Temporal Interference Stimulation Boosts Working Memory Performance in the Frontoparietal Network

Human Brain Mapping, Journal Year: 2025, Volume and Issue: 46(3)

Published: Feb. 12, 2025

ABSTRACT Temporal interference (TI) stimulation is a novel neuromodulation technique that overcomes the depth limitations of traditional transcranial electrical while avoiding invasiveness deep brain stimulation. Our previous behavioral research has demonstrated effects multi‐target TI in enhancing working memory (WM) performance, however, neural mechanisms this special form envelope modulation remain unclear. To address issue, here we designed randomized, double‐blind, crossover study, which consisted task‐based functional magnetic resonance imaging (fMRI) experiment, to explore how offline modulated activity and performance healthy adults. We conducted 2 × within‐subjects design with two factors: (TI vs. Sham) time (pre post). Participants received protocols random order: (beat frequency: 6 Hz, targeting middle frontal gyrus [MFG] inferior parietal lobule [IPL]) sham Neuroimaging data WM task different cognitive loads were acquisited immediately before after found significantly improved d ′ high‐demand task. Whole‐brain analysis showed significant time‐by‐stimulation interactions main clusters IPL precuneus lower activation The generalized psychophysiological interaction (gPPI) revealed task‐modulated connectivity between MFG IPL, improvement observed Notably, increasing induced by was positively correlated better performance. Overall, our findings show specific on frontoparietal network may contribute provide new perspectives for future applications.

Language: Английский

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Evaluating the sensitivity of functional connectivity measures to motion artifact in resting-state fMRI data

NeuroImage, Journal Year: 2021, Volume and Issue: 241, P. 118408 - 118408

Published: July 17, 2021

Functional connectivity (FC) networks are typically inferred from resting-state fMRI data using the Pearson correlation between BOLD time series pairs of brain regions. However, alternative methods estimating functional have not been systematically tested for their sensitivity or robustness to head motion artifact. Here, we evaluate eight different measures artifact Human Connectome Project. We report that FC estimated full has a relatively high residual distance-dependent relationship with compared partial correlation, coherence, and information theory-based measures, even after implementing rigorous mitigation. This disadvantage however, may be offset by higher test-retest reliability, fingerprinting accuracy, system identifiability. offers best both worlds, low intermediate identifiability, caveat reliability accuracy. highlight spatial differences in sub-networks affected metrics. Further, intra-network edges default mode retrosplenial temporal highly correlated all methods. Our findings indicate method is an important consideration studies must chosen carefully based on parameters study.

Language: Английский

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Cognitive Network Science for Understanding Online Social Cognitions: A Brief Review

Topics in Cognitive Science, Journal Year: 2021, Volume and Issue: 14(1), P. 143 - 162

Published: June 12, 2021

Social media are digitalizing massive amounts of users' cognitions in terms timelines and emotional content. Such Big Data opens unprecedented opportunities for investigating cognitive phenomena like perception, personality, information diffusion but requires suitable interpretable frameworks. Since social data come from minds, worthy candidates this challenge networks, models cognition giving structure to mental conceptual associations. This work outlines how network science can open new, quantitative ways understanding through online like: (i) reconstructing users semantically emotionally frame events with contextual knowledge unavailable machine learning, (ii) salience/prominence discourse; (iii) studying personality traits openness-to-experience, curiosity, creativity language posts; (iv) bridging cognitive/emotional content dynamics via multilayer networks comparing the mindsets influencers followers. These advancements combine cognitive-, network- computer understand mechanisms both digital real-world settings limitations concerning representativeness, individual variability, integration. aspects discussed along ethical implications manipulating sociocognitive data. In future, reading expose biases amplified by platforms relevantly inform policy-making, education, markets about complex trends.

Language: Английский

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Spatiotemporal dynamics of EEG microstates in four- to eight-year-old children: Age- and sex-related effects

Developmental Cognitive Neuroscience, Journal Year: 2022, Volume and Issue: 57, P. 101134 - 101134

Published: July 12, 2022

The ultrafast spatiotemporal dynamics of large-scale neural networks can be examined using resting-state electroencephalography (EEG) microstates, representing transient periods synchronized activity that evolve dynamically over time. In adults, four canonical microstates have been shown to explain most topographic variance in EEG. Their temporal structures are age-, sex- and state-dependent, susceptible pathological brain states. However, no studies assessed the spatial properties EEG exclusively during early childhood, a critical period rapid development. Here we sought investigate recorded with high-density large sample 103, 4–8-year-old children. Using data-driven k-means cluster analysis, show reported adult populations already exist childhood. multiple linear regressions, demonstrate two associated age sex. Source localization suggests attention- cognitive control-related govern topographies age- sex-dependent microstates. These novel findings provide unique insights into functional development children captured

Language: Английский

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Combination of structural and functional connectivity explains unique variation in specific domains of cognitive function

NeuroImage, Journal Year: 2022, Volume and Issue: 262, P. 119531 - 119531

Published: Aug. 2, 2022

The relationship between structural and functional brain networks has been characterised as complex: the two mirror each other show mutual influence but they also diverge in their organisation. This work explored whether a combination of connectivity can improve fit regression models cognitive performance. Principal Component Analysis (PCA) was first applied to data from Human Connectome Project identify latent components: Executive Function, Self-regulation, Language, Encoding Sequence Processing. A Regression approach with embedded Step-Wise (SWR-PCR) then used domain based on (SC), (FC) or combined structural-functional (CC) connectivity. Function best explained by CC model. Self-regulation equally well SC FC. Language FC models. Processing were SC. Evaluation out-of-sample models' skill via cross-validation showed that SC, produced generalisable performed most effectively at predicting performance unseen sample. predicted models, followed only present study demonstrates integrating help explaining performance, added explanatory value (in-sample) may be domain-specific come expense reduced generalisation (out-of-sample).

Language: Английский

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Deciphering the clinico-radiological heterogeneity of dysexecutive Alzheimer’s disease

Cerebral Cortex, Journal Year: 2023, Volume and Issue: 33(11), P. 7026 - 7043

Published: Jan. 31, 2023

Dysexecutive Alzheimer's disease (dAD) manifests as a progressive dysexecutive syndrome without prominent behavioral features, and previous studies suggest clinico-radiological heterogeneity within this syndrome. We uncovered using unsupervised machine learning in 52 dAD patients with multimodal imaging cognitive data. A spectral decomposition of covariance between FDG-PET images yielded six latent factors ("eigenbrains") accounting for 48% variance patterns hypometabolism. These eigenbrains differentially related to age at onset, clinical severity, performance. hierarchical clustering on the eigenvalues these four subtypes, i.e. "left-dominant," "right-dominant," "bi-parietal-dominant," "heteromodal-diffuse." Patterns hypometabolism overlapped those tau-PET distribution MRI neurodegeneration each subtype, whereas amyloid deposition were similar across subtypes. Subtypes differed onset severity where heteromodal-diffuse exhibited worse picture, bi-parietal had milder presentation. propose conceptual framework executive components based associations observed dAD. demonstrate that dAD, despite sharing core are diagnosed variability their neuroimaging profiles. Our findings support use data-driven approaches delineate brain-behavior relationships relevant practice physiology.

Language: Английский

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Alterations in hippocampus-centered morphological features and function of the progression from normal cognition to mild cognitive impairment

Asian Journal of Psychiatry, Journal Year: 2024, Volume and Issue: 93, P. 103921 - 103921

Published: Jan. 10, 2024

Language: Английский

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Structural brain networks correlating with poststroke cognition

Human Brain Mapping, Journal Year: 2024, Volume and Issue: 45(5)

Published: March 23, 2024

Abstract Cognitive deficits are a common and debilitating consequence of stroke, yet our understanding the structural neurobiological biomarkers predicting recovery cognition after stroke remains limited. In this longitudinal observational study, we set out to investigate effect both focal lesions connectivity on poststroke cognition. Sixty‐two patients with underwent advanced brain imaging cognitive assessment, utilizing Montreal Assessment (MoCA) Mini‐Mental State Examination (MMSE), at 3‐month 12‐month poststroke. We first evaluated relationship between 3 months using voxel‐based lesion‐symptom mapping. Next, novel correlational tractography approach, multi‐shell diffusion‐weighted magnetic resonance (MRI) data collected time points, was used evaluate white matter connectome cross‐sectionally months, longitudinally (12 minus months). Lesion‐symptom mapping did not yield significant findings. turn, analyses revealed positive associations MoCA MMSE scores bilateral cingulum corpus callosum, stage, longitudinally. These results demonstrate that rather than neural structures, consistent underpins performance two frequently screening tools, MMSE, in people stroke. This finding should encourage clinicians researchers only suspect decline when affect these tracts, but also refine their investigation approaches differentially diagnosing pathology associated decline, regardless aetiology.

Language: Английский

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Aging relates to a disproportionately weaker functional architecture of brain networks during rest and task states

NeuroImage, Journal Year: 2020, Volume and Issue: 209, P. 116521 - 116521

Published: Jan. 8, 2020

Functional connectivity – the co-activation of brain regions forms basis brain's functional architecture. Often measured during resting-state (i.e., in a task-free setting), patterns within and between networks change with age. These are interest to aging researchers because age differences relate older adults' relative cognitive declines. Less is known about large-scale directed tasks. Recent work younger adults has shown that highly correlated rest task states. Whether this finding extends remains largely unexplored. To end, we assessed across whole using fMRI while participants underwent or completed tasks (e.g., reasoning judgement task). Resting-state were less strongly as compared adults. This age-dependent difference could be attributed significantly lower consistency network organization states among Older had distinct segregated resting-state. more diffuse pattern was exacerbated Finally, default mode network, often implicated neurocognitive aging, contributed pattern. findings establish state-dependent, providing greater insight into mechanisms by which may lead

Language: Английский

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The interaction between language and working memory: a systematic review of fMRI studies in the past two decades

AIMS neuroscience, Journal Year: 2020, Volume and Issue: 8(1), P. 1 - 32

Published: Jan. 1, 2020

Language processing involves other cognitive domains, including Working Memory (WM). Much detail about the neural correlates of language and WM interaction remains unclear. This review summarizes evidence for between obtained via functional Magnetic Resonance Imaging (fMRI) in past two decades. The search was limited to PubMed, Google Scholar, Science direct Neurosynth working memory, language, fMRI, neuroimaging, cognition, attention, network, connectome keywords. exclusion criteria consisted studies children, older adults, bilingual or multilingual population, clinical cases, music, sign speech, motor processing, papers, meta-analyses, electroencephalography/event-related potential, positron emission tomography. A total 20 articles were included discussed four categories: comprehension, production, syntax, networks. Studies on are rare. tasks that involve activate common systems. Activated areas can be associated with concepts proposed by Baddeley Hitch (1974), phonological loop (mainly Broca Wernicke's areas), prefrontal cortex right hemispheric regions linked visuospatial sketchpad. There is a clear, dynamic WM, reflected involvement subcortical structures, particularly basal ganglia (caudate), widespread regions. levered demand response task complexity. High capacity readers draw upon buffer memory systems midline cortical decrease demands efficiency. Different networks involved hand an ultimate brain function efficiency, modulated modality attention.

Language: Английский

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