AIMC Topic: Corpus Striatum

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Interpretable deep learning for deconvolutional analysis of neural signals.

Neuron
The widespread adoption of deep learning to model neural activity often relies on "black-box" approaches that lack an interpretable connection between neural activity and network parameters. Here, we propose using algorithm unrolling, a method for in...

Fine-scale striatal parcellation using diffusion MRI tractography and graph neural networks.

Medical image analysis
The striatum, a crucial part of the basal ganglia, plays a key role in various brain functions through its interactions with the cortex. The complex structural and functional diversity across subdivisions within the striatum highlights the necessity ...

Interaction of Indirect and Hyperdirect Pathways on Synchrony and Tremor-Related Oscillation in the Basal Ganglia.

Neural plasticity
Low-frequency oscillatory activity (3-9 Hz) and increased synchrony in the basal ganglia (BG) are recognized to be crucial for Parkinsonian tremor. However, the dynamical mechanism underlying the tremor-related oscillations still remains unknown. In ...

Learning to select actions shapes recurrent dynamics in the corticostriatal system.

Neural networks : the official journal of the International Neural Network Society
Learning to select appropriate actions based on their values is fundamental to adaptive behavior. This form of learning is supported by fronto-striatal systems. The dorsal-lateral prefrontal cortex (dlPFC) and the dorsal striatum (dSTR), which are st...

A Basal Ganglia Computational Model to Explain the Paradoxical Sensorial Improvement in the Presence of Huntington's Disease.

International journal of neural systems
The basal ganglia (BG) represent a critical center of the nervous system for sensorial discrimination. Although it is known that Huntington's disease (HD) affects this brain area, it still remains unclear how HD patients achieve paradoxical improveme...

Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

PloS one
OBJECTIVE: To assess the classification performance between Parkinson's disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT...

The striatum specifies the statistics of behavior.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology

Classification of degenerative parkinsonism subtypes by support-vector-machine analysis and striatal I-FP-CIT indices.

Journal of neurology
OBJECTIVES: To provide an automated classification method for degenerative parkinsonian syndromes (PS) based on semiquantitative I-FP-CIT SPECT striatal indices and support-vector-machine (SVM) analysis.

Feasible Classified Models for Parkinson Disease from Tc-TRODAT-1 SPECT Imaging.

Sensors (Basel, Switzerland)
The neuroimaging techniques such as dopaminergic imaging using Single Photon Emission Computed Tomography (SPECT) with Tc-TRODAT-1 have been employed to detect the stages of Parkinson's disease (PD). In this retrospective study, a total of 202 Tc-TRO...