Ketamine is a multifunctional drug with clinical applications as an anesthetic, pain management medication, and a fast-acting antidepressant. However, it is also recreationally abused for its dissociative effects. Recent studies in rodents are revealing the neuronal mechanisms mediating its actions, but the impact of prolonged exposure to ketamine on brain-wide networks remains less understood. Here, we develop a sub-cellular resolution whole-brain phenotyping approach and utilize it in male mice to show that repeated ketamine administration leads to a dose-dependent decrease in dopamine neurons in midbrain regions linked to behavioral states, alongside an increase in the hypothalamus. Additionally, diverse changes are observed in long-range innervations of the prefrontal cortex, striatum, and sensory areas. Furthermore, the data support a role for post-transcriptional regulation in enabling ketamine-induced neural plasticity. Through an unbiased, high-resolution whole-brain analysis, this study provides important insights into how chronic ketamine exposure reshapes brain-wide networks.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10843582 | PMC |
http://dx.doi.org/10.1016/j.celrep.2023.113491 | DOI Listing |
J Clin Neurosci
January 2025
Department of Orthopedics, The First Affiliated Hospital of Anhui Medical University, Hefei, PR China; Department of Spine Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, PR China. Electronic address:
Background: Cervical spondylotic myelopathy (CSM) is a debilitating condition that affects the cervical spine, leading to neurological impairments. While the neural mechanisms underlying CSM remain poorly understood, changes in brain network connectivity, particularly within the context of static and dynamic functional network connectivity (sFNC and dFNC), may provide valuable insights into disease pathophysiology. This study investigates brain-wide connectivity alterations in CSM patients using both sFNC and dFNC, combined with machine learning approaches, to explore their potential as biomarkers for disease classification and progression.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130.
Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions.
View Article and Find Full Text PDFNature
January 2025
Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Glioblastoma (GBM) infiltrates the brain and can be synaptically innervated by neurons, which drives tumor progression. Synaptic inputs onto GBM cells identified so far are largely short-range and glutamatergic. The extent of GBM integration into the brain-wide neuronal circuitry remains unclear.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, H3A 2B4, Canada.
Excitation-inhibition (E/I) imbalance is theorized as a key mechanism in the pathophysiology of epilepsy, with ample research focusing on elucidating its cellular manifestations. However, few studies investigate E/I imbalance at the macroscale, whole-brain level, and its microcircuit-level mechanisms and clinical significance remain incompletely understood. Here, the Hurst exponent, an index of the E/I ratio, is computed from resting-state fMRI time series, and microcircuit parameters are simulated using biophysical models.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, 410008, P.R. China.
Purpose: Temporal lobe epilepsy (TLE) is a brain network disorder closely associated with synaptic loss and has a genetic basis. However, the in vivo whole-brain synaptic changes at the network-level and the underlying gene expression patterns in patients with TLE remain unclear.
Methods: In this study, we utilized a positron emission tomography with the synaptic vesicle glycoprotein 2 A radioligand [F]SynVesT-1 cohort and two independent transcriptome datasets to investigate the topological properties of the synaptic density similarity network (SDSN) in TLE and its correlation with significantly dysregulated risk genes.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!