Aims: To contrast functional connectivity on ventral and dorsal striatum networks in cocaine dependence relative to pathological gambling, via a resting-state functional connectivity approach; and to determine the association between cocaine dependence-related neuroadaptations indexed by functional connectivity and impulsivity, compulsivity and drug relapse.
Design: Cross-sectional study of 20 individuals with cocaine dependence (CD), 19 individuals with pathological gambling (PG) and 21 healthy controls (HC), and a prospective cohort study of 20 CD followed-up for 12 weeks to measure drug relapse.
Setting And Participants: CD and PG were recruited through consecutive admissions to a public clinic specialized in substance addiction treatment (Centro Provincial de Drogodependencias) and a public clinic specialized in gambling treatment (AGRAJER), respectively; HC were recruited through community advertisement in the same area in Granada (Spain).
Measurements: Seed-based functional connectivity in the ventral striatum (ventral caudate and ventral putamen) and dorsal striatum (dorsal caudate and dorsal putamen), the Kirby delay-discounting questionnaire, the reversal-learning task and a dichotomous measure of cocaine relapse indicated with self-report and urine tests.
Findings: CD relative to PG exhibit enhanced connectivity between the ventral caudate seed and subgenual anterior cingulate cortex, the ventral putamen seed and dorsomedial pre-frontal cortex and the dorsal putamen seed and insula (P≤0.001, kE=108). Connectivity between the ventral caudate seed and subgenual anterior cingulate cortex is associated with steeper delay discounting (P≤0.001, kE=108) and cocaine relapse (P≤0.005, kE=34).
Conclusions: Cocaine dependence-related neuroadaptations in the ventral striatum of the brain network are associated with increased impulsivity and higher rate of cocaine relapse.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1111/add.13076 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Ernst Strüngmann Institute, Frankfurt am Main 60528, Germany.
The dynamics of neuronal systems are characterized by hallmark features such as oscillations and synchrony. However, it has remained unclear whether these characteristics are epiphenomena or are exploited for computation. Due to the challenge of selectively interfering with oscillatory network dynamics in neuronal systems, we simulated recurrent networks of damped harmonic oscillators in which oscillatory activity is enforced in each node, a choice well supported by experimental findings.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Shenzhen Key Laboratory of Biomolecular Assembling and Regulation, Department of Neuroscience, School of Life Sciences, Southern University of Science and Technology, Shenzhen 518055, China.
Ankyrin Repeat Domain-containing Protein 11 () is a causative gene for KBG syndrome, a significant risk factor for Cornelia de Lange syndrome (CdLS), and a highly confident autism spectrum disorder gene. Mutations of lead to developmental abnormalities in multiple organs/tissues including the brain, craniofacial and skeletal bones, and tooth structures with unknown mechanism(s). Here, we find that ANKRD11, via a short peptide fragment in its N-terminal region, binds to the cohesin complex with a high affinity, implicating why mutation can cause CdLS.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Beijing Key Laboratory of Growth and Developmental Regulation for Protected Vegetable Crops, College of Horticulture, China Agricultural University, Beijing 100193, China.
Light serves as an energy source for cell division and expansion during fruit development. Cell expansion significantly influences fruit size and is closely linked to endoreduplication, a unique cell cycle variation characterized by DNA replication without cytokinesis. Paradoxically, under conditions of ample photosynthates, light signaling suppresses cell expansion.
View Article and Find Full Text PDFSports Med Open
January 2025
Department of Physical Education, Tongji University, Shanghai, 200000, China.
Background: While the effects of sleep deprivation on cognitive function are well-documented, its impact on high-intensity endurance performance and underlying neural mechanisms remains underexplored, especially in the context of search and rescue operations where both physical and mental performance are essential. This study examines the neurophysiological basis of sleep deprivation on high-intensity endurance using electroencephalography (EEG). In this crossover study, twenty firefighters were subjected to both sleep deprivation (SD) and normal sleep conditions, with each participant performing endurance treadmill exercise the following morning after each condition.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
Artificial Intelligence Lab, School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500046, India.
The generalization of deep learning (DL) models is critical for accurate lesion segmentation in breast ultrasound (BUS) images. Traditional DL models often struggle to generalize well due to the high frequency and scale variations inherent in BUS images. Moreover, conventional loss functions used in these models frequently result in imbalanced optimization, either prioritizing region overlap or boundary accuracy, which leads to suboptimal segmentation performance.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!