Striosomes Mediate Value-Based Learning Vulnerable in Age and a Huntington's Disease Model.

Learning valence-based responses to favorable and unfavorable options requires judgments of the relative value of the options, a process necessary for species survival. We found, using engineered mice, that circuit connectivity and function of the striosome compartment of the striatum are critical for this type of learning. Calcium imaging during valence-based learning exhibited a selective correlation between learning and striosomal but not matrix signals. This striosomal activity encoded discrimination learning and was correlated with task engagement, which, in turn, could be regulated by chemogenetic excitation and inhibition. Striosomal function during discrimination learning was disturbed with aging and severely so in a mouse model of Huntington's disease. Anatomical and functional connectivity of parvalbumin-positive, putative fast-spiking interneurons (FSIs) to striatal projection neurons was enhanced in striosomes compared with matrix in mice that learned. Computational modeling of these findings suggests that FSIs can modulate the striosomal signal-to-noise ratio, crucial for discrimination and learning.

Reactivation of Dormant Relay Pathways in Injured Spinal Cord by KCC2 Manipulations.

Many human spinal cord injuries are anatomically incomplete but exhibit complete paralysis. It is unknown why spared axons fail to mediate functional recovery in these cases. To investigate this, we undertook a small-molecule screen in mice with staggered bilateral hemisections in which the lumbar spinal cord is deprived of all direct brain-derived innervation, but dormant relay circuits remain. We discovered that a KCC2 agonist restored stepping ability, which could be mimicked by selective expression of KCC2, or hyperpolarizing DREADDs, in the inhibitory interneurons between and around the staggered spinal lesions. Mechanistically, these treatments transformed this injury-induced dysfunctional spinal circuit to a functional state, facilitating the relay of brain-derived commands toward the lumbar spinal cord. Thus, our results identify spinal inhibitory interneurons as a roadblock limiting the integration of descending inputs into relay circuits after injury and suggest KCC2 agonists as promising treatments for promoting functional recovery after spinal cord injury.

Keeping Your Brain in Balance: Homeostatic Regulation of Network Function.

To perform computations with the efficiency necessary for animal survival, neocortical microcircuits must be capable of reconfiguring in response to experience, while carefully regulating excitatory and inhibitory connectivity to maintain stable function. This dynamic fine-tuning is accomplished through a rich array of cellular homeostatic plasticity mechanisms that stabilize important cellular and network features such as firing rates, information flow, and sensory tuning properties. Further, these functional network properties can be stabilized by different forms of homeostatic plasticity, including mechanisms that target excitatory or inhibitory synapses, or that regulate intrinsic neuronal excitability. Here we discuss which aspects of neocortical circuit function are under homeostatic control, how this homeostasis is realized on the cellular and molecular levels, and the pathological consequences when circuit homeostasis is impaired. A remaining challenge is to elucidate how these diverse homeostatic mechanisms cooperate within complex circuits to enable them to be both flexible and stable.

Chronic Stress Alters Striosome-Circuit Dynamics, Leading to Aberrant Decision-Making.

Effective evaluation of costs and benefits is a core survival capacity that in humans is considered as optimal, "rational" decision-making. This capacity is vulnerable in neuropsychiatric disorders and in the aftermath of chronic stress, in which aberrant choices and high-risk behaviors occur. We report that chronic stress exposure in rodents produces abnormal evaluation of costs and benefits resembling non-optimal decision-making in which choices of high-cost/high-reward options are sharply increased. Concomitantly, alterations in the task-related spike activity of medial prefrontal neurons correspond with increased activity of their striosome-predominant striatal projection neuron targets and with decreased and delayed striatal fast-firing interneuron activity. These effects of chronic stress on prefronto-striatal circuit dynamics could be blocked or be mimicked by selective optogenetic manipulation of these circuits. We suggest that altered excitation-inhibition dynamics of striosome-based circuit function could be an underlying mechanism by which chronic stress contributes to disorders characterized by aberrant decision-making under conflict. VIDEO ABSTRACT.

Synapse-type-specific competitive Hebbian learning forms functional recurrent networks.

Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

The Dynamic Basis of Respiratory Rhythm Generation: One Breath at a Time.

Rhythmicity is a universal timing mechanism in the brain, and the rhythmogenic mechanisms are generally dynamic. This is illustrated for the neuronal control of breathing, a behavior that occurs as a one-, two-, or three-phase rhythm. Each breath is assembled stochastically, and increasing evidence suggests that each phase can be generated independently by a dedicated excitatory microcircuit. Within each microcircuit, rhythmicity emerges through three entangled mechanisms: ( a) glutamatergic transmission, which is amplified by ( b) intrinsic bursting and opposed by ( c) concurrent inhibition. This rhythmogenic triangle is dynamically tuned by neuromodulators and other network interactions. The ability of coupled oscillators to reconfigure and recombine may allow breathing to remain robust yet plastic enough to conform to nonventilatory behaviors such as vocalization, swallowing, and coughing. Lessons learned from the respiratory network may translate to other highly dynamic and integrated rhythmic systems, if approached one breath at a time.

Muscle Spasms after Spinal Cord Injury Stem from Changes in Motoneuron Excitability and Synaptic Inhibition, Not Synaptic Excitation.

Muscle spasms are common in chronic spinal cord injury (SCI), posing challenges to rehabilitation and daily activities. Pharmacological management of spasms mostly targets suppression of excitatory inputs, an approach known to hinder motor recovery. To identify better targets, we investigated changes in inhibitory and excitatory synaptic inputs to motoneurons as well as motoneuron excitability in chronic SCI. We induced either a complete or incomplete SCI in adult mice of either sex and divided those with incomplete injury into low or high functional recovery groups. Their sacrocaudal spinal cords were then extracted and used to study plasticity below injury, with tissue from naive animals as a control. Electrical stimulation of the dorsal roots elicited spasm-like activity in preparations of chronic severe SCI but not in the control. To evaluate overall synaptic inhibition activated by sensory stimulation, we measured the rate-dependent depression of spinal root reflexes. We found inhibitory inputs to be impaired in chronic injury models. When synaptic inhibition was blocked pharmacologically, all preparations became clearly spastic, even the control. However, preparations with chronic injuries generated longer spasms than control. We then measured excitatory postsynaptic currents (EPSCs) in motoneurons during sensory-evoked spasms. The data showed no difference in the amplitude of EPSCs or their conductance among animal groups. Nonetheless, we found that motoneuron persistent inward currents activated by the EPSCs were increased in chronic SCI. These findings suggest that changes in motoneuron excitability and synaptic inhibition, rather than excitation, contribute to spasms and are better suited for more effective therapeutic interventions.Significance Statement Neural plasticity following spinal cord injury is crucial for recovery of motor function. Unfortunately, this process is blemished by maladaptive changes that can cause muscle spasms. Pharmacological alleviation of spasms without compromising the recovery of motor function has proven to be challenging. Here, we investigated changes in fundamental spinal mechanisms that can cause spasms post-injury. Our data suggest that the current management strategy for spasms is misdirected toward suppressing excitatory inputs, a mechanism that we found unaltered after injury, which can lead to further motor weakness. Instead, this study shows that more promising approaches might involve restoring synaptic inhibition or modulating motoneuron excitability.

Hippocampal excitation-inhibition balance underlies the 5-HT2C receptor in modulating depressive behaviours.

The implication of 5-hydroxytryptamine 2C receptor (5-HT2CR) activity in depression is a topic of debate, and the underlying mechanisms remain largely unclear. Here, we elucidate how hippocampal excitation-inhibition (E/I) balance underlies the regulatory effects of 5-HT2CR in depression. Molecular biological analyses showed that chronic mild stress (CMS) reduced the expression of 5-HT2CR in hippocampus. We revealed that inhibition of 5-HT2CR induced depressive-like behaviours, reduced GABA release and shifted the E/I balance towards excitation in CA3 pyramidal neurons using behavioural analyses, microdialysis coupled with mass spectrometry and electrophysiological recordings. Moreover, 5-HT2CR modulated the neuronal nitric oxide synthase (nNOS)-carboxy-terminal PDZ ligand of nNOS (CAPON) interaction by influencing intracellular Ca2+ release, as determined by fibre photometry and coimmunoprecipitation. Notably, disruption of nNOS-CAPON with the specific small molecule compound ZLc-002 or AAV-CMV-CAPON-125C-GFP abolished 5-HT2CR inhibition-induced depressive-like behaviours, as well as the impairment in soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex assembly-mediated GABA vesicle release and consequent E/I imbalance. Importantly, optogenetic inhibition of CA3 GABAergic neurons prevented the effects of AAV-CMV-CAPON-125C-GFP on depressive behaviours in the presence of a 5-HT2CR antagonist. Conclusively, our findings disclose the regulatory role of 5-HT2CR in depressive-like behaviours and highlight hippocampal nNOS-CAPON coupling-triggered E/I imbalance as a pivotal cellular event underpinning the behavioural consequences of 5-HT2CR inhibition.

Hierarchical timescales in the neocortex: Mathematical mechanism and biological insights.

A cardinal feature of the neocortex is the progressive increase of the spatial receptive fields along the cortical hierarchy. Recently, theoretical and experimental findings have shown that the temporal response windows also gradually enlarge, so that early sensory neural circuits operate on short timescales whereas higher-association areas are capable of integrating information over a long period of time. While an increased receptive field is accounted for by spatial summation of inputs from neurons in an upstream area, the emergence of timescale hierarchy cannot be readily explained, especially given the dense interareal cortical connectivity known in the modern connectome. To uncover the required neurobiological properties, we carried out a rigorous analysis of an anatomically based large-scale cortex model of macaque monkeys. Using a perturbation method, we show that the segregation of disparate timescales is defined in terms of the localization of eigenvectors of the connectivity matrix, which depends on three circuit properties: 1) a macroscopic gradient of synaptic excitation, 2) distinct electrophysiological properties between excitatory and inhibitory neuronal populations, and 3) a detailed balance between long-range excitatory inputs and local inhibitory inputs for each area-to-area pathway. Our work thus provides a quantitative understanding of the mechanism underlying the emergence of timescale hierarchy in large-scale primate cortical networks.

Homeostatic regulation of brain activity: from endogenous mechanisms to homeostatic nanomachines.

After the initial concepts of the constancy of the internal milieu or homeostasis, put forward by Claude Bernard and Walter Cannon, homeostasis emerged as a mechanism to control oscillations of biologically meaningful variables within narrow physiological ranges. This is a primary need in the central nervous system that is continuously subjected to a multitude of stimuli from the internal and external environments that affect its function and structure, allowing to adapt the individual to the ever-changing daily conditions. Preserving physiological levels of activity despite disturbances that could either depress neural computation or excessively stimulate neural activity is fundamental, and failure of these homeostatic mechanisms can lead to brain diseases. In this review, we cover the role and main mechanisms of homeostatic plasticity involving the regulation of excitability and synaptic strength from the single neuron to the network level. We analyze the relationships between homeostatic and Hebbian plasticity and the conditions under which the preservation of the excitatory/inhibitory balance fails, triggering epileptogenesis and eventually epilepsy. Several therapeutic strategies to cure epilepsy have been designed to strengthen homeostasis when endogenous homeostatic plasticity mechanisms have become insufficient or ineffective to contrast hyperactivity. We describe "on demand" gene therapy strategies including optogenetics, chemogenetics, and chemo-optogenetics, and particularly focus on new closed loop sensor-actuator strategies mimicking homeostatic plasticity that can be endogenously expressed to strengthen the homeostatic defenses against brain diseases.

On the physiological and structural contributors to the overall balance of excitation and inhibition in local cortical networks.

Overall balance of excitation and inhibition in cortical networks is central to their functionality and normal operation. Such orchestrated co-evolution of excitation and inhibition is established through convoluted local interactions between neurons, which are organized by specific network connectivity structures and are dynamically controlled by modulating synaptic activities. Therefore, identifying how such structural and physiological factors contribute to establishment of overall balance of excitation and inhibition is crucial in understanding the homeostatic plasticity mechanisms that regulate the balance. We use biologically plausible mathematical models to extensively study the effects of multiple key factors on overall balance of a network. We characterize a network's baseline balanced state by certain functional properties, and demonstrate how variations in physiological and structural parameters of the network deviate this balance and, in particular, result in transitions in spontaneous activity of the network to high-amplitude slow oscillatory regimes. We show that deviations from the reference balanced state can be continuously quantified by measuring the ratio of mean excitatory to mean inhibitory synaptic conductances in the network. Our results suggest that the commonly observed ratio of the number of inhibitory to the number of excitatory neurons in local cortical networks is almost optimal for their stability and excitability. Moreover, the values of inhibitory synaptic decay time constants and density of inhibitory-to-inhibitory network connectivity are critical to overall balance and stability of cortical networks. However, network stability in our results is sufficiently robust against modulations of synaptic quantal conductances, as required by their role in learning and memory. Our study based on extensive bifurcation analyses thus reveal the functional optimality and criticality of structural and physiological parameters in establishing the baseline operating state of local cortical networks.

Stimulus-related modulation in the 1/f spectral slope suggests an impaired inhibition during a working memory task in people with multiple sclerosis.

BACKGROUND: An imbalance of excitatory and inhibitory synaptic transmission in multiple sclerosis (MS) may lead to cognitive impairment, such as impaired working memory. The 1/f slope of electroencephalography/magnetoencephalography (EEG/MEG) power spectra is shown to be a non-invasive proxy of excitation/inhibition balance. A flatter slope is associated with higher excitation/lower inhibition. OBJECTIVES: To assess the 1/f slope modulation induced by stimulus and its association with behavioral and cognitive measures. METHODS: We analyzed MEG recordings of 38 healthy controls (HCs) and 79 people with multiple sclerosis (pwMS) while performing an n-back task including target and distractor stimuli. Target trials require an answer, while distractor trials do not. We computed the 1/f spectral slope through the fitting oscillations and one over f (FOOOF) algorithm within the time windows 1 second before and after each stimulus presentation. RESULTS: We observed a flatter 1/f slope after distractor stimuli in pwMS compared to HCs. The 1/f slope was significantly steeper after stimulus for both HCs and pwMS and was significantly correlated with reaction times. This modulation in 1/f slope was significantly correlated with visuospatial memory assessed by the BVMT-R test. CONCLUSION: Our results suggest possible inhibitory mechanism deficits in pwMS during a working memory task.

Advances in the Treatment of Cognitive Impairment in Schizophrenia: Targeting NMDA Receptor Pathways.

Cognitive impairment is a core feature of schizophrenia, playing a pivotal role in the pathogenesis and prognosis of this disorder. Cognitive impairment in schizophrenia encompasses a wide range of domains, including processing speed, episodic memory, working memory, and executive function. These deficits persist throughout the course of the illness and significantly impact functional outcomes and quality of life. Therefore, it is imperative to identify the biological basis of cognitive deficits in schizophrenia and develop effective treatments. The role of N-methyl-D-aspartate (NMDA) receptors in synaptic transmission and plasticity has long been recognized, making them potential targets for schizophrenia treatment. This review will focus on emerging pharmacology targeting NMDA receptors, offering strategies for the prevention and treatment of cognitive deficits in schizophrenia.

Oxidative Stress-Induced Damage to the Developing Hippocampus Is Mediated by GSK3ß.

Neonatal brain injury renders the developing brain vulnerable to oxidative stress, leading to cognitive deficit. However, oxidative stress-induced damage to hippocampal circuits and the mechanisms underlying long-term changes in memory and learning are poorly understood. We used high oxygen tension or hyperoxia (HO) in neonatal mice of both sexes to investigate the role of oxidative stress in hippocampal damage. Perinatal HO induces reactive oxygen species and cell death, together with reduced interneuron maturation, inhibitory postsynaptic currents, and dentate progenitor proliferation. Postinjury interneuron stimulation surprisingly improved inhibitory activity and memory tasks, indicating reversibility. With decreased hippocampal levels of Wnt signaling components and somatostatin, HO aberrantly activated glycogen synthase kinase 3 ß activity. Pharmacological inhibition or ablation of interneuron glycogen synthase kinase 3 ß during HO challenge restored progenitor cell proliferation, interneuron development, inhibitory/excitatory balance, as well as hippocampal-dependent behavior. Biochemical targeting of interneuron function may benefit learning deficits caused by oxidative damage.SIGNIFICANCE STATEMENT Premature infants are especially vulnerable to oxidative stress, as their antioxidant defenses are underdeveloped. Indeed, high oxygen tension is associated with poor neurologic outcomes. Because of its sustained postnatal development and role in learning and memory, the hippocampus is especially vulnerable to oxidative damage in premature infants. However, the role of oxidative stress in the developing hippocampus has yet to be explored. With ever-rising rates of neonatal brain injury and no universally viable approach to maximize functional recovery, a better understanding of the mechanisms underlying neonatal brain injury is needed. Addressing this need, this study uses perinatal hyperoxia to study cognitive deficits, pathophysiology, and molecular mechanisms of oxidative damage in the developing hippocampus.

Long-Range Amplitude Coupling Is Optimized for Brain Networks That Function at Criticality.

Brain function depends on segregation and integration of information processing in brain networks often separated by long-range anatomic connections. Neuronal oscillations orchestrate such distributed processing through transient amplitude and phase coupling, yet surprisingly, little is known about local network properties facilitating these functional connections. Here, we test whether criticality, a dynamical state characterized by scale-free oscillations, optimizes the capacity of neuronal networks to couple through amplitude or phase, and transfer information. We coupled in silico networks which exhibit oscillations in the α band (8-16 Hz), and varied excitatory and inhibitory connectivity. We found that phase coupling of oscillations emerges at criticality, and that amplitude coupling, as well as information transfer, are maximal when networks are critical. Importantly, regulating criticality through modulation of synaptic gain showed that critical dynamics, as opposed to a static ratio of excitatory and inhibitory connections, optimize network coupling and information transfer. Our data support the idea that criticality is important for local and global information processing and may help explain why brain disorders characterized by local alterations in criticality also exhibit impaired long-range synchrony, even before degeneration of axonal connections.SIGNIFICANCE STATEMENT To perform adaptively in a changing environment, our brains dynamically coordinate activity across distant areas. Empirical evidence suggests that long-range amplitude and phase coupling of oscillations are systems-level mechanisms enabling transient formation of spatially distributed functional networks on the backbone of a relatively static structural connectome. However, surprisingly little is known about the local network properties that optimize coupling and information transfer. Here, we show that criticality, a dynamical state characterized by scale-free oscillations and a hallmark of neuronal network activity, optimizes the capacity of neuronal networks to couple through amplitude or phase and transfer information.

Effects of Altered Excitation-Inhibition Balance on Decision Making in a Cortical Circuit Model.

The synaptic balance between excitation and inhibition (E/I balance) is a fundamental principle of cortical circuits, and disruptions in E/I balance are commonly linked to cognitive deficits such as impaired decision-making. Explanatory gaps remain in a mechanistic understanding of how E/I balance contributes to cognitive computations, and how E/I disruptions at the synaptic level can propagate to induce behavioral deficits. Here, we studied how E/I perturbations may impair perceptual decision-making in a biophysically-based association cortical circuit model. We found that both elevating and lowering E/I ratio, via NMDA receptor (NMDAR) hypofunction at inhibitory interneurons and excitatory pyramidal neurons, respectively, can similarly impair psychometric performance, following an inverted-U dependence. Nonetheless, these E/I perturbations differentially alter the process of evidence accumulation across time. Under elevated E/I ratio, decision-making is impulsive, overweighting early evidence and underweighting late evidence. Under lowered E/I ratio, decision-making is indecisive, with both evidence integration and winner-take-all competition weakened. The distinct time courses of evidence accumulation at the circuit level can be measured at the behavioral level, using multiple psychophysical task paradigms which provide dissociable predictions. These results are well captured by a generalized drift-diffusion model (DDM) with self-coupling, implementing leaky or unstable integration, which thereby links biophysical circuit modeling to algorithmic process modeling and facilitates model fitting to behavioral choice data. In general, our findings characterize critical roles of cortical E/I balance in cognitive function, bridging from biophysical to behavioral levels of analysis.SIGNIFICANCE STATEMENT Cognitive deficits in multiple neuropsychiatric disorders, including schizophrenia, have been associated with alterations in the balance of synaptic excitation and inhibition (E/I) in cerebral cortical circuits. However, the circuit mechanisms by which E/I imbalance leads to cognitive deficits in decision-making have remained unclear. We used a computational model of decision-making in cortical circuits to study the neural and behavioral effects of E/I imbalance. We found that elevating and lowering E/I ratio produce distinct modes of dysfunction in decision-making processes, which can be dissociated in behavior through psychophysical task paradigms. The biophysical circuit model can be mapped onto a psychological model of decision-making which can facilitate experimental tests of model predictions.

Logarithmically scaled, gamma distributed neuronal spiking.

Naturally log-scaled quantities abound in the nervous system. Distributions of these quantities have non-intuitive properties, which have implications for data analysis and the understanding of neural circuits. Here, we review the log-scaled statistics of neuronal spiking and the relevant analytical probability distributions. Recent work using log-scaling revealed that interspike intervals of forebrain neurons segregate into discrete modes reflecting spiking at different timescales and are each well-approximated by a gamma distribution. Each neuron spends most of the time in an irregular spiking 'ground state' with the longest intervals, which determines the mean firing rate of the neuron. Across the entire neuronal population, firing rates are log-scaled and well approximated by the gamma distribution, with a small number of highly active neurons and an overabundance of low rate neurons (the 'dark matter'). These results are intricately linked to a heterogeneous balanced operating regime, which confers upon neuronal circuits multiple computational advantages and has evolutionarily ancient origins.

Increased propensity for infantile spasms and altered neocortical excitation-inhibition balance in a mouse model of down syndrome carrying human chromosome 21.

Children with Down syndrome (DS, trisomy of chromosome 21) have an increased risk of infantile spasms (IS). As an epileptic encephalopathy, IS may further impair cognitive function and exacerbate neurodevelopmental delays already present in children with DS. To investigate the pathophysiology of IS in DS, we induced IS-like epileptic spasms in a genetic mouse model of DS that carries human chromosome 21q, TcMAC21, the animal model most closely representing gene dosage imbalance in DS. Repetitive extensor/flexor spasms were induced by the GABAB receptor agonist γ-butyrolactone (GBL) and occurred predominantly in young TcMAC21 mice (85%) but also in some euploid mice (25%). During GBL application, background electroencephalographic (EEG) amplitude was reduced, and rhythmic, sharp-and-slow wave activity or high-amplitude burst (epileptiform) events emerged in both TcMAC21 and euploid mice. Spasms occurred only during EEG bursts, but not every burst was accompanied by a spasm. Electrophysiological experiments revealed that basic membrane properties (resting membrane potential, input resistance, action-potential threshold and amplitude, rheobase, input-output relationship) of layer V pyramidal neurons were not different between TcMAC21 mice and euploid controls. However, excitatory postsynaptic currents (EPSCs) evoked at various intensities were significantly larger in TcMAC21 mice than euploid controls, while inhibitory postsynaptic currents (IPSCs) were similar between the two groups, resulting in an increased excitation-inhibition (E-I) ratio. These data show that behavioral spasms with epileptic EEG activity can be induced in young TcMAC21 DS mice, providing proof-of-concept evidence for increased IS susceptibility in these DS mice. Our findings also show that basic membrane properties are similar in TcMAC21 and euploid mice, while the neocortical E-I balance is altered to favor increased excitation in TcMAC21 mice, which may predispose to IS generation.

The spectral slope as a marker of excitation/inhibition ratio and cognitive functioning in multiple sclerosis.

Multiple sclerosis (MS) is a neurodegenerative disease characterized by neuronal and synaptic loss, resulting in an imbalance of excitatory and inhibitory synaptic transmission and potentially cognitive impairment. Current methods for measuring the excitation/inhibition (E/I) ratio are mostly invasive, but recent research combining neurocomputational modeling with measurements of local field potentials has indicated that the slope with which the power spectrum of neuronal activity captured by electro- and/or magnetoencephalography rolls off, is a non-invasive biomarker of the E/I ratio. A steeper roll-off is associated with a stronger inhibition. This novel method can be applied to assess the E/I ratio in people with multiple sclerosis (pwMS), detect the effect of medication such as benzodiazepines, and explore its utility as a biomarker for cognition. We recruited 44 healthy control subjects and 95 pwMS who underwent resting-state magnetoencephalographic recordings. The 1/f spectral slope of the neural power spectra was calculated for each subject and for each brain region. As expected, the spectral slope was significantly steeper in pwMS treated with benzodiazepines (BZDs) compared to pwMS not receiving BZDs (p = .01). In the sub-cohort of pwMS not treated with BZDs, we observed a steeper slope in cognitively impaired pwMS compared to cognitively preserved pwMS (p = .01) and healthy subjects (p = .02). Furthermore, we observed a significant correlation between 1/f spectral slope and verbal and spatial working memory functioning in the brain regions located in the prefrontal and parietal cortex. In this study, we highlighted the value of the spectral slope in MS by quantifying the effect of benzodiazepines and by putting it forward as a potential biomarker of cognitive deficits in pwMS.

Deciphering functional roles of synaptic plasticity and intrinsic neural firing in developing mouse visual cortex layer IV microcircuit.

Between the onset of the critical period of mouse primary visual cortex and eye opening at postnatal day 14 is a complex process and that is vital for the cognitive function of vision. The onset of the critical period of mouse primary visual cortex involves changes of the intrinsic firing property of each neuron and short term plasticity of synapses. In order to investigate the functional role of each factor in regulating the circuit firing activity during the critical period plasticity, we adopted the Markram's model for short term plasticity and Wilson's model for intrinsic neuron firing activity, and construct a microcircuit for mouse visual cortex layer IV based on the connection probabilities from experimental results. Our results indicate that, during CP development, the most critical factors that regulate the firing pattern of microcircuit is the short term plasticity of the synapse from PC to PV and SST interneurons, which upregulates the PV interneuron firing and produces new balance between excitation and inhibition; the intrinsic firing activity of PC and PV during development downregulates the firing frequency of the circuits. In addition, we have investigated the function of feedforward excitatory thalamic-cortical projection to PC and PV interneuron during CP, and found that neural firing activity largely depends on the TC input and the results are similar to the local circuit with minor differences. We conclude that the short term plasticity development during critical period plays a crucial role in regulating the circuit behavior.