AI Article Synopsis

  • Neuroimaging studies indicate that the main symptoms of ALS are linked to issues within specific neural networks, particularly those involving deep cerebral and cerebellar nuclei.
  • Recent research has found significant changes in brain structures such as volume reductions and metabolic alterations, especially in areas like the thalamus and hippocampus, even before symptoms appear.
  • Understanding ALS may require a focus on the integrity of these neural networks, as dysfunction in subcortical nuclei correlates with various clinical symptoms, emphasizing the need for thorough assessments of these brain regions.

Article Abstract

Evidence from neuroimaging studies suggests that the cardinal clinical manifestations of ALS stem from the dysfunction of specific neural networks. The majority of cortico-cortical and cortico-basal networks are physiologically relayed by deep cerebral and cerebellar grey matter nuclei which have been increasingly implicated in the pathophysiology of ALS. A series of recent human imaging papers revealed volume reductions, shape deformations, metabolic alterations and more recently, susceptibility changes in hippocampal subfields, thalamic, striatal, amygdalar and cerebellar nuclei. Thalamic changes have been identified in presymptomatic mutation carriers long before symptom onset and longitudinal studies have consistently confirmed progressive subcortical degeneration during the symptomatic phase of the disease. The dysfunction of circuits relayed by specific subcortical nuclei has been associated with apathy, amnestic deficits, limbic symptoms, extrapyramidal manifestations, sensory disturbances, pseudobulbar affect and cerebellar deficits. In light of emerging imaging data, the clinical heterogeneity of ALS is probably best approached from a network integrity perspective. Accordingly, the comprehensive assessment of subcortical grey matter nuclei seems imperative to untangle complex clinical phenomena in ALS.

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Source
http://dx.doi.org/10.1080/21678421.2024.2405130DOI Listing

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