Cognitive flexibility describes the human ability to switch between modes of mental function to achieve goals. Mental switching is accompanied by transient changes in brain activity, which must occur atop an anatomical architecture that bridges disparate cortical and subcortical regions by underlying white matter tracts. However, an integrated perspective regarding how white matter networks might constrain brain dynamics during cognitive processes requiring flexibility has remained elusive. To address this challenge, we applied emerging tools from graph signal processing to examine whether BOLD signals measured at each point in time correspond to complex underlying anatomical networks in 28 individuals performing a perceptual task that probed cognitive flexibility. We found that the alignment between functional signals and the architecture of the underlying white matter network was associated with greater cognitive flexibility across subjects. By computing a concise measure using multi-modal neuroimaging data, we uncovered an integrated structure-function correlate of human behavior.
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http://dx.doi.org/10.1038/s41562-017-0260-9 | DOI Listing |
Annu Rev Neurosci
January 2025
1Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; email:
Cognition unfolds dynamically over flexible timescales. A major goal of the field is to understand the computational and neurobiological principles that enable this flexibility. Here, we argue that the neurobiology of timing provides a platform for tackling these questions.
View Article and Find Full Text PDFChild Neuropsychol
January 2025
Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland.
Executive function (EF) impairments are prevalent in survivors of neonatal critical illness such as children born very preterm (VPT) or with complex congenital heart disease (cCHD). This paper aimed to describe EF profiles in school-aged children born VPT or with cCHD and in typically developing peers, to identify child-specific and family-environmental factors associated with these profiles and to explore links to everyday-life outcomes. Data from eight EF tests assessing working memory, inhibition, cognitive flexibility, switching, and planning in = 529 children aged between 7 and 16 years was subjected into a latent profile analysis.
View Article and Find Full Text PDFAnimals survive in dynamic environments changing at arbitrary timescales, but such data distribution shifts are a challenge to neural networks. To adapt to change, neural systems may change a large number of parameters, which is a slow process involving forgetting past information. In contrast, animals leverage distribution changes to segment their stream of experience into tasks and associate them with internal task abstracts.
View Article and Find Full Text PDFBMC Psychiatry
January 2025
School of Mental Health, Bengbu Medical University, Bengbu, Anhui, 233030, China.
Background: Although impaired cognitive control is common during the acute detoxification phase of substance use disorders (SUD) and is considered a major cause of relapse, it remains unclear after prolonged methadone maintenance treatment (MMT). The aim of the present study was to elucidate cognitive control in individuals with heroin use disorder (HUD) after prolonged MMT and its association with previous relapse.
Methods: A total of 63 HUD subjects (41 subjects with previous relapse and 22 non-relapse subjects, mean MMT duration: 12.
ACS Sens
January 2025
Tianjin Key Laboratory of Organic Solar Cells and Photochemical Conversion, School of Chemistry and Chemical Engineering, Tianjin University of Technology, Tianjin 300384, PR China.
The simultaneous detection of electroencephalography (EEG) signals and neurotransmitter levels plays an important role as biomarkers for the assessment and monitoring of emotions and cognition. This paper describes the development of boron and nitrogen codoped graphene-diamond (BNGrD) microelectrodes with a diameter of only 200 μm for sensing EEG signals and dopamine (DA) levels, which have been developed for the first time. The optimized BNGrD microelectrode responded sensitively to both EEG and DA signals, with a signal-to-noise ratio of 9 dB for spontaneous EEG signals and a limit of detection as low as 124 nM for DA.
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