Neural excitation/inhibition imbalance and the treatment of severe depression

An influential hypothesis holds that depression is related to a neural excitation/inhibition imbalance, but its role in the treatment of depression remains unclear. Here, we show that unmedicated patients with severe depression demonstrated reduced inhibition of brain-wide resting-state networks relative to healthy controls. Patients using antidepressants showed inhibition that was higher than unmedicated patients and comparable to controls, but they still suffered from severe depression. Subsequent treatment with electroconvulsive therapy (ECT) reduced depressive symptoms, but its effectiveness did not depend on changes in network inhibition. Concomitant pharmacotherapy increased the effectiveness of ECT, but only when the strength of neural inhibition before ECT was within the normal range and not when inhibition was excessive. These findings suggest that reversing the excitation/inhibition imbalance may not be sufficient nor necessary for the effective treatment of severe depression, and that brain-state informed pharmacotherapy management may enhance the effectiveness of ECT.

The Panoramic ECAP Method: Estimating Patient-Specific Patterns of Current Spread and Neural Health in Cochlear Implant Users

The knowledge of patient-specific neural excitation patterns from cochlear implants (CIs) can provide important information for optimizing efficacy and improving speech perception outcomes. The Panoramic ECAP (‘PECAP’) method (Cosentino et al. 2015) uses forward-masked electrically evoked compound action-potentials (ECAPs) to estimate neural activation patterns of CI stimulation. The algorithm requires ECAPs be measured for all combinations of probe and masker electrodes, exploiting the fact that ECAP amplitudes reflect the overlapping excitatory areas of both probes and maskers. Here we present an improved version of the PECAP algorithm that imposes biologically realistic constraints on the solution, that, unlike the previous version, produces detailed estimates of neural activation patterns by modelling current spread and neural health along the intracochlear electrode array and is capable of identifying multiple regions of poor neural health. The algorithm was evaluated for reliability and accuracy in three ways: (1) computer-simulated current-spread and neural-health scenarios, (2) comparisons to psychophysical correlates of neural health and electrode-modiolus distances in human CI users, and (3) detection of simulated neural ‘dead’ regions (using forward masking) in human CI users. The PECAP algorithm reliably estimated the computer-simulated scenarios. A moderate but significant negative correlation between focused thresholds and the algorithm’s neural-health estimates was found, consistent with previous literature. It also correctly identified simulated ‘dead’ regions in all seven CI users evaluated. The revised PECAP algorithm provides an estimate of neural excitation patterns in CIs that could be used to inform and optimize CI stimulation strategies for individual patients in clinical settings.

The Function of Sialidase Revealed by Sialidase Activity Imaging Probe

Sialidase cleaves sialic acid residues from glycans such as glycoproteins and glycolipids. In the brain, desorption of the sialic acid by sialidase is essential for synaptic plasticity, learning and memory and synaptic transmission. BTP3-Neu5Ac has been developed for sensitive imaging of sialidase enzyme activity in mammalian tissues. Sialidase activity in the rat hippocampus detected with BTP3-Neu5Ac increases rapidly by neuronal depolarization. It is presumed that an increased sialidase activity in conjunction with neural excitation is involved in the formation of the neural circuit for memory. Since sialidase inhibits the exocytosis of the excitatory neurotransmitter glutamate, the increased sialidase activity by neural excitation might play a role in the negative feedback mechanism against the glutamate release. Mammalian tissues other than the brain have also been stained with BTP3-Neu5Ac. On the basis of information on the sialidase activity imaging in the pancreas, it was found that sialidase inhibitor can be used as an anti-diabetic drug that can avoid hypoglycemia, a serious side effect of insulin secretagogues. In this review, we discuss the role of sialidase in the brain as well as in the pancreas and skin, as revealed by using a sialidase activity imaging probe. We also present the detection of influenza virus with BTP3-Neu5Ac and modification of BTP3-Neu5Ac.

Word Recognition and Frequency Selectivity in Cochlear Implant Simulation: Effect of Channel Interaction

In cochlear implants (CI), spread of neural excitation may produce channel interaction. Channel interaction disturbs the spectral resolution and, among other factors, seems to impair speech recognition, especially in noise. In this study, two tests were performed with 20 adult normal-hearing (NH) subjects under different vocoded simulations. First, there was a measurement of word recognition in noise while varying the number of selected channels (4, 8, 12 or 16 maxima out of 20) and the degree of simulated channel interaction (“Low”, “Medium” and “High”). Then, there was an evaluation of spectral resolution function of the degree of simulated channel interaction, reflected by the sharpness (Q10dB) of psychophysical tuning curves (PTCs). The results showed a significant effect of the simulated channel interaction on word recognition but did not find an effect of the number of selected channels. The intelligibility decreased significantly for the highest degree of channel interaction. Similarly, the highest simulated channel interaction impaired significantly the Q10dB. Additionally, a strong intra-individual correlation between frequency selectivity and word recognition in noise was observed. Lastly, the individual changes in frequency selectivity were positively correlated with the changes in word recognition when the degree of interaction went from “Low” to “High”. To conclude, the degradation seen for the highest degree of channel interaction suggests a threshold effect on frequency selectivity and word recognition. The correlation between frequency selectivity and intelligibility in noise supports the hypothesis that PTCs Q10dB can account for word recognition in certain conditions. Moreover, the individual variations of performances observed among subjects suggest that channel interaction does not have the same effect on each individual. Finally, these results highlight the importance of taking into account subjects’ individuality and to evaluate channel interaction through the speech processor.

Protein lactylation induced by neural excitation

Lactate is known to have diverse roles in the brain at the molecular and behavioral levels under both physiological and pathophysiological conditions, such as learning and memory and regulation of mood. Recently, a novel post-translational modification called lysine lactylation has been found in histone H3 of mouse macrophages, and the lactylation levels paralleled the intracellular lactate levels1. However, it is unknown whether lysine lactylation occurs in brain cells, and if it does, whether lactylation is induced by the stimuli that accompany changes in lactate levels. Herein, we reveal that lysine lactylation in brain cells is regulated by systemic changes in lactate levels, neural excitation, and behaviorally relevant stimuli. Lysine lactylation levels were increased by lactate treatment and by high-potassium-induced depolarization in cultured primary neurons; these increases were attenuated by pharmacological inhibition of monocarboxylate transporter 2 and lactate dehydrogenase, respectively, suggesting that both cell-autonomous and non-cell-autonomous neuronal mechanisms are involved in overall lysine lactylation. In vivo, electroconvulsive stimulation increased lysine lactylation levels in the prefrontal cortices of mice, and its levels were positively correlated with the expression levels of the neuronal activity marker c-Fos on an individual cell basis. In the social defeat stress model of depression in which brain lactate levels increase, lactylation levels were increased in the prefrontal cortices of the defeated mice, which was accompanied by increased c-Fos expression, decreased social behaviors, and increased anxiety-like behaviors, suggesting that stress-induced neuronal excitation may induce lysine lactylation, thereby affecting mood-related behaviors. Further, we identified 63 candidate lysine-lactylated proteins in the mouse cortex and found that lactylation levels in histone H1 increased in response to defeat stress. This study may open up an avenue for exploration of a novel role of neuronal activity-induced lactate mediated by protein lactylation in the brain.

Applications of Phenomenological Loudness Models to Cochlear Implants

Cochlear implants electrically stimulate surviving auditory neurons in the cochlea to provide severely or profoundly deaf people with access to hearing. Signal processing strategies derive frequency-specific information from the acoustic signal and code amplitude changes in frequency bands onto amplitude changes of current pulses emitted by the tonotopically arranged intracochlear electrodes. This article first describes how parameters of the electrical stimulation influence the loudness evoked and then summarizes two different phenomenological models developed by McKay and colleagues that have been used to explain psychophysical effects of stimulus parameters on loudness, detection, and modulation detection. The Temporal Model is applied to single-electrode stimuli and integrates cochlear neural excitation using a central temporal integration window analogous to that used in models of normal hearing. Perceptual decisions are made using decision criteria applied to the output of the integrator. By fitting the model parameters to a variety of psychophysical data, inferences can be made about how electrical stimulus parameters influence neural excitation in the cochlea. The Detailed Model is applied to multi-electrode stimuli, and includes effects of electrode interaction at a cochlear level and a transform between integrated excitation and specific loudness. The Practical Method of loudness estimation is a simplification of the Detailed Model and can be used to estimate the relative loudness of any multi-electrode pulsatile stimuli without the need to model excitation at the cochlear level. Clinical applications of these models to novel sound processing strategies are described.

Precision Medicine Care in ADHD: The Case for Neural Excitation and Inhibition

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that has become increasingly prevalent worldwide. Its core symptoms, including difficulties regulating attention, activity level, and impulses, appear in early childhood and can persist throughout the lifespan. Current pharmacological options targeting catecholamine neurotransmissions have effectively alleviated symptoms in some, but not all affected individuals, leaving clinicians to implement trial-and-error approach to treatment. In this review, we discuss recent experimental evidence from both preclinical and human studies that suggest imbalance of excitation/inhibition (E/I) in the fronto-striatal circuitry during early development may lead to enduring neuroanatomical abnormality of the circuitry, causing persistence of ADHD symptoms in adulthood. We propose a model of precision medicine care that includes E/I balance as a candidate biomarker for ADHD, development of GABA-modulating medications, and use of magnetic resonance spectroscopy and scalp electrophysiology methods to monitor the effects of treatments on shifting E/I balance throughout the lifespan.