Over the last several years, the use of machine learning (ML) in neuroscience has been
rapidly increasing. Here, we review ML's contributions, both realized and potential, across …

Digital reconstruction of neuronal morphology is a powerful technique for investigating the
nervous system. This process consists of tracing the axonal and dendritic arbors of neurons …

Taking a step-by-step approach to modelling neurons and neural circuitry, this textbook
teaches students how to use computational techniques to understand the nervous system at …

The striatum, the principal input structure of the basal ganglia, is crucial to both motor control
and learning. It receives convergent input from all over the neocortex, hippocampal …

Over hundreds of millions of years, evolution has optimized brain design to maximize its
functionality while minimizing costs associated with building and maintenance. This …

We introduce L-Neuron (www. krasnow. gmu. edu/L-Neuron), a software package for the
generation and study of anatomically accurate neuronal analogs. L-Neuron is based on sets …

It is generally assumed that the variability of neuronal morphology has an important effect on
both the connectivity and the activity of the nervous system, but this effect has not been …

Background The morphological development of neurons is a very complex process
involving both genetic and environmental components. Mathematical modelling and …

Phrenic motoneurons are located in the cervical spinal cord and innervate the diaphragm
muscle, the main inspiratory muscle in mammals. Similar to other skeletal muscles, phrenic …

Brain derived neurotrophic factor (BDNF) signalling through its high-affinity tropomyosin
receptor kinase B (TrkB) is known to have potent effects on motor neuron survival and …