Altered Cortical Ensembles in Mouse Models of Schizophrenia

The shallow cognitive map hypothesis: A hippocampal framework for thought disorder in schizophrenia

Memories are not formed in isolation. They are associated and organized into relational knowledge structures that allow coherent thought. Failure to express such coherent thought is a key hallmark of Schizophrenia. Here we explore the hypothesis that thought disorder arises from disorganized Hippocampal cognitive maps. In doing so, we combine insights from two key lines of investigation, one concerning the neural signatures of cognitive mapping, and another that seeks to understand lower-level cellular mechanisms of cognition within a dynamical systems framework. Specifically, we propose that multiple distinct pathological pathways converge on the shallowing of Hippocampal attractors, giving rise to disorganized Hippocampal cognitive maps and driving conceptual disorganization. We discuss the available evidence at the computational, behavioural, network, and cellular levels. We also outline testable predictions from this framework, including how it could unify major chemical and psychological theories of schizophrenia and how it can provide a rationale for understanding the aetiology and treatment of the disease.

Phase-specific pooling of sparse assembly activity by respiration-related brain oscillations

Neuronal assemblies activate phase-coupled to ongoing respiration-related oscillations (RROs) in the medial prefrontal cortex of mice. The phase coupling strength of assemblies exceeds that of individual neurons. Assemblies preferentially activate during the descending phase of RRO. Despite higher assembly frequency during descending RRO, overlap between active assemblies remains constant across RRO phase. Putative GABAergic interneurons are preferentially recruited by assembly neurons during descending RRO, suggesting that interneurons might contribute to the segregation of active assemblies during the descending phase of RRO. ABSTRACT: Nasal breathing affects cognitive functions, but it has remained largely unclear how respiration-driven inputs shape information processing in neuronal circuits. Current theories emphasize the role of neuronal assemblies, coalitions of transiently active pyramidal cells, as the core unit of cortical network computations. Here, we show that the phase of respiration-related oscillations (RROs) influences the likelihood of activation of a subset of neuronal assemblies in the medial prefrontal cortex (mPFC) of awake mice. RROs bias the activation of neuronal assemblies more efficiently than that of individual neurons by entraining the coactivity of assembly neurons. Moreover, the activation of assemblies is moderately biased towards the descending phase of RROs. Despite the enriched activation of assemblies during descending RRO, the overlap between individual assemblies remains constant across RRO phases. Putative GABAergic interneurons are shown to coactivate with assemblies and receive enhanced excitatory drive from assembly neurons during descending RRO, suggesting that the phase-specific recruitment of putative interneurons might help to keep the activation of different assemblies separated from each other during times of preferred assembly activation. Our results thus identify respiration-synchronized brain rhythms as drivers of neuronal assemblies and point to a role of RROs in defining time windows of enhanced yet segregated assembly activity. Abstract figure legend. Nasal breathing affects cognitive functions, but it has remained largely unclear how respiration-driven inputs shape information processing in neuronal circuits. We show that the phase of respiration-related oscillations (RROs) influences the likelihood of the activation of a subset of neuronal assemblies in the medial prefrontal cortex (mPFC) of awake mice. The activation of assemblies is moderately biased towards the descending phase of RROs, while the overlap between individual assemblies remains constant across RRO phases. Putative GABAergic interneurons are shown to coactivate with assemblies and receive enhanced excitatory drive from assembly neurons during descending RRO, suggesting that the phase-specific recruitment of putative interneurons might help to keep the activation of different assemblies separated from each other. This article is protected by copyright. All rights reserved.

Imaging neural circuit pathology of autism spectrum disorders: autism-associated genes, animal models and the application of in vivo two-photon imaging

Recent advances in human genetics identified genetic variants involved in causing autism spectrum disorders (ASDs). Mouse models that mimic mutations found in patients with ASD exhibit behavioral phenotypes consistent with ASD symptoms. These mouse models suggest critical biological factors of ASD etiology. Another important implication of ASD genetics is the enrichment of ASD risk genes in molecules involved in developing synapses and regulating neural circuit function. Sophisticated in vivo imaging technologies applied to ASD mouse models identify common synaptic impairments in the neocortex, with genetic-mutation-specific defects in local neural circuits. In this article, we review synapse- and circuit-level phenotypes identified by in vivo two-photon imaging in multiple mouse models of ASD and discuss the contributions of altered synapse properties and neural circuit activity to ASD pathogenesis.

NMDA receptors in visual cortex are necessary for normal visuomotor integration and skill learning

The experience of coupling between motor output and visual feedback is necessary for the development of visuomotor skills and shapes visuomotor integration in visual cortex. Whether these experience-dependent changes of responses in V1 depend on modifications of the local circuit or are the consequence of circuit changes outside of V1 remains unclear. Here, we probed the role of N-methyl-d-aspartate (NMDA) receptor-dependent signaling, which is known to be involved in neuronal plasticity, in mouse primary visual cortex (V1) during visuomotor development. We used a local knockout of NMDA receptors and a photoactivatable inhibition of CaMKII in V1 during the first visual experience to probe for changes in neuronal activity in V1 as well as the influence on performance in a visuomotor task. We found that a knockout of NMDA receptors before, but not after, first visuomotor experience reduced responses to unpredictable stimuli, diminished the suppression of predictable feedback in V1, and impaired visuomotor skill learning later in life. Our results demonstrate that NMDA receptor-dependent signaling in V1 is critical during the first visuomotor experience for shaping visuomotor integration and enabling visuomotor skill learning.

Orchestration of Ion Channels and Transporters in Neocortical Development and Neurological Disorders

Electrical activity plays crucial roles in neural circuit formation and remodeling. During neocortical development, neurons are generated in the ventricular zone, migrate to their correct position, elongate dendrites and axons, and form synapses. In this review, we summarize the functions of ion channels and transporters in neocortical development. Next, we discuss links between neurological disorders caused by dysfunction of ion channels (channelopathies) and neocortical development. Finally, we introduce emerging optical techniques with potential applications in physiological studies of neocortical development and the pathophysiology of channelopathies.

High-Frequency Head Impact Disrupts Hippocampal Neural Ensemble Dynamics

We have recently shown that the cognitive impairments in a mouse model of high-frequency head impact (HFHI) are caused by chronic changes to synaptic physiology. To better understand these synaptic changes occurring after repeat head impact, we used Thy1-GcCAMP6f mice to study intracellular and intercellular calcium dynamics and neuronal ensembles in HFHI mice. We performed simultaneous calcium imaging and local field potential (LFP) recordings of the CA1 field during an early-LTP paradigm in acute hippocampal slice preparations 24 h post-impact. As previously reported, HFHI causes a decrease in early-LTP in the absence of any shift in the input-output curve. Calcium analytics revealed that HFHI hippocampal slices have similar numbers of active ROIs, however, the number of calcium transients per ROI was significantly increased in HFHI slices. Ensembles consist of coordinated activity between groups of active ROIs. We exposed the CA1 ensemble to Schaffer-collateral stimulation in an abbreviated LTP paradigm and observed novel coordinated patterns of post stimulus calcium ensemble activity. HFHI ensembles displayed qualitatively similar patterns of post-stimulus ensemble activity to shams but showed significant changes in quantitative ensemble inactivation and reactivation. Previous in vivo and in vitro reports have shown that ensemble activity frequently occurs through a similar set of ROIs firing in a repeating fashion. HFHI slices showed a decrease in such coordinated firing patterns during post stimulus ensemble activity. The present study shows that HFHI alters synaptic activity and disrupts neuronal organization of the ensemble, providing further evidence of physiological synaptic adaptation occurring in the brain after a high frequency of non-pathological head impacts.

Disparate insults relevant to schizophrenia converge on impaired spike synchrony and weaker synaptic interactions in prefrontal local circuits

Schizophrenia results from hundreds of known causes, including genetic, environmental, and developmental insults that cooperatively increase risk of developing the disease. In spite of the diversity of causal factors, schizophrenia presents with a core set of symptoms and brain abnormalities (both structural and functional) that particularly impact the prefrontal cortex. This suggests that many different causal factors leading to schizophrenia may cause prefrontal neurons and circuits to fail in fundamentally similar ways. The nature of convergent malfunctions in prefrontal circuits at the cell and synaptic levels leading to schizophrenia are not known. Here, we apply convergence-guided search to identify core pathological changes in the functional properties of prefrontal circuits that lie downstream of mechanistically distinct insults relevant to the disease. We compare the impacts of blocking NMDA receptors in monkeys and deleting a schizophrenia risk gene in mice on activity timing and effective communication in prefrontal local circuits. Although these manipulations operate through distinct molecular pathways and biological mechanisms, we found they produced convergent pathophysiological effects on prefrontal local circuits. Both manipulations reduced the frequency of synchronous (0-lag) spiking between prefrontal neurons and weakened functional interactions between prefrontal neurons at monosynaptic lags as measured by information transfer between the neurons. The two observations may be related, as reduction in synchronous spiking between prefrontal neurons would be expected to weaken synaptic connections between them via spike-timing-dependent synaptic plasticity. These data suggest that the link between spike timing and synaptic connectivity could comprise the functional vulnerability that multiple risk factors exploit to produce disease.

Current findings and perspectives on aberrant neural oscillations in schizophrenia

There is now consistent evidence that neural oscillation at low- and high-frequencies constitute an important aspect of the pathophysiology of schizophrenia. Specifically, impaired rhythmic activity may underlie the deficit to generate coherent cognition and behavior, leading to the characteristic symptoms of psychosis and cognitive deficits. Importantly, the generating mechanisms of neural oscillations are relatively well-understood and thus enable the targeted search for the underlying circuit impairments and novel treatment targets. In the following review, we will summarize and assess the evidence for aberrant rhythmic activity in schizophrenia through evaluating studies that have utilized Electro/Magnetoencephalography to examine neural oscillations during sensory and cognitive tasks as well as during resting-state measurements. These data will be linked to current evidence from post-mortem, neuroimaging, genetics, and animal models that have implicated deficits in GABAergic interneurons and glutamatergic neurotransmission in oscillatory deficits in schizophrenia. Finally, we will highlight methodological and analytical challenges as well as provide recommendations for future research.

Towards biologically constrained attractor models of schizophrenia

Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing alterations in memory circuits can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing biophysical accounts. Critical points to resolve are the effects of increases vs. decreases in E/I ratio (e.g. through NMDAR blockade) on firing rate tuning and shared noise modulations and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ.

Semantic priming and neurobiology in schizophrenia: A theoretical review

In this theoretical review we bridge the cognitive and neurobiological sciences to shed light on the neurocognitive foundations of the semantic priming effect in schizophrenia. We review and theoretically evaluate the neurotransmitter systems (dopaminergic, GABAergic and glutamatergic) and neurobiological underpinnings of behavioural and electrophysiological (N400) semantic priming in the pathology, and the main hypotheses on their geneses: a disinhibition of the semantic spread of activation, a disorganised semantic storage or noisy lexical-semantic associations, a psychomotor artefact, an artefact of relatedness proportions, or an inability to mobilise contextual information. We further assess the literature on the endophenotype of Formal Thought Disorder from multiple standpoints, ranging from neurophysiology to cognition: considerations are weaved on neuronal (PV basket cell, SST, VIP) and receptor deficits (DRD1, NMDA), neurotransmitter imbalances (dopamine), cortical and dopaminergic lateralisation, inter alia. In conclusion, we put forth novel postulates on the underlying causes of controlled hypopriming, automatic hyperpriming, N400 reversals (larger amplitudes for close associations), indirect versus direct hyperpriming, and the endophenotype of lexical-semantic disturbances in schizophrenia.

The generation of cortical novelty responses through inhibitory plasticity

Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. The generation of novelty responses does not depend on the periodicity but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make experimentally testable predictions.

Differential resting-state patterns across networks are spatially associated with Comt and Trmt2a gene expression patterns in a mouse model of 22q11.2 deletion

Copy number variations (CNV) involving multiple genes are ideal models to study polygenic neuropsychiatric disorders. Since 22q11.2 deletion is regarded as the most important single genetic risk factor for developing schizophrenia, characterizing the effects of this CNV on neural networks offers a unique avenue towards delineating polygenic interactions conferring risk for the disorder. We used a Df(h22q11)/+ mouse model of human 22q11.2 deletion to dissect gene expression patterns that would spatially overlap with differential resting-state functional connectivity (FC) patterns in this model (N = 12 Df(h22q11)/+ mice, N = 10 littermate controls). To confirm the translational relevance of our findings, we analyzed tissue samples from schizophrenia patients and healthy controls using machine learning to explore whether identified genes were co-expressed in humans. Additionally, we employed the STRING protein-protein interaction database to identify potential interactions between genes spatially associated with hypo- or hyper-FC. We found significant associations between differential resting-state connectivity and spatial gene expression patterns for both hypo- and hyper-FC. Two genes, Comt and Trmt2a, were consistently over-expressed across all networks. An analysis of human datasets pointed to a disrupted co-expression of these two genes in the brain in schizophrenia patients, but not in healthy controls. Our findings suggest that COMT and TRMT2A form a core genetic component implicated in differential resting-state connectivity patterns in the 22q11.2 deletion. A disruption of their co-expression in schizophrenia patients points out a prospective cause for the aberrance of brain networks communication in 22q11.2 deletion syndrome on a molecular level.

Scalable and accurate method for neuronal ensemble detection in spiking neural networks

We propose a novel, scalable, and accurate method for detecting neuronal ensembles from a population of spiking neurons. Our approach offers a simple yet powerful tool to study ensemble activity. It relies on clustering synchronous population activity (population vectors), allows the participation of neurons in different ensembles, has few parameters to tune and is computationally efficient. To validate the performance and generality of our method, we generated synthetic data, where we found that our method accurately detects neuronal ensembles for a wide range of simulation parameters. We found that our method outperforms current alternative methodologies. We used spike trains of retinal ganglion cells obtained from multi-electrode array recordings under a simple ON-OFF light stimulus to test our method. We found a consistent stimuli-evoked ensemble activity intermingled with spontaneously active ensembles and irregular activity. Our results suggest that the early visual system activity could be organized in distinguishable functional ensembles. We provide a Graphic User Interface, which facilitates the use of our method by the scientific community.

Dysmaturation Observed as Altered Hippocampal Functional Connectivity at Rest Is Associated With the Emergence of Positive Psychotic Symptoms in Patients With 22q11 Deletion Syndrome

BACKGROUND

Hippocampal alterations are among the most replicated neuroimaging findings across the psychosis spectrum. Moreover, there is strong translational evidence that preserving the maturation of hippocampal networks in mice models prevents the progression of cognitive deficits. However, the developmental trajectory of hippocampal functional connectivity (HFC) and its contribution to psychosis is not well characterized in the human population. 22q11 deletion syndrome (22q11DS) offers a unique model for characterizing early neural correlates of schizophrenia.

METHODS

We acquired resting-state functional magnetic resonance imaging in 242 longitudinally repeated scans from 84 patients with 22q11DS (30 with moderate to severe positive psychotic symptoms) and 94 healthy control subjects in the age span of 6 to 32 years. We obtained bilateral hippocampus to whole-brain functional connectivity and employed a novel longitudinal multivariate approach by means of partial least squares correlation to evaluate the developmental trajectory of HFC across groups.

RESULTS

Relative to control subjects, patients with 22q11DS failed to increase HFC with frontal regions such as the dorsal part of the anterior cingulate cortex, prefrontal cortex, and supplementary motor area. Concurrently, carriers of the deletion had abnormally higher HFC with subcortical dopaminergic areas. Remarkably, this aberrant maturation of HFC was more prominent during midadolescence and was mainly driven by patients exhibiting subthreshold positive psychotic symptoms.

CONCLUSIONS

Our findings suggest a critical period of prefrontal cortex-hippocampal-striatal circuit dysmaturation, particularly during late adolescence, which in light of current translation evidence could be a target for short-term interventions to potentially achieve long-lasting rescue of circuit dysfunctions associated with psychosis.

GABAergic System Dysfunction and Challenges in Schizophrenia Research

Despite strenuous studies since the last century, the precise cause and pathology of schizophrenia are still largely unclear and arguably controversial. Although many hypotheses have been proposed to explain the etiology of schizophrenia, the definitive genes or core pathological mechanism remains absent. Among these hypotheses, however, GABAergic dysfunction stands out as a common feature consistently reported in schizophrenia, albeit a satisfactory mechanism that could be exploited for therapeutic purpose has not been developed yet. This review is focusing on the progress made to date in the field in terms of understanding the mechanisms involving dysfunctional GABAergic system and loops identified in schizophrenia research.

Dynamic patterns of correlated activity in the prefrontal cortex encode information about social behavior

New technologies make it possible to measure activity from many neurons simultaneously. One approach is to analyze simultaneously recorded neurons individually, then group together neurons which increase their activity during similar behaviors into an "ensemble." However, this notion of an ensemble ignores the ability of neurons to act collectively and encode and transmit information in ways that are not reflected by their individual activity levels. We used microendoscopic GCaMP imaging to measure prefrontal activity while mice were either alone or engaged in social interaction. We developed an approach that combines a neural network classifier and surrogate (shuffled) datasets to characterize how neurons synergistically transmit information about social behavior. Notably, unlike optimal linear classifiers, a neural network classifier with a single linear hidden layer can discriminate network states which differ solely in patterns of coactivity, and not in the activity levels of individual neurons. Using this approach, we found that surrogate datasets which preserve behaviorally specific patterns of coactivity (correlations) outperform those which preserve behaviorally driven changes in activity levels but not correlated activity. Thus, social behavior elicits increases in correlated activity that are not explained simply by the activity levels of the underlying neurons, and prefrontal neurons act collectively to transmit information about socialization via these correlations. Notably, this ability of correlated activity to enhance the information transmitted by neuronal ensembles is diminished in mice lacking the autism-associated gene Shank3. These results show that synergy is an important concept for the coding of social behavior which can be disrupted in disease states, reveal a specific mechanism underlying this synergy (social behavior increases correlated activity within specific ensembles), and outline methods for studying how neurons within an ensemble can work together to encode information.

Neuronal ensembles in memory processes

A neuronal ensemble represents the concomitant activity of a specific group of neurons that could encompass a broad repertoire of brain functions such as motor, perceptual, memory or cognitive states. On the other hand, a memory engram portrays the physical manifestation of memory or the changes that enable learning and retrieval. Engram studies focused for many years on finding where memories are stored as in, which cells or brain regions represent a memory trace, and disregarded the investigation of how neuronal activity patterns give rise to such memories. Recent experiments suggest that the association and reactivation of specific neuronal groups could be the main mechanism underlying the brain's ability to remember past experiences and envision future actions. Thus, the growing consensus is that the interaction between neuronal ensembles could allow sequential activity patterns to become memories and recurrent memories to compose complex behaviors. The goal of this review is to propose how the neuronal ensemble framework could be translated and useful to understand memory processes.

Adult trkB Signaling in Parvalbumin Interneurons is Essential to Prefrontal Network Dynamics

Inhibitory interneurons expressing parvalbumin (PV) are central to cortical network dynamics, generation of γ oscillations, and cognition. Dysfunction of PV interneurons disrupts cortical information processing and cognitive behavior. Brain-derived neurotrophic factor (BDNF)/tyrosine receptor kinase B (trkB) signaling regulates the maturation of cortical PV interneurons but is also implicated in their adult multidimensional functions. Using a novel viral strategy for cell-type-specific and spatially restricted expression of a dominant-negative trkB (trkB.DN), we show that BDNF/trkB signaling is essential to the integrity and maintenance of prefrontal PV interneurons in adult male and female mice. Reduced BDNF/trkB signaling in PV interneurons in the medial prefrontal cortex (mPFC) resulted in deficient PV inhibition and increased baseline local field potential (LFP) activity in a broad frequency band. The altered network activity was particularly pronounced during increased activation of the prefrontal network and was associated with changed dynamics of local excitatory neurons, as well as decreased modulation of the LFP, abnormalities that appeared to generalize across stimuli and brain states. In addition, our findings link reduced BDNF/trkB signaling in prefrontal PV interneurons to increased aggression. Together our investigations demonstrate that BDNF/trkB signaling in PV interneurons in the adult mPFC is essential to local network dynamics and cognitive behavior. Our data provide direct support for the suggested association between decreased trkB signaling, deficient PV inhibition, and altered prefrontal circuitry.SIGNIFICANCE STATEMENT Brain-derived neurotrophic factor (BDNF)/tyrosine receptor kinase B (trkB) signaling promotes the maturation of inhibitory parvalbumin (PV) interneurons, neurons central to local cortical dynamics, γ rhythms, and cognition. Here, we used a novel viral approach for reduced BDNF/trkB signaling in PV interneurons in the medial prefrontal cortex (mPFC) to establish the role of BDNF/trkB signaling in adult prefrontal network activities. Reduced BDNF/trkB signaling caused pronounced morphologic alterations, reduced PV inhibition, and deficient prefrontal network dynamics. The altered network activity appeared to manifest across stimuli and brain states and was associated with aberrant local field potential (LFP) activities and increased aggression. The results demonstrate that adult BDNF/trkB signaling is essential to PV inhibition and prefrontal circuit function and directly links BDNF/trkB signaling to network integrity in the adult brain.

Cortical ensembles selective for context

Neural processing of sensory information is strongly influenced by context. For instance, cortical responses are reduced to predictable stimuli, while responses are increased to novel stimuli that deviate from contextual regularities. Such bidirectional modulation based on preceding sensory context is likely a critical component or manifestation of attention, learning, and behavior, yet how it arises in cortical circuits remains unclear. Using volumetric two-photon calcium imaging and local field potentials in primary visual cortex (V1) from awake mice presented with visual "oddball" paradigms, we identify both reductions and augmentations of stimulus-evoked responses depending, on whether the stimulus was redundant or deviant, respectively. Interestingly, deviance-augmented responses were limited to a specific subset of neurons mostly in supragranular layers. These deviance-detecting cells were spatially intermixed with other visually responsive neurons and were functionally correlated, forming a neuronal ensemble. Optogenetic suppression of prefrontal inputs to V1 reduced the contextual selectivity of deviance-detecting ensembles, demonstrating a causal role for top-down inputs. The presence of specialized context-selective ensembles in primary sensory cortex, modulated by higher cortical areas, provides a circuit substrate for the brain's construction and selection of prediction errors, computations which are key for survival and deficient in many psychiatric disorders.

Prioritization of schizophrenia risk genes from GWAS results by integrating multi-omics data

Schizophrenia (SCZ) is a polygenic disease with a heritability approaching 80%. Over 100 SCZ-related loci have so far been identified by genome-wide association studies (GWAS). However, the risk genes associated with these loci often remain unknown. We present a new risk gene predictor, rGAT-omics, that integrates multi-omics data under a Bayesian framework by combining the Hotelling and Box-Cox transformations. The Bayesian framework was constructed using gene ontology, tissue-specific protein-protein networks, and multi-omics data including differentially expressed genes in SCZ and controls, distance from genes to the index single-nucleotide polymorphisms (SNPs), and de novo mutations. The application of rGAT-omics to the 108 loci identified by a recent GWAS study of SCZ predicted 103 high-risk genes (HRGs) that explain a high proportion of SCZ heritability (Enrichment = 43.44 and [Formula: see text]). HRGs were shown to be significantly ([Formula: see text]) enriched in genes associated with neurological activities, and more likely to be expressed in brain tissues and SCZ-associated cell types than background genes. The predicted HRGs included 16 novel genes not present in any existing databases of SCZ-associated genes or previously predicted to be SCZ risk genes by any other method. More importantly, 13 of these 16 genes were not the nearest to the index SNP markers, and them would have been difficult to identify as risk genes by conventional approaches while ten out of the 16 genes are associated with neurological functions that make them prime candidates for pathological involvement in SCZ. Therefore, rGAT-omics has revealed novel insights into the molecular mechanisms underlying SCZ and could provide potential clues to future therapies.

Network Asynchrony Underlying Increased Broadband Gamma Power

Synchronous activity of cortical inhibitory interneurons expressing parvalbumin (PV) underlies expression of cortical γ rhythms. Paradoxically, deficient PV inhibition is associated with increased broadband γ power in the local field potential. Increased baseline broadband γ is also a prominent characteristic in schizophrenia and a hallmark of network alterations induced by NMDAR antagonists, such as ketamine. Whether enhanced broadband γ is a true rhythm, and if so, whether rhythmic PV inhibition is involved or not, is debated. Asynchronous and increased firing activities are thought to contribute to broadband power increases spanning the γ band. Using male and female mice lacking NMDAR activity specifically in PV neurons to model deficient PV inhibition, we here show that neuronal activity with decreased synchronicity is associated with increased prefrontal broadband γ power. Specifically, reduced spike time precision and spectral leakage of spiking activity because of higher firing rates (spike "contamination") affect the broadband γ band. Desynchronization was evident at multiple time scales, with reduced spike entrainment to the local field potential, reduced cross-frequency coupling, and fragmentation of brain states. Local application of S(+)-ketamine in (control) mice with intact NMDAR activity in PV neurons triggered network desynchronization and enhanced broadband γ power. However, our investigations suggest that disparate mechanisms underlie increased broadband γ power caused by genetic alteration of PV interneurons and ketamine-induced power increases in broadband γ. Our study confirms that enhanced broadband γ power can arise from asynchronous activities and demonstrates that long-term deficiency of PV inhibition can be a contributor.SIGNIFICANCE STATEMENT Brain oscillations are fundamental to the coordination of neuronal activity across neurons and structures. γ oscillations (30-80 Hz) have received particular attention through their association with perceptual and cognitive processes. Synchronous activity of inhibitory parvalbumin (PV) interneurons generates cortical γ oscillation, but, paradoxically, PV neuron deficiency is associated with increases in γ oscillations. We here reconcile this conundrum and show how deficient PV inhibition can lead to increased and asynchronous excitatory firing, contaminating the local field potential and manifesting as increased γ power. Thus, increased γ power does not always reflect a genuine rhythm. Further, we show that ketamine-induced γ increases are caused by separate network mechanisms.

Parvalbumin interneuron vulnerability and brain disorders

Parvalbumin-expressing interneurons (PV-INs) are highly vulnerable to stressors and have been implicated in many neuro-psychiatric diseases such as schizophrenia, Alzheimer's disease, autism spectrum disorder, and bipolar disorder. We examined the literature about the current knowledge of the physiological properties of PV-INs and gathered results from diverse research areas to provide insight into their vulnerability to stressors. Among the factors that confer heightened vulnerability are the substantial energy requirements, a strong excitatory drive, and a unique developmental trajectory. Understanding these stressors and elaborating on their impact on PV-IN health is a step toward developing therapies to protect these neurons in various disease states and to retain critical brain functions.

Advances in the computational understanding of mental illness

Computational psychiatry is a rapidly growing field attempting to translate advances in computational neuroscience and machine learning into improved outcomes for patients suffering from mental illness. It encompasses both data-driven and theory-driven efforts. Here, recent advances in theory-driven work are reviewed. We argue that the brain is a computational organ. As such, an understanding of the illnesses arising from it will require a computational framework. The review divides work up into three theoretical approaches that have deep mathematical connections: dynamical systems, Bayesian inference and reinforcement learning. We discuss both general and specific challenges for the field, and suggest ways forward.

Identification and quantification of neuronal ensembles in optical imaging experiments

Recent technical advances in molecular biology and optical imaging have made it possible to record from up to thousands of densely packed neurons in superficial and deep brain regions in vivo, with cellular subtype specificity and high spatiotemporal fidelity. Such optical neurotechnologies are enabling increasingly fine-scaled studies of neuronal circuits and reliably co-active groups of neurons, so-called ensembles. Neuronal ensembles are thought to constitute the basic functional building blocks of brain systems, potentially exhibiting collective computational properties. While the technical framework of in vivo optical imaging and quantification of neuronal activity follows certain widely held standards, analytical methods for study of neuronal co-activity and ensembles lack consensus and are highly varied across the field. Here we provide a comprehensive step-by-step overview of theoretical, experimental, and analytical considerations for the identification and quantification of neuronal ensemble dynamics in high-resolution in vivo optical imaging studies.

Stronger tilt aftereffects in persons with schizophrenia

Individuals with schizophrenia may fail to appropriately use temporal context and apply past environmental regularities to the interpretation of incoming sensory information. Here we use the visual system as a test bed for investigating how prior experience shapes perception in individuals with schizophrenia. Specifically, we use visual aftereffects, illusory percepts resulting from prior exposure to visual input, to measure the influence of prior events on current processing. At a neural level, visual aftereffects arise due to attenuation in the responses of neurons that code the features of the prior stimulus (neuronal adaptation) and subsequent disinhibition of neurons signaling activity at the opposite end of the feature dimension. In the current study, we measured tilt aftereffects and negative afterimages, 2 types of aftereffects that reflect, respectively, adaptation of cortical orientation-coding neurons and adaptation of subcortical and retinal luminance-coding cells in persons with schizophrenia (PSZ; n = 36) and demographically matched healthy controls (HC; n = 22). We observed stronger tilt aftereffects in PSZ compared to HC, but no difference in negative afterimages. Stronger tilt aftereffects were related to more severe negative symptoms. These data suggest oversensitivity to recent regularities, in the form of stronger visual adaptation, at cortical, but not subcortical, levels in schizophrenia. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Mild metabolic stress is sufficient to disturb the formation of pyramidal cell ensembles during gamma oscillations

Disturbances of cognitive functions occur rapidly during acute metabolic stress. However, the underlying mechanisms are not fully understood. Cortical gamma oscillations (30-100 Hz) emerging from precise synaptic transmission between excitatory principal neurons and inhibitory interneurons, such as fast-spiking GABAergic basket cells, are associated with higher brain functions, like sensory perception, selective attention and memory formation. We investigated the alterations of cholinergic gamma oscillations at the level of neuronal ensembles in the CA3 region of rat hippocampal slice cultures. We combined electrophysiology, calcium imaging (CamKII.GCaMP6f) and mild metabolic stress that was induced by rotenone, a lipophilic and highly selective inhibitor of complex I in the respiratory chain of mitochondria. The detected pyramidal cell ensembles showing repetitive patterns of activity were highly sensitive to mild metabolic stress. Whereas such synchronised multicellular activity diminished, the overall activity of individual pyramidal cells was unaffected. Additionally, mild metabolic stress had no effect on the rate of action potential generation in fast-spiking neural units. However, the partial disinhibition of slow-spiking neural units suggests that disturbances of ensemble formation likely result from alterations in synaptic inhibition. Our study bridges disturbances on the (multi-)cellular and network level to putative cognitive impairment on the system level.

Synaptic inhibition in the neocortex: Orchestration and computation through canonical circuits and variations on the theme

The neocortex plays a crucial role in all basic and abstract cognitive functions. Conscious mental processes are achieved through a correct flow of information within and across neocortical networks, whose particular activity state results from a tight balance between excitation and inhibition. The proper equilibrium between these indissoluble forces is operated with multiscale organization: along the dendro-somatic axis of single neurons and at the network level. Fast synaptic inhibition is assured by a multitude of inhibitory interneurons. During cortical activities, these cells operate a finely tuned division of labor that is epitomized by their detailed connectivity scheme. Recent results combining the use of mouse genetics, cutting-edge optical and neurophysiological approaches have highlighted the role of fast synaptic inhibition in driving cognition-related activity through a canonical cortical circuit, involving several major interneuron subtypes and principal neurons. Here we detail the organization of this cortical blueprint and we highlight the crucial role played by different neuron types in fundamental cortical computations. In addition, we argue that this canonical circuit is prone to many variations on the theme, depending on the resolution of the classification of neuronal types, and the cortical area investigated. Finally, we discuss how specific alterations of distinct inhibitory circuits can underlie several devastating brain diseases.

Toxoplasma infection induces microglia-neuron contact and the loss of perisomatic inhibitory synapses

Infection and inflammation within the brain induces changes in neuronal connectivity and function. The intracellular protozoan parasite, Toxoplasma gondii, is one pathogen that infects the brain and can cause encephalitis and seizures. Persistent infection by this parasite is also associated with behavioral alterations and an increased risk for developing psychiatric illness, including schizophrenia. Current evidence from studies in humans and mouse models suggest that both seizures and schizophrenia result from a loss or dysfunction of inhibitory synapses. In line with this, we recently reported that persistent T. gondii infection alters the distribution of glutamic acid decarboxylase 67 (GAD67), an enzyme that catalyzes GABA synthesis in inhibitory synapses. These changes could reflect a redistribution of presynaptic machinery in inhibitory neurons or a loss of inhibitory nerve terminals. To directly assess the latter possibility, we employed serial block face scanning electron microscopy (SBFSEM) and quantified inhibitory perisomatic synapses in neocortex and hippocampus following parasitic infection. Not only did persistent infection lead to a significant loss of perisomatic synapses, it induced the ensheathment of neuronal somata by myeloid-derived cells. Immunohistochemical, genetic, and ultrastructural analyses revealed that these myeloid-derived cells included activated microglia. Finally, ultrastructural analysis identified myeloid-derived cells enveloping perisomatic nerve terminals, suggesting they may actively displace or phagocytose synaptic elements. Thus, these results suggest that activated microglia contribute to perisomatic inhibitory synapse loss following parasitic infection and offer a novel mechanism as to how persistent T. gondii infection may contribute to both seizures and psychiatric illness.

Stimulus-specific regulation of visual oddball differentiation in posterior parietal cortex

The frequency at which a stimulus is presented determines how it is interpreted. For example, a repeated image may be of less interest than an image that violates the prior sequence. This process involves integration of sensory information and internal representations of stimulus history, functions carried out in higher-order sensory areas such as the posterior parietal cortex (PPC). Thus far, there are few detailed reports investigating the single-neuron mechanisms for processing of stimulus presentation frequency in PPC. To address this gap in knowledge, we recorded PPC activity using 2-photon calcium imaging and electrophysiology during a visual oddball paradigm. Calcium imaging results reveal differentiation at the level of single neurons for frequent versus rare conditions which varied depending on whether the stimulus was preferred or non-preferred by the recorded neural population. Such differentiation of oddball conditions was mediated primarily by stimulus-independent adaptation in the frequent condition.

Aberrant Cortical Ensembles and Schizophrenia-like Sensory Phenotypes in Setd1a+/- Mice

BACKGROUND

A breakdown of synchrony within neuronal ensembles leading to destabilization of network "attractors" could be a defining aspect of neuropsychiatric diseases such as schizophrenia, representing a common downstream convergence point for the diverse etiological pathways associated with the disease. Using a mouse genetic model, we demonstrated that altered ensembles are associated with pathological sensory cortical processing phenotypes resulting from loss of function mutations in the Setd1a gene, a recently identified rare risk genotype with very high penetrance for schizophrenia.

METHODS

We used fast two-photon calcium imaging of neuronal populations (calcium indicator GCaMP6s, 10 Hz, 100-250 cells, layer 2/3 of primary visual cortex, i.e., V1) in awake head-fixed mice (Setd1a^+/- vs. wild-type littermate control) during rest and visual stimulation with moving full-field square-wave gratings (0.04 cycles per degree, 2.0 cycles per second, 100% contrast, 12 directions). Multielectrode recordings were analyzed in the time-frequency domain to assess stimulus-induced oscillations and cross-layer phase synchrony.

RESULTS

Neuronal activity and orientation/direction selectivity were unaffected in Setd1a^+/- mice, but correlations between cell pairs in V1 showed altered distributions compared with wild-type mice, in both ongoing and visually evoked activity. Furthermore, population-wide "ensemble activations" in Setd1a^+/- mice were markedly less reliable over time during rest and visual stimulation, resulting in unstable encoding of basic visual information. This alteration of ensembles coincided with reductions in alpha and high-gamma band phase synchrony within and between cortical layers.

CONCLUSIONS

These results provide new evidence for an ensemble hypothesis of schizophrenia and highlight the utility of Setd1a^+/- mice for modeling sensory-processing phenotypes.

Testing Psychosis Phenotypes From Bipolar-Schizophrenia Network for Intermediate Phenotypes for Clinical Application: Biotype Characteristics and Targets

BACKGROUND

Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis.

METHODS

Doing this, the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated.

RESULTS

Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes.

CONCLUSIONS

In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.

Gamma-Band Auditory Steady-State Response as a Neurophysiological Marker for Excitation and Inhibition Balance: A Review for Understanding Schizophrenia and Other Neuropsychiatric Disorders

Altered gamma oscillations have attracted considerable attention as an index of the excitation/inhibition (E/I) imbalance in schizophrenia and other neuropsychiatric disorders. The auditory steady-state response (ASSR) has been the most robust probe of abnormal gamma oscillatory dynamics in schizophrenia. Here, we review recent ASSR studies in patients with schizophrenia and other neuropsychiatric disorders. Preclinical ASSR research, which has contributed to the elucidation of the underlying pathophysiology of these diseases, is also discussed. The developmental trajectory of the ASSR has been explored and may show signs of the maturation and disruption of E/I balance in adolescence. Animal model studies have shown that synaptic interactions between parvalbumin-positive GABAergic interneurons and pyramidal neurons contribute to the regulation of E/I balance, which is related to the generation of gamma oscillation. Therefore, ASSR alteration may be a significant electrophysiological finding related to the E/I imbalance in neuropsychiatric disorders, which is a cross-disease feature and may reflect clinical staging. Future studies regarding ASSR generation, especially in nonhuman primate models, will advance our understanding of the brain circuit and the molecular mechanisms underlying neuropsychiatric disorders.

Ketamine contributes to the alteration of Ca2+ transient evoked by behavioral tests in the prelimbic area of mPFC: A study on chronic CORT-induced depressive mice

Recent studies have showed that ketamine is a rapid and efficient antidepressant, but the mechanism of its antidepressant effect is not fully clear. It is still lack of the research investigating the relation between depressive-like behaviors and neuronal activities in specific brain area after administration of ketamine in vivo. Medial prefrontal cortex (mPFC) involved in the pathogenesis of depression. As a result of effective assessments after behavioral test, most studies lack of direct evidence of the relation between efficacy and the activity of specific brain area. Therefore, we used fiber photometry to explore the alteration of Ca²⁺ transient in the prelimbic (PrL) area of mPFC during behavioral tests in freely moving mice. Our results showed that the chronic corticosterone (CORT) protocol induced depressive-like behaviors. Administration of ketamine reversed these effects. The activation of Ca²⁺ transients was associated with some behaviors during behavioral tests. Struggling, rearing and exploring evoked strong Ca²⁺ transients, but moving and grooming did not. The Ca²⁺ transients amplitude reductions of struggling, rearing and exploring induced by CORT were reversed by ketamine. The results indicated that ketamine ameliorated depressive-like behaviors via mediating neural activation in PrL.

Neuregulin 1: an intriguing therapeutic target for neurodevelopmental disorders

Neurodevelopmental psychiatric disorders including schizophrenia (Sz) and attention deficit hyperactivity disorder (ADHD) are chronic mental illnesses, which place costly and painful burdens on patients, their families and society. In recent years, the epidermal growth factor (EGF) family member Neuregulin 1 (NRG1) and one of its receptors, ErbB4, have received considerable attention due to their regulation of inhibitory local neural circuit mechanisms important for information processing, attention, and cognitive flexibility. Here we examine an emerging body of work indicating that either decreasing NRG1-ErbB4 signaling in fast-spiking parvalbumin positive (PV+) interneurons or increasing it in vasoactive intestinal peptide positive (VIP+) interneurons could reactivate cortical plasticity, potentially making it a future target for gene therapy in adults with neurodevelopmental disorders. We propose preclinical studies to explore this model in prefrontal cortex (PFC), but also review the many challenges in pursuing cell type and brain-region-specific therapeutic approaches for the NRG1 system.

Cognitive Control Errors in Nonhuman Primates Resembling Those in Schizophrenia Reflect Opposing Effects of NMDA Receptor Blockade on Causal Interactions Between Cells and Circuits in Prefrontal and Parietal Cortices

BACKGROUND

The causal biology underlying schizophrenia is not well understood, but it is likely to involve a malfunction in how neurons adjust synaptic connections in response to patterns of activity in networks. We examined statistical dependencies between neural signals at the cell, local circuit, and distributed network levels in prefrontal and parietal cortices of monkeys performing a variant of the AX continuous performance task paradigm. We then quantified changes in the pattern of neural interactions across levels of scale following NMDA receptor (NMDAR) blockade and related these changes to a pattern of cognitive control errors closely matching the performance of patients with schizophrenia.

METHODS

We recorded the spiking activity of 1762 neurons along with local field potentials at multiple electrode sites in prefrontal and parietal cortices concurrently, and we generated binary time series indicating the presence or absence of spikes in single neurons or local field potential power above or below a threshold. We then applied causal discovery analysis to the time series to detect statistical dependencies between the signals (causal interactions) and compared the pattern of these interactions before and after NMDAR blockade.

RESULTS

Global blockade of NMDAR produced distinctive and frequently opposite changes in neural interactions at the cell, local circuit, and network levels in prefrontal and parietal cortices. Cognitive control errors were associated with decreased interactions at the cell level and with opposite changes at the network level in prefrontal and parietal cortices.

CONCLUSIONS

NMDAR synaptic deficits change causal interactions between neural signals at different levels of scale that correlate with schizophrenia-like deficits in cognitive control.

Understanding Cortical Dysfunction in Schizophrenia With TMS/EEG

In schizophrenia and related disorders, a deeper mechanistic understanding of neocortical dysfunction will be essential to developing new diagnostic and therapeutic techniques. To this end, combined transcranial magnetic stimulation and electroencephalography (TMS/EEG) provides a non-invasive tool to simultaneously perturb and measure neurophysiological correlates of cortical function, including oscillatory activity, cortical inhibition, connectivity, and synchronization. In this review, we summarize the findings from a variety of studies that apply TMS/EEG to understand the fundamental features of cortical dysfunction in schizophrenia. These results lend to future applications of TMS/EEG in understanding the pathophysiological mechanisms underlying cognitive deficits in schizophrenia.

AT1 -R is involved in the development of long-lasting, region-dependent and oxidative stress-independent astrocyte morphological alterations induced by Ketamine

Astrocytes play an essential role in the genesis, maturation and regulation of the neurovascular unit. Multiple evidence support that astrocyte reactivity has a close relationship to neurovascular unit dysfunction, oxidative stress and inflammation, providing a suitable scenario for the development of mental disorders. Ketamine has been proposed as a single-use antidepressant treatment in major depression, and its antidepressant effects have been associated with anti-inflammatory properties. However, Ketamine long-lasting effects over the neurovascular unit components remain unclear. Angiotensin II AT₁ receptor (AT₁ -R) blockers have anti-inflammatory, antioxidant and neuroprotective effects. The present work aims to distinguish the acute and long-term Ketamine effects over astrocytes response extended to other neurovascular unit components, and the involvement of AT₁ -R, in prefrontal cortex and ventral tegmental area. Male Wistar rats were administered with AT₁ -R antagonist Candesartan/Vehicle (days 1-10) and Ketamine/Saline (days 6-10). After 14 days drug-free, at basal conditions or after Ketamine Challenge, the brains were processed for oxidative stress analysis, cresyl violet staining and immunohistochemistry for glial, neuronal activation and vascular markers. Repeated Ketamine administration induced long-lasting region-dependent astrocyte reactivity and morphological alterations, and neuroadaptative changes observed as exacerbated oxidative stress and neuronal activation, prevented by the AT₁ -R blockade. Ketamine Challenge decreased microglial and astrocyte reactivity and augmented cellular apoptosis, independently of previous treatment. Overall, AT₁ -R is involved in the development of neuroadaptative changes induced by repeated Ketamine administration but does not interfere with the acute effects supporting the potential use of AT₁ -R blockers as a Ketamine complementary therapy in mental disorders.

Playing the piano with the cortex: role of neuronal ensembles and pattern completion in perception and behavior

Neuronal ensembles, i.e. coactive groups of neurons, have been long postulated to be functional building blocks of cortical circuits and units of the neural code. Calcium imaging of neuronal populations has demonstrated the widespread existence of spontaneous and sensory-evoked ensembles in cortical circuits in vivo. The development of two-photon optical techniques to simultaneously record and activate neurons with single cell resolution ("piano" experiments) has revealed the existence of pattern completion neurons, which can trigger an entire ensemble, and demonstrated a causal relation between ensembles and behavior. We review recent results controlling visual perception with targeted holographic manipulation of cortical ensembles by stimulating pattern completion neurons. Analyzing population activity as neuronal ensembles and exploiting pattern completion could enable control of brain states in health and disease.

Separable neural mechanisms for the pleiotropic association of copy number variants with neuropsychiatric traits

22q11.2, 15q13.3, and 1q21.1 microdeletions attract considerable interest by conferring high risk for a range of neuropsychiatric disorders, including schizophrenia and autism. A fundamental open question is whether divergent or convergent neural mechanisms mediate this genetic pleiotropic association with the same behavioral phenotypes. We use a combination of rodent microdeletion models with high-field neuroimaging to perform a comparative whole-brain characterization of functional and structural mechanisms linked to high-risk states. Resting-state functional and structural magnetic resonance imaging data were acquired on mice carrying heterozygous microdeletions in 22q11.2 (N = 12), 15q13.3 (N = 11), and 1q21.1 (N = 11) loci. We performed network-based statistic, graph, and morphometric analyses. The three microdeletions did not share significant systems-level features. Instead, morphometric analyses revealed microcephaly in 1q21.1 and macrocephaly in 15q13.3 deletions, whereas cerebellar volume was specifically reduced in 22q11.2 deletion. In function, 22q11.2 deletion mice showed widespread cortical hypoconnectivity, accompanied by opposing hyperconnectivity in dopaminergic pathways, which was confirmed by graph analysis. 1q21.1 exhibited distinct changes in posterior midbrain morphology and function, especially in periaqueductal gray, whereas 15q13.3 demonstrated alterations in auditory/striatal system. The combination of cortical hypoconnectivity and dopaminergic hyperconnectivity and reduced cerebellum in 22q11.2 deletion mirrors key neurodevelopmental features of schizophrenia, whereas changes in midbrain and auditory/striatal morphology and topology in 1q21.1 and 15q13.3 rather indicate focal processes possibly linked to the emergence of abnormal salience perception and hallucinations. In addition to insights into pathophysiological processes in these microdeletions, our results establish the general point that microdeletions might increase risk for overlapping neuropsychiatric phenotypes through separable neural mechanisms.

The abiding relevance of mouse models of rare mutations to psychiatric neuroscience and therapeutics

Studies using powerful family-based designs aided by large scale case-control studies, have been instrumental in cracking the genetic complexity of the disease, identifying rare and highly penetrant risk mutations and providing a handle on experimentally tractable model systems. Mouse models of rare mutations, paired with analysis of homologous cognitive and sensory processing deficits and state-of-the-art neuroscience methods to manipulate and record neuronal activity have started providing unprecedented insights into pathogenic mechanisms and building the foundation of a new biological framework for understanding mental illness. A number of important principles are emerging, namely that degradation of the computational mechanisms underlying the ordered activity and plasticity of both local and long-range neuronal assemblies, the building blocks necessary for stable cognition and perception, might be the inevitable consequence and the common point of convergence of the vastly heterogeneous genetic liability, manifesting as defective internally- or stimulus-driven neuronal activation patterns and triggering the constellation of schizophrenia symptoms. Animal models of rare mutations have the unique potential to help us move from "which" (gene) to "how", "where" and "when" computational regimes of neural ensembles are affected. Linking these variables should improve our understanding of how symptoms emerge and how diagnostic boundaries are established at a circuit level. Eventually, a better understanding of pathophysiological trajectories at the level of neural circuitry in mice, aided by basic human experimental biology, should guide the development of new therapeutics targeting either altered circuitry itself or the underlying biological pathways.

Ketamine disinhibits dendrites and enhances calcium signals in prefrontal dendritic spines

A subanesthetic dose of ketamine causes acute psychotomimetic symptoms and sustained antidepressant effects. In prefrontal cortex, the prevailing disinhibition hypothesis posits that N-methyl-d-aspartate receptor (NMDAR) antagonists such as ketamine act preferentially on GABAergic neurons. However, cortical interneurons are heterogeneous. In particular, somatostatin-expressing (SST) interneurons selectively inhibit dendrites and regulate synaptic inputs, yet their response to systemic NMDAR antagonism is unknown. Here, we report that ketamine acutely suppresses the activity of SST interneurons in the medial prefrontal cortex of the awake mouse. The deficient dendritic inhibition leads to greater synaptically evoked calcium transients in the apical dendritic spines of pyramidal neurons. By manipulating NMDAR signaling via GluN2B knockdown, we show that ketamine’s actions on the dendritic inhibitory mechanism has ramifications for frontal cortex-dependent behaviors and cortico-cortical connectivity. Collectively, these results demonstrate dendritic disinhibition and elevated calcium levels in dendritic spines as important local-circuit alterations driven by the administration of subanesthetic ketamine.

The authors show that a subanesthetic dose of ketamine markedly elevate calcium signals in apical dendritic spines in the mouse prefrontal cortex. This effect is driven by a local-circuit mechanism that involves the suppression of somatostatin interneurons leading to dendritic disinhibition.

Maternal inflammation has a profound effect on cortical interneuron development in a stage and subtype-specific manner

Severe infections during pregnancy are one of the major risk factors for cognitive impairment in the offspring. It has been suggested that maternal inflammation leads to dysfunction of cortical GABAergic interneurons that in turn underlies cognitive impairment of the affected offspring. However, the evidence comes largely from studies of adult or mature brains and how the impairment of inhibitory circuits arises upon maternal inflammation is unknown. Here we show that maternal inflammation affects multiple steps of cortical GABAergic interneuron development, i.e., proliferation of precursor cells, migration and positioning of neuroblasts, as well as neuronal maturation. Importantly, the development of distinct subtypes of cortical GABAergic interneurons was discretely impaired as a result of maternal inflammation. This translated into a reduction in cell numbers, redistribution across cortical regions and layers, and changes in morphology and cellular properties. Furthermore, selective vulnerability of GABAergic interneuron subtypes was associated with the stage of brain development. Thus, we propose that maternally derived insults have developmental stage-dependent effects, which contribute to the complex etiology of cognitive impairment in the affected offspring.

Calcium Imaging in Drug Discovery for Psychiatric Disorders

The past 5 years have seen a sharp increase in the number of studies using calcium imaging in behaving rodents. These studies have helped identify important roles for individual cells, brain regions, and circuits in some of the core behavioral phenotypes of psychiatric disorders, such as schizophrenia and autism, and have characterized network dysfunction in well-established models of these disorders. Since rescuing clinically relevant behavioral deficits in disease model mice remains a foundation of preclinical CNS research, these studies have the potential to inform new therapeutic approaches targeting specific cell types or projections, or perhaps most importantly, the network-level context in which neurons function. In this mini-review, we will provide a brief overview of recent insights into psychiatric disease-associated mouse models and behavior paradigms, focusing on those achieved by cellular resolution imaging of calcium dynamics in neural populations. We will then discuss how these experiments can support efforts within the pharmaceutical industry, such as target identification, assay development, and candidate screening and validation. Calcium imaging is uniquely capable of bridging the gap between two of the key resources that currently enable CNS drug discovery: genomic and transcriptomic data from human patients, and translatable, population-resolution measures of brain activity (such as fMRI and EEG). Applying this knowledge could yield real value to patients in the near future.

Effects of ketamine on orientation selectivity and variability of neuronal responses in primary visual cortex

The plasticity of the adult brain is one of the most highly evolving areas of recent neuroscience research. It has been acknowledged that the visual cortex in adulthood can adapt and restructure the neuronal connections in response to a sensory experience or to an imposed input such as in adaptation or ocular deprivation protocols. In order to understand the basic cellular mechanisms of plasticity in the primary visual cortex (V1), we examined the effects of ketamine, a non-competitive, glutamatergic NMDAR (N-methyl-D-aspartate receptor) antagonist, on the orientation of cortical cells by measuring their response variability and the Gaussian tuning curves in adult anesthetised mouse and cat. Neurons were recorded extracellularly using glass electrodes. The ketamine was applied locally by placing a custom-cut filter paper (1x1mm) soaked in ketamine solution (10 mg/ml) on the cortical surface next the site of the recording tip, in both species. Our results show that the local and acute exposure of ketamine on V1 changes the preferred orientation of the visual neurons established during the critical period of development. Furthermore, ketamine also leads to a decrease in the orientation selectivity (measured by orientation selectivity index, OSI) and the variability of neuronal evoked responses (measured by Fano factor), but does not affect spontaneous activity. These results suggest that ketamine induces plasticity in V1 neurons that might be operated by a different pathway than that of NMDARs.

Recapitulation and Reversal of Schizophrenia-Related Phenotypes in Setd1a-Deficient Mice

SETD1A, a lysine-methyltransferase, is a key schizophrenia susceptibility gene. Mice carrying a heterozygous loss-of-function mutation of the orthologous gene exhibit alterations in axonal branching and cortical synaptic dynamics accompanied by working memory deficits. We show that Setd1a binds both promoters and enhancers with a striking overlap between Setd1a and Mef2 on enhancers. Setd1a targets are highly expressed in pyramidal neurons and display a complex pattern of transcriptional up- and downregulations shaped by presumed opposing functions of Setd1a on promoters and Mef2-bound enhancers. Notably, evolutionarily conserved Setd1a targets are associated with neuropsychiatric genetic risk burden. Reinstating Setd1a expression in adulthood rescues cognitive deficits. Finally, we identify LSD1 as a major counteracting demethylase for Setd1a and show that its pharmacological antagonism results in a full rescue of the behavioral and morphological deficits in Setd1a-deficient mice. Our findings advance understanding of how SETD1A mutations predispose to schizophrenia (SCZ) and point to novel therapeutic interventions.

Parvalbumin-Positive Interneurons Regulate Neuronal Ensembles in Visual Cortex

For efficient cortical processing, neural circuit dynamics must be spatially and temporally regulated with great precision. Although parvalbumin-positive (PV) interneurons can control network synchrony, it remains unclear how they contribute to spatio-temporal patterning of activity. We investigated this by optogenetic inactivation of PV cells with simultaneous two-photon Ca2+ imaging from populations of neurons in mouse visual cortex in vivo. For both spontaneous and visually evoked activity, PV interneuron inactivation decreased network synchrony. But, interestingly, the response reliability and spatial extent of coactive neuronal ensembles during visual stimulation were also disrupted by PV-cell suppression, which reduced the functional repertoire of ensembles. Thus, PV interneurons can control the spatio-temporal dynamics of multineuronal activity by functionally sculpting neuronal ensembles and making them more different from each other. In doing so, inhibitory circuits could help to orthogonalize multicellular patterns of activity, enabling neural circuits to more efficiently occupy a higher dimensional space of potential dynamics.

Neural and neuronal discoordination in schizophrenia: From ensembles through networks to symptoms

Despite the substantial knowledge accumulated by past research, the exact mechanisms of the pathogenesis of schizophrenia and causal treatments still remain unclear. Deficits of cognition and information processing in schizophrenia are today often viewed as the primary and core symptoms of this devastating disorder. These deficits likely result from disruptions in the coordination of neuronal and neural activity. The aim of this review is to bring together convergent evidence of discoordinated brain circuits in schizophrenia at multiple levels of resolution, ranging from principal cells and interneurons, neuronal ensembles and local circuits, to large-scale brain networks. We show how these aberrations could underlie deficits in cognitive control and other higher order cognitive-behavioural functions. Converging evidence from both animal models and patients with schizophrenia is presented in an effort to gain insight into common features of deficits in the brain information processing in this disorder, marked by disruption of several neurotransmitter and signalling systems and severe behavioural outcomes.

GluA4-Targeted AAV Vectors Deliver Genes Selectively to Interneurons while Relying on the AAV Receptor for Entry

Selective gene delivery into subtypes of interneurons remains an important challenge in vector development. Adeno-associated virus (AAV) vector particles are especially promising for intracerebral injections. For cell entry, AAV2 particles are supposed to attach to heparan-sulfate proteoglycans (HSPGs) followed by endocytosis via the AAV receptor (AAVR). Here, we assessed engineered AAV particles deficient in HSPG attachment but competent in recognizing the glutamate receptor 4 (GluA4, also known as GluRD or GRIA4) through a displayed GluA4-specific DARPin (designed ankyrin repeat protein). When injected into the mouse brain, histological evaluation revealed that in various regions, more than 90% of the transduced cells were interneurons, mainly of the parvalbumin-positive subtype. Although part of the selectivity was mediated by the DARPin, the chosen spleen focus-forming virus (SFFV) promoter had contributed as well. Further analysis revealed that the DARPin mediated selective attachment to GluA4-positive cells, whereas gene delivery required expression of AAVR. Our data suggest that cell selectivity of AAV particles can be modified rationally and efficiently through DARPins, but expression of the AAV entry receptor remains essential.