Machine learning and brain-computer interface approaches in prognosis and individualized care strategies for individuals with amyotrophic lateral sclerosis: A systematic review.

Amyotrophic lateral sclerosis (ALS) characterized by progressive degeneration of motor neurons is a debilitating disease, posing substantial challenges in both prognosis and daily life assistance. However, with the advancement of machine learning (ML) which is renowned for tackling many real-world settings, it can offer unprecedented opportunities in prognostic studies and facilitate individuals with ALS in motor-imagery tasks. ML models, such as random forests (RF), have emerged as the most common and effective algorithms for predicting disease progression and survival time in ALS.

Integrative Roles of Dopamine Pathway and Calcium Channels Reveal a Link between Schizophrenia and Opioid Use Disorder.

Several theories have been proposed to explain the mechanisms of substance use in schizophrenia. Brain neurons pose a potential to provide novel insights into the association between opioid addiction, withdrawal, and schizophrenia. Thus, we exposed zebrafish larvae at 2 days post-fertilization (dpf) to domperidone (DPM) and morphine, followed by morphine withdrawal.

The role of neuron-glia interactions in the emergence of ultra-slow oscillations.

Ultra-slow cortical oscillatory activity of 1-100 mHz has been recorded in human by electroencephalography and in dissociated cultures of cortical rat neurons, but the underlying mechanisms remain to be elucidated. This study presents a computational model of ultra-slow oscillatory activity based on the interaction between neurons and astrocytes. We predict that the frequency of these oscillations closely depends on activation of astrocytes in the network, which is reflected by oscillations of their intracellular calcium concentrations with periods between tens of seconds and minutes.