Bridging the translational neuroscience gap: Development of the ‘shiftability’ paradigm and an exemplar protocol to capture psilocybin-elicited ‘shift’ in neurobiological mechanisms in autism DOI Open Access
Tobias P. Whelan, Eileen Daly, Nicolaas A.J. Puts

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: May 26, 2023

Abstract Clinical trials of pharmacological approaches targeting the core features autism have failed. This is despite evidence from preclinical studies, genetics, post-mortem studies and correlational analyses linking peripheral central markers multiple candidate neurochemical systems to brain function in autism. Whilst this has part been explained by heterogeneity autistic population, field largely relied upon association link chemistry function. The only way directly establish that a neurotransmitter or neuromodulator involved change it observe shift experimental approach dominates neuroscience, but not human studies. There very little direct describing how modulate information processing living brain. As result, our understanding differences contribute neurodiversity limited impedes ability translate findings animal into humans. Here, we begin introducing “shiftability” paradigm, an bridge translational gap research. We then provide overview methodologies used explain most recent choice psilocybin as probe serotonin system vivo . Finally, summary protocol for ‘PSILAUT’, exemplar study which uses test hypothesis functions differently non-autistic adults.

Language: Английский

Measuring the effects of motion corruption in fetal fMRI DOI Creative Commons

Athena Taymourtash,

Ernst Schwartz, Karl‐Heinz Nenning

et al.

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(2)

Published: Jan. 23, 2025

Abstract Irregular and unpredictable fetal movement is the most common cause of artifacts in utero functional magnetic resonance imaging (fMRI), affecting analysis limiting our understanding early brain development. The accurate detection corrupted connectivity (FC) resulting from motion or preprocessing, instead neural activity, a prerequisite for reliable valid FC Approaches to address this problem adult data are limited utility fMRI. In study, we evaluate novel technique robust computational assessment artifacts, quantitative comparison regression models artifact removal analysis. It exploits association between dynamic non‐stationarity movement, detect residual noise. To validate detail, used parametric generative model events fMRI blood oxygenation level‐dependent (BOLD) signal. We conducted systematic evaluation 11 commonly sample 70 fetuses with gestational age 19–39 weeks. Results demonstrate that proposed method has better accuracy identifying compared methods designed adults. technique, suggests censoring, global signal anatomical component‐based effective compensating motion. benchmarking realistic BOLD enables investigators conducting effectively quantify impact alternative strategies mitigating impact. code publicly available at: https://github.com/cirmuw/fetalfMRIproc .

Language: Английский

Citations

0
A hierarchical model of early brain functional network development DOI Creative Commons
Wei Gao

Trends in Cognitive Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

Functional brain networks emerge prenatally, grow interactively during the first years of life, and optimize both within-network topology between-network interactions as individuals age. This review summarizes research that has characterized this process over past two decades, aims to link functional network growth with emerging behaviors, thereby developing a more holistic understanding behavior from perspective. synthesis suggests development brain's follows an overlapping hierarchy, progressing primary sensory/motor socioemotional-centered finally higher-order cognitive/executive control networks. Risk-related alterations, resilience factors, treatment effects, novel therapeutic opportunities are also discussed encourage consideration future imaging-assisted methods for identifying risks interventions.

Language: Английский

Citations

0
Structural and functional connectome relationships in early childhood DOI Creative Commons
Yoonmi Hong, Emil Cornea, Jessica B. Girault

et al.

Developmental Cognitive Neuroscience, Journal Year: 2023, Volume and Issue: 64, P. 101314 - 101314

Published: Oct. 14, 2023

There is strong evidence that the functional connectome highly related to white matter in older children and adults, though little known about structure-function relationships early childhood. We investigated development of cortical coupling longitudinally scanned at 1, 2, 4, 6 years age (N = 360) a comparison sample adults 89). also applied novel graph convolutional neural network-based deep learning model with new loss function better capture inter-subject heterogeneity predict an individual's connectivity from corresponding structural connectivity. found regional patterns childhood were consistent adult patterns. In addition, our improved prediction individual its counterpart compared existing models.

Language: Английский

Citations

9
Entropy, complexity, and maturity in children's neural responses to naturalistic video lessons DOI Creative Commons
Marie Amalric, Jessica F. Cantlon

Cortex, Journal Year: 2023, Volume and Issue: 163, P. 14 - 25

Published: March 18, 2023

Temporal characteristics of neural signals are often overlooked in traditional fMRI developmental studies but critical to studying brain functions ecologically valid settings. In the present study, we explore temporal properties children's responses during naturalistic mathematics and grammar tasks. To do so, introduce a novel measure fMRI: entropy, which indicates complexity BOLD signals. We show that patterns activity have lower greater variability children than adults association cortex not sensory-motor cortex. also entropy is associated with both child-adult similarity functional connectivity synchrony, increases size functionally connected networks addition, maturity (i.e., synchrony) content-specific regions. These exploratory findings suggest hypothesis indexes increasing breadth diversity processes available for analyzing mathematical information over development.

Language: Английский

Citations

7
An Overview of Brain Fingerprint Identification Based on Various Neuroimaging Technologies DOI
Shihao Zhang, Wenting Yang, Haonan Mou

et al.

IEEE Transactions on Cognitive and Developmental Systems, Journal Year: 2023, Volume and Issue: 16(1), P. 151 - 164

Published: Sept. 12, 2023

As a novel category of biometric features, research on brain fingerprints has become hot topic in neuroscience, not only for its reliable performance individual identification but also specifying the activity different humans. Such unique data are extracted using various neuroimaging technologies. Although literature reviewed extraction and application via electroencephalogram (EEG), little work been done presenting comprehensive review that covers techniques extracting fingerprints. This article presents systematic recent scientific focuses fingerprint four major techniques, namely, EEG, magnetic resonance imaging (MRI), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS). It first summarizes acquisition methods popular sets, which organized form graphs tables intuitive comparison. Next, this analyzes advantages disadvantages feature based proposes an trend comparative analysis identity recognition algorithms from perspective computational technology. Finally, we elaborate open questions potential further research.

Language: Английский

Citations

7
The confound of head position in within-session connectome fingerprinting in infants DOI Creative Commons
Graham S. King, Anna Truzzi, Rhodri Cusack

et al.

NeuroImage, Journal Year: 2022, Volume and Issue: 265, P. 119808 - 119808

Published: Dec. 10, 2022

Language: Английский

Citations

8
Identification of morphological fingerprint in perinatal brains using quasi-conformal mapping and contrastive learning DOI
Boyang Wang, Weihao Zheng, Ying Wang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: July 18, 2024

Abstract The morphological fingerprint in the brain is capable of identifying uniqueness an individual. However, whether such individual patterns are present perinatal brains, and which attributes or cortical regions better characterize differences neonates remain unclear. In this study, we proposed a deep learning framework that projected three-dimensional spherical meshes three features (i.e., thickness, mean curvature, sulcal depth) onto two-dimensional planes through quasi-conformal mapping, employed ResNet18 contrastive for identification. We used cross-sectional structural MRI data 461 infants, incorporating with augmentation, to train model fine-tuned parameters based on 40 infants who had longitudinal scans. was validated fold 20 scanned infant data, remarkable Top1 Top5 accuracies 85.90% 92.20% were achieved, respectively. sensorimotor visual cortices recognized as most contributive Moreover, folding morphology demonstrated greater discriminative capability than thickness. These findings provided evidence emergence fingerprints at beginning third trimester, may hold promising implications understanding formation during early development.

Language: Английский

Citations

1
Integrative, segregative, and degenerate harmonics of the structural connectome DOI Creative Commons
Benjamin Snow Sipes, Srikantan S. Nagarajan, Ashish Raj

et al.

Communications Biology, Journal Year: 2024, Volume and Issue: 7(1)

Published: Aug. 14, 2024

Abstract Unifying integration and segregation in the brain has been a fundamental puzzle neuroscience ever since conception of “binding problem.” Here, we introduce framework that places within continuum based on property brain–its structural connectivity graph Laplacian harmonics new feature term gap-spectrum. This organizes into three regimes–integrative, segregative, degenerate–that together account for various group-level properties. Integrative segregative occupy ends continuum, they share properties such as reproducibility across individuals, stability to perturbation, involve “bottom-up” sensory networks. Degenerate are middle subject-specific, flexible, “top-down” The proposed accommodates inter-subject variation, sensitivity changes, structure-function coupling ways offer promising avenues studying cognition consciousness brain.

Language: Английский

Citations

1
Brain age prediction and deviations from normative trajectories in the neonatal connectome DOI Creative Commons
Huili Sun, Saloni Mehta, Milana Khaitova

et al.

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Nov. 26, 2024

Structural and functional connectomes undergo rapid changes during the third trimester first month of postnatal life. Despite progress, our understanding developmental trajectories connectome in perinatal period remains incomplete. Brain age prediction uses machine learning to estimate brain's maturity relative normative data. The difference between individual's predicted chronological age—or brain gap (BAG)—represents deviation from these trajectories. Here, we assess BAGs using structural for infants We use resting-state fMRI DTI data 611 (174 preterm; 437 term) Developing Human Connectome Project (dHCP) connectome-based predictive modeling predict postmenstrual (PMA). accurately PMA term preterm infants. Predicted ages each modality are correlated. At network level, nearly all canonical networks—even putatively later developing ones—generate accurate prediction. Additionally, associated with exposures toddler behavioral outcomes. Overall, results underscore importance deviations models period. authors show that altered development after birth, driven by exposures, influences long-term cognitive

Language: Английский

Citations

1
Integrative, Segregative, and Degenerate Harmonics of the Structural Connectome DOI Creative Commons
Benjamin Snow Sipes, Srikantan S. Nagarajan, Ashish Raj

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 28, 2024

Unifying integration and segregation in the brain has been a fundamental puzzle neuroscience ever since conception of "binding problem." Here, we introduce framework that places within continuum based on property brain--its structural connectivity graph Laplacian harmonics new feature term gap-spectrum. This organizes into three regimes--integrative, segregative, degenerate--that together account for various group-level properties. Integrative segregative occupy ends continuum, they share properties such as reproducibility across individuals, stability to perturbation, involve "bottom-up" sensory networks. Degenerate are middle subject-specific, flexible, "top-down" The proposed accommodates inter-subject variation, sensitivity changes, structure-function coupling ways offer promising avenues studying cognition consciousness brain.

Language: Английский

Citations

0