AIMC Topic: gamma-Aminobutyric Acid

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Maturation of GABAergic signalling times the opening of a critical period in Drosophila melanogaster.

Scientific reports
Critical periods (CPs) during the development of neural networks are widely documented. Activity manipulation during open CPs leads to debilitating effects to the mature neural network. Detailed understanding of the contribution of CPs to network dev...

SMART MRS: A Simulated MEGA-PRESS ARTifacts toolbox for GABA-edited MRS.

Magnetic resonance in medicine
PURPOSE: To create a Python-based toolbox to simulate commonly occurring artifacts for single voxel gamma-aminobutyric acid (GABA)-edited MRS data.

Stabilizing sequence learning in stochastic spiking networks with GABA-Modulated STDP.

Neural networks : the official journal of the International Neural Network Society
Cortical networks are capable of unsupervised learning and spontaneous replay of complex temporal sequences. Endowing artificial spiking neural networks with similar learning abilities remains a challenge. In particular, it is unresolved how differen...

Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks.

Magnetic resonance imaging
PURPOSE: To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edite...

Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time.

Magma (New York, N.Y.)
PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete sc...

Magnetic Resonance Spectroscopy Spectral Registration Using Deep Learning.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Deep learning-based methods have been successfully applied to MRI image registration. However, there is a lack of deep learning-based registration methods for magnetic resonance spectroscopy (MRS) spectral registration (SR).

Classification of antiseizure drugs in cultured neuronal networks using multielectrode arrays and unsupervised learning.

Epilepsia
OBJECTIVE: Antiseizure drugs (ASDs) modulate synaptic and ion channel function to prevent abnormal hypersynchronous or excitatory activity arising in neuronal networks, but the relationship between ASDs with respect to their impact on network activit...

Frequency and phase correction of J-difference edited MR spectra using deep learning.

Magnetic resonance in medicine
PURPOSE: To investigate whether a deep learning-based (DL) approach can be used for frequency-and-phase correction (FPC) of MEGA-edited MRS data.

An efficient analytical reduction of detailed nonlinear neuron models.

Nature communications
Detailed conductance-based nonlinear neuron models consisting of thousands of synapses are key for understanding of the computational properties of single neurons and large neuronal networks, and for interpreting experimental results. Simulations of ...

Reducing variability in motor cortex activity at a resting state by extracellular GABA for reliable perceptual decision-making.

Journal of computational neuroscience
Interaction between sensory and motor cortices is crucial for perceptual decision-making, in which intracortical inhibition might have an important role. We simulated a neural network model consisting of a sensory network (N) and a motor network (N) ...