The role of voltage dependence of the NMDA receptor in cellular and network oscillation

Premotor Neuron Divergence Reflects Vocal Evolution

To identify mechanisms of behavioral evolution, we investigated the hindbrain circuit that generates distinct vocal patterns in two closely related frog species. Male Xenopus laevis and Xenopus petersii produce courtship calls that include a fast trill: trains of ∼60 Hz sound pulses. Although fast trill rates are similar, X. laevis fast trills have a longer duration and period than those of X. petersii To pinpoint the neural basis of these differences, we used whole-cell patch-clamp recordings in a key premotor hindbrain nucleus (the Xenopus parabrachial area, PB_X) in ex vivo brains that produce fictive vocalizations, vocal nerve activity corresponding to advertisement call patterns. We found two populations of PB_X neurons with distinct properties: fast trill neurons (FTNs) and early vocal neurons (EVNs). FTNs, but not EVNs, appear to be intrinsically tuned to produce each species' call patterns because: (1) X. laevis FTNs generate longer and slower depolarizations than X. petersii FTNs during their respective fictive vocalizations, (2) current steps in FTNs induce burst durations that are significantly longer in X. laevis than X. petersii, and (3) synaptically isolated FTNs oscillate in response to NMDA in a species-specific manner: longer and slower in X. laevis than in X. petersii Therefore, divergence of premotor neuron membrane properties is a strong candidate for generating vocal differences between species.SIGNIFICANCE STATEMENT The vertebrate hindbrain includes multiple neural circuits that generate rhythmic behaviors including vocalizations. Male African clawed frogs produce courtship calls that are unique to each species and differ in temporal patterns. Here, we identified two functional subtypes of neurons located in the parabrachial nucleus: a hindbrain region implicated in vocal and respiratory control across vertebrates. One of these neuronal subtypes exhibits distinct properties across species that can account for the evolutionary divergence of song patterns. Our results suggest that changes to this group of neurons during evolution may have had a major role in establishing novel behaviors in closely related species.

The integrative role of the sigh in psychology, physiology, pathology, and neurobiology

"Sighs, tears, grief, distress" expresses Johann Sebastian Bach in a musical example for the relationship between sighs and deep emotions. This review explores the neurobiological basis of the sigh and its relationship with psychology, physiology, and pathology. Sighs monitor changes in brain states, induce arousal, and reset breathing variability. These behavioral roles homeostatically regulate breathing stability under physiological and pathological conditions. Sighs evoked in hypoxia evoke arousal and thereby become critical for survival. Hypoarousal and failure to sigh have been associated with sudden infant death syndrome. Increased breathing irregularity may provoke excessive sighing and hyperarousal, a behavioral sequence that may play a role in panic disorders. Essential for generating sighs and breathing is the pre-Bötzinger complex. Modulatory and synaptic interactions within this local network and between networks located in the brainstem, cerebellum, cortex, hypothalamus, amygdala, and the periaqueductal gray may govern the relationships between physiology, psychology, and pathology. Unraveling these circuits will lead to a better understanding of how we balance emotions and how emotions become pathological.

A systematic review of the effects of NMDA receptor antagonists on oscillatory activity recorded in vivo

Distinct frequency bands can be differentiated from neuronal ensemble recordings, such as local field potentials or electrocorticogram recordings. Recent years have witnessed a rapid acceleration of research examining how N-methyl-D-aspartate receptor (NMDAR) antagonists influence fundamental frequency bands in cortical and subcortical brain regions. Herein, we systematically review findings from in vivo studies with a focus on delta, theta, gamma and more recently identified high-frequency oscillations. We also discuss some of the current hypotheses that are considered to account for the actions of NMDAR antagonists on these frequency bands. The data emphasize a close relationship between altered oscillatory activity and NMDAR blockade, with both local and large-scale networks accounting for their effects. These findings may have fundamental implications for the psychotomimetic effects produced by NMDAR antagonists.

Modeling Neural Activity

This paper provides an overview of different types of models for studying activity of nerve cells and their networks with a special emphasis on neural oscillations. One part describes the neuronal models based on the Hodgkin and Huxley formalism first described in the 1950s. It is discussed how further simplifications of this formalism enable mathematical analysis of the process of neural excitability. The focus of the paper’s second component is on network activity. Understanding network function is one of the important frontiers remaining in neuroscience. At present, experimental techniques can only provide global recordings or samples of the activity of the huge networks that form the nervous system. Models in neuroscience can therefore play a critical role by providing a framework for integration of necessarily incomplete datasets, thereby providing insight into the mechanisms of neural function. Network models can either explicitly contain individual network nodes that model the neurons, or they can be based on representations of compound population activity. The latter approach was pioneered by Wilson and Cowan in the 1970s. Finally I provide an overview and discuss how network models are employed in the study of neuronal network pathology such as epilepsy.

The dynamics of neurological disease: integrating computational, experimental and clinical neuroscience

There is a vast (and rapidly growing) amount of experimental and clinical data of the nervous system at very diverse spatial scales of activity (e.g. from sub-cellular through to whole organ), with many neurological disorders characterized by oscillations in neural activity across these disparate scales. Computer modelling and the development of associated mathematical theories provide us with a unique opportunity to integrate information from across these diverse scales of activity; leading to explanations of the potential mechanisms underlying the time-evolving dynamics and, more importantly, allowing the development of new hypotheses regarding neural function that may be tested experimentally and ultimately translated into the clinic. The purpose of this special issue is to present an overview of current integrative research in the areas of epilepsy, Parkinson's disease and schizophrenia, where multidisciplinary relationships involving theory, experimental and clinical research are becoming increasingly established.