Brain Connectivity and Network Analysis in Amyotrophic Lateral Sclerosis.
Vijay RengaPublished in: Neurology research international (2022)
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no effective treatment or cure. ALS is characterized by the death of lower motor neurons (LMNs) in the spinal cord and upper motor neurons (UMNs) in the brain and their networks. Since the lower motor neurons are under the control of UMN and the networks, cortical degeneration may play a vital role in the pathophysiology of ALS. These changes that are not apparent on routine imaging with CT scans or MRI brain can be identified using modalities such as diffusion tensor imaging, functional MRI, arterial spin labelling (ASL), electroencephalogram (EEG), magnetoencephalogram (MEG), functional near-infrared spectroscopy (fNIRS), and positron emission tomography (PET) scan. They can help us generate a representation of brain networks and connectivity that can be visualized and parsed out to characterize and quantify the underlying pathophysiology in ALS. In addition, network analysis using graph measures provides a novel way of understanding the complex network changes occurring in the brain. These have the potential to become biomarker for the diagnosis and treatment of ALS. This article is a systematic review and overview of the various connectivity and network-based studies in ALS.
Keyphrases
- resting state
- amyotrophic lateral sclerosis
- functional connectivity
- white matter
- computed tomography
- positron emission tomography
- spinal cord
- network analysis
- contrast enhanced
- magnetic resonance imaging
- multiple sclerosis
- high resolution
- cerebral ischemia
- spinal cord injury
- magnetic resonance
- neuropathic pain
- climate change
- deep learning
- risk assessment
- working memory
- single molecule
- blood brain barrier
- neural network
- room temperature
- replacement therapy
- ionic liquid