Dataset Information

A long-range, recurrent neuronal network linking the emotion regions with the somatic motor cortex.

ABSTRACT: Recurrent neural networks (RNNs) are designed to learn sequential patterns in silico, but it is unclear whether and how an RNN forms in the native networks of the mammalian brain. Here, we report an innate RNN, which is formed by the unidirectional connections from three basic units: input units arriving from emotion regions, a hidden unit in the medial prefrontal cortex (mPFC), and output units located at the somatic motor cortex (sMO). Specifically, the neurons from basal lateral amygdala (BLA) and the insular cortex (IC) project to the mPFC motor-cortex-projecting (MP) neurons. These MP neurons form a local self-feedback loop and target major projecting neurons of the sMO. Within the sMO, the neurons in the infragranular layers receive stronger input than the neurons in supragranular layers. Finally, we show in vivo evidence that the communications from the emotion regions to the sMO are abolished when MP neurons are chemogenetically silenced.

SUBMITTER: Wang Y

PROVIDER: S-EPMC8507441 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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Publications

A long-range, recurrent neuronal network linking the emotion regions with the somatic motor cortex.

Wang Yihan Y Sun Qian-Quan QQ

Cell reports 20210901 12

Recurrent neural networks (RNNs) are designed to learn sequential patterns in silico, but it is unclear whether and how an RNN forms in the native networks of the mammalian brain. Here, we report an innate RNN, which is formed by the unidirectional connections from three basic units: input units arriving from emotion regions, a hidden unit in the medial prefrontal cortex (mPFC), and output units located at the somatic motor cortex (sMO). Specifically, the neurons from basal lateral amygdala (BLA ...[more]

PMID: 34551292

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Project description:Motor skills are frequently impaired in multiple sclerosis (MS) patients following grey and white matter damage with cortical excitability abnormalities. We applied advanced diffusion imaging with 3T magnetic resonance tomography for neurite orientation dispersion and density imaging (NODDI), as well as diffusion tensor imaging (DTI) in 50 MS patients and 49 age-matched healthy controls to quantify microstructural integrity of the motor system. To assess excitability, we determined resting motor thresholds using non-invasive transcranial magnetic stimulation. As measures of cognitive-motor performance, we conducted neuropsychological assessments including the Nine-Hole Peg Test, Trail Making Test part A and B (TMT-A and TMT-B) and the Symbol Digit Modalities Test (SDMT). Patients were evaluated clinically including assessments with the Expanded Disability Status Scale. A hierarchical regression model revealed that lower neurite density index (NDI) in primary motor cortex, suggestive for axonal loss in the grey matter, predicted higher motor thresholds, i.e. reduced excitability in MS patients (p = .009, adjusted r² = 0.117). Furthermore, lower NDI was indicative of decreased cognitive-motor performance (p = .007, adjusted r² = .142 for TMT-A; p = .009, adjusted r² = .129 for TMT-B; p = .006, adjusted r² = .142 for SDMT). Motor WM tracts of patients were characterized by overlapping clusters of lowered NDI (p <.05, Cohen's d = 0.367) and DTI-based fractional anisotropy (FA) (p <.05, Cohen's d = 0.300), with NDI exclusively detecting a higher amount of abnormally appearing voxels. Further, orientation dispersion index of motor tracts was increased in patients compared to controls, suggesting a decreased fiber coherence (p <.05, Cohen's d = 0.232). This study establishes a link between microstructural characteristics and excitability of neural tissue, as well as cognitive-motor performance in multiple sclerosis. We further demonstrate that the NODDI parameters neurite density index and orientation dispersion index detect a larger amount of abnormally appearing voxels in patients compared to healthy controls, as opposed to the classical DTI parameter FA. Our work outlines the potential for microstructure imaging using advanced biophysical models to forecast excitability alterations in neuroinflammation.

Dataset Information

A long-range, recurrent neuronal network linking the emotion regions with the somatic motor cortex.

Publications

A long-range, recurrent neuronal network linking the emotion regions with the somatic motor cortex.

Similar Datasets

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