AIMC Topic: Dopamine
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Item Response Modeling and Artificial Neural Network for Differentiation of Parkinson's Patients and Subjects Without Evidence of Dopaminergic Deficit.
CPT: pharmacometrics & systems pharmacology
Mar 5, 2025
Approximately 15% of patients suspected of having Parkinson's disease (PD) present dopamine active transporter (DaT) scans without evidence of dopaminergic deficits (SWEDD), most of which will never develop PD. Leveraging Movement Disorders Society U...
High Spatiotemporal Precision Mapping of Optical Nanosensor Array Using Machine Learning.
ACS sensors
Sep 25, 2024
Optical nanosensors, including single-walled carbon nanotubes (SWCNTs), provide real-time spatiotemporal reporting at the single-molecule level within a nanometer-scale area. However, their superior sensitivity also makes them susceptible to slight e...
Resolution of tonic concentrations of highly similar neurotransmitters using voltammetry and deep learning.
Molecular psychiatry
Apr 25, 2024
With advances in our understanding regarding the neurochemical underpinnings of neurological and psychiatric diseases, there is an increased demand for advanced computational methods for neurochemical analysis. Despite having a variety of techniques ...
Development of surface molecular-imprinted electrochemical sensor for palmitic acid with machine learning assistance.
Talanta
Apr 24, 2024
Palmitic acid (PA) is a kind of saturated high fatty acid, which is involved in physiological safety and food quality. A surface molecularly imprinted polymer (MIP) electrochemical sensor was prepared on MXene surface using dopamine (DA) as functiona...
Parkinson's disease diagnosis using deep learning: A bibliometric analysis and literature review.
Ageing research reviews
Mar 28, 2024
Parkinson's Disease (PD) is a progressive neurodegenerative illness triggered by decreased dopamine secretion. Deep Learning (DL) has gained substantial attention in PD diagnosis research, with an increase in the number of published papers in this di...
Presynaptic Dopaminergic Imaging Characterizes Patients with REM Sleep Behavior Disorder Due to Synucleinopathy.
Annals of neurology
Mar 11, 2024
OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy ...
Deep learning-based image analysis identifies a DAT-negative subpopulation of dopaminergic neurons in the lateral Substantia nigra.
Communications biology
Nov 10, 2023
Here we present a deep learning-based image analysis platform (DLAP), tailored to autonomously quantify cell numbers, and fluorescence signals within cellular compartments, derived from RNAscope or immunohistochemistry. We utilised DLAP to analyse su...
Social behavioral profiling by unsupervised deep learning reveals a stimulative effect of dopamine D3 agonists on zebrafish sociality.
Cell reports methods
Jan 5, 2023
It has been a major challenge to systematically evaluate and compare how pharmacological perturbations influence social behavioral outcomes. Although some pharmacological agents are known to alter social behavior, precise description and quantificati...
Multilevel development of cognitive abilities in an artificial neural network.
Proceedings of the National Academy of Sciences of the United States of America
Sep 19, 2022
Several neuronal mechanisms have been proposed to account for the formation of cognitive abilities through postnatal interactions with the physical and sociocultural environment. Here, we introduce a three-level computational model of information pro...
Neurochemical Concentration Prediction Using Deep Learning vs Principal Component Regression in Fast Scan Cyclic Voltammetry: A Comparison Study.
ACS chemical neuroscience
Jul 25, 2022
Neurotransmitters, such as dopamine and serotonin, are responsible for mediating a wide array of neurologic functions, from memory to motivation. From measurements using fast scan cyclic voltammetry (FSCV), one of the main tools used to detect synapt...
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