Over the past decade, Deep Artificial Neural Networks (DNNs) have become the state-of-the-
art algorithms in Machine Learning (ML), speech recognition, computer vision, natural …

The computational neuroscience field has heavily concentrated on the modeling of neuronal
functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes …

Modeling the neuronal processes underlying short-term working memory remains the focus
of many theoretical studies in neuroscience. In this paper, we propose a mathematical …

Amyloid beta ($ A\beta $) plaques are associated with neurodegenerative diseases such as
Alzheimer's disease. Due to the involvement of $ A\beta $ plaques in the functioning of the …

Astrocytes generate ATP through glycolysis and mitochondrion respiration, using glucose,
lactate, fatty acids, amino acids, and ketone bodies as metabolic fuels. Astrocytic …

Mammalian brains operate in very special surroundings: to survive they have to react quickly
and effectively to the pool of stimuli patterns previously recognized as danger. Many …

Recent research has shown that a glial cell of astrocyte underpins a self-repair mechanism
in the human brain, where spiking neurons provide direct and indirect feedbacks to …

While Moore's law has driven exponential computing power expectations, its nearing end
calls for new avenues for improving the overall system performance. One of these avenues …

Neuromorphic computing is becoming a popular approach for implementations of brain-
inspired machine learning tasks. As a paradigm for both hardware and algorithm design …

Neurological diseases can be studied by performing bio-hybrid experiments using a real-
time biomimetic Spiking Neural Network (SNN) platform. The Hodgkin-Huxley model offers a …