Local coherence oscillations in the EEG during development in the fetal baboon

The numerous γ-aminobutyric acid type A receptor (GABAAR) subtypes are differentially expressed and mediate distinct functions at neuronal level. In this study we have investigated GABAAR-mediated modulation of the spontaneous activity patterns of primary neuronal networks from murine frontal cortex by characterizing the effects induced by a wide selection of pharmacological tools at a plethora of activity parameters in microelectrode array (MEA) recordings. The basic characteristics of the primary cortical neurons used in the recordings were studied in some detail, and the expression levels of various GABAAR subunits were investigated by western blotting and RT-qPCR. In the MEA recordings, the pan-GABAAR agonist muscimol and the GABABR agonist baclofen were observed to mediate phenotypically distinct changes in cortical network activity. Selective augmentation of αβγ GABAAR signaling by diazepam and of δ-containing GABAAR (δ-GABAAR) signaling by DS1 produced pronounced changes in the majority of the activity parameters, both drugs mediating similar patterns of activity changes as muscimol. The apparent importance of δ-GABAAR signaling for network activity was largely corroborated by the effects induced by the functionally selective δ-GABAAR agonists THIP and Thio-THIP, whereas the δ-GABAAR selective potentiator DS2 only mediated modest effects on network activity, even when co-applied with low THIP concentrations. Interestingly, diazepam exhibited dramatically right-shifted concentration-response relationships at many of the activity parameters when co-applied with a trace concentration of DS1 compared to when applied alone. In contrast, the potencies and efficacies displayed by DS1 at the networks were not substantially altered by the concomitant presence of diazepam. In conclusion, the holistic nature of the information extractable from the MEA recordings offers interesting insights into the contributions of various GABAAR subtypes/subgroups to cortical network activity and the putative functional interplay between these receptors in these neurons.

Event Abstract Back to Event Effects of paroksetine administration on cortical EEG of elderly rats Bilge Özerman1*, A. Nurten2, U. Dalanay3, I. Özen2, S. Karamürsel4 and I. Kara2 1 Department of Biophysics, Istanbul Medical Faculty, Istanbul University, Turkey 2 Department of Neuroscience, Institute for Experimental Medical Research, Istanbul University, Turkey 3 Berlin Medical University, Charite, Germany 4 Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, Turkey Paroxetine, which is a selective serotonin reuptake inhibitor (SSRI), was used for treatment of depression. We aimed to study the effect of paroxetine on cortical electrical activity of elderly rats, as the age-related serotonin reduction occurs in cerebral cortex. Elderly Wistar albino rats (n=9) were anaesthetized with thiopental (50 mg/kg i.p.). Eight pairs of epidural electrodes were positioned symmetrically on both hemispheres to the medial and frontal localization of pre- and post- frontoparietal and occipital regions. A reference electrode was placed above the cerebellum. The following week of the operation control EEG recordings carried out by Neuroscan during 15 min for each animal. Records were repeated at the end of three weeks of paroxetine (4 mg/kg i.p.) administration. Subsequent continuous EEG recordings were compared as frequency spectra with the basal EEG value of the animal. EEG records were divided into 2 seconds epochs and analyzed by averaged frequency spectra (0-48 Hz). Moving averages were calculated for five points. A series of point to point two tail paired Student's t-test was applied for the each channel. Topographic maps of rats were constructed from the grand average of amplitude spectra. The frequency band of 0.5- 4 Hz was expressed as delta, 4-8 Hz as theta, 8-11 Hz as alpha1, 11-14 Hz as alpha2, 14-25 Hz as beta1, 25-35 Hz as beta2 and 35-45 Hz as gamma. Following three weeks of paroxetine administration, the amplitudes of delta, alpha2, beta1 and gamma bands were significantly altered (p<0.05). The increment in the amplitude was determined for delta frequency band of medial cortical localizations in both hemispheres and for gamma frequency band of medial postfrontal and lateral frontal cortex in right hemisphere with localizations excluded frontal and medial postfrontal cortex in left hemisphere. The decrement in the amplitude of alpha2 and beta1 bands was identified in all cortical localizations. The frequency analysis of continuous EEG recordings from 16 channels of elderly Wistar rats was showed that paroxetine administration of three weeks caused significant alterations in cortical activity. These findings guided this study for the next step to carry on with the analysis of evoked potentials in order to elucidate the cognitive effect of paroxetine administration. Conference: 10th International Conference on Cognitive Neuroscience, Bodrum, Turkey, 1 Sep - 5 Sep, 2008. Presentation Type: Poster Presentation Topic: Animal Models of Cognition Citation: Özerman B, Nurten A, Dalanay U, Özen I, Karamürsel S and Kara I (2008). Effects of paroksetine administration on cortical EEG of elderly rats. Conference Abstract: 10th International Conference on Cognitive Neuroscience. doi: 10.3389/conf.neuro.09.2009.01.079 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 01 Dec 2008; Published Online: 01 Dec 2008. * Correspondence: Bilge Özerman, Department of Biophysics, Istanbul Medical Faculty, Istanbul University, Istanbul, Turkey, bilgeozerman@hotmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Bilge Özerman A. Nurten U. Dalanay I. Özen S. Karamürsel I. Kara Google Bilge Özerman A. Nurten U. Dalanay I. Özen S. Karamürsel I. Kara Google Scholar Bilge Özerman A. Nurten U. Dalanay I. Özen S. Karamürsel I. Kara PubMed Bilge Özerman A. Nurten U. Dalanay I. Özen S. Karamürsel I. Kara Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Variability-dominated auditory cortical dysfunction and targeted VNS modulation in a Mecp2+/- model of Rett syndrome.

Traumatic brain injury (TBI) remains the leading cause of death and disability worldwide with no existing effective treatment. The early phase after TBI induction triggers numerous molecular cascades to regulate adaptive processes and cortical network activity. Kinases play a particularly prominent role in modifying peptide substrates, which include ion channels, receptors, transcription factors and inflammatory mediators. This study aimed to better understand the post-injury serine/threonine kinome; (1) Which kinases conduct phosphorylation-induced alterations of target peptides following unilateral TBI in mouse cortex? (2) How do these kinases effectuate pathological network hyperexcitability, which has detrimental long-term outcomes? We used a serine/threonine kinase assay at 4 h, 24 h and 72 h post-TBI to identify hyper-/hypo-active/phosphorylated kinases and peptides in the ipsilateral and contralateral cortical hemispheres relative to sham-operated controls. We pharmacologically mimicked the changes seen in ERK1/2 and PKC kinase activity, and using microelectrode array recordings we explored their significant electrophysiological implications on spontaneous and evoked cortical activity. We then used these findings to manipulate key kinase activity changes at 24 h post-TBI to rescue the hyperexcitability that is seen in the contralateral cortical network at this timepoint back to sham level. The contribution of specific downstream peptide target channel/receptor subunits was also shown. We conclude that volatile kinase activity has potent implications on cortical network activity after the injury and that these kinases and/or their peptide substrates should be more seriously considered as therapeutic targets for the clinical treatment of TBI.

The characterization of the subthreshold, ongoing activity in cortical neurons has been the focus of numerous studies. This activity, described as spontaneous slow waves in membrane potential, has been observed in a span of species in diverse cortical and subcortical areas. We here characterized membrane potential fluctuations in motor and the frontal association cortices cortical neurons of ketamine–xylazine anesthetized rats. We recorded from 95 neurons from a range of cortical depths to unravel the network and cellular mechanisms that shape the subthreshold ongoing spontaneous activity of these neurons. We define a unitary event that generates the subthreshold ongoing activity: giant synaptic potentials (GSPs). These events have a duration of 87 ± 50 ms and an amplitude of 19 ± 6.4 mV. They occur at a frequency of 3.7 ± 0.8 Hz and involve an increase in conductance change of 22 ± 21%. GSPs are mainly due to excitatory activity that occurs throughout all cortical layers, unaffected by the intrinsic properties of the cells. Indeed, blocking the GABAA receptors, a procedure that had a profound effect on cortical activity, did not alter these unitary events. We propose that this unitary event is composed of individual, excitatory synaptic potentials that appear at different levels of synchrony and that the level of synchrony determines the shape of the subthreshold activity.

Event Abstract Back to Event Wireless telemetry as an ideal tool for continuous intrahippocampal EEG recording in chronic epilepsy mouse models Yana Van Den Herrewegen1*, An Buckinx1*, Gino De Smet1, Ilse J. Smolders1 and Dimitri De Bundel1 1 Vrije Universiteit Brussel, Experimental Pharmacology (EFAR), cluster Neurosciences, Belgium Tethered recording systems are routinely used as a method for long-term continuous EEG monitoring in animal models of epilepsy. Nevertheless, tethered systems display some disadvantages when chronically used in mice, in some cases even compromising experiments and behavioral follow-up of the mice. Therefore, wireless telemetry systems are increasingly being used as an alternative method to precisely measure biopotentials in the rodent brain. As EEG recordings are the most powerful read-outs in animal models of epilepsy, we evaluated the use of wireless radio-telemetry in the intrahippocampal post-status epilepticus kainic acid model, an established mouse model for studying temporal lobe epilepsy and epileptogenesis. Via intraperitoneal implantation of a radiofrequency transmitter (ETA-F10, DSI) and electrodes positioned in the hippocampus, we were able to record intrahippocampal signals for up to two months. We could clearly monitor the epileptic activity during the status epilepticus, followed by a short latent period and the subsequent occurrence of the typical spontaneous epileptic discharges. This study discusses the advantages of telemetric EEG recordings and strategies to maximize the signal-to-noise ratio in order to obtain high-quality deep-brain EEG recordings. In conclusion, wireless telemetry systems are a valuable EEG monitoring method in the intrahippocampal kainic acid mouse model and other models of chronic epilepsy in mice. References Bouilleret V, Ridoux V, Depaulis A, et al. Recurrent seizures and hippocampal sclerosis following intrahippocampal kainate injection in adult mice: electroencephalography, histopathology and synaptic reorganization similar to mesial temporal lobe epilepsy. Neuroscience. 1999; Mar;89(3):717-29. Duveau V, Pouyatos B, Bressand K, et al. Differential Effects of Antiepileptic Drugs on Focal Seizures in the Intrahippocampal Kainate Mouse Model of Mesial Temporal Lobe Epilepsy. CNS Neuroscience & Therapeutics: CNS Neurosci Ther. 2016;(22):497-50. doi: 10.1111/cns.12523 Lundt A, Wormuth C, Siwek ME, et al. EEG Radiotelemetry in Small Laboratory Rodents: A Powerful State-of-the Art Approach in Neuropsychiatric, Neurodegenerative, and Epilepsy Research. Neural Plasticity. 2016;2016:8213878. doi:10.1155/2016/8213878. Twele F, Tollner K, Bankstahl M, Loscher W, et al. The effects of carbamazepine in the intrahippocampal kainate model of temporal lobe epilepsy depend on seizure definition and mouse strain. Epilepsia Open, 2016; 1(1):45–60,. doi: 10.1002/epi4.2 Zayachkivsky A, Lehmkuhle MJ, Dudek FE. Long-term Continuous EEG Monitoring in Small Rodent Models of Human Disease Using the Epoch Wireless Transmitter System. Journal of Visualized Experiments : JoVE. 2015;(101):52554. doi:10.3791/52554. Keywords: wireless radio-telemetry, EEG, Epilepsy, Temporal Lobe, mouse models, Seizures Conference: 12th National Congress of the Belgian Society for Neuroscience, Gent, Belgium, 22 May - 22 May, 2017. Presentation Type: Poster Presentation Topic: Novel Methods and Technology Development Citation: Van Den Herrewegen Y, Buckinx A, De Smet G, Smolders IJ and De Bundel D (2019). Wireless telemetry as an ideal tool for continuous intrahippocampal EEG recording in chronic epilepsy mouse models. Front. Neurosci. Conference Abstract: 12th National Congress of the Belgian Society for Neuroscience. doi: 10.3389/conf.fnins.2017.94.00001 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 02 May 2017; Published Online: 25 Jan 2019. * Correspondence: Miss. Yana Van Den Herrewegen, Vrije Universiteit Brussel, Experimental Pharmacology (EFAR), cluster Neurosciences, Brussels, 1090, Belgium, yana.van.den.herrewegen@vub.ac.be Miss. An Buckinx, Vrije Universiteit Brussel, Experimental Pharmacology (EFAR), cluster Neurosciences, Brussels, 1090, Belgium, an.buckinx@vub.be Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Yana Van Den Herrewegen An Buckinx Gino De Smet Ilse J Smolders Dimitri De Bundel Google Yana Van Den Herrewegen An Buckinx Gino De Smet Ilse J Smolders Dimitri De Bundel Google Scholar Yana Van Den Herrewegen An Buckinx Gino De Smet Ilse J Smolders Dimitri De Bundel PubMed Yana Van Den Herrewegen An Buckinx Gino De Smet Ilse J Smolders Dimitri De Bundel Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Introduction The impact of EEG referencing on sleep oscillations, such as spindles and slow oscillations, is largely overlooked across studies. While it is recognized that a topographic head plot of EEG activity does not reflect the true location of the underlying cortical activity, spatial distributions, as well as spectral properties and morphology of EEG oscillations can change dramatically as a function of referencing scheme. It is therefore vital to understand the impact of referencing when drawing inferences about the nature of EEG sleep oscillations. In this study, we use MRI structural data to construct subject-specific forward models of EEG signals. Using these models, we can simulate cortical activity and observe its true representation on the scalp. In particular, we simulate spindles and slow wave oscillations and examine how referencing affects topography, spectral power, and phase of oscillations. Methods High-density EEG (Brain Vision, 64-channel) polysomnography was performed on 9 healthy young subjects. 3T structural MRI scans were acquired and forward models were built in MNE-Python using 3-shell Boundary Element Models (BEM) based on individual anatomical details processed with Freesurfer. Simulations of various sleep spindle and slow oscillation dynamics were projected to the sensor space. Different referencing schemes (common average, Laplacian, linked-mastoid) were then applied to the experimental and simulated data and analyzed for effects on time-frequency characteristics of sleep oscillations. Results Analyses of experimental data showed distinct reference-based differences in topographical distribution of spectral power and phase of oscillations. Simulated data revealed many scenarios in which the spatial distribution of activity the EEG sensor space poorly represented the true location of the underlying source activity. Moreover, there were alterations to the spatial spread and envelope form of sleep spindle events under different referencing schemes despite from identical source activities. Conclusion This study shows that spindle and slow oscillation activity is highly variable across referencing schemes and that EEG topographical plots on the scalp may poorly represent cortical activity locations. It is thus vital to consider the choice of referencing when quantifying characteristics of sleep EEG oscillations. Support This work was supported by R01 NS-096177.

Irregular ongoing activity in cortical networks is often modeled as arising from recurrent connectivity. Yet it remains unclear to what extent its presence corrupts sensory signal transmission and network computational capabilities. In a recurrent cortical-like network, we have determined the activity patterns that are better transmitted and self-sustained by the network. We show that reproducible spiking and subthreshold dynamics can be triggered if the statistics of the imposed external drive are consistent with patterns previously seen in the ongoing activity. A subset of neurons in the network, constrained to replay temporal pattern segments extracted from the recorded ongoing activity of the same network, reliably drives the remaining, free-running neurons to call the rest of the pattern. Comparison with surrogate Poisson patterns indicates that the efficiency of the recall and completion process depends on the similarity between the statistical properties of the input with previous ongoing activity The reliability of evoked dynamics in recurrent networks is thus dependent on the stimulus used, and we propose that the similarity between spontaneous and evoked activity in sensory cortical areas could be a signature of efficient transmission and propagation across cortical networks.

It has been argued that coupling among the neural signals activated by a visual object supports binding of local features into a coherent object perception. During visual stimulation by a grating texture we studied functional coupling by calculating spectral coherence among pairs of signals recorded in the striate cortex of awake monkeys. Multiple unit activity (MUA) and local field potentials (LFP, 1-140 Hz) were extracted from seven parallel broad band recordings. Spectral coherence was dominated by high-frequency oscillations in the range 35-50 Hz and often by additional low-frequency components (0-12 Hz). Functional coupling among separate cortical sites was more stimulus specific for MUA than for LFP: MUA coherence at high and low frequencies depended highly significantly on: (i) the similarity of the preferred orientations at the two sites - the more similar the higher the coherence; (ii) the orientation of the stimulus grating - with highest coherence at half angle between the preferred orientations at the two sites; (iii) cortical distance - coherence decreases to noise levels at approximately 3 mm (MUA) and 6 mm (LFP). Coherence of fast oscillations did not depend on the degree of coaxiality of the orientation-sensitive receptive fields, whereas low frequencies showed significant dependency. This indicates that different frequency components can engage different coupling networks in the striate cortex which probably support different coding tasks. Changes in average oscillation frequency with stimulus orientation were highly significant for fast oscillations while there was no dependency for low frequencies. Finally, stimulus-related spectral power and coherence of fast oscillations were considerably higher than of low frequency components. Fast oscillations may therefore contribute more to feature binding and coding of object continuity than low-frequency components, at least for texture surfaces as analysed here.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired communication, abnormal social interactions, and restricted, repetitive behaviors. Pathogenic mutations in UBE3B result in neurodevelopmental disease, including intellectual disability, lack of speech, and ASD. UBE3B is an E3 ubiquitin ligase that tags substrate proteins with ubiquitin, marking them for proteasomal degradation. The ubiquitin-proteasome system (UPS) regulates several signaling pathways critical for neurodevelopment, including neurogenesis and synaptogenesis, and mutations in various UPS genes have been identified in ASD and related neurodevelopmental disorders. To investigate the function of UBE3B in the brain and how its disruption gives rise to neurodevelopmental abnormalities, we generated a central nervous system-specific conditional Ube3b knockout (cKO) mouse model and evaluated the resulting neurobehavioral phenotypes. We found that Ube3b cKO mice exhibit severe deficits in vocalization, social behavior, learning and memory, and motor skills. Assessment of invivo neuronal phenotypes revealed defects in dendritic morphogenesis, reduced excitatory synapse density, diminished spontaneous cortical circuit activity, decreased AMPA receptor surface expression, and hyperexcitability of excitatory cortical neurons. Using quantitative proteomics, we profiled the proteome and ubiquitome of neural stem cells and identified 116 proteins that exhibited increased protein levels and reduced ubiquitination following loss of UBE3B. These proteins were highly enriched for ones involved in synaptic processes, and we confirmed interaction of UBE3B with several key synaptic proteins, including ATP1A1, DOCK7, NLGN2, and STX12. Collectively, our findings identify a role for UBE3B in regulating social, cognitive, and motor functions, and neuronal morphogenesis and activity by fine-tuning the synaptic proteome.

Event Abstract Back to Event Searching for Autocoherence in the Cortical Network with a Time-Frequency Analysis of the Local Field Potential Samuel P. Burns1, 2*, Robert M. Shapley2, Michael J. Shel1 and Dajun Xing2 1 Courant Institute of Mathematical Sciences, United States 2 New York University, United States Elevated gamma-band activity in the power spectrum of recorded local field potentials (LFP) is a phenomenon that is found in many regions of the brain. The mechanisms that generate this gamma-band activity remain unexplained. In this study we analyze LFP measurements recorded from macaque V1 where visual stimulation evokes a noisy response with peak spectral power in the gamma-band near 40Hz. We are seeking to understand the underlying neural mechanisms that generate gamma-band spectral peaks in V1 cortex. Modeling studies of neuronal networks of inhibitory neurons, and with both inhibitory and excitatory neurons, have found that neurons in these networks may exhibit synchronized spiking or synchronized membrane potentials that give rise to deterministic, harmonic network oscillations in the gamma-band. That such temporally coherent oscillations underlie the experimentally observed gamma-band peak, we refer to as the coherent oscillator hypothesis. To test this hypothesis, we have developed a specialized time series analysis technique to analyze the coherence of the temporal phase content of a signal. This technique uses the continuous Gabor transform (CGT; Mallat 2006) to investigate a signal at each temporal frequency. Using our CGT technique, we formulate a statistical test to compare the coherent oscillator hypothesis against the measurements of LFP in vivo in macaque V1 cortex. In short, the data do not support the coherent oscillator hypothesis. Our interpretation is that the source of the gamma-band spectral peak is a signal of a more stochastic nature, for instance, arising from a resonant network partly driven by random inputs. Conference: Bernstein Symposium 2008, Munich, Germany, 8 Oct - 10 Oct, 2008. Presentation Type: Poster Presentation Topic: All Abstracts Citation: Burns SP, Shapley RM, Shel MJ and Xing D (2008). Searching for Autocoherence in the Cortical Network with a Time-Frequency Analysis of the Local Field Potential. Front. Comput. Neurosci. Conference Abstract: Bernstein Symposium 2008. doi: 10.3389/conf.neuro.10.2008.01.036 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 13 Nov 2008; Published Online: 13 Nov 2008. * Correspondence: Samuel P Burns, Courant Institute of Mathematical Sciences, New York, United States, sburns@cims.nyu.edu Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Samuel P Burns Robert M Shapley Michael J Shel Dajun Xing Google Samuel P Burns Robert M Shapley Michael J Shel Dajun Xing Google Scholar Samuel P Burns Robert M Shapley Michael J Shel Dajun Xing PubMed Samuel P Burns Robert M Shapley Michael J Shel Dajun Xing Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking often coincided with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.

Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.

Recent advances in brain-computer interface (BCI) technologies have shown the feasibility of neural decoding for both users' gait intent and continuous kinematics. However, the cortical adaptation and the dynamics of cortical involvement in human upright walking with a closed-loop BCI in virtual environment (VE) have yet to be demonstrated. To address explore this possibility, we designed a closed-loop BCI to allow users to control a virtual avatar to walk using their encephalography (EEG). Delta band EEG (0.1–3 Hz) was used as the main feature in prediction. Our results demonstrate the feasibility of using a closed-loop BCI to learn to control a walking avatar. The average decoding accuracies (Pearson's r values) across all subjects increased from (Hip: 0.18 ± 0.31; Knee: 0.23 ± 0.33; Ankle: 0.14 ± 0.22) on Day 1 to (Hip: 0.40 ± 0.24; Knee: 0.55 ± 0.20; Ankle: 0.29 ± 0.22) on Day 8. Source localization revealed significant differences in cortical network activity between walking with and without closed-loop BCI control of the virtual avatar. This current study demonstrates the feasibility of using a closed-loop EEG-based BCI-VR to trigger cortical adaptation, promoting cortical involvement, and monitoring cortical activity from non-invasive EEG. Our system may be relevant for neurological gait rehabilitation as a clinical tool for post-stroke physical training and clinical assessment.

Predicting early recovery of consciousness after cardiac arrest supported by quantitative electroencephalography