Optogenetic inhibition of the limbic corticothalamic circuit does not alter spontaneous oscillatory activity, auditory-evoked oscillations, and deviant detection.

Aberrant neuronal circuit dynamics are at the core of complex neuropsychiatric disorders, such as schizophrenia (SZ). Clinical assessment of the integrity of neuronal circuits in SZ has consistently described aberrant resting-state gamma oscillatory activity, decreased auditory-evoked gamma responses, and abnormal mismatch responses. We hypothesized that corticothalamic circuit manipulation could recapitulate SZ circuit phenotypes in rodent models. In this study, we optogenetically inhibited the mediodorsal thalamus-to-prefrontal cortex (MDT-to-PFC) or the PFC-to-MDT projection in rats and assessed circuit function through electrophysiological readouts. We found that MDT-PFC perturbation could not recapitulate SZ-linked phenotypes such as broadband gamma disruption, altered evoked oscillatory activity, and diminished mismatch negativity responses. Therefore, the induced functional impairment of the MDT-PFC pathways cannot account for the oscillatory abnormalities described in SZ.

Open Hardware Implementation of Real-Time Phase and Amplitude Estimation for Neurophysiologic Signals.

Adaptive deep brain stimulation (aDBS) is a promising concept in the field of DBS that consists of delivering electrical stimulation in response to specific events. Dynamic adaptivity arises when stimulation targets dynamically changing states, which often calls for a reliable and fast causal estimation of the phase and amplitude of the signals. Here, we present an open-hardware implementation that exploits the concepts of resonators and Hilbert filters embedded in an open-hardware platform. To emulate real-world scenarios, we built a hardware setup that included a system to replay and process different types of physiological signals and test the accuracy of the instantaneous phase and amplitude estimates. The results show that the system can provide a precise and reliable estimation of the phase even in the challenging scenario of dealing with high-frequency oscillations (~250 Hz) in real-time. The framework might be adopted in neuromodulation studies to quickly test biomarkers in clinical and preclinical settings, supporting the advancement of aDBS.

Glutamatergic and GABAergic Receptor Modulation Present Unique Electrophysiological Fingerprints in a Concentration-Dependent and Region-Specific Manner.

Brain function depends on complex circuit interactions between excitatory and inhibitory neurons embedded in local and long-range networks. Systemic GABAA-receptor (GABAAR) or NMDA-receptor (NMDAR) modulation alters the excitatory-inhibitory balance (EIB), measurable with electroencephalography (EEG). However, EEG signatures are complex in localization and spectral composition. We developed and applied analytical tools to investigate the effects of two EIB modulators, MK801 (NMDAR antagonist) and diazepam (GABAAR modulator), on periodic and aperiodic EEG features in freely-moving male Sprague Dawley rats. We investigated how, across three brain regions, EEG features are correlated with EIB modulation. We found that the periodic component was composed of seven frequency bands that presented region-dependent and compound-dependent changes. The aperiodic component was also different between compounds and brain regions. Importantly, the parametrization into periodic and aperiodic components unveiled correlations between quantitative EEG and plasma concentrations of pharmacological compounds. MK-801 exposures were positively correlated with the slope of the aperiodic component. Concerning the periodic component, MK-801 exposures correlated negatively with the peak frequency of low-γ oscillations but positively with those of high-γ and high-frequency oscillations (HFOs). As for the power, θ and low-γ oscillations correlated negatively with MK-801, whereas mid-γ correlated positively. Diazepam correlated negatively with the knee of the aperiodic component, positively to ß and negatively to low-γ oscillatory power, and positively to the modal frequency of θ, low-γ, mid-γ, and high-γ. In conclusion, correlations between exposures and pharmacodynamic effects can be better-understood thanks to the parametrization of EEG into periodic and aperiodic components. Such parametrization could be key in functional biomarker discovery.