AI Article Synopsis
Article Abstract
Recent advances in biocompatible materials, miniaturized instrumentation, advanced computational algorithms, and genetic tools have enabled the development of novel methods and approaches to quantify the behavior of individuals or groups of animals. In conjunction with technologies that allow simultaneous monitoring of neural responses, quantitative studies of complex behaviors can reveal tighter links between the external sensory cues in the vicinity of the organism and neural responses they elicit, and how internal neural representations finally get mapped onto the behavior generated. In this review, we examine a few approaches that are beginning to be widely exploited for understanding neural-behavioral response transformations.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.cois.2021.07.004 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Multi-gate neuron-like transistors based on ensembles of aligned nanowires on flexible substrates.
Nano Converg
January 2025
Bendable Electronics and Sustainable Technologies (BEST) Group, Electrical and Computer Engineering Department, Northeastern University, Boston, MA, 02115, USA.
The intriguing way the receptors in biological skin encode the tactile data has inspired the development of electronic skins (e-skin) with brain-inspired or neuromorphic computing. Starting with local (near sensor) data processing, there is an inherent mechanism in play that helps to scale down the data. This is particularly attractive when one considers the huge data produced by large number of sensors expected in a large area e-skin such as the whole-body skin of a robot.
View Article and Find Full Text PDFDisentangling the neural underpinnings of response inhibition in disruptive behavior and co-occurring ADHD.
Eur Child Adolesc Psychiatry
January 2025
Department of Child and Adolescent Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
While impaired response inhibition has been reported in attention-deficit/hyperactivity disorder (ADHD), findings in disruptive behavior disorders (DBDs) have been inconsistent, probably due to unaccounted effects of co-occurring ADHD in DBD. This study investigated the associations of behavioral and neural correlates of response inhibition with DBD and ADHD symptom severity, covarying for each other in a dimensional approach. Functional magnetic resonance imaging data were available for 35 children and adolescents with DBDs (8-18 years old, 19 males), and 31 age-matched unaffected controls (18 males) while performing a performance-adjusted stop-signal task.
View Article and Find Full Text PDFComparison of the amyloid plaque proteome in Down syndrome, early-onset Alzheimer's disease, and late-onset Alzheimer's disease.
Acta Neuropathol
January 2025
Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA.
Down syndrome (DS) is strongly associated with Alzheimer's disease (AD) due to APP overexpression, exhibiting Amyloid-β (Aβ) and Tau pathology similar to early-onset (EOAD) and late-onset AD (LOAD). We evaluated the Aβ plaque proteome of DS, EOAD, and LOAD using unbiased localized proteomics on post-mortem paraffin-embedded tissues from four cohorts (n = 20/group): DS (59.8 ± 4.
View Article and Find Full Text PDFLocalization of Cholecystokinin/Sulfakinin Neuropeptides in Biomphalaria glabrata, an Intermediate Host for Schistosomiasis.
J Comp Neurol
January 2025
Institute of Neurobiology, University of Puerto Rico, Medical Sciences Campus, San Juan, Puerto Rico.
Snails belonging to the genus Biomphalaria serve as obligatory intermediate hosts for the trematode Schistosoma mansoni, the causative agent for the most widespread form of schistosomiasis. The simpler nervous systems of gastropod molluscs, such as Biomphalaria, provide advantageous models for investigating neural responses to infection at the cellular and network levels. The present study examined neuropeptides related to cholecystokinin (CCK), a major multifunctional regulator of central nervous system (CNS) function in mammals.
View Article and Find Full Text PDFMGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction.
BMC Bioinformatics
January 2025
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu, 611756, Sichuan, China.
Background: Drug response prediction is critical in precision medicine to determine the most effective and safe treatments for individual patients. Traditional prediction methods relying on demographic and genetic data often fall short in accuracy and robustness. Recent graph-based models, while promising, frequently neglect the critical role of atomic interactions and fail to integrate drug fingerprints with SMILES for comprehensive molecular graph construction.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!