Fine-tuning neural excitation/inhibition for tailored ketamine use in treatment-resistant depression

The glutamatergic modulator ketamine has been shown to rapidly reduce depressive symptoms in patients with treatment-resistant major depressive disorder (TRD). Although its mechanisms of action are not fully understood, changes in cortical excitation/inhibition (E/I) following ketamine administration are well documented in animal models and could represent a potential biomarker of treatment response. Here, we analyse neuromagnetic virtual electrode time series collected from the primary somatosensory cortex in 18 unmedicated patients with TRD and in an equal number of age-matched healthy controls during a somatosensory ‘airpuff’ stimulation task. These two groups were scanned as part of a clinical trial of ketamine efficacy under three conditions: (a) baseline; (b) 6–9 h following subanesthetic ketamine infusion; and (c) 6–9 h following placebo-saline infusion. We obtained estimates of E/I interaction strengths by using dynamic causal modelling (DCM) on the time series, thereby allowing us to pinpoint, under each scanning condition, where each subject’s dynamics lie within the Poincaré diagram—as defined in dynamical systems theory. We demonstrate that the Poincaré diagram offers classification capability for TRD patients, in that the further the patients’ coordinates were shifted (by virtue of ketamine) toward the stable (top-left) quadrant of the Poincaré diagram, the more their depressive symptoms improved. The same relationship was not observed by virtue of a placebo effect—thereby verifying the drug-specific nature of the results. We show that the shift in neural dynamics required for symptom improvement necessitates an increase in both excitatory and inhibitory coupling. We present accompanying MATLAB code made available in a public repository, thereby allowing for future studies to assess individually tailored treatments of TRD.

Alterations in the Excitatory and Inhibitory Coupling in Migraine: A Magnetic Resonance Study

Background: There is evidence suggesting that an imbalance between the levels of the excitatory neurotransmitter, glutamate, and inhibitory neurotransmitter, gamma aminobutyric acid (GABA), leads to migraine attacks; however, the pathophysiology and specific diagnostic markers remain unknown. Methods: Twenty-one migraine patients (18 female, 3 male, mean age=40.63 14.23years) and 11 healthy controls (9 female, 2 male, mean age=39.78 15.31 years) were included in this study. We used 1H-MRS at 3 Tesla with voxels-of-interest located in the bilateral thalamus and subgenual anterior cingulate cortex (SG ACC) to quantify the GABA and GLX (glutamate-glutamine complex) concentrations measured via the Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS) sequence in migraineurs and healthy controls. Result: Statistical analyses revealed significantly decreased GLX/NAA (N-acetylaspartate) in the right thalamus of migraine patients compared to healthy controls. However, we found no group differences in GABA levels in the SG ACC and bilateral thalamus.Conclusion: The right thalamus may be involved in the pain modulation process of migraineurs through changes in the GLX levels. Decreased GLX levels within the right thalamus might be associated with the disruption of "excitation-inhibition" homeostasis in migraine.Trial registration: ClinicalTrials.gov, NCT02580968. Registered 30 October 2015, https://clinicaltrials.gov/ct2/show/study/NCT02580968

Synchronization in coupled neural network with inhibitory coupling

A theoretical model of a network of neuron-like elements was constructed. The network included several subnetworks. The first subnetwork was used to translate a constant-amplitude signal into a spike sequence (conversion of amplitude to frequency). A similar process occurs in the brain when perceiving visual information. With an increase in the flow of information, the generation frequency of the neural ensemble participating in the processing increases. Further, the first subnetwork transmitted excitation to two large interconnected subnetworks. These subnetworks simulated the dynamics of the cortical neuronal populations. It was shown that in the presence of inhibitory coupling, the neuronal ensembles demonstrate antiphase dynamics. Various connectivity topologies and various types of neuron-like oscillators were investigated. We compare the results obtained in a discrete neuron model (Rulkov model) and a continuous-time model (Hodgkin-Huxley). It is shown that in the case of a discrete neuron model, the periodic dynamics is manifested in the alternate excitation of various neural ensembles. In the case of the continuous-time model, periodic modulation of the synchronization index of neural ensembles is observed.

Bilateral auditory processing studied by selective cold-deactivation of cricket hearing organs

ABSTRACTWe studied bilateral processing in the auditory ON neurons of crickets using reversible cold-deactivation of the hearing organs by means of Peltier elements. Intracellular recordings of the neurons’ activity in response to acoustic stimuli were obtained, while either the ipsilateral or the contralateral hearing organ was cold-deactivated. Afferent activity was abolished at a temperature of about 10°C. In ON1 contralateral inhibition has no effect on the latency and amplitude of the phasic onset activity, it enhances the decline of the onset activity and decreases the subsequent tonic spiking response to acoustic stimuli. As a consequence the phasic onset activity becomes more salient and reciprocal inhibition may support the detection of sound pulses. Contralateral inhibition had a significant impact on the tonic ON1 response, in line with its presumed function to enhance the bilateral auditory contrast. In ON2, experiments confirmed a bilateral excitatory input, with the ipsilateral input dominating the response, and no inhibitory coupling between the ON2 neurons.

Transition Dynamics of Epileptic Seizures in the Coupled Thalamocortical Network Model

In this paper, based on the two-compartment unidirectionally coupled thalamocortical model network, we investigated the transition dynamics of epileptic seizures, by considering the inhibitory coupling strength from cortical inhibitory interneuronal (IN) population to excitatory pyramidal (PY) neuronal population as the key bifurcation parameter. The results show that in the single compartment thalamocortical model, inner-compartment inhibitory functions of IN can make the system transit from the absence seizures to the tonic oscillations. In the case of two-compartment coupled thalamocortical model network, the inter-compartment inhibitory coupling functions from the first compartment can drive the second compartment to more easily initiate the absence and tonic seizures at the lower inhibitory coupling strengths, respectively. Also, the driven functions can make the amplitudes of these seizures vary irregularly. Detailed investigations reveal that along with the various state transitions, the system consecutively undergoes Hopf bifurcations, fold of cycles bifurcations and torus bifurcations, respectively. In particular, the reinforcing inter-compartment inhibitory coupling function can induce the chaotic dynamics. We highlight the unidirectional coupling functions between two compartments which might give new insights into the propagation and evolution dynamics of epileptic seizures.