The brain's function changes during various activities, and numerous studies have explored this field. An intriguing and significant area of research is the brain's functioning during imagination and periods of inactivity. This study explores the differences in brain connectivity during music listening and imagination: by identifying distinct neural connectivity patterns and providing insights into the cognitive mechanisms underlying auditory imagination. Effective connectivity matrices were generated using generalized partial directed coherence (GPDC) and directed Directed Transfer Function (dDTF) methods applied to non-invasive electroencephalography data from these two conditions. Statistical tests were performed to illustrate the differences in brain connectivity, followed by the creation of brain graphs and the application of a non-parametric permutation test to demonstrate statistical significance. Data classification between listening to music and imagining it was performed using an Support Vector Machine (SVM) classifier with different feature vectors. Combining features extracted from GPDC and dDTF achieved an accuracy of 71.3% while using GPDC and dDTF features individually yielded accuracies of 60% and 62.1%, respectively. Among all the graph's global features, only modularity and small-worldness showed statistically significant differences in dDTF and GPDC. Overall, findings reveal that information flows from the left hemisphere to the right hemisphere increases during music imagination compared with listening, highlighting distinct neural connectivity patterns associated with imaginative processes. The study provides novel insights into the distinct neural connectivity patterns during music listening and imagination, contributing to the broader understanding of cognitive processes associated with auditory imagination and perception.
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http://dx.doi.org/10.1089/brain.2024.0042 | DOI Listing |
Patterns (N Y)
December 2024
Medical Robot Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
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Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA.
Quantitative Susceptibility Mapping (QSM) is a technique that derives tissue magnetic susceptibility distributions from phase measurements obtained through Magnetic Resonance (MR) imaging. This involves solving an ill-posed dipole inversion problem, however, and thus time-consuming and cumbersome data acquisition from several distinct head orientations becomes necessary to obtain an accurate solution. Most recent (supervised) deep learning methods for single-phase QSM require training data obtained via multiple orientations.
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August 2024
Department of Mathematics, University of Texas at Arlington, Texas, USA 76019.
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January 2025
Department of Biomedical Engineering, Boston University, Boston, MA, 02215, USA.
Intracranial electrical kilohertz stimulation has recently been shown to achieve similar therapeutic benefit as conventional frequencies around 140 Hz. However, it is unknown how kilohertz stimulation influences neural activity in the mammalian brain. Using cellular calcium imaging in awake mice, we demonstrate that intracranial stimulation at 1 kHz evokes robust responses in many individual neurons, comparable to those induced by conventional 40 and 140 Hz stimulation in both the hippocampus and sensorimotor cortex.
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January 2025
Department of Physiology, Development and Neuroscience, Downing site, University of Cambridge, Cambridge, United Kingdom.
The gonadotropin-releasing hormone (GnRH) neurons represent the key output cells of the neural network controlling mammalian fertility. We used GCaMP fiber photometry to record the population activity of the GnRH neuron distal projections in the ventral arcuate nucleus where they merge before entering the median eminence to release GnRH into the portal vasculature. Recordings in freely behaving intact male and female mice revealed abrupt ~8 min duration increases in activity that correlated perfectly with the appearance of a subsequent pulse of luteinizing hormone (LH).
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