Neuronal Oscillations Research Articles

A memristive circuit for self-organized network topology formation based on guided axon growth

Circuit implementations of neuronal networks so far have been focusing on synaptic weight changes as network growth principles. Besides these weight changes, however, it is also useful to incorporate additional network growth principles such as guided axon growth and pruning. These allow for dynamical signal delays and a higher degree of self-organization, and can thus lead to novel circuit design principles. In this work we develop an ideal, bio-inspired electrical circuit mimicking growth and pruning controlled by guidance cues. The circuit is based on memristively coupled neuronal oscillators. As coupling element, we use memsensors consisting of a general sensor, two gradient sensors, and two memristors. The oscillators and memsensors are arranged in a grid structure, where oscillators and memsensors realize nodes and edges, respectively. This allows for arbitrary 2D growth scenarios with axon growth controlled by guidance cues. Simulation results show that the circuit successfully mimics a biological example in which two neurons initially grow towards two target neurons, where undesired connections are pruned later on.

Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis

The electrical activity of the neural processes involved in cognitive functions is captured in EEG signals, allowing the exploration of the integration and coordination of neuronal oscillations across multiple spatiotemporal scales. We have proposed a novel approach that combines the transformation of EEG signal into image sequences, considering cross-frequency phase synchronisation (CFS) dynamics involved in low-level auditory processing, with the development of a two-stage deep learning model for the detection of developmental dyslexia (DD). This deep learning model exploits spatial and temporal information preserved in the image sequences to find discriminative patterns of phase synchronisation over time achieving a balanced accuracy of up to 83%. This result supports the existence of differential brain synchronisation dynamics between typical and dyslexic seven-year-old readers. Furthermore, we have obtained interpretable representations using a novel feature mask to link the most relevant regions during classification with the cognitive processes attributed to normal reading and those corresponding to compensatory mechanisms found in dyslexia.Graphical

Mesenchymal Stem Cells Promote an Increase in Neuronal Oscillation via Glutamate Tonic Release

Mesenchymal stromal cells (MSCs) hold therapeutic potential for neurological disorders, but their impact on neuronal activity remains unclear. We investigated the effects of SB623 cells (Notch-1 intracellular domain-transfected MSCs) and parental MSCs on human induced pluripotent stem cell (iPSC)-derived neurons using multi-electrode arrays. SB623 cells significantly increased neuronal activity and oscillation in a dose-dependent manner, surpassing astrocytes in promoting network bursts. Strikingly, glutamatergic neurons showed a rapid increase in activity and bursts compared to GABAergic neurons, suggesting glutamate release from SB623 cells. We confirmed this by finding high glutamate levels in SB623 cell conditioned medium, which were reduced by glutaminase inhibition. Glutamate release was further implicated by the reduced excitability in co-cultures with astrocytes, known glutamate scavengers. Our findings reveal a novel mechanism for MSCs: promoting neuronal activity and network formation through tonic glutamate release, with potential implications for MSC-based therapies.

Application of HFO and scaling analysis of neuronal oscillations in the presurgical evaluation of focal epilepsy

PurposeTo explore the utility of high frequency oscillations (HFO) and long-range temporal correlations (LRTCs) in preoperative assessment of epilepsy. MethodsMEG ripples were detected in 59 drug-resistant epilepsy patients, comprising 5 with parietal lobe epilepsy (PLE), 21 with frontal lobe epilepsy (FLE), 14 with lateral temporal lobe epilepsy (LTLE), and 19 with mesial temporal lobe epilepsy (MTLE) to identify the epileptogenic zone (EZ). The results were compared with clinical MEG reports and resection area. Subsequently, LRTCs were quantified at the source-level by detrended fluctuation analysis (DFA) and life/waiting -time at 5 bands for 90 cerebral cortex regions. The brain regions with larger DFA exponents and standardized life-waiting biomarkers were compared with the resection results. ResultsCompared to MEG sensor-level data, ripple sources were more frequently localized within the resection area. Moreover, source-level analysis revealed a higher proportion of DFA exponents and life-waiting biomarkers with relatively higher rankings, primarily distributed within the resection area (p<0.01). Moreover, these two LRCT indices across five distinct frequency bands correlated with EZ. ConclusionHFO and source-level LRTCs are correlated with EZ. Integrating HFO and LRTCs may be an effective approach for presurgical evaluation of epilepsy.

Dissociation of attentional state and behavioral outcome using local field potentials.

Successful behavior depends on attentional state and other factors related to decision-making, which may modulate neuronal activity differently. Here, we investigated whether attentional state and behavioral outcome (i.e., whether a target is detected or missed) are distinguishable using the power and phase of local field potential (LFP) recorded bilaterally from area V4 of monkeys performing a cued visual attention task. To link each trial's outcome to pairwise measures of attention that are typically averaged across trials, we used several methods to obtain single-trial estimates of spike count correlation and phase consistency. Surprisingly, while attentional location was best discriminated using gamma and high-gamma power, behavioral outcome was best discriminated by alpha power and steady-state visually evoked potential. Power outperformed absolute phase in attentional/behavioral discriminability, although single-trial gamma phase consistency provided reasonably high attentional discriminability. Our results suggest a dissociation between the neuronal mechanisms that regulate attentional focus and behavioral outcome.

Clinical asymmetry in Parkinson’s disease is characterized by prevalence of subthalamic pause-burst neurons and alpha-beta oscillations

ObjectiveWe aimed to establish specific biomarkers of Parkinson’s disease (PD) by comparing activity of more affected (MA) and less affected (LA) subthalamic nucleus (STN) of patients with prominent clinical asymmetry. MethodsWe recorded single unit activity and local field potentials (LFP) of the STN during deep brain stimulation surgeries. Neuronal firing patterns and discharge rate, as well as oscillatory features of both single cells and LFP, were analyzed. ResultsWe observed notable differences in proportions of irregular-burst and pause-burst, but not tonic neurons, between the hemispheres. Oscillations of pause-burst neurons correlated significantly with the bradykinesia and rigidity scores of the corresponding hemibody. LFP derived from MA STN featured greater power in 12–15 Hz. ConclusionsOur results provide evidence that the increased proportion of units with prolonged pauses may be associated with PD. We also speculate that some of them may gain rhythmicity in the alpha-beta range in relation to hypokinetic symptoms, long-term disease, or both. SignificanceOur findings highlight the relation between specific oscillatory features of the STN, predominance of subthalamic pause-burst units and PD pathophysiology.

Mechanism of an Intrinsic Oscillation in Rat Geniculate Interneurons.

Depolarizing current injections produced a rhythmic bursting of action potentials - a bursting oscillation - in a set of local interneurons in the lateral geniculate nucleus (LGN) of rats. The current dynamics underlying this firing pattern have not been determined, though this cell type constitutes an important cellular component of thalamocortical circuitry, and contributes to both pathologic and non-pathologic brain states. We thus investigated the source of the bursting oscillation using pharmacological manipulations in LGN slices in vitro and in silico. 1. Selective blockade of calcium channel subtypes revealed that high-threshold calcium currents and contributed strongly to the oscillation. 2. Increased extracellular K+ concentration (decreased K+currents) eliminated the oscillation. 3. Selective blockade of K+ channel subtypes demonstrated that the calcium-sensitive potassium current ( ) was of primary importance. A morphologically simplified, multicompartment model of the thalamic interneuron characterized the oscillation as follows: 1. The low-threshold calcium current provided the strong initial burst characteristic of the oscillation. 2. Alternating fluxes through high-threshold calcium channels and then provided the continuing oscillation's burst and interburst periods respectively. This interplay between and contrasts with the current dynamics underlying oscillations in thalamocortical and reticularis neurons, which primarily involve and , or and respectively. These findings thus point to a novel electrophysiological mechanism for generating intrinsic oscillations in a major thalamic cell type. Because local interneurons can sculpt the behavior of thalamocortical circuits, these results suggest new targets for the manipulation of ascending thalamocortical network activity.

Differential effects of allopregnanolone and diazepam on social behavior through modulation of neural oscillation dynamics in basolateral amygdala and medial prefrontal cortex.

Effective treatments for major depressive disorder (MDD) have long been needed. One hypothesis for the mechanism of depression involves a decrease in neuroactive steroids such as allopregnanolone, an endogenous positive allosteric modulator of the γ-aminobutyric acid-gated chloride channel (GABAA) receptor. In our previous study, we discovered that allopregnanolone, not diazepam, exhibited antidepressant-like effects in the social interaction test (SIT) of social defeat stress (SDS) model mice. However, the dynamics of neuronal activity underlying the antidepressant-like effect remain unknown. In the current study, we conducted local field potentials (LFPs) recordings from the basolateral amygdala (BLA) and the medial prefrontal cortex (mPFC) during the SIT to elucidate the relationship between the antidepressant-like effect and neuronal oscillation. We discovered that allopregnanolone has antidepressant-like effects in the SIT of SDS model mice by decreasing intervals of repetitive social interaction (inter-event intervals), resulting in increase of total social interaction time. We also found that theta and beta oscillation increased in BLA at the onset of social interaction following administration of allopregnanolone, which differed from the effects of diazepam. Theta and beta power in BLA within the social interaction zone exhibited a positive correlation with interaction time. This increase of theta and beta power was negatively correlated with inter-event intervals. Regarding theta-band coordinated activity between the BLA and mPFC, theta power correlation decreased at the onset of social interaction with the administration of allopregnanolone. These findings suggest that theta activity in BLA following social interaction and the reduced theta-band coordinated activity between the BLA and mPFC are implicated in social interaction, which is one of the antidepressant behaviors. These differences in neural activity could elucidate the distinctive mechanism underlying antidepressant-like effects of neuroactive steroids, as opposed to benzodiazepines.

Adult-born granule cells modulate CA2 network activity during retrieval of developmental memories of the mother.

Adult-born granule cells (abGCs) project to the CA2 region of the hippocampus, but it remains unknown how this circuit affects behavioral function. Here, we show that abGC input to the CA2 of adult mice is involved in the retrieval of remote developmental memories of the mother. Ablation of abGCs impaired the ability to discriminate between a caregiving mother and a novel mother, and this ability returned after abGCs were regenerated. Chemogenetic inhibition of projections from abGCs to the CA2 also temporarily prevented the retrieval of remote mother memories. These findings were observed when abGCs were inhibited at 4-6 weeks old, but not when they were inhibited at 10-12 weeks old. We also found that abGCs are necessary for differentiating features of CA2 network activity, including theta-gamma coupling and sharp wave ripples, in response to novel versus familiar social stimuli. Taken together, these findings suggest that abGCs are necessary for neuronal oscillations associated with discriminating between social stimuli, thus enabling retrieval of remote developmental memories of the mother by their adult offspring.

Adult-born granule cells modulate CA2 network activity during retrieval of developmental memories of the mother

Adult-born granule cells (abGCs) project to the CA2 region of the hippocampus, but it remains unknown how this circuit affects behavioral function. Here, we show that abGC input to the CA2 of adult mice is involved in the retrieval of remote developmental memories of the mother. Ablation of abGCs impaired the ability to discriminate between a caregiving mother and a novel mother, and this ability returned after abGCs were regenerated. Chemogenetic inhibition of projections from abGCs to the CA2 also temporarily prevented the retrieval of remote mother memories. These findings were observed when abGCs were inhibited at 4–6 weeks old, but not when they were inhibited at 10–12 weeks old. We also found that abGCs are necessary for differentiating features of CA2 network activity, including theta-gamma coupling and sharp wave ripples, in response to novel versus familiar social stimuli. Taken together, these findings suggest that abGCs are necessary for neuronal oscillations associated with discriminating between social stimuli, thus enabling retrieval of remote developmental memories of the mother by their adult offspring.

Extensive soma-soma plate-like contact sites (ephapses) connect suprachiasmatic nucleus neurons.

The hypothalamic suprachiasmatic nucleus (SCN) is the central pacemaker for mammalian circadian rhythms. As such, this ensemble of cell-autonomous neuronal oscillators with divergent periods must maintain coordinated oscillations. To investigate ultrastructural features enabling such synchronization, 805 coronal ultrathin sections of mouse SCN tissue were imaged with electron microscopy and aligned into a volumetric stack, from which selected neurons within the SCN core were reconstructed insilico. We found that clustered SCN core neurons were physically connected to each other via multiple large soma-to-soma plate-like contacts. In some cases, a sliver of a glial process was interleaved. These contacts were large, covering on average ∼21% of apposing neuronal somata. It is possible that contacts may be the electrophysiological substrate for synchronization between SCN neurons. Such plate-like contacts may explain why the synchronization of SCN neurons is maintained even when chemical synaptic transmission or electrical synaptic transmission via gap junctions is blocked. Such ephaptic contact-mediated synchronization among nearby neurons may therefore contribute to the wave-like oscillations of circadian core clock genes and calcium signals observed in the SCN.

Serotonin modulates infraslow oscillation in the dentate gyrus during Non-REM sleep.

Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with electrophysiological and optical imaging tools during sleep-wake cycles. We found that the activity of major glutamatergic cell populations in the DG is organized into in-fraslow oscillations (0.01 - 0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep. Further experiments revealed that the infraslow oscillation in the DG is modulated by rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by 5-HT1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.

Congenital deafness reduces alpha-gamma cross-frequency coupling in the auditory cortex

Neurons within a neuronal network can be grouped by bottom-up and top-down influences using synchrony in neuronal oscillations. This creates the representation of perceptual objects from sensory features. Oscillatory activity can be differentiated into stimulus-phase-locked (evoked) and non-phase-locked (induced). The former is mainly determined by sensory input, the latter by higher-level (cortical) processing. Effects of auditory deprivation on cortical oscillations have been studied in congenitally deaf cats (CDCs) using cochlear implant (CI) stimulation. CI-induced alpha, beta, and gamma activity were compromised in the auditory cortex of CDCs. Furthermore, top-down information flow between secondary and primary auditory areas in hearing cats, conveyed by induced alpha oscillations, was lost in CDCs. Here we used the matching pursuit algorithm to assess components of such oscillatory activity in local field potentials recorded in primary field A1. Additionally to the loss of induced alpha oscillations, we also found a loss of evoked theta activity in CDCs. The loss of theta and alpha activity in CDCs can be directly related to reduced high-frequency (gamma-band) activity due to cross-frequency coupling. Here we quantified such cross-frequency coupling in adult 1) hearing-experienced, acoustically stimulated cats (aHCs), 2) hearing-experienced cats following acute pharmacological deafening and subsequent CIs, thus in electrically stimulated cats (eHCs), and 3) electrically stimulated CDCs. We found significant cross-frequency coupling in all animal groups in > 70% of auditory-responsive sites. The predominant coupling in aHCs and eHCs was between theta/alpha phase and gamma power. In CDCs such coupling was lost and replaced by alpha oscillations coupling to delta/theta phase. Thus, alpha/theta oscillations synchronize high-frequency gamma activity only in hearing-experienced cats. The absence of induced alpha and theta oscillations contributes to the loss of induced gamma power in CDCs, thereby signifying impaired local network activity.

Assessment of the excitation-inhibition ratio in the Fmr1 KO2 mouse using neuronal oscillation dynamics.

In vitro and ex vivo studies have shown consistent indications of hyperexcitability in the Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mouse model of autism spectrum disorder. We recently introduced a method to quantify network-level functional excitation-inhibition ratio from the neuronal oscillations. Here, we used this measure to study whether the implicated synaptic excitation-inhibition disturbances translate to disturbances in network physiology in the Fragile X Messenger Ribonucleoprotein 1 (Fmr1) gene knockout model. Vigilance-state scoring was used to extract segments of inactive wakefulness as an equivalent behavioral condition to the human resting-state and, subsequently, we performed high-frequency resolution analysis of the functional excitation-inhibition biomarker, long-range temporal correlations, and spectral power. We corroborated earlier studies showing increased high-frequency power in Fragile X Messenger Ribonucleoprotein 1 (Fmr1) knockout mice. Long-range temporal correlations were higher in the gamma frequency ranges. Contrary to expectations, functional excitation-inhibition was lower in the knockout mice in high frequency ranges, suggesting more inhibition-dominated networks. Exposure to the Gamma-aminobutyric acid (GABA)-agonist clonazepam decreased the functional excitation-inhibition in both genotypes, confirming that increasing inhibitory tone results in a reduction of functional excitation-inhibition. In addition, clonazepam decreased electroencephalogram power and increased long-range temporal correlations in both genotypes. These findings show applicability of these new resting-state electroencephalogram biomarkers to animal for translational studies and allow investigation of the effects of lower-level disturbances in excitation-inhibition balance.

Optogenetic stimulation of medial septal glutamatergic neurons modulates theta-gamma coupling in the hippocampus

Hippocampal cross-frequency theta-gamma coupling (TGC) is a basic mechanism for information processing, retrieval, and consolidation of long-term and working memory. While the role of entorhinal afferents in the modulation of hippocampal TGC is widely accepted, the influence of other main input to the hippocampus, from the medial septal area (MSA, the pacemaker of the hippocampal theta rhythm) is poorly understood. Optogenetics allows us to explore how different neuronal populations of septohippocampal circuits control neuronal oscillations in vivo. Rhythmic activation of septal glutamatergic neurons has been shown to drive hippocampal theta oscillations, but the role of these neuronal populations in information processing during theta activation has remained unclear. Here we investigated the influence of phasic activation of MSA glutamatergic neurons expressing channelrhodopsin II on theta-gamma coupling in the hippocampus. During the experiment, local field potentials of MSA and hippocampus of freely behaving mice were modulated by 470 nm light flashes with theta frequency (2–10) Hz. It was shown that both the power and the strength of modulation of gamma rhythm nested on hippocampal theta waves depend on the frequency of stimulation. The modulation of the amplitude of slow gamma rhythm (30–50 Hz) prevailed over modulation of fast gamma (55–100 Hz) during flash trains and the observed effects were specific for theta stimulation of MSA. We discuss the possibility that phasic depolarization of septal glutamatergic neurons controls theta-gamma coupling in the hippocampus and plays a role in memory retrieval and consolidation.

Learning spiking neuronal networks with artificial neural networks: neural oscillations.

First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be hard to build and expensive to simulate for complex living systems. On the other hand, modern data-driven methods thrive at modeling many types of high-dimensional and noisy data. Still, the training and interpretation of these data-driven models remain challenging. Here, we combine the two types of methods to model stochastic neuronal network oscillations. Specifically, we develop a class of artificial neural networks to provide faithful surrogates to the high-dimensional, nonlinear oscillatory dynamics produced by a spiking neuronal network model. Furthermore, when the training data set is enlarged within a range of parameter choices, the artificial neural networks become generalizable to these parameters, covering cases in distinctly different dynamical regimes. In all, our work opens a new avenue for modeling complex neuronal network dynamics with artificial neural networks.

Phase-amplitude coupling detection and analysis of human 2-dimensional neural cultures in multi-well microelectrode array in vitro

BackgroundHuman induced pluripotent stem cell (hiPSC)- derived neurons offer the possibility of studying human-specific neuronal behaviors in physiologic and pathologic states in vitro. It is unclear whether cultured neurons can achieve the fundamental network behaviors required to process information in the brain. Investigating neuronal oscillations and their interactions, as occurs in cross-frequency coupling (CFC), addresses this question. New methodsWe examined whether networks of two-dimensional (2D) cultured hiPSC-derived cortical neurons grown with hiPSC-derived astrocytes on microelectrode array plates recapitulate the CFC that is present in vivo. We employed the modulation index method for detecting phase-amplitude coupling (PAC) and used offline spike sorting to analyze the contribution of single neuron spiking to network behavior. ResultsWe found that PAC is present, the degree of PAC is specific to network structure, and it is modulated by external stimulation with bicuculline administration. Modulation of PAC is not driven by single neurons, but by network-level interactions. Comparison with existing methodsPAC has been demonstrated in multiple regions of the human cortex as well as in organoids. This is the first report of analysis demonstrating the presence of coupling in 2D cultures. ConclusionCFC in the form of PAC analysis explores communication and integration between groups of neurons and dynamical changes across networks. In vitro PAC analysis has the potential to elucidate the underlying mechanisms as well as capture the effects of chemical, electrical, or ultrasound stimulation; providing insight into modulation of neural networks to treat nervous system disorders in vivo.

Optically Tunable Electrical Oscillations in Oxide-Based Memristors for Neuromorphic Computing.

The application of hardware-based neural networks can be enhanced by integrating sensory neurons and synapses that enable direct input from external stimuli. This work reports direct optical control of an oscillatory neuron based on volatile threshold switching in V3O5. The devices exhibit electroforming-free operation with switching parameters that can be tuned by optical illumination. Using temperature-dependent electrical measurements, conductive atomic force microscopy (C-AFM), in situ thermal imaging, and lumped element modelling, it is shown that the changes in switching parameters, including threshold and hold voltages, arise from overall conductivity increase of the oxide film due to the contribution of both photoconductive and bolometric characteristics of V3O5, which eventually affects the oscillation dynamics. Furthermore, V3O5 is identified as a new bolometric material with a temperature coefficient of resistance (TCR) as high as -4.6% K-1 at 423 K. The utility of these devicesis illustrated by demonstrating in-sensor reservoir computing with reduced computational effort and an optical encoding layer for spiking neural network (SNN), respectively, using a simulated array of devices.

Highly biomimetic spiking neuron using SiGe heterojunction bipolar transistors for energy-efficient neuromorphic systems

We demonstrate a highly biomimetic spiking neuron capable of fast and energy-efficient neuronal oscillation dynamics. Our simple neuron circuit is constructed using silicon–germanium heterojunction based bipolar transistors (HBTs) with nanowire structure. The HBT has a hysteresis window with steep switching characteristics and high current margin in the low voltage range, which enables a high spiking frequency (~ 245 kHz) with low energy consumption (≤ 1.37 pJ/spike). Also, gated structure achieves a stable balance in the activity of the neural system by incorporating both excitatory and inhibitory signal. Furthermore, inhibition of multiple strengths can be realized by adjusting the integration time according to the amplitude of the inhibitory signal. In addition, the spiking frequency can be tuned by mutually controlling the hysteresis window in the HBTs. These results ensure the sparse activity and homeostasis of neural networks.

Delineating mechanisms underlying parvalbumin neuron impairment in different neurological and neurodegenerative disorders: the emerging role of mitochondrial dysfunction.

Given the current paucity of effective treatments in many neurological disorders, delineating pathophysiological mechanisms among the major psychiatric and neurodegenerative diseases may fuel the development of novel, potent treatments that target shared pathways. Recent evidence suggests that various pathological processes, including bioenergetic failure in mitochondria, can perturb the function of fast-spiking, parvalbumin-positive neurons (PV+). These inhibitory neurons critically influence local circuit regulation, the generation of neuronal network oscillations and complex brain functioning. Here, we survey PV+ cell vulnerability in the major neuropsychiatric, and neurodegenerative diseases and review associated cellular and molecular pathophysiological alterations purported to underlie disease aetiology.