Contributions of diverse excitatory and inhibitory neurons to recurrent network activity in cerebral cortex

Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer

OBJECTIVE

To confirm and investigate why pathological high-frequency oscillations (pHFOs), including ripples (80-200 Hz) and fast ripples (200-600 Hz), are generated during the UP-DOWN transition of the slow wave and if information transmission mediated by ripple temporal coupling is disrupted in the seizure-onset zone (SOZ).

METHODS

We isolated 217 total units from 175.95 intracranial electroencephalography (iEEG) contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the SOZ, HFOs and associated action potentials (APs) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross-correlograms.

RESULTS

At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p < < .001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p < < .001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d = .11-.83) and fast ripples (d = .36-.90) at the UP-DOWN transition (p < .05 f.d.r. corrected), respectively. By comparison, also in the SOZ, 6.6% (d = .14-.30) and 8.5% (d = .33-.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows that ripple and fast ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by >50% in the SOZ compared to the non-SOZ (N = 3).

SIGNIFICANCE

The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. Ripple temporal correlations across brain regions may be important in memory consolidation and are disrupted in the SOZ, perhaps by pHFO generation.

Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible (≈ 0 mV $ \approx 0{\mathrm{\;mV}}$ ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

Sleep and wake in a model of the thalamocortical system with Martinotti cells

The mechanisms leading to the alternation between active (UP) and silent (DOWN) states during sleep slow waves (SWs) remain poorly understood. Previous models have explained the transition to the DOWN state by a progressive failure of excitation because of the build-up of adaptation currents or synaptic depression. However, these models are at odds with recent studies suggesting a role for presynaptic inhibition by Martinotti cells (MaCs) in generating SWs. Here, we update a classical large-scale model of sleep SWs to include MaCs and propose a different mechanism for the generation of SWs. In the wake mode, the network exhibits irregular and selective activity with low firing rates (FRs). Following an increase in the strength of background inputs and a modulation of synaptic strength and potassium leak potential mimicking the reduced effect of acetylcholine during sleep, the network enters a sleep-like regime in which local increases of network activity trigger bursts of MaC activity, resulting in strong disfacilitation of the local network via presynaptic GABAB1a -type inhibition. This model replicates findings on slow wave activity (SWA) during sleep that challenge previous models, including low and skewed FRs that are comparable between the wake and sleep modes, higher synchrony of transitions to DOWN states than to UP states, the possibility of triggering SWs by optogenetic stimulation of MaCs, and the local dependence of SWA on synaptic strength. Overall, this work points to a role for presynaptic inhibition by MaCs in the generation of DOWN states during sleep.

Transcranial ultrasound stimulation selectively affects cortical neurovascular coupling across neuronal types and LFP frequency bands

Previous studies have affirmed that transcranial ultrasound stimulation (TUS) can influence cortical neurovascular coupling across low-frequency (0-2 Hz)/high-frequency (160-200 Hz) neural oscillations and hemodynamics. Nevertheless, the selectivity of this coupling triggered by transcranial ultrasound stimulation for spike activity (> 300 Hz) and additional frequency bands (4-150 Hz) remains elusive. We applied transcranial ultrasound stimulation to mice visual cortex while simultaneously recording total hemoglobin concentration, spike activity, and local field potentials. Our findings include (1) a significant increase in coupling strength between spike firing rates of putative inhibitory neurons/putative excitatory neurons and total hemoglobin concentration post-transcranial ultrasound stimulation; (2) an ~ 2.1-fold higher Pearson correlation coefficient between putative inhibitory neurons and total hemoglobin concentration compared with putative excitatory neurons and total hemoglobin concentration (*P < 0.05); (3) a notably greater cross-correlation between putative inhibitory neurons and total hemoglobin concentration than that between putative excitatory neurons and total hemoglobin concentration (*P < 0.05); (4) an enhancement of Pearson correlation coefficient between the relative power of γ frequency band (30-80 Hz), hγ frequency band (80-150 Hz) and total hemoglobin concentration following transcranial ultrasound stimulation (*P < 0.05); and (5) strongest cross-correlation observed at negative delay for θ frequency band, and positive delay for α, β, γ, hγ frequency bands. Collectively, these results demonstrate that cortical neurovascular coupling evoked by transcranial ultrasound stimulation exhibits selectivity concerning neuronal types and local field potential frequency bands.

Id2 GABAergic interneurons comprise a neglected fourth major group of cortical inhibitory cells

Cortical GABAergic interneurons (INs) represent a diverse population of mainly locally projecting cells that provide specialized forms of inhibition to pyramidal neurons and other INs. Most recent work on INs has focused on subtypes distinguished by expression of Parvalbumin (PV), Somatostatin (SST), or Vasoactive Intestinal Peptide (VIP). However, a fourth group that includes neurogliaform cells (NGFCs) has been less well characterized due to a lack of genetic tools. Here, we show that these INs can be accessed experimentally using intersectional genetics with the gene Id2. We find that outside of layer 1 (L1), the majority of Id2 INs are NGFCs that express high levels of neuropeptide Y (NPY) and exhibit a late-spiking firing pattern, with extensive local connectivity. While much sparser, non-NGFC Id2 INs had more variable properties, with most cells corresponding to a diverse group of INs that strongly expresses the neuropeptide CCK. In vivo, using silicon probe recordings, we observed several distinguishing aspects of NGFC activity, including a strong rebound in activity immediately following the cortical down state during NREM sleep. Our study provides insights into IN diversity and NGFC distribution and properties, and outlines an intersectional genetics approach for further study of this underappreciated group of INs.

Altered Thalamocortical Signaling in a Mouse Model of Parkinson's Disease

Activation of the primary motor cortex (M1) is important for the execution of skilled movements and motor learning, and its dysfunction contributes to the pathophysiology of Parkinson's disease (PD). A well-accepted idea in PD research, albeit not tested experimentally, is that the loss of midbrain dopamine leads to decreased activation of M1 by the motor thalamus. Here, we report that midbrain dopamine loss altered motor thalamus input in a laminar- and cell type-specific fashion and induced laminar-specific changes in intracortical synaptic transmission. Frequency-dependent changes in synaptic dynamics were also observed. Our results demonstrate that loss of midbrain dopaminergic neurons alters thalamocortical activation of M1 in both male and female mice, and provide novel insights into circuit mechanisms for motor cortex dysfunction in a mouse model of PD.SIGNIFICANCE STATEMENT Loss of midbrain dopamine neurons increases inhibition from the basal ganglia to the motor thalamus, suggesting that it may ultimately lead to reduced activation of primary motor cortex (M1). In contrast with this line of thinking, analysis of M1 activity in patients and animal models of Parkinson's disease report hyperactivation of this region. Our results are the first report that midbrain dopamine loss alters the input-output function of M1 through laminar and cell type specific effects. These findings support and expand on the idea that loss of midbrain dopamine reduces motor cortex activation and provide experimental evidence that reconciles reduced thalamocortical input with reports of altered activation of motor cortex in patients with Parkinson's disease.

Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer

Objective

To confirm and investigate why pathological HFOs (pHFOs), including Ripples [80-200 Hz] and fast ripples [200-600 Hz], are generated during the UP-DOWN transition of the slow wave and if pHFOs interfere with information transmission.

Methods

We isolated 217 total units from 175.95 iEEG contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (0.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the seizure onset zone (SOZ), HFOs and associated action potentials (AP) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross correlograms.

Results

At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p<<0.001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p<<0.001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d=0.11-0.83) and fast ripples (d=0.36-0.90) at the UP-DOWN transition (p<0.05 f.d.r corrected), respectively. By comparison, also in the SOZ, 6.6% (d=0.14-0.30) and 8.5% (d=0.33-0.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by ~50-80% in the SOZ compared to the non-SOZ (N=3).

Significance

The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. The pathological neurons and pHFOs disrupt ripple temporal correlations across brain regions that transfer information and may be important in memory consolidation.

Identifying properties of pattern completion neurons in a computational model of the visual cortex

Neural ensembles are found throughout the brain and are believed to underlie diverse cognitive functions including memory and perception. Methods to activate ensembles precisely, reliably, and quickly are needed to further study the ensembles' role in cognitive processes. Previous work has found that ensembles in layer 2/3 of the visual cortex (V1) exhibited pattern completion properties: ensembles containing tens of neurons were activated by stimulation of just two neurons. However, methods that identify pattern completion neurons are underdeveloped. In this study, we optimized the selection of pattern completion neurons in simulated ensembles. We developed a computational model that replicated the connectivity patterns and electrophysiological properties of layer 2/3 of mouse V1. We identified ensembles of excitatory model neurons using K-means clustering. We then stimulated pairs of neurons in identified ensembles while tracking the activity of the entire ensemble. Our analysis of ensemble activity quantified a neuron pair's power to activate an ensemble using a novel metric called pattern completion capability (PCC) based on the mean pre-stimulation voltage across the ensemble. We found that PCC was directly correlated with multiple graph theory parameters, such as degree and closeness centrality. To improve selection of pattern completion neurons in vivo, we computed a novel latency metric that was correlated with PCC and could potentially be estimated from modern physiological recordings. Lastly, we found that stimulation of five neurons could reliably activate ensembles. These findings can help researchers identify pattern completion neurons to stimulate in vivo during behavioral studies to control ensemble activation.

Comparison between an exact and a heuristic neural mass model with second-order synapses

Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that the output firing rate of a neural population can be described by a static nonlinear transfer function (NMM1). However, a recent exact mean-field theory for quadratic integrate-and-fire (QIF) neurons challenges this view by showing that the mean firing rate is not a static function of the neuronal state but follows two coupled nonlinear differential equations (NMM2). Here we analyze and compare these two descriptions in the presence of second-order synaptic dynamics. First, we derive the mathematical equivalence between the two models in the infinitely slow synapse limit, i.e., we show that NMM1 is an approximation of NMM2 in this regime. Next, we evaluate the applicability of this limit in the context of realistic physiological parameter values by analyzing the dynamics of models with inhibitory or excitatory synapses. We show that NMM1 fails to reproduce important dynamical features of the exact model, such as the self-sustained oscillations of an inhibitory interneuron QIF network. Furthermore, in the exact model but not in the limit one, stimulation of a pyramidal cell population induces resonant oscillatory activity whose peak frequency and amplitude increase with the self-coupling gain and the external excitatory input. This may play a role in the enhanced response of densely connected networks to weak uniform inputs, such as the electric fields produced by noninvasive brain stimulation.

Recurrent activity in neuronal avalanches

A new statistical analysis of large neuronal avalanches observed in mouse and rat brain tissues reveals a substantial degree of recurrent activity and cyclic patterns of activation not seen in smaller avalanches. To explain these observations, we adapted a model of structural weakening in materials. In this model, dynamical weakening of neuron firing thresholds closely replicates experimental avalanche size distributions, firing number distributions, and patterns of cyclic activity. This agreement between model and data suggests that a mechanism like dynamical weakening plays a key role in recurrent activity found in large neuronal avalanches. We expect these results to illuminate the causes and dynamics of large avalanches, like those seen in seizures.

Involvement of GABAergic Interneuron Subtypes in 4-Aminopyridine-Induced Seizure-Like Events in Mouse Entorhinal Cortex in Vitro

Single-unit recordings performed in temporal lobe epilepsy patients and in models of temporal lobe seizures have shown that interneurons are active at focal seizure onset. We performed simultaneous patch-clamp and field potential recordings in entorhinal cortex slices of GAD65 and GAD67 C57BL/6J male mice that express green fluorescent protein in GABAergic neurons to analyze the activity of specific interneuron (IN) subpopulations during acute seizure-like events (SLEs) induced by 4-aminopyridine (4-AP; 100 μm). IN subtypes were identified as parvalbuminergic (INPV, n = 17), cholecystokinergic (INCCK), n = 13], and somatostatinergic (INSOM, n = 15), according to neurophysiological features and single-cell digital PCR. INPV and INCCK discharged at the start of 4-AP-induced SLEs characterized by either low-voltage fast or hyper-synchronous onset pattern. In both SLE onset types, INSOM fired earliest before SLEs, followed by INPV and INCCK discharges. Pyramidal neurons became active with variable delays after SLE onset. Depolarizing block was observed in ∼50% of cells in each INs subgroup, and it was longer in IN (∼4 s) than in pyramidal neurons (<1 s). As SLE evolved, all IN subtypes generated action potential bursts synchronous with the field potential events leading to SLE termination. High-frequency firing throughout the SLE occurred in one-third of INPV and INSOM We conclude that entorhinal cortex INs are very active at the onset and during the progression of SLEs induced by 4-AP. These results support earlier in vivo and in vivo evidence and suggest that INs have a preferential role in focal seizure initiation and development.SIGNIFICANCE STATEMENT Focal seizures are believed to result from enhanced excitation. Nevertheless, we and others demonstrated that cortical GABAergic networks may initiate focal seizures. Here, we analyzed for the first time the role of different IN subtypes in seizures generated by 4-aminopyridine in the mouse entorhinal cortex slices. We found that in this in vitro focal seizure model, all IN types contribute to seizure initiation and that INs precede firing of principal cells. This evidence is in agreement with the active role of GABAergic networks in seizure generation.

NMDA receptors as therapeutic targets for depression treatment: Evidence from clinical to basic research

Ketamine, functioning as a channel blocker of the excitatory glutamate-gated N-methyl-d-aspartate (NMDA) receptors, displays compelling fast-acting and sustained antidepressant effects for treatment-resistant depression. Over the past decades, clinical and preclinical studies have implied that the pathology of depression is associated with dysfunction of glutamatergic transmission. In particular, the discovery of antidepressant agents modulating NMDA receptor function has prompted breakthroughs for depression treatment compared with conventional antidepressants targeting the monoaminergic system. In this review, we first summarized the signalling pathway of the ketamine-mediated antidepressant effects, based on the glutamate hypothesis of depression. Second, we reviewed the hypotheses of the synaptic mechanism and network of ketamine antidepressant effects within different brain areas and distinct subcellular localizations, including NMDA receptor antagonism on GABAergic interneurons, extrasynaptic and synaptic NMDA receptor-mediated antagonism, and ketamine blocking bursting activities in the lateral habenula. Third, we reviewed the different roles of NMDA receptor subunits in ketamine-mediated cognitive and psychiatric behaviours in genetically-manipulated rodent models. Finally, we summarized the structural basis of NMDA receptor channel blockers and discussed NMDA receptor modulators that have been reported to exert potential antidepressant effects in animal models or in clinical trials. Integrating the cutting-edge technologies of cryo-EM and artificial intelligence-based drug design (AIDD), we expect that the next generation of first-in-class rapid antidepressants targeting NMDA receptors would be an emerging direction for depression therapeutics. This article is part of the Special Issue on 'Ketamine and its Metabolites'.

Macroscopic dynamics of neural networks with heterogeneous spiking thresholds

Mean-field theory links the physiological properties of individual neurons to the emergent dynamics of neural population activity. These models provide an essential tool for studying brain function at different scales; however, for their application to neural populations on large scale, they need to account for differences between distinct neuron types. The Izhikevich single neuron model can account for a broad range of different neuron types and spiking patterns, thus rendering it an optimal candidate for a mean-field theoretic treatment of brain dynamics in heterogeneous networks. Here we derive the mean-field equations for networks of all-to-all coupled Izhikevich neurons with heterogeneous spiking thresholds. Using methods from bifurcation theory, we examine the conditions under which the mean-field theory accurately predicts the dynamics of the Izhikevich neuron network. To this end, we focus on three important features of the Izhikevich model that are subject here to simplifying assumptions: (i) spike-frequency adaptation, (ii) the spike reset conditions, and (iii) the distribution of single-cell spike thresholds across neurons. Our results indicate that, while the mean-field model is not an exact model of the Izhikevich network dynamics, it faithfully captures its different dynamic regimes and phase transitions. We thus present a mean-field model that can represent different neuron types and spiking dynamics. The model comprises biophysical state variables and parameters, incorporates realistic spike resetting conditions, and accounts for heterogeneity in neural spiking thresholds. These features allow for a broad applicability of the model as well as for a direct comparison to experimental data.

Creation of Neuronal Ensembles and Cell-Specific Homeostatic Plasticity through Chronic Sparse Optogenetic Stimulation

Cortical computations emerge from the dynamics of neurons embedded in complex cortical circuits. Within these circuits, neuronal ensembles, which represent subnetworks with shared functional connectivity, emerge in an experience-dependent manner. Here we induced ensembles in ex vivo cortical circuits from mice of either sex by differentially activating subpopulations through chronic optogenetic stimulation. We observed a decrease in voltage correlation, and importantly a synaptic decoupling between the stimulated and nonstimulated populations. We also observed a decrease in firing rate during Up-states in the stimulated population. These ensemble-specific changes were accompanied by decreases in intrinsic excitability in the stimulated population, and a decrease in connectivity between stimulated and nonstimulated pyramidal neurons. By incorporating the empirically observed changes in intrinsic excitability and connectivity into a spiking neural network model, we were able to demonstrate that changes in both intrinsic excitability and connectivity accounted for the decreased firing rate, but only changes in connectivity accounted for the observed decorrelation. Our findings help ascertain the mechanisms underlying the ability of chronic patterned stimulation to create ensembles within cortical circuits and, importantly, show that while Up-states are a global network-wide phenomenon, functionally distinct ensembles can preserve their identity during Up-states through differential firing rates and correlations.SIGNIFICANCE STATEMENT The connectivity and activity patterns of local cortical circuits are shaped by experience. This experience-dependent reorganization of cortical circuits is driven by complex interactions between different local learning rules, external input, and reciprocal feedback between many distinct brain areas. Here we used an ex vivo approach to demonstrate how simple forms of chronic external stimulation can shape local cortical circuits in terms of their correlated activity and functional connectivity. The absence of feedback between different brain areas and full control of external input allowed for a tractable system to study the underlying mechanisms and development of a computational model. Results show that differential stimulation of subpopulations of neurons significantly reshapes cortical circuits and forms subnetworks referred to as neuronal ensembles.

Effects of optogenetic inhibition of a small fraction of parvalbumin-positive interneurons on the representation of sensory stimuli in mouse barrel cortex

Inhibitory interneurons play central roles in the modulation of spontaneous network activity and in processing of neuronal information. In sensory neocortical areas, parvalbumin-positive (PV+) GABAergic interneurons control the representation and processing of peripheral sensory inputs. We studied the functional role of PV+ interneurons in the barrel cortex of anesthetized adult PVCre mice by combining extracellular multi-electrode recordings with optogenetic silencing of a small fraction of PV+ interneurons. In all cortical layers, optogenetic inhibition caused an increase in spontaneous network activity from theta to gamma frequencies. The spatio-temporal representation of sensory inputs was studied by stimulating one or two whiskers at different intervals and analyzing the resulting local field potential (LFP) and single unit (SU) response. Silencing PV+ interneurons caused an increase in LFP response to sensory stimulation and a decrease in temporal discrimination of consecutive whisker deflections. The combined effect of whisker deflection and optogenetic inhibition was highly similar to the linear sum of the individual effects of these two manipulations. SU recordings revealed that optogenetic silencing reduced stimulus detectability by increasing stimulus-evoked firing rate by a constant offset, suggesting that PV+ interneurons improve signal-to-noise ratio by reducing ongoing spiking activity, thereby sharpening the spatio-temporal representation of sensory stimuli.

Disinhibitory circuit mediated by connections from vasoactive intestinal polypeptide to somatostatin interneurons underlies the paradoxical decrease in spike synchrony with increased border ownership selective neuron firing rate

The activity of border ownership selective (BOS) neurons in intermediate-level visual areas indicates which side of a contour owns a border relative to its classical receptive field and provides a fundamental component of figure-ground segregation. A physiological study reported that selective attention facilitates the activity of BOS neurons with a consistent border ownership preference, defined as two neurons tuned to respond to the same visual object. However, spike synchrony between this pair is significantly suppressed by selective attention. These neurophysiological findings are derived from a biologically-plausible microcircuit model consisting of spiking neurons including two subtypes of inhibitory interneurons, somatostatin (SOM) and vasoactive intestinal polypeptide (VIP) interneurons, and excitatory BOS model neurons. In our proposed model, BOS neurons and SOM interneurons cooperate and interact with each other. VIP interneurons not only suppress SOM interneuron responses but also are activated by feedback signals mediating selective attention, which leads to disinhibition of BOS neurons when they are directing selective attention toward an object. Our results suggest that disinhibition arising from the synaptic connections from VIP to SOM interneurons plays a critical role in attentional modulation of neurons in intermediate-level visual areas.

Paradoxical self-sustained dynamics emerge from orchestrated excitatory and inhibitory homeostatic plasticity rules

Cortical networks have the remarkable ability to self-assemble into dynamic regimes in which excitatory positive feedback is balanced by recurrent inhibition. This inhibition-stabilized regime is increasingly viewed as the default dynamic regime of the cortex, but how it emerges in an unsupervised manner remains unknown. We prove that classic forms of homeostatic plasticity are unable to drive recurrent networks to an inhibition-stabilized regime due to the well-known paradoxical effect. We next derive a novel family of cross-homeostatic rules that lead to the unsupervised emergence of inhibition-stabilized networks. These rules shed new light on how the brain may reach its default dynamic state and provide a valuable tool to self-assemble artificial neural networks into ideal computational regimes.

Self-sustained neural activity maintained through local recurrent connections is of fundamental importance to cortical function. Converging theoretical and experimental evidence indicates that cortical circuits generating self-sustained dynamics operate in an inhibition-stabilized regime. Theoretical work has established that four sets of weights (W_E←E, W_E←I, W_I←E, and W_I←I) must obey specific relationships to produce inhibition-stabilized dynamics, but it is not known how the brain can appropriately set the values of all four weight classes in an unsupervised manner to be in the inhibition-stabilized regime. We prove that standard homeostatic plasticity rules are generally unable to generate inhibition-stabilized dynamics and that their instability is caused by a signature property of inhibition-stabilized networks: the paradoxical effect. In contrast, we show that a family of “cross-homeostatic” rules overcome the paradoxical effect and robustly lead to the emergence of stable dynamics. This work provides a model of how—beginning from a silent network—self-sustained inhibition-stabilized dynamics can emerge from learning rules governing all four synaptic weight classes in an orchestrated manner.

John EK, Potesta CV, Gallagher MJ, Zhou C. Artificial sleep-like up/down-states induce synaptic plasticity in cortical neurons from mouse brain slices

During non-rapid eye movement (NREM) sleep, cortical neuron activity alternates between a depolarized (firing, up-state) and a hyperpolarized state (down-state) coinciding with delta electroencephalogram (EEG) slow-wave oscillation (SWO, 0. 5-4 Hz) in vivo. Recently, we have found that artificial sleep-like up/down-states can potentiate synaptic strength in layer V cortical neurons ex vivo. Using mouse coronal brain slices, whole cell voltage-clamp recordings were made from layer V cortical pyramidal neurons to record spontaneous excitatory synaptic currents (sEPSCs) and inhibitory synaptic currents (sIPSCs). Artificial sleep-like up/down-states (as SWOs, 0.5 Hz, 10 min, current clamp mode) were induced by injecting sinusoidal currents into layer V cortical neurons. Baseline pre-SWO recordings were recorded for 5 min and post-SWO recordings for at least 25-30 min. Compared to pre-SWO sEPSCs or sIPSCs, post-SWO sEPSCs or sIPSCs in layer V cortical neurons exhibited significantly larger amplitudes and a higher frequency for 30 min. This finding suggests that both sEPSCs and sIPSCs could be potentiated in layer V cortical neurons by the low-level activity of SWOs, and sEPSCs and sIPSCs maintained a balance in layer V cortical neurons during pre- and post-SWO periods. Overall, this study presents an ex vivo method to show SWO's ability to induce synaptic plasticity in layer V cortical neurons, which may underlie sleep-related synaptic potentiation for sleep-related memory consolidation in vivo.

A microcircuit model involving parvalbumin, somatostatin, and vasoactive intestinal polypeptide inhibitory interneurons for the modulation of neuronal oscillation during visual processing

Various subtypes of inhibitory interneurons contact one another to organize cortical networks. Most cortical inhibitory interneurons express 1 of 3 genes: parvalbumin (PV), somatostatin (SOM), or vasoactive intestinal polypeptide (VIP). This diversity of inhibition allows the flexible regulation of neuronal responses within and between cortical areas. However, the exact roles of these interneuron subtypes and of excitatory pyramidal (Pyr) neurons in regulating neuronal network activity and establishing perception (via interactions between feedforward sensory and feedback attentional signals) remain largely unknown. To explore the regulatory roles of distinct neuronal types in cortical computation, we developed a computational microcircuit model with biologically plausible visual cortex layers 2/3 that combined Pyr neurons and the 3 inhibitory interneuron subtypes to generate network activity. In simulations with our model, inhibitory signals from PV and SOM neurons preferentially induced neuronal firing at gamma (30-80 Hz) and beta (20-30 Hz) frequencies, respectively, in agreement with observed physiological results. Furthermore, our model indicated that rapid inhibition from VIP to SOM subtypes underlies marked attentional modulation for low-gamma frequency (30-50 Hz) in Pyr neuron responses. Our results suggest the distinct but cooperative roles of inhibitory interneuron subtypes in the establishment of visual perception.

Perturbation of Cortical Excitability in a Conditional Model of PCDH19 Disorder

PCDH19 epilepsy (DEE9) is an X-linked syndrome associated with cognitive and behavioral disturbances. Since heterozygous females are affected, while mutant males are spared, it is likely that DEE9 pathogenesis is related to disturbed cell-to-cell communication associated with mosaicism. However, the effects of mosaic PCDH19 expression on cortical networks are unknown. We mimicked the pathology of DEE9 by introducing a patch of mosaic protein expression in one hemisphere of the cortex of conditional PCDH19 knockout mice one day after birth. In the contralateral area, PCDH19 expression was unaffected, thus providing an internal control. In this model, we characterized the physiology of the disrupted network using local field recordings and two photon Ca²⁺ imaging in urethane anesthetized mice. We found transient episodes of hyperexcitability in the form of brief hypersynchronous spikes or bursts of field potential oscillations in the 9–25 Hz range. Furthermore, we observed a strong disruption of slow wave activity, a crucial component of NREM sleep. This phenotype was present also when PCDH19 loss occurred in adult mice, demonstrating that PCDH19 exerts a function on cortical circuitry outside of early development. Our results indicate that a focal mosaic mutation of PCDH19 disrupts cortical networks and broaden our understanding of DEE9.

Loss of neuronal heterogeneity in epileptogenic human tissue impairs network resilience to sudden changes in synchrony

A myriad of pathological changes associated with epilepsy can be recast as decreases in cell and circuit heterogeneity. We thus propose recontextualizing epileptogenesis as a process where reduction in cellular heterogeneity, in part, renders neural circuits less resilient to seizure. By comparing patch clamp recordings from human layer 5 (L5) cortical pyramidal neurons from epileptogenic and non-epileptogenic tissue, we demonstrate significantly decreased biophysical heterogeneity in seizure-generating areas. Implemented computationally, this renders model neural circuits prone to sudden transitions into synchronous states with increased firing activity, paralleling ictogenesis. This computational work also explains the surprising finding of significantly decreased excitability in the population-activation functions of neurons from epileptogenic tissue. Finally, mathematical analyses reveal a bifurcation structure arising only with low heterogeneity and associated with seizure-like dynamics. Taken together, this work provides experimental, computational, and mathematical support for the theory that ictogenic dynamics accompany a reduction in biophysical heterogeneity.

Structural changes in the neocortex as correlates of variations in EEG spectra and seizure susceptibility in rat brains with different degrees of dysplasia

Disturbances of the early stages of neurogenesis lead to irreversible changes in the structure of the mature brain and its functional impairment, including increased excitability, which may be the basis for drug‐resistant epilepsy. The range of possible clinical symptoms is as wide as the different stages of disturbed neurogenesis may be. In this study, we used a quadruple model of brain dysplasia by comparing structural and functional disorders in animals whose neurogenesis was disturbed with a single dose of 1 Gy of gamma rays at one of the four stages of neurogenesis, that is, on days 13, 15, 17, or 19 of prenatal development.

When reached adulthood, the prenatally irradiated rats received EEG teletransmitter implantation. Thereafter, pilocarpine was administered and significant differences in susceptibility to seizure behavioral symptoms were detected depending on the degree of brain dysplasia. Before, during, and after the seizures significant correlations were found between the density of parvalbumin‐immunopositive neurons located in the cerebral cortex and the intensity of behavioral seizure symptoms or increases in the power of particular EEG bands. Neurons expressing calretinin or NPY showed also dysplasia‐related increases without, however, correlations with parameters of seizure intensity. The results point to significant roles of parvalbumin‐expressing interneurons, and also to expression of NPY—an endogenous anticonvulsant and neuroprotectant reducing susceptibility to seizures and supporting neuronal survival.

Variations in Commissural Input Processing Across Different Types of Cortical Projection Neurons

To understand how incoming cortical inputs are processed by different types of cortical projection neurons in the medial prefrontal cortex, we compared intrinsic physiological properties of and commissural excitatory/inhibitory influences on layer 5 intratelencephalic (IT), layer 5 pyramidal tract (PT), and layers 2/3 IT projection neurons. We found that intrinsic physiological properties and commissural synaptic transmission varied across the three types of projection neurons. The rank order of intrinsic excitability was layer 5 PT > layer 5 IT > layers 2/3 IT neurons. Commissural connectivity was higher in layers 2/3 than layer 5 projection neurons, but commissural excitatory influence was stronger on layer 5 than layers 2/3 pyramidal neurons. Paired-pulse ratio was also greater in PT than IT neurons. These results indicate that commissural inputs activate deep layer PT neurons most preferentially and superficial layer IT neurons least preferentially. Deep layer PT neurons might faithfully transmit cortical input signals to downstream subcortical structures for reliable control of behavior, whereas superficial layer IT neurons might integrate cortical input signals from diverse sources in support of higher-order cognitive functions.

Learning-induced plasticity in the barrel cortex is disrupted by inhibition of layer 4 somatostatin-containing interneurons

Gaba-ergic neurons are a diverse cell class with extensive influence over cortical processing, but their role in experience-dependent plasticity is not completely understood. Here we addressed the role of cortical somatostatin- (SOM-INs) and vasoactive intestinal polypeptide- (VIP-INs) containing interneurons in a Pavlovian conditioning where stimulation of the vibrissae is used as a conditioned stimulus and tail shock as unconditioned one. This procedure induces a plastic change observed as an enlargement of the cortical functional representation of vibrissae activated during conditioning. Using layer-targeted, cell-selective DREADD transductions, we examined the involvement of SOM-INs and VIP-INs activity in learning-related plastic changes. Under optical recordings, we injected DREADD-expressing vectors into layer IV (L4) barrels or layer II/III (L2/3) areas corresponding to the activated vibrissae. The activity of the interneurons was modulated during all conditioning sessions, and functional 2-deoxyglucose (2DG) maps were obtained 24 h after the last session. In mice with L4 but not L2/3 SOM-INs suppressed during conditioning, the plastic change of whisker representation was absent. The behavioral effect of conditioning was disturbed. Both L4 SOM-INs excitation and L2/3 VIP-INs inhibition during conditioning did not affect the plasticity or the conditioned response. We found the activity of L4 SOM-INs is indispensable in the formation of learning-induced plastic change. We propose that L4 SOM-INs may provide disinhibition by blocking L4 parvalbumin interneurons, allowing a flow of information into upper cortical layers during learning.

Comprehensive characterization of oscillatory signatures in a model circuit with PV- and SOM-expressing interneurons

Neural circuits contain a wide variety of interneuron types, which differ in their biophysical properties and connectivity patterns. The two most common interneuron types, parvalbumin-expressing and somatostatin-expressing cells, have been shown to be differentially involved in many cognitive functions. These cell types also show different relationships with the power and phase of oscillations in local field potentials. The mechanisms that underlie the emergence of different oscillatory rhythms in neural circuits with more than one interneuron subtype, and the roles specific interneurons play in those mechanisms, are not fully understood. Here, we present a comprehensive analysis of all possible circuit motifs and input regimes that can be achieved in circuits comprised of excitatory cells, PV-like fast-spiking interneurons and SOM-like low-threshold spiking interneurons. We identify 18 unique motifs and simulate their dynamics over a range of input strengths. Using several characteristics, such as oscillation frequency, firing rates, phase of firing and burst fraction, we cluster the resulting circuit dynamics across motifs in order to identify patterns of activity and compare these patterns to behaviors that were generated in circuits with one interneuron type. In addition to the well-known PING and ING gamma oscillations and an asynchronous state, our analysis identified three oscillatory behaviors that were generated by the three-cell-type motifs only: theta-nested gamma oscillations, stable beta oscillations and theta-locked bursting behavior, which have also been observed in experiments. Our characterization provides a map to interpret experimental activity patterns and suggests pharmacological manipulations or optogenetics approaches to validate these conclusions.

Differential Excitability of PV and SST Neurons Results in Distinct Functional Roles in Inhibition Stabilization of Up States

Up states are the best studied example of an emergent neural dynamic regime. Computational models based on a single class of inhibitory neurons indicate that Up states reflect bistable dynamic systems in which positive feedback is stabilized by strong inhibition and predict a paradoxical effect in which increased drive to inhibitory neurons results in decreased inhibitory activity. To date, however, computational models have not incorporated empirically defined properties of parvalbumin (PV) and somatostatin (SST) neurons. Here we first experimentally characterized the frequency-current (F-I) curves of pyramidal (Pyr), PV, and SST neurons from mice of either sex, and confirmed a sharp difference between the threshold and slopes of PV and SST neurons. The empirically defined F-I curves were incorporated into a three-population computational model that simulated the empirically derived firing rates of pyramidal, PV, and SST neurons. Simulations revealed that the intrinsic properties were sufficient to predict that PV neurons are primarily responsible for generating the nontrivial fixed points representing Up states. Simulations and analytical methods demonstrated that while the paradoxical effect is not obligatory in a model with two classes of inhibitory neurons, it is present in most regimes. Finally, experimental tests validated predictions of the model that the Pyr ↔ PV inhibitory loop is stronger than the Pyr ↔ SST loop.SIGNIFICANCE STATEMENT Many cortical computations, such as working memory, rely on the local recurrent excitatory connections that define cortical circuit motifs. Up states are among the best studied examples of neural dynamic regimes that rely on recurrent excitatory excitation. However, this positive feedback must be held in check by inhibition. To address the relative contribution of PV and SST neurons, we characterized the intrinsic input-output differences between these classes of inhibitory neurons and, using experimental and theoretical methods, show that the higher threshold and gain of PV leads to a dominant role in network stabilization.

HDAC6 is critical for ketamine-induced impairment of dendritic and spine growth in GABAergic projection neurons

Ketamine is widely used in infants and children for anesthesia; both anesthetic and sub-anesthetic doses of ketamine have been reported to preferentially inhibit the GABAergic neurons. Medium spiny neurons (MSNs), the GABAergic projection neurons in the striatum, are vulnerable to anesthetic exposure in the newborn brain. Growth of dendrites requires a deacetylase to remove acetyl from tubulin in the growth cone to destabilize the tubulin. Histone deacetylase 6 (HDAC6) affects microtubule dynamics, which are involved in neurite elongation. In this study we used a human induced pluripotent stem cells (iPSCs)-derived striatal GABA neuron system to investigate the effects of ketamine on HDAC6 and the morphological development of MSNs. We showed that exposure to ketamine (1-500 μM) decreased dendritic growth, dendrite branches, and dendritic spine density in MSNs in a time- and concentration-dependent manner. We revealed that ketamine treatment concentration-dependently inhibited the expression of HDAC6 or aberrantly translocated HDAC6 into the nucleus. Ketamine inhibition on HDAC6 resulted in α-tubulin hyperacetylation, consequently increasing the stability of microtubules and delaying the dendritic growth of MSNs. Finally, we showed that the effects of a single-dose exposure on MSNs were reversible and lasted for at least 10 days. This study reveals a novel role of HDAC6 as a regulator for ketamine-induced deficits in the morphological development of MSNs and provides an innovative method for prevention and treatment with respect to ketamine clinical applications.

Model neocortical microcircuit supports beta and gamma rhythms

Gamma and beta rhythms in neocortical circuits are thought to be caused by distinct subcircuits involving different type of interneurons. However, it is not clear how these distinct but inter-linked intrinsic circuits interact with afferent drive to engender the two rhythms. We report a biophysical computational model to investigate the hypothesis that tonic and phasic drive might engender beta and gamma oscillations, respectively, in a neocortical circuit.

Emergence of Neuronal Synchronisation in Coupled Areas

One of the most fundamental questions in the field of neuroscience is the emergence of synchronous behaviour in the brain, such as phase, anti-phase, and shift-phase synchronisation. In this work, we investigate how the connectivity between brain areas can influence the phase angle and the neuronal synchronisation. To do this, we consider brain areas connected by means of excitatory and inhibitory synapses, in which the neuron dynamics is given by the adaptive exponential integrate-and-fire model. Our simulations suggest that excitatory and inhibitory connections from one area to another play a crucial role in the emergence of these types of synchronisation. Thus, in the case of unidirectional interaction, we observe that the phase angles of the neurons in the receiver area depend on the excitatory and inhibitory synapses which arrive from the sender area. Moreover, when the neurons in the sender area are synchronised, the phase angle variability of the receiver area can be reduced for some conductance values between the areas. For bidirectional interactions, we find that phase and anti-phase synchronisation can emerge due to excitatory and inhibitory connections. We also verify, for a strong inhibitory-to-excitatory interaction, the existence of silent neuronal activities, namely a large number of excitatory neurons that remain in silence for a long time.

Somatostatin interneurons activated by 5-HT2A receptor suppress slow oscillations in medial entorhinal cortex

Serotonin (5-HT) is one of the major neuromodulators present in the mammalian brain and has been shown to play a role in multiple physiological processes. The mechanisms by which 5-HT modulates cortical network activity, however, are not yet fully understood. We investigated the effects of 5-HT on slow oscillations (SOs), a synchronized cortical network activity universally present across species. SOs are observed during anesthesia and are considered to be the default cortical activity pattern. We discovered that (±)3,4-methylenedioxymethamphetamine (MDMA) and fenfluramine, two potent 5-HT releasers, inhibit SOs within the entorhinal cortex (EC) in anesthetized mice. Combining opto- and pharmacogenetic manipulations with in vitro electrophysiological recordings, we uncovered that somatostatin-expressing (Sst) interneurons activated by the 5-HT_2A receptor (5-HT_2AR) play an important role in the suppression of SOs. Since 5-HT_2AR signaling is involved in the etiology of different psychiatric disorders and mediates the psychological effects of many psychoactive serotonergic drugs, we propose that the newly discovered link between Sst interneurons and 5-HT will contribute to our understanding of these complex topics.

Somatostatin expressing GABAergic interneurons in the medial entorhinal cortex preferentially inhibit layerIII-V pyramidal cells

GABA released from heterogeneous types of interneurons acts in a complex spatio-temporal manner on postsynaptic targets in the networks. In addition to GABA, a large fraction of GABAergic cells also express neuromodulator peptides. Somatostatin (SOM) containing interneurons, in particular, have been recognized as key players in several brain circuits, however, the action of SOM and its downstream network effects remain largely unknown. Here, we used optogenetics, electrophysiologic, anatomical and behavioral experiments to reveal that the dendrite-targeting, SOM⁺ GABAergic interneurons demonstrate a unique layer-specific action in the medial entorhinal cortex (MEC) both in terms of GABAergic and SOM-related properties. We show that GABAergic and somatostatinergic neurotransmission originating from SOM⁺ local interneurons preferentially inhibit layer_III-V pyramidal cells, known to be involved in memory formation. We propose that this dendritic GABA–SOM dual inhibitory network motif within the MEC serves to selectively modulate working-memory formation without affecting the retrieval of already learned spatial navigation tasks.

Miklós Kecskés et al. show that somatostatin-expressing interneurons in the medial entorhinal cortex regulate deep-layer pyramidal neurons and impact short-term memory in mice.

Influence of Autapses on Synchronization in Neural Networks With Chemical Synapses

A great deal of research has been devoted on the investigation of neural dynamics in various network topologies. However, only a few studies have focused on the influence of autapses, synapses from a neuron onto itself via closed loops, on neural synchronization. Here, we build a random network with adaptive exponential integrate-and-fire neurons coupled with chemical synapses, equipped with autapses, to study the effect of the latter on synchronous behavior. We consider time delay in the conductance of the pre-synaptic neuron for excitatory and inhibitory connections. Interestingly, in neural networks consisting of both excitatory and inhibitory neurons, we uncover that synchronous behavior depends on their synapse type. Our results provide evidence on the synchronous and desynchronous activities that emerge in random neural networks with chemical, inhibitory and excitatory synapses where neurons are equipped with autapses.

Imperceptible Somatosensory Single Pulse and Pulse Train Stimulation Oppositely Modulate Mu Rhythm Activity and Perceptual Performance

Subliminal stimulation alters conscious perception – a potential mechanism is the modulation of cortical background rhythms especially in the alpha range. Here, in the human somatosensory domain, we assessed effects of subthreshold (imperceptible) electrical finger nerve stimulation – either presented as single pulses or as brief (1 s) 7 Hz pulse trains—on mu-alpha rhythm and perceptual performance. In electroencephalography, subthreshold single pulses transiently (~150–350 ms poststimulus) increased mu activity (event-related synchronization), while, interestingly, subthreshold trains led to prolonged (>1 s) mu desynchronization. In psychophysics, detection of near-threshold target stimuli was consistently reduced when presented together with subthreshold trains (at three delays), whereas for targets paired with subthreshold single pulses detection remained unaffected (30 and 180 ms) or was even elevated (60 ms). Though both imperceptible, single pulses and pulse trains exerted opposite effects on neural signaling and perception. We suggest that the common neural basis is preferential activation of cortical inhibitory interneurons. While the inhibitory impact of a subthreshold single pulse (reflected by mu synchronization) is not psychophysically detectable—rather perception may be facilitated—repetition of the same subthreshold pulse shifts the excitation-inhibition balance toward an inhibitory cortical state (reflected by perceptual impediment) accompanied by mu desynchronization. These differential findings provide novel insights on the notion of alpha activity mediating functional inhibition.

Preventing neuronal edema increases network excitability after traumatic brain injury

Edema is an important target for clinical intervention after traumatic brain injury (TBI). We used in vivo cellular resolution imaging and electrophysiological recording to examine the ionic mechanisms underlying neuronal edema and their effects on neuronal and network excitability after controlled cortical impact (CCI) in mice. Unexpectedly, we found that neuronal edema 48 hours after CCI was associated with reduced cellular and network excitability, concurrent with an increase in the expression ratio of the cation-chloride cotransporters (CCCs) NKCC1 and KCC2. Treatment with the CCC blocker bumetanide prevented neuronal swelling via a reversal in the NKCC1/KCC2 expression ratio, identifying altered chloride flux as the mechanism of neuronal edema. Importantly, bumetanide treatment was associated with increased neuronal and network excitability after injury, including increased susceptibility to spreading depolarizations (SDs) and seizures, known agents of clinical worsening after TBI. Treatment with mannitol, a first-line edema treatment in clinical practice, was also associated with increased susceptibility to SDs and seizures after CCI, showing that neuronal volume reduction, regardless of mechanism, was associated with an excitability increase. Finally, we observed an increase in excitability when neuronal edema normalized by 1 week after CCI. We conclude that neuronal swelling may exert protective effects against damaging excitability in the aftermath of TBI and that treatment of edema has the potential to reverse these effects.

Neurostimulation stabilizes spiking neural networks by disrupting seizure-like oscillatory transitions

An improved understanding of the mechanisms underlying neuromodulatory approaches to mitigate seizure onset is needed to identify clinical targets for the treatment of epilepsy. Using a Wilson–Cowan-motivated network of inhibitory and excitatory populations, we examined the role played by intrinsic and extrinsic stimuli on the network’s predisposition to sudden transitions into oscillatory dynamics, similar to the transition to the seizure state. Our joint computational and mathematical analyses revealed that such stimuli, be they noisy or periodic in nature, exert a stabilizing influence on network responses, disrupting the development of such oscillations. Based on a combination of numerical simulations and mean-field analyses, our results suggest that high variance and/or high frequency stimulation waveforms can prevent multi-stability, a mathematical harbinger of sudden changes in network dynamics. By tuning the neurons’ responses to input, stimuli stabilize network dynamics away from these transitions. Furthermore, our research shows that such stabilization of neural activity occurs through a selective recruitment of inhibitory cells, providing a theoretical undergird for the known key role these cells play in both the healthy and diseased brain. Taken together, these findings provide new vistas on neuromodulatory approaches to stabilize neural microcircuit activity.

Impaired State-Dependent Potentiation of GABAergic Synaptic Currents Triggers Seizures in a Genetic Generalized Epilepsy Model

Epileptic activity in genetic generalized epilepsy (GGE) patients preferentially appears during sleep and its mechanism remains unknown. Here, we found that sleep-like slow-wave oscillations (0.5 Hz SWOs) potentiated excitatory and inhibitory synaptic currents in layer V cortical pyramidal neurons from wild-type (wt) mouse brain slices. In contrast, SWOs potentiated excitatory, but not inhibitory, currents in cortical neurons from a heterozygous (het) knock-in (KI) Gabrg2+Q/390X model of Dravet epilepsy syndrome. This created an imbalance between evoked excitatory and inhibitory currents to effectively prompt neuronal action potential firings. Similarly, physiologically similar up-/down-state induction (present during slow-wave sleep) in cortical neurons also potentiated excitatory synaptic currents within brain slices from wt and het KI mice. Moreover, this state-dependent potentiation of excitatory synaptic currents entailed some signaling pathways of homeostatic synaptic plasticity. Consequently, in het KI mice, in vivo SWO induction (using optogenetic methods) triggered generalized epileptic spike-wave discharges (SWDs), being accompanied by sudden immobility, facial myoclonus, and vibrissa twitching. In contrast, in wt littermates, SWO induction did not cause epileptic SWDs and motor behaviors. To our knowledge, this is the first mechanism to explain why epileptic SWDs preferentially happen during non rapid eye-movement sleep and quiet-wakefulness in human GGE patients.

Decreased reproducibility and abnormal experience-dependent plasticity of network dynamics in Fragile X circuits

Fragile X syndrome is a neurodevelopmental disorder associated with a broad range of neural phenotypes. Interpreting these findings has proven challenging because some phenotypes may reflect compensatory mechanisms or normal forms of plasticity differentially engaged by experiential differences. To help minimize compensatory and experiential influences, we used an ex vivo approach to study network dynamics and plasticity of cortical microcircuits. In Fmr1^−/y circuits, the spatiotemporal structure of Up-states was less reproducible, suggesting alterations in the plasticity mechanisms governing network activity. Chronic optical stimulation revealed normal homeostatic plasticity of Up-states, however, Fmr1^−/y circuits exhibited abnormal experience-dependent plasticity as they did not adapt to chronically presented temporal patterns in an interval-specific manner. These results, suggest that while homeostatic plasticity is normal, Fmr1^−/y circuits exhibit deficits in the ability to orchestrate multiple forms of synaptic plasticity and to adapt to sensory patterns in an experience-dependent manner—which is likely to contribute to learning deficits.

Diversity and function of corticopetal and corticofugal GABAergic projection neurons

It is still widely thought that cortical projections to distant brain areas derive by and large from glutamatergic neurons. However, an increasing number of reports provide evidence that cortical GABAergic neurons comprise a smaller population of 'projection neurons' in addition to the well-known and much-studied interneurons. GABAergic long-range axons that derive from, or project to, cortical areas are thought to entrain distant brain areas for efficient information transfer and processing. Research conducted over the past 10 years has revealed that cortical GABAergic projection neurons are highly diverse in terms of molecular marker expression, synaptic targeting (identity of targeted cell types), activity pattern during distinct behavioural states and precise temporal recruitment relative to ongoing neuronal network oscillations. As GABAergic projection neurons connect many cortical areas unidirectionally or bidirectionally, it is safe to assume that they participate in the modulation of a whole series of behavioural and cognitive functions. We expect future research to examine how long-range GABAergic projections fine-tune activity in distinct distant networks and how their recruitment alters the behaviours that are supported by these networks.

Inhibition stabilization is a widespread property of cortical networks

Many cortical network models use recurrent coupling strong enough to require inhibition for stabilization. Yet it has been experimentally unclear whether inhibition-stabilized network (ISN) models describe cortical function well across areas and states. Here, we test several ISN predictions, including the counterintuitive (paradoxical) suppression of inhibitory firing in response to optogenetic inhibitory stimulation. We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex. Simple two-population ISN models describe the data well and let us quantify coupling strength. Although some models predict a non-ISN to ISN transition with increasingly strong sensory stimuli, we find ISN effects without sensory stimulation and even during light anesthesia. Additionally, average paradoxical effects result only with transgenic, not viral, opsin expression in parvalbumin (PV)-positive neurons; theory and expression data show this is consistent with ISN operation. Taken together, these results show strong coupling and inhibition stabilization are common features of the cortex.

Common Principles in Functional Organization of VIP/Calretinin Cell-Driven Disinhibitory Circuits Across Cortical Areas

In the brain, there is a vast diversity of different structures, circuitries, cell types, and cellular genetic expression profiles. While this large diversity can often occlude a clear understanding of how the brain works, careful analyses of analogous studies performed across different brain areas can hint at commonalities in neuronal organization. This in turn can yield a fundamental understanding of necessary circuitry components that are crucial for how information is processed across the brain. In this review, we outline recent in vivo and in vitro studies that have been performed in different cortical areas to characterize the vasoactive intestinal polypeptide (VIP)- and/or calretinin (CR)-expressing cells that specialize in inhibiting GABAergic interneurons. In doing so, we make the case that, across cortical structures, interneuron-specific cells commonly specialize in the synaptic disinhibition of excitatory neurons, which can ungate the integration and plasticity of external inputs onto excitatory neurons. In line with this, activation of interneuron- specific cells enhances animal performance across a variety of behavioral tasks that involve learning, memory formation, and sensory discrimination, and may represent a key target for therapeutic interventions under different pathological conditions. As such, interneuron-specific cells across different cortical structures are an essential network component for information processing and normal brain function.

Structure of cortical network activity across natural wake and sleep states in mice

Cortical neurons fire intermittently and synchronously during non-rapid eye movement sleep (NREMS), in which active and silent periods are referred to as ON and OFF periods, respectively. Neuronal firing rates during ON periods (NREMS-ON-activity) are similar to those of wakefulness (W-activity), raising the possibility that NREMS-ON neuronal-activity is fragmented W-activity. To test this, we investigated the patterning and organization of cortical spike trains and of spike ensembles in neuronal networks using extracellular recordings in mice. Firing rates of neurons during NREMS-ON and W were similar, but showed enhanced bursting in NREMS with no apparent preference in occurrence, relative to the beginning or end of the on-state. Additionally, there was an overall increase in the randomness of occurrence of sequences comprised of multi-neuron ensembles in NREMS recorded from tetrodes. In association with increased burst firing, somatic calcium transients were increased in NREMS. The increased calcium transients associated with bursting during NREM may activate calcium-dependent, cell-signaling pathways for sleep related cellular processes.

Up and Down States and Memory Consolidation Across Somatosensory, Entorhinal, and Hippocampal Cortices

In the course of a day, brain states fluctuate, from conscious awake information-acquiring states to sleep states, during which previously acquired information is further processed and stored as memories. One hypothesis is that memories are consolidated and stored during "offline" states such as sleep, a process thought to involve transfer of information from the hippocampus to other cortical areas. Up and Down states (UDS), patterns of activity that occur under anesthesia and sleep states, are likely to play a role in this process, although the nature of this role remains unclear. Here we review what is currently known about these mechanisms in three anatomically distinct but interconnected cortical areas: somatosensory cortex, entorhinal cortex, and the hippocampus. In doing so, we consider the role of this activity in the coordination of "replay" during sleep states, particularly during hippocampal sharp-wave ripples. We conclude that understanding the generation and propagation of UDS may provide key insights into the cortico-hippocampal dialogue linking archi- and neocortical areas during memory formation.

Distinct subtypes of inhibitory interneurons differentially promote the propagation of rate and temporal codes in the feedforward neural network

Sensory information is believed to be encoded in neuronal spikes using two different neural codes, the rate code (spike firing rate) and the temporal code (precisely-timed spikes). Since the sensory cortex has a highly hierarchical feedforward structure, sensory information-carrying neural codes should reliably propagate across the feedforward network (FFN) of the cortex. Experimental evidence suggests that inhibitory interneurons, such as the parvalbumin-positive (PV) and somatostatin-positive (SST) interneurons, that have distinctively different electrophysiological and synaptic properties, modulate the neural codes during sensory information processing in the cortex. However, how PV and SST interneurons impact on the neural code propagation in the cortical FFN is unknown. We address this question by building a five-layer FFN model consisting of a physiologically realistic Hodgkin-Huxley-type models of excitatory neurons and PV/SST interneurons at different ratios. In response to different firing rate inputs (20-80 Hz), a higher ratio of PV over SST interneurons promoted a reliable propagation of all ranges of firing rate inputs. In contrast, in response to a range of precisely-timed spikes in the form of pulse-packets [with a different number of spikes (α, 40-400 spikes) and degree of dispersion (σ, 0-20 ms)], a higher ratio of SST over PV interneurons promoted a reliable propagation of pulse-packets. Our simulation results show that PV and SST interneurons differentially promote a reliable propagation of the rate and temporal codes, respectively, indicating that the dynamic recruitment of PV and SST interneurons may play critical roles in a reliable propagation of sensory information-carrying neural codes in the cortical FFN.

Understanding the Effects of General Anesthetics on Cortical Network Activity Using Ex Vivo Preparations

General anesthetics have been used to ablate consciousness during surgery for more than 150 yr. Despite significant advances in our understanding of their molecular-level pharmacologic effects, comparatively little is known about how anesthetics alter brain dynamics to cause unconsciousness. Consequently, while anesthesia practice is now routine and safe, there are many vagaries that remain unexplained. In this paper, the authors review the evidence that cortical network activity is particularly sensitive to general anesthetics, and suggest that disruption to communication in, and/or among, cortical brain regions is a common mechanism of anesthesia that ultimately produces loss of consciousness. The authors review data from acute brain slices and organotypic cultures showing that anesthetics with differing molecular mechanisms of action share in common the ability to impair neurophysiologic communication. While many questions remain, together, ex vivo and in vivo investigations suggest that a unified understanding of both clinical anesthesia and the neural basis of consciousness is attainable.

Barrel cortex VIP/ChAT interneurons suppress sensory responses in vivo

Cortical interneurons expressing vasoactive intestinal polypeptide (VIP) and choline acetyltransferase (ChAT) are sparsely distributed throughout the neocortex, constituting only 0.5% of its neuronal population. The co-expression of VIP and ChAT suggests that these VIP/ChAT interneurons (VChIs) can release both γ-aminobutyric acid (GABA) and acetylcholine (ACh). In vitro physiological studies quantified the response properties and local connectivity patterns of the VChIs; however, the function of VChIs has not been explored in vivo. To study the role of VChIs in cortical network dynamics and their long-range connectivity pattern, we used in vivo electrophysiology and rabies virus tracing in the barrel cortex of mice. We found that VChIs have a low spontaneous spiking rate (approximately 1 spike/s) in the barrel cortex of anesthetized mice; nevertheless, they responded with higher fidelity to whisker stimulation than the neighboring layer 2/3 pyramidal neurons (Pyrs). Analysis of long-range inputs to VChIs with monosynaptic rabies virus tracing revealed that direct thalamic projections are a significant input source to these cells. Optogenetic activation of VChIs in the barrel cortex of awake mice suppresses the sensory responses of excitatory neurons in intermediate amplitudes of whisker deflections while increasing the evoked spike latency. The effect of VChI activation on the response was similar for both high-whisking (HW) and low-whisking (LW) conditions. Our findings demonstrate that, despite their sparsity, VChIs can effectively modulate sensory processing in the cortical microcircuit.

All-Optical Electrophysiology Reveals the Role of Lateral Inhibition in Sensory Processing in Cortical Layer 1

Cortical layer 1 (L1) interneurons have been proposed as a hub for attentional modulation of underlying cortex, but the transformations that this circuit implements are not known. We combined genetically targeted voltage imaging with optogenetic activation and silencing to study the mechanisms underlying sensory processing in mouse barrel cortex L1. Whisker stimuli evoked precisely timed single spikes in L1 interneurons, followed by strong lateral inhibition. A mild aversive stimulus activated cholinergic inputs and evoked a bimodal distribution of spiking responses in L1. A simple conductance-based model that only contained lateral inhibition within L1 recapitulated the sensory responses and the winner-takes-all cholinergic responses, and the model correctly predicted that the network would function as a spatial and temporal high-pass filter for excitatory inputs. Our results demonstrate that all-optical electrophysiology can reveal basic principles of neural circuit function in vivo and suggest an intuitive picture for how L1 transforms sensory and modulatory inputs. VIDEO ABSTRACT.