample Characteristic - OrganismO_LIHomo sapiens C_LI Sample Characteristic - EnvironmentO_LISchool- and community-based sample C_LI Sample Characteristic - LocationO_LIChongqing and Beijing, China C_LI DurationO_LI10 years (2013-2022) C_LI

neuroscience↗

bioRxiv2020

DREAM: A Toolbox to Decode Rhythms of the Brain System

Rhythms of the brain are generated by neural oscillations across multiple frequencies, which can be observed with multiple modalities. Following the natural log linear law of frequency distribution, these oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. This perspective on neural oscillations has been increasingly applied to study human brain function and related behaviors. In practice, relevant signals are commonly measured as a discrete time series, and thus the sampling period and number of samples determine the number and ranges of decodable frequency intervals. However, these limits have been often ignored by researchers who instead decode measured oscillations into multiple frequency intervals using a fixed sample period and numbers of samples. One reason for such misuse is the lack of an easy-to-use toolbox to implement automatic decomposition of frequency intervals. We report on a toolbox with a graphical user interface for achieving local and remote decoding rhythms of the brain system (DREAM) which is accessible to the public via GitHub. We provide worked examples of DREAM used to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM analyzed the head motion oscillations and found that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age interval from 7 to 9 years. It is interesting that the higher frequency bands contains more head movements, and showed stronger age-motion associations but the weaker sex-motion interactions. Using the fast functional magnetic resonance imaging data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. A novel result indicated that the higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, these findings demonstrated the applicability of DREAM for frequency-specific human brain mapping as well as the assessments on their measurement reliability and validity.

neuroscience↗