The thermodynamic theory of action potential propagation: a sound basis for unification of the physics of nerve impulses

The thermodynamic theory of action potential propagation challenges the conventional understanding of the nerve signal as an exclusively electrical phenomenon. Often misunderstood as to its basic tenets and predictions, the thermodynamic theory is virtually ignored in mainstream neuroscience. Addressing a broad audience of neuroscientists, we here attempt to stimulate interest in the theory. We do this by providing a concise overview of its background, discussion of its intimate connection to Albert Einstein’s treatment of the thermodynamics of interfaces and outlining its potential contribution to the building of a physical brain theory firmly grounded in first principles and the biophysical reality of individual nerve cells. As such, the paper does not attempt to advocate the superiority of the thermodynamic theory over any other approach to model the nerve impulse, but is meant as an open invitation to the neuroscience community to experimentally test the assumptions and predictions of the theory on their validity.

Neuropharmacology

Medications used in the treatment of nervous system disorders typically modulate neurotransmitter function or action potential propagation and alter neurologic function. This chapter reviews the principles of pharmacokinetics, the major targets for drug action to provide a basis for understanding how medications exert their action, and disease-specific treatments. An understanding of the pharmacokinetic principles of neurologic medications is important for prescribing and ordering medication. Multiple routes of administration, including intravenous, sublingual, intramuscular, subcutaneous, rectal, oral, and transdermal, are available for delivery of neurologic medications.

An Algorithm for Tracking the Position and Velocity of Multiple Neuronal Signals Using Implantable Microelectrodes In Vivo

Increasingly complex multi-electrode arrays for the study of neurons both in vitro and in vivo have been developed with the aim of tracking the conduction of neural action potentials across a complex interconnected network. This is usually performed through the use of electrodes to record from single or small groups of microelectrodes, and using only one electrode to monitor an action potential at any given time. More complex high-density electrode structures (with thousands of electrodes or more) capable of tracking action potential propagation have been developed but are not widely available. We have developed an algorithm taking data from clusters of electrodes positioned such that action potentials are detected by multiple sites, and using this to detect the location and velocity of action potentials from multiple neurons. The system has been tested by analyzing recordings from probes implanted into the locust nervous system, where recorded positions and velocities correlate well with the known physical form of the nerve.

An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays

Neurons communicate with each other by sending action potentials through their axons. The velocity of axonal signal propagation describes how fast electrical action potentials can travel, and can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon reconstruction, to date, mainly relies on a manual approach to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing. In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called "electrical footprints" of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph, based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned and axonal action-potential propagation velocities are computed. We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput. We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.

Neuron–Oligodendrocyte Communication in Myelination of Cortical GABAergic Cells

Axonal myelination by oligodendrocytes increases the speed and reliability of action potential propagation, and so plays a pivotal role in cortical information processing. The extent and profile of myelination vary between different cortical layers and groups of neurons. Two subtypes of cortical GABAergic neurons are myelinated: fast-spiking parvalbumin-expressing cells and somatostatin-containing cells. The expression of pre-nodes on the axon of these inhibitory cells before myelination illuminates communication between oligodendrocytes and neurons. We explore the consequences of myelination for action potential propagation, for patterns of neuronal connectivity and for the expression of behavioral plasticity.