Functional and effective connectivity are relatively new techniques in the analysis of functional neuroimaging studies in humans. They have previously been used in studies of 'normal' psychological and neurological processes such as vision before gradually transferring into use in pathological disease states such as schizophrenia. These techniques are now beginning to extend into the field of substance misuse and dependence. So far, most functional neuroimaging studies in this field have shown consistent patterns of activation in several brain regions, and theories are emerging based upon these and animal models. Studies of brain connectivity can now begin to help further unravel the tangle of disparate brain regions and their connections that underpin the psychopharmacological processes of dependence.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1515/revneuro.2005.16.2.151 | DOI Listing |
Neurosci Biobehav Rev
December 2024
Interdisciplinary Neuroscience Program, University of Nevada, Las Vegas; Department of Psychology, University of Nevada, Las Vegas.
This review highlights the crucial role of neuroelectrophysiology in illuminating the mechanisms underlying Alzheimer's disease (AD) pathogenesis and progression, emphasizing its potential to inform the development of effective treatments. Electrophysiological techniques provide unparalleled precision in exploring the intricate networks affected by AD, offering insights into the synaptic dysfunction, network alterations, and oscillatory abnormalities that characterize the disease. We discuss a range of electrophysiological methods, from non-invasive clinical techniques like electroencephalography and magnetoencephalography to invasive recordings in animal models.
View Article and Find Full Text PDFBMC Neurosci
December 2024
Department of Medicine, The University of Chicago, 5841 S Maryland Ave, Chicago, IL, 60637, USA.
Background: Understanding the neural basis of behavior requires insight into how different brain systems coordinate with each other. Existing connectomes for various species have highlighted brain systems essential to various aspects of behavior, yet their application to complex learned behaviors remains limited. Research on vocal learning in songbirds has extensively focused on the vocal control network, though recent work implicates a variety of circuits in contributing to important aspects of vocal behavior.
View Article and Find Full Text PDFSci Rep
December 2024
Laboratory of Brain Imaging, Nencki Institute of Experimental Biology, Pasteura 3, Warsaw, 02-093, Poland.
Patients with major depressive disorder (MDD) and borderline personality disorder (BPD) are reported to have disrupted autobiographical memory (AM). Using functional magnetic resonance imaging we investigated behavioral and neural processing of the recall of emotional (sad and happy) memories in 30 MDD, 18 BPD, and 34 healthy control (HC) unmedicated women. The behavioral results showed that the MDD group experienced more sadness than the HC after the sad recall, while BPD participants experienced less happiness than HC after the happy recall.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland.
The study of the cortical basis of reading has greatly benefited from the use of naturalistic paradigms that permit eye movements. However, due to the short stimulus lengths used in most naturalistic reading studies, it remains unclear how reading of texts comprising more than isolated sentences modulates cortical processing. To address this question, we used magnetoencephalography to study the spatiospectral distribution of oscillatory activity during naturalistic reading of multi-page texts.
View Article and Find Full Text PDFSci Rep
December 2024
Brain Dynamics Lab, Interdisciplinary Center of Biomedical and Engineering Research for Health, Universidad de Valparaíso, Valparaíso, Chile.
Multi-state metastability in neuroimaging signals reflects the brain's flexibility to transition between network configurations in response to changing environments or tasks. We modeled these dynamics with a Kuramoto network of 90 nodes oscillating at an intrinsic frequency of 40 Hz, interconnected using human brain structural connectivity strengths and delays. We simulated this model for 30 min to generate multi-state metastability.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!