Rapid neocortical dynamics: cellular and network mechanisms

How many neurons are sufficient for perception of cortical activity?

Many theories of brain function propose that activity in sparse subsets of neurons underlies perception and action. To place a lower bound on the amount of neural activity that can be perceived, we used an all-optical approach to drive behaviour with targeted two-photon optogenetic activation of small ensembles of L2/3 pyramidal neurons in mouse barrel cortex while simultaneously recording local network activity with two-photon calcium imaging. By precisely titrating the number of neurons stimulated, we demonstrate that the lower bound for perception of cortical activity is ~14 pyramidal neurons. We find a steep sigmoidal relationship between the number of activated neurons and behaviour, saturating at only ~37 neurons, and show this relationship can shift with learning. Furthermore, activation of ensembles is balanced by inhibition of neighbouring neurons. This surprising perceptual sensitivity in the face of potent network suppression supports the sparse coding hypothesis, and suggests that cortical perception balances a trade-off between minimizing the impact of noise while efficiently detecting relevant signals.

Prefrontal Neural Ensembles Develop Selective Code for Stimulus Associations within Minutes of Novel Experiences

Prevailing theories posit that the hippocampus rapidly learns stimulus conjunctions during novel experiences, whereas the neocortex learns slowly through subsequent, off-line interaction with the hippocampus. Parallel evidence, however, shows that the medial prefrontal cortex (mPFC; a critical node of the neocortical network supporting long-term memory storage) undergoes rapid modifications of gene expression, synaptic structure, and physiology at the time of encoding. These observations, along with impaired learning with disrupted mPFC, suggest that mPFC neurons may exhibit rapid neural plasticity during novel experiences; however, direct empirical evidence is lacking. We extracellularly recorded action potentials of cells in the prelimbic region of the mPFC, while male rats received a sequence of stimulus presentations for the first time in life. Moment-to-moment tracking of neural ensemble firing patterns revealed that the prelimbic network activity exhibited an abrupt transition within 1 min after the first encounter of an aversive but not neutral stimulus. This network-level change was driven by ∼15% of neurons that immediately elevated their spontaneous firing rates (FRs) and developed firing responses to a neutral stimulus preceding the aversive stimulus within a few instances of their pairings. When a new sensory stimulus was paired with the same aversive stimulus, about half of these neurons generalized firing responses to the new stimulus association. Thus, prelimbic neurons are capable of rapidly forming ensemble codes for novel stimulus associations within minutes. This circuit property may enable the mPFC to rapidly detect and selectively encode the central content of novel experiences.SIGNIFICANCE STATEMENT During a new experience, a region of the brain, called the hippocampus, rapidly forms its memory and later instructs another region, called the neocortex, that stores its content. Consistent with this dominant view, cells in the neocortex gradually strengthen the selectivity for the memory content over weeks after novel experiences. However, we still do not know precisely when these cells begin to develop the selectivity. We found that neocortical cells were capable of forming the selectivity for ongoing events within a few minutes of new experiences. This finding provides support for an alternative view that the neocortex works with, but not follows, the hippocampus to form new memories.

Interstitial ions: A key regulator of state-dependent neural activity?

Throughout the nervous system, ion gradients drive fundamental processes. Yet, the roles of interstitial ions in brain functioning is largely forgotten. Emerging literature is now revitalizing this area of neuroscience by showing that interstitial cations (K+, Ca2+ and Mg2+) are not static quantities but change dynamically across states such as sleep and locomotion. In turn, these state-dependent changes are capable of sculpting neuronal activity; for example, changing the local interstitial ion composition in the cortex is sufficient for modulating the prevalence of slow-frequency neuronal oscillations, or potentiating the gain of visually evoked responses. Disturbances in interstitial ionic homeostasis may also play a central role in the pathogenesis of central nervous system diseases. For example, impairments in K+ buffering occur in a number of neurodegenerative diseases, and abnormalities in neuronal activity in disease models disappear when interstitial K+ is normalized. Here we provide an overview of the roles of interstitial ions in physiology and pathology. We propose the brain uses interstitial ion signaling as a global mechanism to coordinate its complex activity patterns, and ion homeostasis failure contributes to central nervous system diseases affecting cognitive functions and behavior.

Astroglial FMRP modulates synaptic signaling and behavior phenotypes in FXS mouse model

Fragile X syndrome (FXS) is one of the most common inherited intellectual disability (ID) disorders, in which the loss of FMRP protein induces a range of cellular signaling changes primarily through excess protein synthesis. Although neuron-centered molecular and cellular events underlying FXS have been characterized, how different CNS cell types are involved in typical FXS synaptic signaling changes and behavioral phenotypes is largely unknown. Recent evidence suggests that selective loss of astroglial FMRP is able to dysregulate glutamate uptake, increase spine density, and impair motor-skill learning. Here we investigated the effect of astroglial FMRP on synaptic signaling and FXS-related behavioral and learning phenotypes in astroglial Fmr1 cKO and cON mice in which FMRP expression is selectively diminished or restored in astroglia. We found that selective loss of astroglial FMRP contributes to cortical hyperexcitability by enhancing NMDAR-mediated evoked but not spontaneous miniEPSCs and elongating cortical UP state duration. Selective loss of astroglial FMRP is also sufficient to increase locomotor hyperactivity, significantly diminish social novelty preference, and induce memory acquisition and extinction deficits in astroglial Fmr1 cKO mice. Importantly, re-expression of astroglial FMRP is able to significantly rescue the hyperactivity (evoked NMDAR response, UP state duration, and open field test) and social novelty preference in astroglial Fmr1 cON mice. These results demonstrate a profound role of astroglial FMRP in the evoked synaptic signaling, spontaneously occurring cortical UP states, and FXS-related behavioral and learning phenotypes and provide important new insights in the cell type consideration for the FMRP reactivation strategy.

Can REM Sleep Localize the Epileptogenic Zone? A Systematic Review and Analysis

Epilepsy is a common and debilitating neurological disease. When medication cannot control seizures in up to 40% of cases, surgical resection of epileptogenic tissue is a clinically and cost- effective therapy to achieve seizure freedom. To simultaneously resect minimal yet sufficient cortex, exquisite localization of the epileptogenic zone (EZ) is crucial. However, localization is not straightforward, given relative difficulty of capturing seizures, constraints of the inverse problem in source localization, and possible disparate locations of symptomatogenic vs. epileptogenic regions. Thus, attention has been paid to which state of vigilance best localizes the EZ, in the hopes that one or another sleep-wake state may hold the key to improved accuracy of localization. Studies investigating this topic have employed diverse methodologies and produced diverse results. Nonetheless, rapid eye movement sleep (REM) has emerged as a promising sleep-wake state, as epileptic phenomena captured in REM may spatially correspond more closely to the EZ. Cortical neuronal asynchrony in REM may spatially constrain epileptic phenomena to reduce propagation away from the source generator, rendering them of high localizing value. However, some recent work demonstrates best localization in sleep-wake states other than REM, and there are reports of REM providing clearly false localization. Moreover, synchronistic properties and basic mechanisms of human REM remain to be fully characterized. Amidst these uncertainties, there is an urgent need for recording and analytical techniques to improve accuracy of localization. Here we present a systematic review and quantitative analysis of pertinent literature on whether and how REM may help localize epileptogenic foci. To help streamline and accelerate future work on the intriguing anti-epileptic properties of REM, we also introduce a simple, conceptually clear set-theoretic framework to conveniently and rigorously describe the spatial properties of epileptic phenomena in the brain.

Slow Wave Sleep Is a Promising Intervention Target for Alzheimer's Disease

Alzheimer's disease (AD) is the major cause of dementia, characterized by the presence of amyloid-beta plaques and neurofibrillary tau tangles. Plaques and tangles are associated with sleep-wake cycle disruptions, including the disruptions in non-rapid eye movement (NREM) slow wave sleep (SWS). Alzheimer's patients spend less time in NREM sleep and exhibit decreased slow wave activity (SWA). Consistent with the critical role of SWS in memory consolidation, reduced SWA is associated with impaired memory consolidation in AD patients. The aberrant SWA can be modeled in transgenic mouse models of amyloidosis and tauopathy. Animal models exhibited slow wave impairments early in the disease progression, prior to the deposition of amyloid-beta plaques, however, in the presence of abundant oligomeric amyloid-beta. Optogenetic rescue of SWA successfully halted the amyloid accumulation and restored intraneuronal calcium levels in mice. On the other hand, optogenetic acceleration of slow wave frequency exacerbated amyloid deposition and disrupted neuronal calcium homeostasis. In this review, we summarize the evidence and the mechanisms underlying the existence of a positive feedback loop between amyloid/tau pathology and SWA disruptions that lead to further accumulations of amyloid and tau in AD. Moreover, since SWA disruptions occur prior to the plaque deposition, SWA disruptions may provide an early biomarker for AD. Finally, we propose that therapeutic targeting of SWA in AD might lead to an effective treatment for Alzheimer's patients.

Dynamic representations in networked neural systems

A group of neurons can generate patterns of activity that represent information about stimuli; subsequently, the group can transform and transmit activity patterns across synapses to spatially distributed areas. Recent studies in neuroscience have begun to independently address the two components of information processing: the representation of stimuli in neural activity and the transmission of information in networks that model neural interactions. Yet only recently are studies seeking to link these two types of approaches. Here we briefly review the two separate bodies of literature; we then review the recent strides made to address this gap. We continue with a discussion of how patterns of activity evolve from one representation to another, forming dynamic representations that unfold on the underlying network. Our goal is to offer a holistic framework for understanding and describing neural information representation and transmission while revealing exciting frontiers for future research.

Shaping the Cortical Landscape: Functions and Mechanisms of Top-Down Cortical Feedback Pathways

Cortical feedback pathways are proposed to guide cognition and behavior according to context and goal-direction. At the cellular level, cortical feedback pathways target multiple excitatory and inhibitory populations. However, we currently lack frameworks that link how the cellular mechanisms of cortical feedback pathways underlie their cognitive/behavioral functions. To establish this link, we expand on the framework of signal routing, the ability of cortical feedback pathways to proactively modulate how feedforward signals are propagated throughout the cortex. We propose that cortical feedback modulates routing through multiple mechanisms: preparing intended motor representations, setting the trigger conditions for evoking cortical outputs, altering coupling strengths between cortical regions, and suppressing expected sensory representations. In developing this framework, we first define the anatomy of cortical feedback pathways and identify recent advances in studying their functions at high specificity and resolution. Second, we review the diverse functions of cortical feedback pathways throughout the cortical hierarchy and evaluate these functions from the framework of signal routing. Third, we review the conserved cellular targets and circuit impacts of cortical feedback. Fourth, we introduce the concept of the “cortical landscape,” a graphical depiction of the routes through cortex that are favored at a specific moment in time. We propose that the cortical landscape, analogous to energy landscapes in physics and chemistry, can capture important features of signal routing including coupling strength, trigger conditions, and preparatory states. By resolving the cortical landscape, we may be able to quantify how the cellular processes of cortical feedback ultimately shape cognition and behavior.

Examining fMRI time-series entropy as a marker for brain E/I balance with pharmacological neuromodulation in a non-human primate translational model

Recently, there has been a lot of interest in the neuroimaging community in exploring fMRI time-series measures of local neuronal activity and excitation/inhibition (E/I) balance in the brain. In this preliminary study we probed the sensitivity of widely used sample entropy (SE) measure at multiple scales to controlled alteration of the brain's E/I balance in non-human primates (NHPs) with a well-characterized sub-anesthetic ketamine infusion fMRI model. We found that SE failed to detect the expected changes in E/I balance induced by ketamine. Subsequently, noticing that the complexity in the time series contributing SE could be dominated by non-neuronal noise in this experimental setting, we developed a new time-series measure called restricted sample entropy (RSE) by restricting SE estimations to regular portions of the fMRI time-series. RSE was able to adequately reflect the increased excitatory activity engendered by disinhibition of glutamergic neurons, through sub-anesthetic ketamine infusion. These results show that RSE is potentially a powerful tool for examining local neural activity, E/I balance, and alterations in brain state.

Selective inhibition of glycogen synthase kinase 3α corrects pathophysiology in a mouse model of fragile X syndrome

Fragile X syndrome is caused by FMR1 gene silencing and loss of the encoded fragile X mental retardation protein (FMRP), which binds to mRNA and regulates translation. Studies in the Fmr1-/y mouse model of fragile X syndrome indicate that aberrant cerebral protein synthesis downstream of metabotropic glutamate receptor 5 (mGluR5) signaling contributes to disease pathogenesis, but clinical trials using mGluR5 inhibitors were not successful. Animal studies suggested that treatment with lithium might be an alternative approach. Targets of lithium include paralogs of glycogen synthase kinase 3 (GSK3), and nonselective small-molecule inhibitors of these enzymes improved disease phenotypes in a fragile X syndrome mouse model. However, the potential therapeutic use of GSK3 inhibitors has been hampered by toxicity arising from inhibition of both α and β paralogs. Recently, we developed GSK3 inhibitors with sufficient paralog selectivity to avoid a known toxic consequence of dual inhibition, that is, increased β-catenin stabilization. We show here that inhibition of GSK3α, but not GSK3β, corrected aberrant protein synthesis, audiogenic seizures, and sensory cortex hyperexcitability in Fmr1-/y mice. Although inhibiting either paralog prevented induction of NMDA receptor-dependent long-term depression (LTD) in the hippocampus, only inhibition of GSK3α impaired mGluR5-dependent and protein synthesis-dependent LTD. Inhibition of GSK3α additionally corrected deficits in learning and memory in Fmr1-/y mice; unlike mGluR5 inhibitors, there was no evidence of tachyphylaxis or enhanced psychotomimetic-induced hyperlocomotion. GSK3α selective inhibitors may have potential as a therapeutic approach for treating fragile X syndrome.

Presynaptic dopamine deficit in minimally conscious state patients following traumatic brain injury

Dopaminergic stimulation has been proposed as a treatment strategy for post-traumatic brain injured patients in minimally conscious state based on a clinical trial using amantadine, a weak dopamine transporter blocker. However, a specific contribution of dopaminergic neuromodulation in minimally conscious state is undemonstrated. In a phase 0 clinical trial, we evaluated 13 normal volunteers and seven post-traumatic minimally conscious state patients using 11C-raclopride PET to estimate dopamine 2-like receptors occupancy in the striatum and central thalamus before and after dopamine transporter blockade with dextroamphetamine. If a presynaptic deficit was observed, a third and a fourth 11C-raclopride PET were acquired to evaluate changes in dopamine release induced by l-DOPA and l-DOPA+dextroamphetamine. Permutation analysis showed a significant reduction of dopamine release in patients, demonstrating a presynaptic deficit in the striatum and central thalamus that could not be reversed by blocking the dopamine transporter. However, administration of the dopamine precursor l-DOPA reversed the presynaptic deficit by restoring the biosynthesis of dopamine from both ventral tegmentum and substantia nigra. The advantages of alternative pharmacodynamic approaches in post-traumatic minimally conscious state patients should be tested in clinical trials, as patients currently refractory to amantadine might benefit from them.

Chloride dynamics alter the input-output properties of neurons

Fast synaptic inhibition is a critical determinant of neuronal output, with subcellular targeting of synaptic inhibition able to exert different transformations of the neuronal input-output function. At the receptor level, synaptic inhibition is primarily mediated by chloride-permeable Type A GABA receptors. Consequently, dynamics in the neuronal chloride concentration can alter the functional properties of inhibitory synapses. How differences in the spatial targeting of inhibitory synapses interact with intracellular chloride dynamics to modulate the input-output function of neurons is not well understood. To address this, we developed computational models of multi-compartment neurons that incorporate experimentally parametrised mechanisms to account for neuronal chloride influx, diffusion, and extrusion. We found that synaptic input (either excitatory, inhibitory, or both) can lead to subcellular variations in chloride concentration, despite a uniform distribution of chloride extrusion mechanisms. Accounting for chloride changes resulted in substantial alterations in the neuronal input-output function. This was particularly the case for peripherally targeted dendritic inhibition where dynamic chloride compromised the ability of inhibition to offset neuronal input-output curves. Our simulations revealed that progressive changes in chloride concentration mean that the neuronal input-output function is not static but varies significantly as a function of the duration of synaptic drive. Finally, we found that the observed effects of dynamic chloride on neuronal output were mediated by changes in the dendritic reversal potential for GABA. Our findings provide a framework for understanding the computational effects of chloride dynamics on dendritically targeted synaptic inhibition.

Progressive alignment of inhibitory and excitatory delay may drive a rapid developmental switch in cortical network dynamics

Nervous system maturation occurs on multiple levels-synaptic, circuit, and network-at divergent timescales. For example, many synaptic properties mature gradually, whereas emergent network dynamics can change abruptly. Here we combine experimental and theoretical approaches to investigate a sudden transition in spontaneous and sensory evoked thalamocortical activity necessary for the development of vision. Inspired by in vivo measurements of timescales and amplitudes of synaptic currents, we extend the Wilson and Cowan model to take into account the relative onset timing and amplitudes of inhibitory and excitatory neural population responses. We study this system as these parameters are varied within amplitudes and timescales consistent with developmental observations to identify the bifurcations of the dynamics that might explain the network behaviors in vivo. Our findings indicate that the inhibitory timing is a critical determinant of thalamocortical activity maturation; a gradual decay of the ratio of inhibitory to excitatory onset time drives the system through a bifurcation that leads to a sudden switch of the network spontaneous activity from high-amplitude oscillations to a nonoscillatory active state. This switch also drives a change from a threshold bursting to linear response to transient stimuli, also consistent with in vivo observation. Thus we show that inhibitory timing is likely critical to the development of network dynamics and may underlie rapid changes in activity without similarly rapid changes in the underlying synaptic and cellular parameters.NEW & NOTEWORTHY Relying on a generalization of the Wilson-Cowan model, which allows a solid analytic foundation for the understanding of the link between maturation of inhibition and network dynamics, we propose a potential explanation for the role of developing excitatory/inhibitory synaptic delays in mediating a sudden switch in thalamocortical visual activity preceding vision onset.

Cortical State Fluctuations across Layers of V1 during Visual Spatial Perception

Many factors modulate the state of cortical activity, but the importance of cortical state variability for sensory perception remains debated. We trained mice to detect spatially localized visual stimuli and simultaneously measured local field potentials and excitatory and inhibitory neuron populations across layers of primary visual cortex (V1). Cortical states with low spontaneous firing and correlations in excitatory neurons, and suppression of 3- to 7-Hz oscillations in layer 4, accurately predicted single-trial visual detection. Our results show that cortical states exert strong effects at the initial stage of cortical processing in V1 and can play a prominent role for visual spatial behavior in mice.

Neuromodulation of Brain State and Behavior

Neural activity and behavior are both notoriously variable, with responses differing widely between repeated presentation of identical stimuli or trials. Recent results in humans and animals reveal that these variations are not random in their nature, but may in fact be due in large part to rapid shifts in neural, cognitive, and behavioral states. Here we review recent advances in the understanding of rapid variations in the waking state, how variations are generated, and how they modulate neural and behavioral responses in both mice and humans. We propose that the brain has an identifiable set of states through which it wanders continuously in a nonrandom fashion, owing to the activity of both ascending modulatory and fast-acting corticocortical and subcortical-cortical neural pathways. These state variations provide the backdrop upon which the brain operates, and understanding them is critical to making progress in revealing the neural mechanisms underlying cognition and behavior.

Interneuron NMDA Receptor Ablation Induces Hippocampus-Prefrontal Cortex Functional Hypoconnectivity after Adolescence in a Mouse Model of Schizophrenia

Although the etiology of schizophrenia is still unknown, it is accepted to be a neurodevelopmental disorder that results from the interaction of genetic vulnerabilities and environmental insults. Although schizophrenia's pathophysiology is still unclear, postmortem studies point toward a dysfunction of cortical interneurons as a central element. It has been suggested that alterations in parvalbumin-positive interneurons in schizophrenia are the consequence of a deficient signaling through NMDARs. Animal studies demonstrated that early postnatal ablation of the NMDAR in corticolimbic interneurons induces neurobiochemical, physiological, behavioral, and epidemiological phenotypes related to schizophrenia. Notably, the behavioral abnormalities emerge only after animals complete their maturation during adolescence and are absent if the NMDAR is deleted during adulthood. This suggests that interneuron dysfunction must interact with development to impact on behavior. Here, we assess in vivo how an early NMDAR ablation in corticolimbic interneurons impacts on mPFC and ventral hippocampus functional connectivity before and after adolescence. In juvenile male mice, NMDAR ablation results in several pathophysiological traits, including increased cortical activity and decreased entrainment to local gamma and distal hippocampal theta rhythms. In addition, adult male KO mice showed reduced ventral hippocampus-mPFC-evoked potentials and an augmented low-frequency stimulation LTD of the pathway, suggesting that there is a functional disconnection between both structures in adult KO mice. Our results demonstrate that early genetic abnormalities in interneurons can interact with postnatal development during adolescence, triggering pathophysiological mechanisms related to schizophrenia that exceed those caused by NMDAR interneuron hypofunction alone.SIGNIFICANCE STATEMENT NMDAR hypofunction in cortical interneurons has been linked to schizophrenia pathophysiology. How a dysfunction of GABAergic cortical interneurons interacts with maturation during adolescence has not been clarified yet. Here, we demonstrate in vivo that early postnatal ablation of the NMDAR in corticolimbic interneurons results in an overactive but desynchronized PFC before adolescence. Final postnatal maturation during this stage outspreads the impact of the genetic manipulation toward a functional disconnection of the ventral hippocampal-prefrontal pathway, probably as a consequence of an exacerbated propensity toward hippocampal-evoked depotentiation plasticity. Our results demonstrate a complex interaction between genetic and developmental factors affecting cortical interneurons and PFC function.

Whole-Neuron Synaptic Mapping Reveals Spatially Precise Excitatory/Inhibitory Balance Limiting Dendritic and Somatic Spiking

The balance between excitatory and inhibitory (E and I) synapses is thought to be critical for information processing in neural circuits. However, little is known about the spatial principles of E and I synaptic organization across the entire dendritic tree of mammalian neurons. We developed a new open-source reconstruction platform for mapping the size and spatial distribution of E and I synapses received by individual genetically-labeled layer 2/3 (L2/3) cortical pyramidal neurons (PNs) in vivo. We mapped over 90,000 E and I synapses across twelve L2/3 PNs and uncovered structured organization of E and I synapses across dendritic domains as well as within individual dendritic segments. Despite significant domain-specific variation in the absolute density of E and I synapses, their ratio is strikingly balanced locally across dendritic segments. Computational modeling indicates that this spatially precise E/I balance dampens dendritic voltage fluctuations and strongly impacts neuronal firing output.

Transient neocortical gamma oscillations induced by neuronal response modulation

In this paper a mean field model of spatio-temporal electroencephalographic activity in the neocortex is used to computationally study the emergence of neocortical gamma oscillations as a result of neuronal response modulation. It is shown using a numerical bifurcation analysis that gamma oscillations emerge robustly in the solutions of the model and transition to beta oscillations through coordinated modulation of the responsiveness of inhibitory and excitatory neuronal populations. The spatio-temporal pattern of the propagation of these oscillations across the neocortex is illustrated by solving the equations of the model using a finite element software package. Thereby, it is shown that the gamma oscillations remain localized to the regions of neuronal modulation. Moreover, it is discussed that the inherent spatial averaging effect of commonly used electrocortical measurement techniques can significantly alter the amplitude and pattern of fast oscillations in neocortical recordings, and hence can potentially affect physiological interpretations of these recordings.

GABA-mediated tonic inhibition differentially modulates gain in functional subtypes of cortical interneurons

The binding of GABA (γ-aminobutyric acid) to extrasynaptic GABA_A receptors generates tonic inhibition that acts as a powerful modulator of cortical network activity. Despite GABA being present throughout the extracellular space of the brain, previous work has shown that GABA may differentially modulate the excitability of neuron subtypes according to variation in chloride gradient. Here, using biophysically detailed neuron models, we predict that tonic inhibition can differentially modulate the excitability of neuron subtypes according to variation in electrophysiological properties. Surprisingly, tonic inhibition increased the responsiveness (or gain) in models with features typical for somatostatin interneurons but decreased gain in models with features typical for parvalbumin interneurons. Patch-clamp recordings from cortical interneurons supported these predictions, and further in silico analysis was then performed to seek a putative mechanism underlying gain modulation. We found that gain modulation in models was dependent upon the magnitude of tonic current generated at depolarized membrane potential-a property associated with outward rectifying GABA_A receptors. Furthermore, tonic inhibition produced two biophysical changes in models of relevance to neuronal excitability: 1) enhanced action potential repolarization via increased current flow into the dendritic compartment, and 2) reduced activation of voltage-dependent potassium channels. Finally, we show theoretically that reduced potassium channel activation selectively increases gain in models possessing action potential dynamics typical for somatostatin interneurons. Potassium channels in parvalbumin-type models deactivate rapidly and are unavailable for further modulation. These findings show that GABA can differentially modulate interneuron excitability and suggest a mechanism through which this occurs in silico via differences of intrinsic electrophysiological properties.

Mechanisms underlying gain modulation in the cortex

Cortical gain regulation allows neurons to respond adaptively to changing inputs. Neural gain is modulated by internal and external influences, including attentional and arousal states, motor activity and neuromodulatory input. These influences converge to a common set of mechanisms for gain modulation, including GABAergic inhibition, synaptically driven fluctuations in membrane potential, changes in cellular conductance and changes in other biophysical neural properties. Recent work has identified GABAergic interneurons as targets of neuromodulatory input and mediators of state-dependent gain modulation. Here, we review the engagement and effects of gain modulation in the cortex. We highlight key recent findings that link phenomenological observations of gain modulation to underlying cellular and circuit-level mechanisms. Finally, we place these cellular and circuit interactions in the larger context of their impact on perception and cognition.

Cholinergic Modulation Promotes Attentional Modulation in Primary Visual Cortex- A Modeling Study

Attention greatly influences sensory neural processing by enhancing firing rates of neurons that represent the attended stimuli and by modulating their tuning properties. The cholinergic system is believed to partly mediate the attention contingent improvement of cortical processing by influencing neuronal excitability, synaptic transmission and neural network characteristics. Here, we used a biophysically based model to investigate the mechanisms by which cholinergic system influences sensory information processing in the primary visual cortex (V1) layer 4C. The physiological properties and architectures of our model were inspired by experimental data and include feed-forward input from dorsal lateral geniculate nucleus that sets up orientation preference in V1 neural responses. When including a cholinergic drive, we found significant sharpening in orientation selectivity, desynchronization of LFP gamma power and spike-field coherence, decreased response variability and correlation reduction mostly by influencing intracortical interactions and by increasing inhibitory drive. Our results indicated that these effects emerged due to changes specific to the behavior of the inhibitory neurons. The behavior of our model closely resembles the effects of attention on neural activities in monkey V1. Our model suggests precise mechanisms through which cholinergic modulation may mediate the effects of attention in the visual cortex.

Local cortical desynchronization and pupil-linked arousal differentially shape brain states for optimal sensory performance

Instantaneous brain states have consequences for our sensation, perception, and behaviour. Fluctuations in arousal and neural desynchronization likely pose perceptually relevant states. However, their relationship and their relative impact on perception is unclear. We here show that, at the single-trial level in humans, local desynchronization in sensory cortex (expressed as time-series entropy) versus pupil-linked arousal differentially impact perceptual processing. While we recorded electroencephalography (EEG) and pupillometry data, stimuli of a demanding auditory discrimination task were presented into states of high or low desynchronization of auditory cortex via a real-time closed-loop setup. Desynchronization and arousal distinctly influenced stimulus-evoked activity and shaped behaviour displaying an inverted u-shaped relationship: States of intermediate desynchronization elicited minimal response bias and fastest responses, while states of intermediate arousal gave rise to highest response sensitivity. Our results speak to a model in which independent states of local desynchronization and global arousal jointly optimise sensory processing and performance.

Layer 2/3 Pyramidal Neurons Control the Gain of Cortical Output

Initial anatomical and physiological studies suggested that sensory information relayed from the periphery by the thalamus is serially processed in primary sensory cortical areas. It is thought to propagate from layer 4 (L4) up to L2/3 and down to L5, which constitutes the main output of the cortex. However, more recent experiments point toward the existence of a direct processing of thalamic input by L5 neurons. Therefore, the role of L2/3 neurons in the sensory processing operated by L5 neurons is now highly debated. Using cell type-specific and reversible optogenetic manipulations in the somatosensory cortex of both anesthetized and awake mice, we demonstrate that L2/3 pyramidal neurons play a major role in amplifying sensory-evoked responses in L5 neurons. The amplification effect scales with the velocity of the sensory stimulus, indicating that L2/3 pyramidal neurons implement gain control in deep-layer neurons.

The asynchronous state's relation to large-scale potentials in cortex

Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.

A Distinct Class of Bursting Neurons with Strong Gamma Synchronization and Stimulus Selectivity in Monkey V1

Cortical computation depends on interactions between excitatory and inhibitory neurons. The contributions of distinct neuron types to sensory processing and network synchronization in primate visual cortex remain largely undetermined. We show that in awake monkey V1, there exists a distinct cell type (››30% of neurons) that has narrow-waveform (NW) action potentials and high spontaneous discharge rates and fires in high-frequency bursts. These neurons are more stimulus selective and phase locked to 30- to 80-Hz gamma oscillations than other neuron types. Unlike other neuron types, their gamma-phase locking is highly predictive of orientation tuning. We find evidence for strong rhythmic inhibition in these neurons, suggesting that they interact with interneurons to act as excitatory pacemakers for the V1 gamma rhythm. We did not find a similar class of NW bursting neurons in L2-L4 of mouse V1. Given its properties, this class of NW bursting neurons should be pivotal for the encoding and transmission of stimulus information.

Cellular and synaptic phenotypes lead to disrupted information processing in Fmr1-KO mouse layer 4 barrel cortex

Sensory hypersensitivity is a common and debilitating feature of neurodevelopmental disorders such as Fragile X Syndrome (FXS). How developmental changes in neuronal function culminate in network dysfunction that underlies sensory hypersensitivities is unknown. By systematically studying cellular and synaptic properties of layer 4 neurons combined with cellular and network simulations, we explored how the array of phenotypes in Fmr1-knockout (KO) mice produce circuit pathology during development. We show that many of the cellular and synaptic pathologies in Fmr1-KO mice are antagonistic, mitigating circuit dysfunction, and hence may be compensatory to the primary pathology. Overall, the layer 4 network in the Fmr1-KO exhibits significant alterations in spike output in response to thalamocortical input and distorted sensory encoding. This developmental loss of layer 4 sensory encoding precision would contribute to subsequent developmental alterations in layer 4-to-layer 2/3 connectivity and plasticity observed in Fmr1-KO mice, and circuit dysfunction underlying sensory hypersensitivity.

Locus coeruleus-norepinephrine modulation of sensory processing and perception: A focused review

The locus coeruleus-norepinephrine (LC-NE) system is involved in many brain functions and neurological disorders. In this review we discuss how LC-NE signaling affects the activity of cortical and subcortical sensory neurons, and how it influences perception-driven behaviors associated with mammalian somatosensory, visual, auditory, and olfactory systems. We summarize the consistent as well as seemingly inconsistent findings across brain areas and sensory modalities and propose a framework to understand these phenomena from the perspective of adrenergic receptor expression, dose-dependent physiology and excitation-inhibition balance. We also discuss potential future research directions in this field.

GABAergic modulation of serotonergic neurons in the dorsal raphe nucleus

The dorsal raphe nucleus (DRN), located in the brainstem, is involved in several functions such as sleep, temperature regulation, stress responses, and anxiety behaviors. This nucleus contains the largest population of serotonin expressing neurons in the brain. Serotonergic DRN neurons receive tonic γ-aminobutyric acid (GABA)inhibitory inputs from several brain areas, as well as from interneurons within the same nucleus. Serotonergic and GABAergic neurons in the DRN can be distinguished by their size, location, pharmacological responses, and electrophysiological properties. GABAergic neurons regulate the excitability of DRN serotonergic neurons and the serotonin release in different brain areas. Also, it has been shown that GABAergic neurons can synchronize the activity of serotonergic neurons across functions such as sleep or alertness. Moreover, dysregulation of GABA signaling in the DRN has been linked to psychiatric disorders such as anxiety and depression. This review focuses on GABAergic transmission in the DRN. The interaction between GABAergic and serotonergic neurons is discussed considering some physiological implications. Also, the main electrophysiological and morphological characteristics of serotonergic and GABAergic neurons are described.

Noise sharing and Mexican-hat coupling in a stochastic neural field

A diffusion-type coupling operator that is biologically significant in neuroscience is a difference of Gaussian functions (Mexican-hat operator) used as a spatial-convolution kernel. We are interested in pattern formation by stochastic neural field equations, a class of space-time stochastic differential-integral equations using the Mexican-hat kernel. We explore quantitatively how the parameters that control the shape of the coupling kernel, the coupling strength, and aspects of spatially smoothed space-time noise influence the pattern in the resulting evolving random field. We confirm that a spatial pattern that is damped in time in a deterministic system may be sustained and amplified by stochasticity. We find that spatially smoothed noise alone causes pattern formation even without direct spatial coupling. Our analysis of the interaction between coupling and noise sharing allows us to determine parameter combinations that are optimal for the formation of spatial pattern.

Can Oscillatory Alpha-Gamma Phase-Amplitude Coupling be Used to Understand and Enhance TMS Effects?

Recent applications of simultaneous scalp electroencephalography (EEG) and transcranial magnetic stimulation (TMS) suggest that adapting stimulation to underlying brain states may enhance neuroplastic effects of TMS. It is often assumed that longer-lasting effects of TMS on brain function may be mediated by phasic interactions between TMS pulses and endogenous cortical oscillatory dynamics. The mechanisms by which TMS exerts its neuromodulatory effects, however, remain unknown. Here, we discuss evidence concerning the functional effects on synaptic plasticity of oscillatory cross-frequency coupling in cortical networks as a potential framework for understanding the neuromodulatory effects of TMS. We first discuss evidence for interactions between endogenous oscillatory brain dynamics and externally induced electromagnetic field activity. Alpha band (8-12 Hz) activities are of special interest here because of the wide application and therapeutic effectiveness of rhythmic TMS (rTMS) using a stimulus repetition frequency at or near 10 Hz. We discuss the large body of literature on alpha oscillations suggesting that alpha oscillatory cycles produce periodic inhibition or excitation of neuronal processing through phase-amplitude coupling (PAC) of low-frequency oscillations with high-frequency broadband (or gamma) bursting. Such alpha-gamma coupling may reflect excitability of neuronal ensembles underlying neuroplasticity effects of TMS. We propose that TMS delivery with simultaneous EEG recording and near real-time estimation of source-resolved alpha-gamma PAC might be used to select the precise timing of TMS pulse deliveries so as to enhance the neuroplastic effects of TMS therapies.

Cortex-wide Changes in Extracellular Potassium Ions Parallel Brain State Transitions in Awake Behaving Mice

Brain state fluctuations modulate sensory processing, but the factors governing state-dependent neural activity remain unclear. Here, we tracked the dynamics of cortical extracellular K+ concentrations ([K+]o) during awake state transitions and manipulated [K+]o in slices, during visual processing, and during skilled motor execution. When mice transitioned from quiescence to locomotion, [K+]o increased by 0.6-1.0 mM in all cortical areas analyzed, and this preceded locomotion by 1 s. Emulating the state-dependent [K+]o increase in cortical slices caused neuronal depolarization and enhanced input-output transformation. In vivo, locomotion increased the gain of visually evoked responses in layer 2/3 of visual cortex; this effect was recreated by imposing a [K+]o increase. Elevating [K+]o in the motor cortex increased movement-induced neuronal spiking in layer 5 and improved motor performance. Thus, [K+]o increases in a cortex-wide state-dependent manner, and this [K+]o increase affects both sensory and motor processing through the dynamic modulation of neural activity.

Short-term dynamics of input and output of CA1 network greatly differ between the dorsal and ventral rat hippocampus

Background

The functional heterogeneity of the hippocampus along its longitudinal axis at the level of behavior is an established concept; however, the neurobiological mechanisms are still unknown. Diversifications in the functioning of intrinsic hippocampal circuitry including short-term dynamics of synaptic inputs and neuronal output, that are important determinants of information processing in the brain, may profoundly contribute to functional specializations along the hippocampus. The objectives of the present study were the examination of the role of the GABA_A receptor-mediated inhibition, the μ-opioid receptors and the effect of stimulation intensity on the dynamics of both synaptic input and neuronal output of CA1 region in the dorsal and ventral hippocampus. We used recordings of field potentials from adult rat hippocampal slices evoked by brief repetitive activation of Schaffer collaterals.

Results

We find that the local CA1 circuit of the dorsal hippocampus presents a remarkably increased dynamic range of frequency-dependent short-term changes in both input and output, ranging from strong facilitation to intense depression at low and high stimulation frequencies respectively. Furthermore, the input–output relationship in the dorsal CA1 circuit is profoundly influenced by frequency and time of presynaptic activation. Strikingly, the ventral hippocampus responds mostly with depression, displaying a rather monotonous input–output relationship over frequency and time. Partial blockade of GABA_A receptor-mediated transmission (by 5 μM picrotoxin) profoundly influences input and output dynamics in the dorsal hippocampus but affected only the neuronal output in the ventral hippocampus. M-opioid receptors control short-term dynamics of input and output in the dorsal hippocampus but they play no role in the ventral hippocampus.

Conclusion

The results demonstrate that information processing by CA1 local network is highly diversified between the dorsal and ventral hippocampus. Transient detection of incoming patterns of activity and frequency-dependent sustained signaling of amplified neuronal information may be assigned to the ventral and dorsal hippocampal circuitry respectively. This disparity should have profound implications for the functional roles ascribed to distinct segments along the long axis of the hippocampus.

Electronic supplementary material

The online version of this article (10.1186/s12868-019-0517-5) contains supplementary material, which is available to authorized users.

Spontaneous Vesicle Fusion Is Differentially Regulated at Cholinergic and GABAergic Synapses

The locomotion of C. elegans is balanced by excitatory and inhibitory neurotransmitter release at neuromuscular junctions. However, the molecular mechanisms that maintain the balance of synaptic transmission remain enigmatic. Here, we investigated the function of voltage-gated Ca²⁺ channels in triggering spontaneous release at cholinergic and GABAergic synapses. Recordings of the miniature excitatory/inhibitory postsynaptic currents (mEPSCs and mIPSCs, respectively) showed that UNC-2/CaV2 and EGL-19/CaV1 channels are the two major triggers for spontaneous release. Notably, however, Ca²⁺-independent spontaneous release was observed at GABAergic but not cholinergic synapses. Functional screening led to the identification of hypomorphic unc-64/Syntaxin-1A and snb-1/VAMP2 mutants in which mEPSCs are severely impaired, whereas mIPSCs remain unaltered, indicating differential regulation of these currents at cholinergic and GABAergic synapses. Moreover, Ca²⁺-independent spontaneous GABA release was nearly abolished in the hypomorphic unc-64 and snb-1 mutants, suggesting distinct mechanisms for Ca²⁺-dependent and Ca²⁺-independent spontaneous release.

Neuroligin-2 Determines Inhibitory Synaptic Transmission in the Lateral Septum to Optimize Stress-Induced Neuronal Activation and Avoidance Behavior

BACKGROUND

Investigations in the neocortex have revealed that the balance of excitatory and inhibitory synaptic transmission (E/I ratio) is important for proper information processing. The disturbance of this balance underlies many neuropsychiatric illnesses, including autism spectrum disorder and schizophrenia. However, little is known about the contribution of E/I balance to the functioning of subcortical brain regions, such as the lateral septum (LS), a structure that plays important roles in regulating anxiety-related behavior.

METHODS

We manipulated E/I balance in the mouse LS by localized conditional deletion of neuroligin-2, a postsynaptic cell adhesion protein located at gamma-aminobutyric acidergic synapses and important for inhibitory synaptic transmission. We then performed analyses of synaptic transmission in the LS, stress-induced expression of immediate early gene c-fos, and anxiety-related and depression-related behavior.

RESULTS

The absence of neuroligin-2 in the LS in the mature mouse brain resulted in postsynaptic impairment of inhibitory synaptic transmission. Importantly, the reduced inhibition and resulting E/I imbalance decreased the responsiveness of LS neurons to stress. Furthermore, this E/I imbalance in the LS was associated with impaired stress-induced activation of downstream hypothalamic nuclei and reduced avoidance behavior of the animals in the elevated plus maze.

CONCLUSIONS

Our results described the synaptic function of neuroligin-2 in the LS, uncovered a positive association between c-Fos-expressing neurons in the LS and downstream hypothalamic areas and avoidance behavior, and demonstrated that intact inhibitory synaptic transmission and proper E/I balance are required for the optimal functioning of this subcortical circuit.

Oxygen-Glucose Deprivation Differentially Affects Neocortical Pyramidal Neurons and Parvalbumin-Positive Interneurons

Stroke is a devastating brain disorder. The pathophysiology of stroke is associated with an impaired excitation-inhibition balance in the area that surrounds the infarct core after the insult, the peri-infarct zone. Here we exposed slices from adult mouse prefrontal cortex to oxygen-glucose deprivation and reoxygenation (OGD-RO) to study ischemia-induced changes in the activity of excitatory pyramidal neurons and inhibitory parvalbumin (PV)-positive interneurons. We found that during current-clamp recordings, PV-positive interneurons were more vulnerable to OGD-RO than pyramidal neurons as indicated by the lower percentage of recovery of PV-positive interneurons. However, neither the amplitude of OGD-induced depolarization observed in current-clamp mode nor the OGD-associated current observed in voltage-clamp mode differed between the two cell types. Large amplitude, presumably action-potential dependent, spontaneous postsynaptic inhibitory currents recorded from pyramidal neurons were less frequent after OGD-RO than in control condition. Disynaptic inhibitory postsynaptic currents (dIPSCs) in pyramidal neurons produced predominantly by PV-positive interneurons were reduced by OGD-RO. Following OGD-RO, dendrites of PV-positive interneurons exhibited more pathological beading than those of pyramidal neurons. Our data support the hypothesis that the differential vulnerability to ischemia-like conditions of excitatory and inhibitory neurons leads to the altered excitation-inhibition balance associated with stroke pathophysiology.

Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales

Cortical activity is organized across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms-1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons' spiking activity and its coupling to local population rate and to arousal level across 0.01-100 Hz frequency range. In mouse medial prefrontal cortex, the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anticorrelated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of individual neurons' population coupling strength. These observations demonstrate how neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI.

Cellular switches orchestrate rhythmic circuits

Small inhibitory neuronal circuits have long been identified as key neuronal motifs to generate and modulate the coexisting rhythms of various motor functions. Our paper highlights the role of a cellular switching mechanism to orchestrate such circuits. The cellular switch makes the circuits reconfigurable, robust, adaptable, and externally controllable. Without this cellular mechanism, the circuit rhythms entirely rely on specific tunings of the synaptic connectivity, which makes them rigid, fragile, and difficult to control externally. We illustrate those properties on the much studied architecture of a small network controlling both the pyloric and gastric rhythms of crabs. The cellular switch is provided by a slow negative conductance often neglected in mathematical modeling of central pattern generators. We propose that this conductance is simple to model and key to computational studies of rhythmic circuit neuromodulation.

The roles of alpha oscillation in working memory retention

INTRODUCTION

Brain processes of working memory involve oscillatory activities at multiple frequencies in local and long-range neural networks. The current study addressed the specific roles of alpha oscillations during memory encoding and retention, supporting the hypothesis that multiple functional mechanisms of alpha oscillations exist in parallel.

METHOD

We recorded magnetoencephalography (MEG) in 25 healthy young adults, who performed a variant of a Sternberg working memory task. A sequential list of five consonant letters was visually presented and was followed after a 2.0 s retention interval by a probe of a pair of two letters from the study list. Participants responded whether the probe pair was in same or reversed order in the list.

RESULT

Reaction time (RT) was shortest for the first letters in the list, increased with increasing serial position, and shorter for the last position. RT was substantially longer for the probe in reversed order. Time-frequency analysis of the MEG revealed event-related desynchronization (ERD) of alpha oscillations during the encoding interval and an alpha power increase (ERS) during memory retention. Alpha ERD during encoding occurred at 10 Hz and ERS during retention at 12 Hz, suggesting different alpha mechanisms. Analysis of alpha coherence and alpha-gamma cross-spectral coupling, applied to MEG beamformer source activity, revealed connectivity across brain areas. Additionally, alpha-gamma coupling identified centers of local computation. The connectivity between occipital and frontotemporal areas was correlated with alpha ERS during memory retention. Cross-frequency coupling between alpha phase and gamma amplitude depicted a hierarchy of information flow from frontal to temporal and occipital brain areas.

CONCLUSION

Alpha decrease during encoding indicates an active state of visual processing, while subsequent ERS indicates inhibition of further visual input for protecting the memory, and phasic timing of temporal and occipital gamma oscillations is related to a long-range working memory networks.

Neuronal Dynamics Underlying Communication Signals in a Weakly Electric Fish: Implications for Connectivity in a Pacemaker Network

Neuronal networks can produce stable oscillations and synchrony that are under tight control yet flexible enough to rapidly switch between dynamical states. The pacemaker nucleus in the weakly electric fish comprises a network of electrically coupled neurons that fire synchronously at high frequency. This activity sets the timing for an oscillating electric organ discharge with the lowest cycle-to-cycle variability of all known biological oscillators. Despite this high temporal precision, pacemaker activity is behaviorally modulated on millisecond time-scales for the generation of electrocommunication signals. The network mechanisms that allow for this combination of stability and flexibility are not well understood. In this study, we use an in vitro pacemaker preparation from Apteronotus leptorhynchus to characterize the neural responses elicited by the synaptic inputs underlying electrocommunication. These responses involve a variable increase in firing frequency and a prominent desynchronization of neurons that recovers within 5 oscillation cycles. Using a previously developed computational model of the pacemaker network, we show that the frequency changes and rapid resynchronization observed experimentally are most easily explained when model neurons are interconnected more densely and with higher coupling strengths than suggested by published data. We suggest that the pacemaker network achieves both stability and flexibility by balancing coupling strength with interconnectivity and that variation in these network features may provide a substrate for species-specific evolution of electrocommunication signals.

Understanding Sensory Information Processing Through Simultaneous Multi-area Population Recordings

The goal of sensory neuroscience is to understand how the brain creates its myriad of representations of the world, and uses these representations to produce perception and behavior. Circuits of neurons in spatially segregated regions of brain tissue have distinct functional specializations, and these regions are connected to form a functional processing hierarchy. Advances in technology for recording neuronal activity from multiple sites in multiple cortical areas mean that we are now able to collect data that reflects how information is transformed within and between connected members of this hierarchy. This advance is an important step in understanding the brain because, after the sensory organs have transduced a physical signal, every processing stage takes the activity of other neurons as its input, not measurements of the physical world. However, as we explore the potential of studying how populations of neurons in multiple areas respond in concert, we must also expand both the analytical tools that we use to make sense of these data and the scope of the theories that we attempt to define. In this article, we present an overview of some of the most promising analytical approaches for making inferences from population recordings in multiple brain areas, such as dimensionality reduction and measuring changes in correlated variability, and examine how they may be used to address longstanding questions in sensory neuroscience.

Mice With Decreased Number of Interneurons Exhibit Aberrant Spontaneous and Oscillatory Activity in the Cortex

GABAergic (γ-aminobutyric acid) neurons are inhibitory neurons and protect neural tissue from excessive excitation. Cortical GABAergic neurons play a pivotal role for the generation of synchronized cortical network oscillations. Imbalance between excitatory and inhibitory mechanisms underlies many neuropsychiatric disorders and is correlated with abnormalities in oscillatory activity, especially in the gamma frequency range (30–80 Hz). We investigated the functional changes in cortical network activity in response to developmentally reduced inhibition in the adult mouse barrel cortex (BC). We used a mouse model that displays ∼50% fewer cortical interneurons due to the loss of Rac1 protein from Nkx2.1/Cre-expressing cells [Rac1 conditional knockout (cKO) mice], to examine how this developmental loss of cortical interneurons may affect basal synaptic transmission, synaptic plasticity, spontaneous activity, and neuronal oscillations in the adult BC. The decrease in the number of interneurons increased basal synaptic transmission, as examined by recording field excitatory postsynaptic potentials (fEPSPs) from layer II networks in the Rac1 cKO mouse cortex, decreased long-term potentiation (LTP) in response to tetanic stimulation but did not alter the pair-pulse ratio (PPR). Furthermore, under spontaneous recording conditions, Rac1 cKO brain slices exhibit enhanced sensitivity and susceptibility to emergent spontaneous activity. We also find that this developmental decrease in the number of cortical interneurons results in local neuronal networks with alterations in neuronal oscillations, exhibiting decreased power in low frequencies (delta, theta, alpha) and gamma frequency range (30–80 Hz) with an extra aberrant peak in high gamma frequency range (80–150 Hz). Therefore, our data show that disruption in GABAergic inhibition alters synaptic properties and plasticity, while it additionally disrupts the cortical neuronal synchronization in the adult BC.

Deficiency of AMPAR-Palmitoylation Aggravates Seizure Susceptibility

Synaptic AMPAR expression controls the strength of excitatory synaptic transmission and plasticity. An excess of synaptic AMPARs leads to epilepsy in response to seizure-inducible stimulation. The appropriate regulation of AMPARs plays a crucial role in the maintenance of the excitatory/inhibitory synaptic balance; however, the detailed mechanisms underlying epilepsy remain unclear. Our previous studies have revealed that a key modification of AMPAR trafficking to and from postsynaptic membranes is the reversible, posttranslational S-palmitoylation at the C-termini of receptors. To clarify the role of palmitoylation-dependent regulation of AMPARs in vivo, we generated GluA1 palmitoylation-deficient (Cys811 to Ser substitution) knock-in mice. These mutant male mice showed elevated seizure susceptibility and seizure-induced neuronal activity without impairments in synaptic transmission, gross brain structure, or behavior at the basal level. Disruption of the palmitoylation site was accompanied by upregulated GluA1 phosphorylation at Ser831, but not at Ser845, in the hippocampus and increased GluA1 protein expression in the cortex. Furthermore, GluA1 palmitoylation suppressed excessive spine enlargement above a certain size after LTP. Our findings indicate that an abnormality in GluA1 palmitoylation can lead to hyperexcitability in the cerebrum, which negatively affects the maintenance of network stability, resulting in epileptic seizures.SIGNIFICANCE STATEMENT AMPARs predominantly mediate excitatory synaptic transmission. AMPARs are regulated in a posttranslational, palmitoylation-dependent manner in excitatory synapses of the mammalian brain. Reversible palmitoylation dynamically controls synaptic expression and intracellular trafficking of the receptors. Here, we generated GluA1 palmitoylation-deficient knock-in mice to clarify the role of AMPAR palmitoylation in vivo We showed that an abnormality in GluA1 palmitoylation led to hyperexcitability, resulting in epileptic seizure. This is the first identification of a specific palmitoylated protein critical for the seizure-suppressing process. Our data also provide insight into how predicted receptors such as AMPARs can effectively preserve network stability in the brain. Furthermore, these findings help to define novel key targets for developing anti-epileptic drugs.

Sensory experience inversely regulates feedforward and feedback excitation-inhibition ratio in rodent visual cortex

Brief (2-3d) monocular deprivation (MD) during the critical period induces a profound loss of responsiveness within binocular (V1b) and monocular (V1m) regions of rodent primary visual cortex. This has largely been ascribed to long-term depression (LTD) at thalamocortical synapses, while a contribution from intracortical inhibition has been controversial. Here we used optogenetics to isolate and measure feedforward thalamocortical and feedback intracortical excitation-inhibition (E-I) ratios following brief MD. Despite depression at thalamocortical synapses, thalamocortical E-I ratio was unaffected in V1b and shifted toward excitation in V1m, indicating that thalamocortical excitation was not effectively reduced. In contrast, feedback intracortical E-I ratio was shifted toward inhibition in V1m, and a computational model demonstrated that these opposing shifts produced an overall suppression of layer 4 excitability. Thus, feedforward and feedback E-I ratios can be independently tuned by visual experience, and enhanced feedback inhibition is the primary driving force behind loss of visual responsiveness.

Competing inhibition-stabilized networks in sensory and memory processing

In simplified models of neocortical circuits, inhibition is either modeled in a feedforward manner or through mutual inhibitory interactions that provide for competition between neuronal populations. By contrast, recent work has suggested a critical role for recurrent inhibition as a negative feedback element that stabilizes otherwise unstable recurrent excitation. Here, we show how models based upon a motif of recurrently connected "E-I" pairs of excitatory and inhibitory units can be used to describe experimental observations in sensory and memory networks. In a sensory network model of binocular rivalry, a model based on competing E-I motifs captures psychophysical observations about how incongruous images presented to the two eyes compete. In a model of cortical working memory, an architecturally similar model with modified synaptic time constants can mathematically accumulate signals into a working memory buffer in a manner that is robust to the abrupt removal of cells. These results suggest the inhibition-stabilized E-I motif as a fundamental building block for models of a wide array of neocortical dynamics.

Alterations of Coherent Theta and Gamma Network Oscillations as an Early Biomarker of Temporal Lobe Epilepsy and Alzheimer's Disease

Alzheimer's disease (AD) and temporal lobe epilepsy (TLE) are the most common forms of neurodegenerative disorders characterized by the loss of cells and progressive irreversible alteration of cognitive functions, such as attention and memory. AD may be an important cause of epilepsy in the elderly. Early diagnosis of diseases is very important for their successful treatment. Many efforts have been done for defining new biomarkers of these diseases. Significant advances have been made in the searching of some AD and TLE reliable biomarkers, including cerebrospinal fluid and plasma measurements and glucose positron emission tomography. However, there is a great need for the biomarkers that would reflect changes of brain activity within few milliseconds to obtain information about cognitive disturbances. Successful early detection of AD and TLE requires specific biomarkers capable of distinguishing individuals with the progressing disease from ones with other pathologies that affect cognition. In this article, we review recent evidence suggesting that magnetoencephalographic recordings and coherent analysis coupled with behavioral evaluation can be a promising approach to an early detection of AD and TLE. Highlights -Data reviewed include the results of clinical and experimental studies.-Theta and gamma rhythms are disturbed in epilepsy and AD.-Common and different behavioral and oscillatory features of pathologies are compared.-Coherent analysis can be useful for an early diagnostics of diseases.