Altered Cortical Ensembles in Mouse Models of Schizophrenia

Standardizing a method for functional assessment of neural networks in brain organoids

During the last decade brain organoids have emerged as an attractive model system, allowing stem cells to be differentiated into complex 3D models, recapitulating many aspects of human brain development. Whilst many studies have analysed anatomical and cytoarchitectural characteristics of organoids, their functional characterisation has been limited, and highly variable between studies. Standardised, consistent methods for recording functional activity are critical to providing a functional understanding of neuronal networks at the synaptic and network level that can yield useful information about functional network phenotypes in disease and healthy states. In this study we outline a detailed methodology for calcium imaging and Multi-Electrode Array (MEA) recordings in brain organoids. To illustrate the utility of these functional interrogation techniques in uncovering induced differences in neural network activity we applied various stimulating media protocols. We demonstrate overlapping information from the two modalities, with comparable numbers of active cells in the four treatment groups and an increase in synchronous behaviour in BrainPhys treated groups. Further development of analysis pipelines to reveal network level changes in brain organoids will enrich our understanding of network formation and perturbation in these structures, and aid in the future development of drugs that target neurological disorders at the network level.

Differential disruptions in population coding along the dorsal-ventral axis of CA1 in the APP/PS1 mouse model of Aβ pathology

Alzheimer's Disease (AD) is characterized by a range of behavioral alterations, including memory loss and psychiatric symptoms. While there is evidence that molecular pathologies, such as amyloid beta (Aβ), contribute to AD, it remains unclear how this histopathology gives rise to such disparate behavioral deficits. One hypothesis is that Aβ exerts differential effects on neuronal circuits across brain regions, depending on the neurophysiology and connectivity of different areas. To test this, we recorded from large neuronal populations in dorsal CA1 (dCA1) and ventral CA1 (vCA1), two hippocampal areas known to be structurally and functionally diverse, in the APP/PS1 mouse model of amyloidosis. Despite similar levels of Aβ pathology, dCA1 and vCA1 showed distinct disruptions in neuronal population activity as animals navigated a virtual reality environment. In dCA1, pairwise correlations and entropy, a measure of the diversity of activity patterns, were decreased in APP/PS1 mice relative to age-matched C57BL/6 controls. However, in vCA1, APP/PS1 mice had increased pair-wise correlations and entropy as compared to age matched controls. Finally, using maximum entropy models, we connected the microscopic features of population activity (correlations) to the macroscopic features of the population code (entropy). We found that the models' performance increased in predicting dCA1 activity, but decreased in predicting vCA1 activity, in APP/PS1 mice relative to the controls. Taken together, we found that Aβ exerts distinct effects across different hippocampal regions, suggesting that the various behavioral deficits of AD may reflect underlying heterogeneities in neuronal circuits and the different disruptions that Aβ pathology causes in those circuits.

Large-scale coupling of prefrontal activity patterns as a mechanism for cognitive control in health and disease: evidence from rodent models

Cognitive control of behavior is crucial for well-being, as allows subject to adapt to changing environments in a goal-directed way. Changes in cognitive control of behavior is observed during cognitive decline in elderly and in pathological mental conditions. Therefore, the recovery of cognitive control may provide a reliable preventive and therapeutic strategy. However, its neural basis is not completely understood. Cognitive control is supported by the prefrontal cortex, structure that integrates relevant information for the appropriate organization of behavior. At neurophysiological level, it is suggested that cognitive control is supported by local and large-scale synchronization of oscillatory activity patterns and neural spiking activity between the prefrontal cortex and distributed neural networks. In this review, we focus mainly on rodent models approaching the neuronal origin of these prefrontal patterns, and the cognitive and behavioral relevance of its coordination with distributed brain systems. We also examine the relationship between cognitive control and neural activity patterns in the prefrontal cortex, and its role in normal cognitive decline and pathological mental conditions. Finally, based on these body of evidence, we propose a common mechanism that may underlie the impaired cognitive control of behavior.

Rodents' visual gamma as a biomarker of pathological neural conditions

Neural gamma oscillations (indicatively 30-100 Hz) are ubiquitous: they are associated with a broad range of functions in multiple cortical areas and across many animal species. Experimental and computational works established gamma rhythms as a global emergent property of neuronal networks generated by the balanced and coordinated interaction of excitation and inhibition. Coherently, gamma activity is strongly influenced by the alterations of synaptic dynamics which are often associated with pathological neural dysfunctions. We argue therefore that these oscillations are an optimal biomarker for probing the mechanism of cortical dysfunctions. Gamma oscillations are also highly sensitive to external stimuli in sensory cortices, especially the primary visual cortex (V1), where the stimulus dependence of gamma oscillations has been thoroughly investigated. Gamma manipulation by visual stimuli tuning is particularly easy in rodents, which have become a standard animal model for investigating the effects of network alterations on gamma oscillations. Overall, gamma in the rodents' visual cortex offers an accessible probe on dysfunctional information processing in pathological conditions. Beyond vision-related dysfunctions, alterations of gamma oscillations in rodents were indeed also reported in neural deficits such as migraine, epilepsy and neurodegenerative or neuropsychiatric conditions such as Alzheimer's, schizophrenia and autism spectrum disorders. Altogether, the connections between visual cortical gamma activity and physio-pathological conditions in rodent models underscore the potential of gamma oscillations as markers of neuronal (dys)functioning.

Optogenetics 2.0: challenges and solutions towards a quantitative probing of neural circuits

To exploit the full potential of optogenetics, we need to titrate and tailor optogenetic methods to emulate naturalistic circuit function. For that, the following prerequisites need to be met: first, we need to target opsin expression not only to genetically defined neurons per se, but to specifically target a functional node. Second, we need to assess the scope of optogenetic modulation, i.e. the fraction of optogenetically modulated neurons. Third, we need to integrate optogenetic control in a closed loop setting. Fourth, we need to further safe and stable gene expression and light delivery to bring optogenetics to the clinics. Here, we review these concepts for the human and rodent brain.

Phencyclidine Disrupts Neural Coordination and Cognitive Control by Dysregulating Translation

Background

Phencyclidine (PCP) causes psychosis, is abused with increasing frequency, and was extensively used in antipsychotic drug discovery. PCP discoordinates hippocampal ensemble action potential discharge and impairs cognitive control in rats, but how this uncompetitive NMDA receptor (NMDAR) antagonist impairs cognition remains unknown.

Methods

The effects of PCP were investigated on hippocampal CA1 ensemble action potential discharge in vivo in urethane-anesthetized rats and during awake behavior in mice, on synaptic responses in ex vivo mouse hippocampus slices, in mice on a hippocampus-dependent active place avoidance task that requires cognitive control, and on activating the molecular machinery of translation in acute hippocampus slices. Mechanistic causality was assessed by comparing the PCP effects with the effects of inhibitors of protein synthesis, group I metabotropic glutamate receptors (mGluR1/5), and subunit-selective NMDARs.

Results

Consistent with ionotropic actions, PCP discoordinated CA1 ensemble action potential discharge. PCP caused hyperactivity and impaired active place avoidance, despite the rodents having learned the task before PCP administration. Consistent with metabotropic actions, PCP exaggerated protein synthesis-dependent DHPG-induced mGluR1/5-stimulated long-term synaptic depression. Pretreatment with anisomycin or the mGluR1/5 antagonist MPEP, both of which repress translation, prevented PCP-induced discoordination and the cognitive and sensorimotor impairments. PCP as well as the NR2A-containing NMDAR antagonist NVP-AAM077 unbalanced translation that engages the Akt, mTOR (mechanistic target of rapamycin), and 4EBP1 translation machinery and increased protein synthesis, whereas the NR2B-containing antagonist Ro25-6981 did not.

Conclusions

PCP dysregulates translation, acting through NR2A-containing NMDAR subtypes, recruiting mGluR1/5 signaling pathways, and leading to neural discoordination that is central to the cognitive and sensorimotor impairments.

Whole-brain mapping reveals the divergent impact of ketamine on the dopamine system

Ketamine is a multifunctional drug with clinical applications as an anesthetic, pain management medication, and a fast-acting antidepressant. However, it is also recreationally abused for its dissociative effects. Recent studies in rodents are revealing the neuronal mechanisms mediating its actions, but the impact of prolonged exposure to ketamine on brain-wide networks remains less understood. Here, we develop a sub-cellular resolution whole-brain phenotyping approach and utilize it in male mice to show that repeated ketamine administration leads to a dose-dependent decrease in dopamine neurons in midbrain regions linked to behavioral states, alongside an increase in the hypothalamus. Additionally, diverse changes are observed in long-range innervations of the prefrontal cortex, striatum, and sensory areas. Furthermore, the data support a role for post-transcriptional regulation in enabling ketamine-induced neural plasticity. Through an unbiased, high-resolution whole-brain analysis, this study provides important insights into how chronic ketamine exposure reshapes brain-wide networks.

Scn2a insufficiency alters spontaneous neuronal Ca2+ activity in somatosensory cortex during wakefulness

SCN2A protein-truncating variants (PTV) can result in neurological disorders such as autism spectrum disorder and intellectual disability, but they are less likely to cause epilepsy in comparison to missense variants. While in vitro studies showed PTV reduce action potential firing, consequences at in vivo network level remain elusive. Here, we generated a mouse model of Scn2a insufficiency using antisense oligonucleotides (Scn2a ASO mice), which recapitulated key clinical feature of SCN2A PTV disorders. Simultaneous two-photon Ca2+ imaging and electrocorticography (ECoG) in awake mice showed that spontaneous Ca2+ transients in somatosensory cortical neurons, as well as their pairwise co-activities were generally decreased in Scn2a ASO mice during spontaneous awake state and induced seizure state. The reduction of neuronal activities and paired co-activity are mechanisms associated with motor, social and cognitive deficits observed in our mouse model of severe Scn2a insufficiency, indicating these are likely mechanisms driving SCN2A PTV pathology.

Low-dose lithium adjunct to quetiapine improves cognitive task performance in mice with MK801-induced long-term cognitive impairment: Evidence from a pilot study

BACKGROUND

Low-dose lithium (LD-Li) has been shown to rescue cognitive impairment in mouse models of short-term mild cognitive impairment, dementia, and schizophrenia. However, few studies have characterized the effects of LD-Li, alone or in conjunction with anti-psychotics, in the mouse model of MK801-induced long term cognitive impairment.

METHODS

The present study used in vivo Ca2+ imaging and a battery of cognitive function assessments to investigate the long-term effects of LD-Li on cognition in mice exposed to repeated injections of MK801. Prefrontal Ca2+ activity was visualized to estimate alterations in neural activity in the model mice. Pre-pulse inhibition (PPI), novel object recognition (NOR), Morris water maze (MWM), and fear conditioning (FC) tasks were used to characterize cognitive performance; open field activity (OFA) testing was used to observe psychotic symptoms. Two treatment strategies were tested: LD-Li [250 mg/d human equivalent dose (HED)] adjunct to quetiapine (QTP; 600 mg/d HED); and QTP-monotherapy (mt; 600 mg/d HED).

RESULTS

Compared to the QTP-mt group, the LD-Li + QTP group showed greatly improved cognitive performance on all measures between experimental days 29 and 85. QTP-mt improved behavioral measures compared to untreated controls, but the effects persisted only from day 29 to day 43. These data suggest that LD-Li + QTP is superior to QTP-mt for improving long-term cognitive impairments in the MK801 mouse model.

LIMITATIONS

There is no medical consensus regarding lithium use in patients with schizophrenia.

CONCLUSION

More pre-clinical and clinical studies are needed to further investigate effective treatment strategies for patients with long-term cognitive impairments, such as chronic schizophrenia.

Advocating for neurodata privacy and neurotechnology regulation

The ability to record and alter brain activity by using implantable and nonimplantable neural devices, while poised to have significant scientific and clinical benefits, also raises complex ethical concerns. In this Perspective, we raise awareness of the ability of artificial intelligence algorithms and data-aggregation tools to decode and analyze data containing highly sensitive information, jeopardizing personal neuroprivacy. Voids in existing regulatory frameworks, in fact, allow unrestricted decoding and commerce of neurodata. We advocate for the implementation of proposed ethical and human rights guidelines, alongside technical options such as data encryption, differential privacy and federated learning to ensure the protection of neurodata privacy. We further encourage regulatory bodies to consider taking a position of responsibility by categorizing all brain-derived data as sensitive health data and apply existing medical regulations to all data gathered via pre-registered neural devices. Lastly, we propose that a technocratic oath may instill a deontology for neurotechnology practitioners akin to what the Hippocratic oath represents in medicine. A conscientious societal position that thoroughly rejects the misuse of neurodata would provide the moral compass for the future development of the neurotechnology field.

Top-down input modulates visual context processing through an interneuron-specific circuit

Visual stimuli that deviate from the current context elicit augmented responses in the primary visual cortex (V1). These heightened responses, known as "deviance detection," require local inhibition in the V1 and top-down input from the anterior cingulate area (ACa). Here, we investigated the mechanisms by which the ACa and V1 interact to support deviance detection. Local field potential recordings in mice during an oddball paradigm showed that ACa-V1 synchrony peaks in the theta/alpha band (≈10 Hz). Two-photon imaging in the V1 revealed that mainly pyramidal neurons exhibited deviance detection, while contextually redundant stimuli increased vasoactive intestinal peptide (VIP)-positive interneuron (VIP) activity and decreased somatostatin-positive interneuron (SST) activity. Optogenetic drive of ACa-V1 inputs at 10 Hz activated V1-VIPs but inhibited V1-SSTs, mirroring the dynamics present during the oddball paradigm. Chemogenetic inhibition of V1-VIPs disrupted Aca-V1 synchrony and deviance detection in the V1. These results outline temporal and interneuron-specific mechanisms of top-down modulation that support visual context processing.

Robust multisensory deviance detection in the mouse parietal associative area

Context modulates how information is processed in the mammalian brain. For example, brain responses are amplified to contextually unusual stimuli. This phenomenon, known as "deviance detection,"1,2 is well documented in early, primary sensory cortex, where large responses are generated to simple stimuli that deviate from their context in low-order properties, such as line orientation, size, or pitch.2,3,4,5 However, the extent to which neural deviance detection manifests (1) in broader cortical networks and (2) to simple versus complex stimuli, which deviate only in their higher-order, multisensory properties, is not known. Consistent with a predictive processing framework,6,7 we hypothesized that deviance detection manifests in a hierarchical manner across cortical networks,8,9 emerging later and further downstream when stimulus deviance is complex. To test this, we examined brain responses of awake mice to simple unisensory deviants (e.g., visual line gratings, deviating from context in their orientation alone) versus complex multisensory deviants (i.e., audiovisual pairs, deviating from context only in their audiovisual pairing but not visual or auditory content alone). We find that mouse parietal associative area-a higher cortical region-displays robust multisensory deviance detection. In contrast, primary visual cortex exhibits strong unisensory visual deviance detection but weaker multisensory deviance detection. These results suggest that deviance detection signals in the cortex may be conceptualized as "prediction errors," which are primarily fed forward-or downstream-in cortical networks.6,7.

Spatiotemporal dynamics across visual cortical laminae support a predictive coding framework for interpreting mismatch responses

Context modulates neocortical processing of sensory data. Unexpected visual stimuli elicit large responses in primary visual cortex (V1)-a phenomenon known as deviance detection (DD) at the neural level, or "mismatch negativity" (MMN) when measured with EEG. It remains unclear how visual DD/MMN signals emerge across cortical layers, in temporal relation to the onset of deviant stimuli, and with respect to brain oscillations. Here we employed a visual "oddball" sequence-a classic paradigm for studying aberrant DD/MMN in neuropsychiatric populations-and recorded local field potentials in V1 of awake mice with 16-channel multielectrode arrays. Multiunit activity and current source density profiles showed that although basic adaptation to redundant stimuli was present early (50 ms) in layer 4 responses, DD emerged later (150-230 ms) in supragranular layers (L2/3). This DD signal coincided with increased delta/theta (2-7 Hz) and high-gamma (70-80 Hz) oscillations in L2/3 and decreased beta oscillations (26-36 Hz) in L1. These results clarify the neocortical dynamics elicited during an oddball paradigm at a microcircuit level. They are consistent with a predictive coding framework, which posits that predictive suppression is present in cortical feed-back circuits, which synapse in L1, whereas "prediction errors" engage cortical feed-forward processing streams, which emanate from L2/3.

Developmental loss of ErbB4 in PV interneurons disrupts state-dependent cortical circuit dynamics

GABAergic inhibition plays an important role in the establishment and maintenance of cortical circuits during development. Neuregulin 1 (Nrg1) and its interneuron-specific receptor ErbB4 are key elements of a signaling pathway critical for the maturation and proper synaptic connectivity of interneurons. Using conditional deletions of the ERBB4 gene in mice, we tested the role of this signaling pathway at two developmental timepoints in parvalbumin-expressing (PV) interneurons, the largest subpopulation of cortical GABAergic cells. Loss of ErbB4 in PV interneurons during embryonic, but not late postnatal development leads to alterations in the activity of excitatory and inhibitory cortical neurons, along with severe disruption of cortical temporal organization. These impairments emerge by the end of the second postnatal week, prior to the complete maturation of the PV interneurons themselves. Early loss of ErbB4 in PV interneurons also results in profound dysregulation of excitatory pyramidal neuron dendritic architecture and a redistribution of spine density at the apical dendritic tuft. In association with these deficits, excitatory cortical neurons exhibit normal tuning for sensory inputs, but a loss of state-dependent modulation of the gain of sensory responses. Together these data support a key role for early developmental Nrg1/ErbB4 signaling in PV interneurons as a powerful mechanism underlying the maturation of both the inhibitory and excitatory components of cortical circuits.

Perspectives on adaptive dynamical systems

Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.

Increased Central Auditory Gain and Decreased Parvalbumin-Positive Cortical Interneuron Density in the Df1/+ Mouse Model of Schizophrenia Correlate With Hearing Impairment

Background

Hearing impairment is a risk factor for schizophrenia. Patients with 22q11.2 deletion syndrome have a 25% to 30% risk of schizophrenia, and up to 60% also have varying degrees of hearing impairment, primarily from middle-ear inflammation. The Df1/+ mouse model of 22q11.2 deletion syndrome recapitulates many features of the human syndrome, including schizophrenia-relevant brain abnormalities and high interindividual variation in hearing ability. However, the relationship between brain abnormalities and hearing impairment in Df1/+ mice has not been examined.

Methods

We measured auditory brainstem responses, cortical auditory evoked potentials, and/or cortical parvalbumin-positive (PV+) interneuron density in over 70 adult mice (32 Df1/+, 39 wild-type). We also performed longitudinal auditory brainstem response measurements in an additional 20 animals (13 Df1/+, 7 wild-type) from 3 weeks of age.

Results

Electrophysiological markers of central auditory excitability were elevated in Df1/+ mice. PV+ interneurons, which are implicated in schizophrenia pathology, were reduced in density in the auditory cortex but not the secondary motor cortex. Both auditory brain abnormalities correlated with hearing impairment, which affected approximately 60% of adult Df1/+ mice and typically emerged before 6 weeks of age.

Conclusions

In the Df1/+ mouse model of 22q11.2 deletion syndrome, abnormalities in central auditory excitability and auditory cortical PV+ immunoreactivity correlate with hearing impairment. This is the first demonstration of cortical PV+ interneuron abnormalities correlating with hearing impairment in a mouse model of either schizophrenia or middle-ear inflammation.

Deep psychophysiological phenotyping of adolescents and adults with 22q11.2 deletion syndrome: a multilevel approach to defining core disease processes

BACKGROUND

22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal interstitial-deletion disorder, occurring in approximately 1 in 2000 to 6000 live births. Affected individuals exhibit variable clinical phenotypes that can include velopharyngeal anomalies, heart defects, T-cell-related immune deficits, dysmorphic facial features, neurodevelopmental disorders, including autism, early cognitive decline, schizophrenia, and other psychiatric disorders. Developing comprehensive treatments for 22q11.2DS requires an understanding of both the psychophysiological and neural mechanisms driving clinical outcomes. Our project probes the core psychophysiological abnormalities of 22q11.2DS in parallel with molecular studies of stem cell-derived neurons to unravel the basic mechanisms and pathophysiology of 22q11.2-related psychiatric disorders, with a primary focus on psychotic disorders. Our study is guided by the central hypothesis that abnormal neural processing associates with psychophysiological processing and underlies clinical diagnosis and symptomatology. Here, we present the scientific background and justification for our study, sharing details of our study design and human data collection protocol.

METHODS

Our study is recruiting individuals with 22q11.2DS and healthy comparison subjects between the ages of 16 and 60 years. We are employing an extensive psychophysiological assessment battery (e.g., EEG, evoked potential measures, and acoustic startle) to assess fundamental sensory detection, attention, and reactivity. To complement these unbiased measures of cognitive processing, we will develop stem-cell derived neurons and examine neuronal phenotypes relevant to neurotransmission. Clinical characterization of our 22q11.2DS and control participants relies on diagnostic and research domain criteria assessments, including standard Axis-I diagnostic and neurocognitive measures, following from the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) and the North American Prodrome Longitudinal Study (NAPLS) batteries. We are also collecting measures of autism spectrum (ASD) and attention deficit/hyperactivity disorder (ADHD)-related symptoms.

DISCUSSION

Studying 22q11.2DS in adolescence and adulthood via deep phenotyping across multiple clinical and biological domains may significantly increase our knowledge of its core disease processes. Our manuscript describes our ongoing study's protocol in detail. These paradigms could be adapted by clinical researchers studying 22q11.2DS, other CNV/single gene disorders, or idiopathic psychiatric syndromes, as well as by basic researchers who plan to incorporate biobehavioral outcome measures into their studies of 22q11.2DS.

Low-dose lithium mono- and adjunctive therapies improve MK-801-induced cognitive impairment and schizophrenia-like behavior in mice - Evidence from altered prefrontal lobe Ca2+ activity

BACKGROUND

Few studies have evaluated lithium either as monotherapy or in combination with anti-psychotic agents to improve cognition in murine models of schizophrenia.

METHODS

Visualization of Ca²⁺ activity in the prefrontal cortex was used to characterize brain neural activity. Novel object recognition (NOR), Morris water maze (MWM), and fear conditioning (FCT) tests were used to characterize cognitive performance; while pre-pulse inhibition (PPI), elevated plus maze (EPM) and the open field test (OFT) were used to characterize schizophrenia-like behavior.

RESULTS

A 28-day course of low-dose lithium (human equivalent dose of 250 mg/day) combined with moderate-dose quetiapine (human equivalent dose of 600 mg/day) improved Ca²⁺ ratio by 70.10 %, PPI by 69.28 %, NOR by 70.09 %, MWM by 71.28 %, FCT by 68.56 %, EPM by 70.95 % and OFT by 75.23 % compared to the results of positive controls. Unexpectedly, moderate-dose lithium (human equivalent dose of 500 mg/day) used either as monotherapy or as an adjunct with quetiapine worsened Ca²⁺ activity, PPI, MWM, FCT, EPM, and OPT.

LIMITATIONS

Our study cannot explain the contrasting positive and negative effects of low-dose and moderate-dose lithium, respectively, when used either as monotherapies or as adjuncts. Further studies, especially Western blotting, may reveal molecular mechanisms of action.

CONCLUSIONS

Low-dose lithium (human equivalent dose of 250 mg/day) combined with moderate-dose quetiapine (human equivalent dose of 600 mg/day) provided the best improvements. Furthermore, benefits persisted for 14 days post-treatment. Our data provide directions for further research of therapeutic alternatives to mitigate schizophrenia-related cognopathy.

The molecular pathology of schizophrenia: an overview of existing knowledge and new directions for future research

Despite enormous efforts employing various approaches, the molecular pathology in the schizophrenia brain remains elusive. On the other hand, the knowledge of the association between the disease risk and changes in the DNA sequences, in other words, our understanding of the genetic pathology of schizophrenia, has dramatically improved over the past two decades. As the consequence, now we can explain more than 20% of the liability to schizophrenia by considering all analyzable common genetic variants including those with weak or no statistically significant association. Also, a large-scale exome sequencing study identified single genes whose rare mutations substantially increase the risk for schizophrenia, of which six genes (SETD1A, CUL1, XPO7, GRIA3, GRIN2A, and RB1CC1) showed odds ratios larger than ten. Based on these findings together with the preceding discovery of copy number variants (CNVs) with similarly large effect sizes, multiple disease models with high etiological validity have been generated and analyzed. Studies of the brains of these models, as well as transcriptomic and epigenomic analyses of patient postmortem tissues, have provided new insights into the molecular pathology of schizophrenia. In this review, we overview the current knowledge acquired from these studies, their limitations, and directions for future research that may redefine schizophrenia based on biological alterations in the responsible organ rather than operationalized criteria.

Visually evoked neuronal ensembles reactivate during sleep

Neuronal ensembles, defined as groups of coactive neurons, dominate cortical activity and are causally related to perceptual states and behavior. Interestingly, ensembles occur spontaneously in the absence of sensory stimulation. To better understand the function of ensembles in spontaneous activity, we explored if ensembles also occur during different brain states, including sleep, using two-photon calcium imaging from mouse primary visual cortex. We find that ensembles are present during all wake and sleep states, with different characteristics depending on the exact sleep stage. Moreover, visually evoked ensembles are reactivated during subsequent slow wave sleep cycles. Our results are consistent with the hypothesis that repeated sensory stimulation can reconfigure cortical circuits and imprint neuronal ensembles that are reactivated during sleep for potential processing or memory consolidation.

One-Sentence Summary

Cortical neuronal ensembles are present across wake and sleep states, and visually evoked ensembles are reactivated in subsequent slow-wave sleep.

Whole-brain mapping reveals the divergent impact of ketamine on the dopamine system

Ketamine is a multifunctional drug with clinical applications as an anesthetic, as a pain management medication and as a transformative fast-acting antidepressant. It is also abused as a recreational drug due to its dissociative property. Recent studies in rodents are revealing the neuronal mechanisms that mediate the complex actions of ketamine, however, its long-term impact due to prolonged exposure remains much less understood with profound scientific and clinical implications. Here, we develop and utilize a high-resolution whole-brain phenotyping approach to show that repeated ketamine administration leads to a dosage-dependent decrease of dopamine (DA) neurons in the behavior state-related midbrain regions and, conversely, an increase within the hypothalamus. Congruently, we show divergently altered innervations of prefrontal cortex, striatum, and sensory areas. Further, we present supporting data for the post-transcriptional regulation of ketamine-induced structural plasticity. Overall, through an unbiased whole-brain analysis, we reveal the divergent brain-wide impact of chronic ketamine exposure on the association and sensory pathways.

Spatiotemporal dynamics across visual cortical laminae support a predictive coding framework for interpreting mismatch responses

Context modulates neocortical processing of sensory data. Unexpected visual stimuli elicit large responses in primary visual cortex (V1) -- a phenomenon known as deviance detection (DD) at the neural level, or "mismatch negativity" (MMN) when measured with EEG. It remains unclear how visual DD/MMN signals emerge across cortical layers, in temporal relation to the onset of deviant stimuli, and with respect to brain oscillations. Here we employed a visual "oddball" sequence - a classic paradigm for studying aberrant DD/MMN in neuropsychiatric populations - and recorded local field potentials in V1 of awake mice with 16-channel multielectrode arrays. Multiunit activity and current source density profiles showed that while basic adaptation to redundant stimuli was present early (50ms) in layer 4 responses, DD emerged later (150-230ms) in supragranular layers (L2/3). This DD signal coincided with increased delta/theta (2-7Hz) and high-gamma (70-80Hz) oscillations in L2/3 and decreased beta oscillations (26-36hz) in L1. These results clarify the neocortical dynamics elicited during an oddball paradigm at a microcircuit level. They are consistent with a predictive coding framework, which posits that predictive suppression is present in cortical feed-back circuits, which synapse in L1, while "prediction errors" engage cortical feed-forward processing streams, which emanate from L2/3.

Multimodal mismatch responses in associative but not primary visual cortex support hierarchical predictive coding in cortical networks

A key function of the mammalian neocortex is to process sensory data in the context of current and past stimuli. Primary sensory cortices, such as V1, respond weakly to stimuli that typical in their context but strongly to novel stimuli, an effect known as "deviance detection". How deviance detection occurs in associative cortical regions that are downstream of V1 is not well-understood. Here we investigated parietal associative area (PTLp) responses to auditory, visual, and audio-visual mismatches with two-photon calcium imaging and local field potential recordings. We employed basic unisensory auditory and visual oddball paradigms as well as a novel multisensory oddball paradigm, involving typical parings (VaAc or VbAd) presented at p=.88 with rare "deviant" pairings (e.g. VaAd or VbAc) presented at p=.12. We found that PTLp displayed robust deviance detection responses to auditory-visual mismatches, both in individual neurons and in population theta and gamma-band oscillations. In contrast, V1 neurons displayed deviance detection only to visual deviants in a unisensory context, but not to auditory or auditory-visual mismatches. Taken together, these results accord with a predictive processing framework for cortical responses, wherein modality specific prediction errors (i.e. deviance detection responses) are computed in functionally specified cortical areas and feed-forward to update higher brain regions.

Expression of the primate-specific LINC00473 RNA in mouse neurons promotes excitability and CREB-regulated transcription

The LINC00473 (Lnc473) gene has previously been shown to be associated with cancer and psychiatric disorders. Its expression is elevated in several types of tumors and decreased in the brains of patients diagnosed with schizophrenia or major depression. In neurons, Lnc473 transcription is strongly responsive to synaptic activity, suggesting a role in adaptive, plasticity-related mechanisms. However, the function of Lnc473 is largely unknown. Here, using a recombinant adeno-associated viral vector, we introduced a primate-specific human Lnc473 RNA into mouse primary neurons. We show that this resulted in a transcriptomic shift comprising downregulation of epilepsy-associated genes and a rise in cAMP response element binding protein (CREB) activity, which was driven by augmented CREB-regulated transcription coactivator 1 (CRTC1) nuclear localization. Moreover, we demonstrate that ectopic Lnc473 expression increased neuronal excitability as well as network excitability. These findings suggest that primates may possess a lineage-specific activity-dependent modulator of CREB-regulated neuronal excitability.

A frontosensory circuit for visual context processing is synchronous in the theta/alpha band

Visual processing is strongly influenced by context. Stimuli that deviate from contextual regularities elicit augmented responses in primary visual cortex (V1). These heightened responses, known as "deviance detection," require both inhibition local to V1 and top-down modulation from higher areas of cortex. Here we investigated the spatiotemporal mechanisms by which these circuit elements interact to support deviance detection. Local field potential recordings in mice in anterior cingulate area (ACa) and V1 during a visual oddball paradigm showed that interregional synchrony peaks in the theta/alpha band (6-12 Hz). Two-photon imaging in V1 revealed that mainly pyramidal neurons exhibited deviance detection, while vasointestinal peptide-positive interneurons (VIPs) increased activity and somatostatin-positive interneurons (SSTs) decreased activity (adapted) to redundant stimuli (prior to deviants). Optogenetic drive of ACa-V1 inputs at 6-12 Hz activated V1-VIPs but inhibited V1-SSTs, mirroring the dynamics present during the oddball paradigm. Chemogenetic inhibition of VIP interneurons disrupted ACa-V1 synchrony and deviance detection responses in V1. These results outline spatiotemporal and interneuron-specific mechanisms of top-down modulation that support visual context processing.

Neural ensembles in the murine medial prefrontal cortex process distinct information during visual perceptual learning

BACKGROUND

Perceptual learning refers to an augmentation of an organism's ability to respond to external stimuli, which has been described in most sensory modalities. Visual perceptual learning (VPL) is a manifestation of plasticity in visual information processing that occurs in the adult brain, and can be used to ameliorate the ability of patients with visual defects mainly based on an improvement of detection or discrimination of features in visual tasks. While some brain regions such as the primary visual cortex have been described to participate in VPL, the way more general high-level cognitive brain areas are involved in this process remains unclear. Here, we showed that the medial prefrontal cortex (mPFC) was essential for both the training and maintenance processes of VPL in mouse models.

RESULTS

We built a new VPL model in a custom-designed training chamber to enable the utilization of miniScopes when mice freely executed the VPL task. We found that pyramidal neurons in the mPFC participate in both the training process and maintenance of VPL. By recording the calcium activity of mPFC pyramidal neurons while mice freely executed the task, distinct ON and OFF neural ensembles tuned to different behaviors were identified, which might encode different cognitive information. Decoding analysis showed that mouse behaviors could be well predicted using the activity of each ON ensemble. Furthermore, VPL recruited more reward-related components in the mPFC.

CONCLUSION

We revealed the neural mechanism underlying vision improvement following VPL and identify distinct ON and OFF neural ensembles in the mPFC that tuned to different information during visual perceptual training. These results uncover an important role of the mPFC in VPL, with more reward-related components being also involved, and pave the way for future clarification of the reward signal coding rules in VPL.

Rescue of neuropsychiatric phenotypes in a mouse model of 16p11.2 duplication syndrome by genetic correction of an epilepsy network hub

Neuropsychiatric disorders (NPDs) are frequently co-morbid with epilepsy, but the biological basis of shared risk remains poorly understood. The 16p11.2 duplication is a copy number variant that confers risk for diverse NPDs including autism spectrum disorder, schizophrenia, intellectual disability and epilepsy. We used a mouse model of the 16p11.2 duplication (16p11.2dup/+) to uncover molecular and circuit properties associated with this broad phenotypic spectrum, and examined genes within the locus capable of phenotype reversal. Quantitative proteomics revealed alterations to synaptic networks and products of NPD risk genes. We identified an epilepsy-associated subnetwork that was dysregulated in 16p11.2dup/+ mice and altered in brain tissue from individuals with NPDs. Cortical circuits from 16p11.2dup/+ mice exhibited hypersynchronous activity and enhanced network glutamate release, which increased susceptibility to seizures. Using gene co-expression and interactome analysis, we show that PRRT2 is a major hub in the epilepsy subnetwork. Remarkably, correcting Prrt2 copy number rescued aberrant circuit properties, seizure susceptibility and social deficits in 16p11.2dup/+ mice. We show that proteomics and network biology can identify important disease hubs in multigenic disorders, and reveal mechanisms relevant to the complex symptomatology of 16p11.2 duplication carriers.

Complement-dependent loss of inhibitory synapses on pyramidal neurons following Toxoplasma gondii infection

The apicomplexan parasite Toxoplasma gondii has developed mechanisms to establish a central nervous system infection in virtually all warm-blooded animals. Acute T. gondii infection can cause neuroinflammation, encephalitis, and seizures. Meanwhile, studies in humans, nonhuman primates, and rodents have linked chronic T. gondii infection with altered behavior and increased risk for neuropsychiatric disorders, including schizophrenia. These observations and associations raise questions about how this parasitic infection may alter neural circuits. We previously demonstrated that T. gondii infection triggers the loss of inhibitory perisomatic synapses, a type of synapse whose dysfunction or loss has been linked to neurological and neuropsychiatric disorders. We showed that phagocytic cells (including microglia and infiltrating monocytes) contribute to the loss of these inhibitory synapses. Here, we show that these phagocytic cells specifically ensheath excitatory pyramidal neurons, leading to the preferential loss of perisomatic synapses on these neurons and not those on cortical interneurons. Moreover, we show that infection induces an increased expression of the complement C3 gene, including by populations of these excitatory neurons. Infecting C3-deficient mice with T. gondii revealed that C3 is required for the loss of perisomatic inhibitory synapses. Interestingly, loss of C1q did not prevent the loss of perisomatic synapses following infection. Together, these findings provide evidence that T. gondii induces changes in excitatory pyramidal neurons that trigger the selective removal of inhibitory perisomatic synapses and provide a role for a nonclassical complement pathway in the remodeling of inhibitory circuits in the infected brain.

Using Nonhuman Primate Models to Reverse-Engineer Prefrontal Circuit Failure Underlying Cognitive Deficits in Schizophrenia

In this chapter, I review studies in nonhuman primates that emulate the circuit failure in prefrontal cortex responsible for working memory and cognitive control deficits in schizophrenia. These studies have characterized how synaptic malfunction, typically induced by blockade of NMDAR, disrupts neural function and computation in prefrontal networks to explain errors in cognitive tasks that are seen in schizophrenia. This work is finding causal relationships between pathogenic events of relevance to schizophrenia at vastly different levels of scale, from synapses, to neurons, local, circuits, distributed networks, computation, and behavior. Pharmacological manipulation, the dominant approach in primate models, has limited construct validity for schizophrenia pathogenesis, as the disease results from a complex interplay between environmental, developmental, and genetic factors. Genetic manipulation replicating schizophrenia risk is more advanced in rodent models. Nonetheless, gene manipulation in nonhuman primates is rapidly advancing, and primate developmental models have been established. Integration of large scale neural recording, genetic manipulation, and computational modeling in nonhuman primates holds considerable potential to provide a crucial schizophrenia model moving forward. Data generated by this approach is likely to fill several crucial gaps in our understanding of the causal sequence leading to schizophrenia in humans. This causal chain presents a vexing problem largely because it requires understanding how events at very different levels of scale relate to one another, from genes to circuits to cognition to social interactions. Nonhuman primate models excel here. They optimally enable discovery of causal relationships across levels of scale in the brain that are relevant to cognitive deficits in schizophrenia. The mechanistic understanding of prefrontal circuit failure they promise to provide may point the way to more effective therapeutic interventions to restore function to prefrontal networks in the disease.

SCN1A channelopathies: Navigating from genotype to neural circuit dysfunction

The SCN1A gene is strongly associated with epilepsy and plays a central role for supporting cortical excitation-inhibition balance through the expression of Na_V1.1 within inhibitory interneurons. The phenotype of SCN1A disorders has been conceptualized as driven primarily by impaired interneuron function that predisposes to disinhibition and cortical hyperexcitability. However, recent studies have identified SCN1A gain-of-function variants associated with epilepsy, and the presence of cellular and synaptic changes in mouse models that point toward homeostatic adaptations and complex network remodeling. These findings highlight the need to understand microcircuit-scale dysfunction in SCN1A disorders to contextualize genetic and cellular disease mechanisms. Targeting the restoration of microcircuit properties may be a fruitful strategy for the development of novel therapies.

The contribution of gamma bursting to spontaneous gamma activity in schizophrenia

Increased spontaneous gamma (30-100 Hz) activity (SGA) has been reported in the auditory cortex in schizophrenia. This phenomenon has been correlated with psychotic symptoms such as auditory hallucinations and could reflect the dysfunction of NMDA receptors on parvalbumin-expressing inhibitory interneurons. Previous findings are from time-averaged spectra, so it is unknown whether increased spontaneous gamma occurs at a constant level, or rather in bursts. To better understand the dynamical nature of spontaneous gamma activity in schizophrenia, here we examined the contribution of gamma bursting and the slope of the EEG spectrum to this phenomenon. The main results from this data set were previously reported. Participants were 24 healthy control participants (HC) and 24 matched participants with schizophrenia (SZ). The data were from EEG recordings during auditory steady-state stimulation, which were localized to bilateral pairs of dipoles in auditory cortex. Time-frequency analysis was performed using Morlet wavelets. Oscillation bursts in the gamma range were defined as periods during which power exceeded 2 standard deviations above the trial-wide average value for at least one cycle. We extracted the burst parameters power, count, and area, as well as non-burst trial power and spectral slope. Gamma burst power and non-burst trial power were greater in SZ than HC, but burst count and area did not differ. Spectral slope was less negative in SZ than HC. Regression modeling found that gamma burst power alone best predicted SGA for both HC and SZ (> = 90% of variance), while spectral slope made a small contribution and non-burst trial power did not influence SGA. Increased SGA in the auditory cortex in schizophrenia is accounted for by increased power within gamma bursts, rather than a tonic increase in gamma-range activity, or a shift in spectral slope. Further research will be necessary to determine if these measures reflect different network mechanisms. We propose that increased gamma burst power is the main component of increased SGA in SZ and could reflect abnormally increased plasticity in cortical circuits due to enhanced plasticity of synapses on parvalbumin-expressing inhibitory interneurons. Thus, increased gamma burst power may be involved in producing psychotic symptoms and cognitive dysfunction.

Could psychedelic drugs have a role in the treatment of schizophrenia? Rationale and strategy for safe implementation

Schizophrenia is a widespread psychiatric disorder that affects 0.5-1.0% of the world's population and induces significant, long-term disability that exacts high personal and societal cost. Negative symptoms, which respond poorly to available antipsychotic drugs, are the primary cause of this disability. Association of negative symptoms with cortical atrophy and cell loss is widely reported. Psychedelic drugs are undergoing a significant renaissance in psychiatric disorders with efficacy reported in several conditions including depression, in individuals facing terminal cancer, posttraumatic stress disorder, and addiction. There is considerable evidence from preclinical studies and some support from human studies that psychedelics enhance neuroplasticity. In this Perspective, we consider the possibility that psychedelic drugs could have a role in treating cortical atrophy and cell loss in schizophrenia, and ameliorating the negative symptoms associated with these pathological manifestations. The foremost concern in treating schizophrenia patients with psychedelic drugs is induction or exacerbation of psychosis. We consider several strategies that could be implemented to mitigate the danger of psychotogenic effects and allow treatment of schizophrenia patients with psychedelics to be implemented. These include use of non-hallucinogenic derivatives, which are currently the focus of intense study, implementation of sub-psychedelic or microdosing, harnessing of entourage effects in extracts of psychedelic mushrooms, and blocking 5-HT2A receptor-mediated hallucinogenic effects. Preclinical studies that employ appropriate animal models are a prerequisite and clinical studies will need to be carefully designed on the basis of preclinical and translational data. Careful research in this area could significantly impact the treatment of one of the most severe and socially debilitating psychiatric disorders and open an exciting new frontier in psychopharmacology.

Psychosis spectrum illnesses as disorders of prefrontal critical period plasticity

Emerging research on neuroplasticity processes in psychosis spectrum illnesses-from the synaptic to the macrocircuit levels-fill key gaps in our models of pathophysiology and open up important treatment considerations. In this selective narrative review, we focus on three themes, emphasizing alterations in spike-timing dependent and Hebbian plasticity that occur during adolescence, the critical period for prefrontal system development: (1) Experience-dependent dysplasticity in psychosis emerges from activity decorrelation within neuronal ensembles. (2) Plasticity processes operate bidirectionally: deleterious environmental and experiential inputs shape microcircuits. (3) Dysregulated plasticity processes interact across levels of scale and time and include compensatory mechanisms that have pathogenic importance. We present evidence that-given the centrality of progressive dysplastic changes, especially in prefrontal cortex-pharmacologic or neuromodulatory interventions will need to be supplemented by corrective learning experiences for the brain if we are to help people living with these illnesses to fully thrive.

Dimensionality reduction and recurrence analysis reveal hidden structures of striatal pathological states

A pipeline is proposed here to describe different features to study brain microcircuits on a histological scale using multi-scale analyses, including the uniform manifold approximation and projection (UMAP) dimensional reduction technique and modularity algorithm to identify neuronal ensembles, Runs tests to show significant ensembles activation, graph theory to show trajectories between ensembles, and recurrence analyses to describe how regular or chaotic ensembles dynamics are. The data set includes ex-vivo NMDA-activated striatal tissue in control conditions as well as experimental models of disease states: decorticated, dopamine depleted, and L-DOPA-induced dyskinetic rodent samples. The goal was to separate neuronal ensembles that have correlated activity patterns. The pipeline allows for the demonstration of differences between disease states in a brain slice. First, the ensembles were projected in distinctive locations in the UMAP space. Second, graphs revealed functional connectivity between neurons comprising neuronal ensembles. Third, the Runs test detected significant peaks of coactivity within neuronal ensembles. Fourth, significant peaks of coactivity were used to show activity transitions between ensembles, revealing recurrent temporal sequences between them. Fifth, recurrence analysis shows how deterministic, chaotic, or recurrent these circuits are. We found that all revealed circuits had recurrent activity except for the decorticated circuits, which tended to be divergent and chaotic. The Parkinsonian circuits exhibit fewer transitions, becoming rigid and deterministic, exhibiting a predominant temporal sequence that disrupts transitions found in the controls, thus resembling the clinical signs of rigidity and paucity of movements. Dyskinetic circuits display a higher recurrence rate between neuronal ensembles transitions, paralleling clinical findings: enhancement in involuntary movements. These findings confirm that looking at neuronal circuits at the histological scale, recording dozens of neurons simultaneously, can show clear differences between control and diseased striatal states: "fingerprints" of the disease states. Therefore, the present analysis is coherent with previous ones of striatal disease states, showing that data obtained from the tissue are robust. At the same time, it adds heuristic ways to interpret circuitry activity in different states.

Upper cortical layer-driven network impairment in schizophrenia

Schizophrenia is one of the most widespread and complex mental disorders. To characterize the impact of schizophrenia, we performed single-nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. In addition, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most marked in upper-layer GABAergic neurons, including down-regulation in energy metabolism and up-regulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Last, Visium spatial transcriptomics further corroborated upper-layer neuron vulnerability in schizophrenia. Overall, our results point toward general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology.

Disrupted-in-schizophrenia-1 is required for normal pyramidal cell-interneuron communication and assembly dynamics in the prefrontal cortex

We interrogated prefrontal circuit function in mice lacking Disrupted-in-schizophrenia-1 (Disc1-mutant mice), a risk factor for psychiatric disorders. Single-unit recordings in awake mice revealed reduced average firing rates of fast-spiking interneurons (INTs), including optogenetically identified parvalbumin-positive cells, and a lower proportion of INTs phase-coupled to ongoing gamma oscillations. Moreover, we observed decreased spike transmission efficacy at local pyramidal cell (PYR)-INT connections in vivo, suggesting a reduced excitatory effect of local glutamatergic inputs as a potential mechanism of lower INT rates. On the network level, impaired INT function resulted in altered activation of PYR assemblies: While assembly activations defined as coactivations within 25 ms were observed equally often, the expression strength of individual assembly patterns was significantly higher in Disc1-mutant mice. Our data, thus, reveal a role of Disc1 in shaping the properties of prefrontal assembly patterns by setting INT responsiveness to glutamatergic drive.

Conceptual framework for neuronal ensemble identification and manipulation related to behavior using calcium imaging

Significance: The identification and manipulation of spatially identified neuronal ensembles with optical methods have been recently used to prove the causal link between neuronal ensemble activity and learned behaviors. However, the standardization of a conceptual framework to identify and manipulate neuronal ensembles from calcium imaging recordings is still lacking. Aim: We propose a conceptual framework for the identification and manipulation of neuronal ensembles using simultaneous calcium imaging and two-photon optogenetics in behaving mice. Approach: We review the computational approaches that have been used to identify and manipulate neuronal ensembles with single cell resolution during behavior in different brain regions using all-optical methods. Results: We proposed three steps as a conceptual framework that could be applied to calcium imaging recordings to identify and manipulate neuronal ensembles in behaving mice: (1) transformation of calcium transients into binary arrays; (2) identification of neuronal ensembles as similar population vectors; and (3) targeting of neuronal ensemble members that significantly impact behavioral performance. Conclusions: The use of simultaneous two-photon calcium imaging and two-photon optogenetics allowed for the experimental demonstration of the causal relation of population activity and learned behaviors. The standardization of analytical tools to identify and manipulate neuronal ensembles could accelerate interventional experiments aiming to reprogram the brain in normal and pathological conditions.

Encoding of social novelty by sparse GABAergic neural ensembles in the prelimbic cortex

Although the prelimbic (PrL) area is associated with social behaviors, the neural ensembles that regulate social preference toward novelty or familiarity remain unknown. Using miniature two-photon microscopy (mTPM) to visualize social behavior-associated neuronal activity within the PrL in freely behaving mice, we found that the Ca2+ transients of GABAergic neurons were more highly correlated with social behaviors than those of glutamatergic neurons. Chemogenetic suppression of social behavior-activated GABAergic neurons in the PrL disrupts social novelty behaviors. Restoring the MeCP2 level in PrL GABAergic neurons in MECP2 transgenic (MECP2-TG) mice rescues the social novelty deficits. Moreover, we identified and characterized sparsely distributed NewPNs and OldPNs of GABAergic interneurons in the PrL preferentially responsible for new and old mouse exploration, respectively. Together, we propose that social novelty information may be encoded by the responses of NewPNs and OldPNs in the PrL area, possibly via synergistic actions on both sides of the seesaw.

Oscillatory Neural Signatures of Visual Perception Across Developmental Stages in Individuals With 22q11.2 Deletion Syndrome

BACKGROUND

Numerous behavioral studies have highlighted the contribution of visual perceptual deficits to the nonverbal cognitive profile of individuals with 22q11.2 deletion syndrome. However, the neurobiological processes underlying these widespread behavioral alterations are yet to be fully understood. Thus, in this paper, we investigated the role of neural oscillations toward visuoperceptual deficits to elucidate the neurobiology of sensory impairments in deletion carriers.

METHODS

We acquired 125 high-density electroencephalography recordings during a visual grating task in a group of 62 deletion carriers and 63 control subjects. Stimulus-elicited oscillatory responses were analyzed with 1) time-frequency analysis using wavelets decomposition at sensor and source level, 2) intertrial phase coherence, and 3) Granger causality connectivity in source space. Additional analyses examined the development of neural oscillations across age bins.

RESULTS

Deletion carriers had decreased theta-band (4-8 Hz) and gamma-band (58-68 Hz) spectral power compared with control subjects in response to the visual stimuli, with an absence of age-related increase of theta- and gamma-band responses. Moreover, adult deletion carriers had decreased gamma- and theta-band responses but increased alpha/beta desynchronization (10-25 Hz) that correlated with behavioral performance. Granger causality estimates reflected an increased frontal-occipital connectivity in the beta range (22-40 Hz).

CONCLUSIONS

Deletion carriers exhibited decreased theta- and gamma-band responses to visual stimuli, while alpha/beta desynchronization was preserved. Overall, the lack of age-related changes in deletion carriers implicates developmental impairments in circuit mechanisms underlying neural oscillations. The dissociation between the maturation of theta/gamma- and alpha/beta-band responses may indicate a selective impairment in supragranular cortical layers, leading to compensatory top-down connectivity.

An increase of inhibition drives the developmental decorrelation of neural activity

Throughout development, the brain transits from early highly synchronous activity patterns to a mature state with sparse and decorrelated neural activity, yet the mechanisms underlying this process are poorly understood. The developmental transition has important functional consequences, as the latter state is thought to allow for more efficient storage, retrieval, and processing of information. Here, we show that, in the mouse medial prefrontal cortex (mPFC), neural activity during the first two postnatal weeks decorrelates following specific spatial patterns. This process is accompanied by a concomitant tilting of excitation-inhibition (E-I) ratio toward inhibition. Using optogenetic manipulations and neural network modeling, we show that the two phenomena are mechanistically linked, and that a relative increase of inhibition drives the decorrelation of neural activity. Accordingly, in mice mimicking the etiology of neurodevelopmental disorders, subtle alterations in E-I ratio are associated with specific impairments in the correlational structure of spike trains. Finally, capitalizing on EEG data from newborn babies, we show that an analogous developmental transition takes place also in the human brain. Thus, changes in E-I ratio control the (de)correlation of neural activity and, by these means, its developmental imbalance might contribute to the pathogenesis of neurodevelopmental disorders.

Pattern decorrelation in the mouse medial prefrontal cortex enables social preference and requires MeCP2

Sociability is crucial for survival, whereas social avoidance is a feature of disorders such as Rett syndrome, which is caused by loss-of-function mutations in MECP2. To understand how a preference for social interactions is encoded, we used in vivo calcium imaging to compare medial prefrontal cortex (mPFC) activity in female wild-type and Mecp2-heterozygous mice during three-chamber tests. We found that mPFC pyramidal neurons in Mecp2-deficient mice are hypo-responsive to both social and nonsocial stimuli. Hypothesizing that this limited dynamic range restricts the circuit's ability to disambiguate coactivity patterns for different stimuli, we suppressed the mPFC in wild-type mice and found that this eliminated both pattern decorrelation and social preference. Conversely, stimulating the mPFC in MeCP2-deficient mice restored social preference, but only if it was sufficient to restore pattern decorrelation. A loss of social preference could thus indicate impaired pattern decorrelation rather than true social avoidance.

Schizophrenia Hypothesis: Autonomic Nervous System Dysregulation of Fetal and Adult Immune Tolerance

The autonomic nervous system can control immune cell activation via both sympathetic adrenergic and parasympathetic cholinergic nerve release of norepinephrine and acetylcholine. The hypothesis put forward in this paper suggests that autonomic nervous system dysfunction leads to dysregulation of immune tolerance mechanisms in brain-resident and peripheral immune cells leading to excessive production of pro-inflammatory cytokines such as Tumor Necrosis Factor alpha (TNF-α). Inactivation of Glycogen Synthase Kinase-3β (GSK3β) is a process that takes place in macrophages and microglia when a toll-like receptor 4 (TLR4) ligand binds to the TLR4 receptor. When Damage-Associated Molecular Patterns (DAMPS) and Pathogen-Associated Molecular Patterns (PAMPS) bind to TLR4s, the phosphatidylinositol-3-kinase (PI3K)-protein kinase B (Akt) pathway should be activated, leading to inactivation of GSK3β. This switches the macrophage from producing pro-inflammatory cytokines to anti-inflammatory cytokines. Acetylcholine activation of the α7 subunit of the nicotinic acetylcholine receptor (α7 nAChR) on the cell surface of immune cells leads to PI3K/Akt pathway activation and can control immune cell polarization. Dysregulation of this pathway due to dysfunction of the prenatal autonomic nervous system could lead to impaired fetal immune tolerance mechanisms and a greater vulnerability to Maternal Immune Activation (MIA) resulting in neurodevelopmental abnormalities. It could also lead to the adult schizophrenia patient’s immune system being more vulnerable to chronic stress-induced DAMP release. If a schizophrenia patient experiences chronic stress, an increased production of pro-inflammatory cytokines such as TNF-α could cause significant damage. TNF-α could increase the permeability of the intestinal and blood brain barrier, resulting in lipopolysaccharide (LPS) and TNF-α translocation to the brain and consequent increases in glutamate release. MIA has been found to reduce Glutamic Acid Decarboxylase mRNA expression, resulting in reduced Gamma-aminobutyric acid (GABA) synthesis, which combined with an increase of glutamate release could result in an imbalance of glutamate and GABA neurotransmitters. Schizophrenia could be a “two-hit” illness comprised of a genetic “hit” of autonomic nervous system dysfunction and an environmental hit of MIA. This combination of factors could lead to neurotransmitter imbalance and the development of psychotic symptoms.

An in vitro model of neuronal ensembles

Advances in 3D neuronal cultures, such as brain spheroids and organoids, are allowing unprecedented in vitro access to some of the molecular, cellular and developmental mechanisms underlying brain diseases. However, their efficacy in recapitulating brain network properties that encode brain function remains limited, thereby precluding development of effective in vitro models of complex brain disorders like schizophrenia. Here, we develop and characterize a Modular Neuronal Network (MoNNet) approach that recapitulates specific features of neuronal ensemble dynamics, segregated local-global network activities and a hierarchical modular organization. We utilized MoNNets for quantitative in vitro modelling of schizophrenia-related network dysfunctions caused by highly penetrant mutations in SETD1A and 22q11.2 risk loci. Furthermore, we demonstrate its utility for drug discovery by performing pharmacological rescue of alterations in neuronal ensembles stability and global network synchrony. MoNNets allow in vitro modelling of brain diseases for investigating the underlying neuronal network mechanisms and systematic drug discovery.

Neural circuit pathology driven by Shank3 mutation disrupts social behaviors

Dysfunctional sociability is a core symptom in autism spectrum disorder (ASD) that may arise from neural-network dysconnectivity between multiple brain regions. However, pathogenic neural-network mechanisms underlying social dysfunction are largely unknown. Here, we demonstrate that circuit-selective mutation (ctMUT) of ASD-risk Shank3 gene within a unidirectional projection from the prefrontal cortex to the basolateral amygdala alters spine morphology and excitatory-inhibitory balance of the circuit. Shank3 ctMUT mice show reduced sociability as well as elevated neural activity and its amplitude variability, which is consistent with the neuroimaging results from human ASD patients. Moreover, the circuit hyper-activity disrupts the temporal correlation of socially tuned neurons to the events of social interactions. Finally, optogenetic circuit activation in wild-type mice partially recapitulates the reduced sociability of Shank3 ctMUT mice, while circuit inhibition in Shank3 ctMUT mice partially rescues social behavior. Collectively, these results highlight a circuit-level pathogenic mechanism of Shank3 mutation that drives social dysfunction.

Optogenetic Methods to Investigate Brain Alterations in Preclinical Models

Investigating the neuronal dynamics supporting brain functions and understanding how the alterations in these mechanisms result in pathological conditions represents a fundamental challenge. Preclinical research on model organisms allows for a multiscale and multiparametric analysis in vivo of the neuronal mechanisms and holds the potential for better linking the symptoms of a neurological disorder to the underlying cellular and circuit alterations, eventually leading to the identification of therapeutic/rescue strategies. In recent years, brain research in model organisms has taken advantage, along with other techniques, of the development and continuous refinement of methods that use light and optical approaches to reconstruct the activity of brain circuits at the cellular and system levels, and to probe the impact of the different neuronal components in the observed dynamics. These tools, combining low-invasiveness of optical approaches with the power of genetic engineering, are currently revolutionizing the way, the scale and the perspective of investigating brain diseases. The aim of this review is to describe how brain functions can be investigated with optical approaches currently available and to illustrate how these techniques have been adopted to study pathological alterations of brain physiology.

Intrinsic excitability mechanisms of neuronal ensemble formation

Neuronal ensembles are coactive groups of cortical neurons, found in spontaneous and evoked activity, that can mediate perception and behavior. To understand the mechanisms that lead to the formation of ensembles, we co-activated layer 2/3 pyramidal neurons in brain slices from mouse visual cortex, in animals of both sexes, replicating in vitro an optogenetic protocol to generate ensembles in vivo. Using whole-cell and perforated patch-clamp pair recordings we found that, after optogenetic or electrical stimulation, coactivated neurons increased their correlated activity, a hallmark of ensemble formation. Coactivated neurons showed small biphasic changes in presynaptic plasticity, with an initial depression followed by a potentiation after a recovery period. Optogenetic and electrical stimulation also induced significant increases in frequency and amplitude of spontaneous EPSPs, even after single-cell stimulation. In addition, we observed unexpected strong and persistent increases in neuronal excitability after stimulation, with increases in membrane resistance and reductions in spike threshold. A pharmacological agent that blocks changes in membrane resistance reverted this effect. These significant increases in excitability can explain the observed biphasic synaptic plasticity. We conclude that cell-intrinsic changes in excitability are involved in the formation of neuronal ensembles. We propose an ‘iceberg’ model, by which increased neuronal excitability makes subthreshold connections suprathreshold, enhancing the effect of already existing synapses, and generating a new neuronal ensemble.

In the brain, groups of neurons that are activated together – also known as neuronal ensembles – are the basic units that underpin perception and behavior. Yet, exactly how these coactive circuits are established remains under investigation.

In 1949, Canadian psychologist Donald Hebb proposed that, when brains learn something new, the neurons which are activated together connect to form ensembles, and their connections become stronger each time this specific piece of knowledge is recalled. This idea that ‘neurons that fire together, wire together’ can explain how memories are acquired and recalled, by strengthening their wiring.

However, recent studies have questioned whether strengthening connections is the only mechanism by which neural ensembles can be created. Changes in the excitability of neurons (how easily they are to fire and become activated) may also play a role. In other words, ensembles could emerge because certain neurons become more excitable and fire more readily.

To solve this conundrum, Alejandre-García et al. examined both hypotheses in the same system. Neurons in slices of the mouse visual cortex were stimulated electrically or optically, via a technique that controls neural activity with light. The activity of individual neurons and their connections was then measured with electrodes.

Spontaneous activity among connected neurons increased after stimulation, indicative of the formation of neuronal ensembles. Connected neurons also showed small changes in the strength of their connections, which first decreased and then rebounded after an initial recovery period.

Intriguingly, cells also showed unexpected strong and persistent increases in neuronal excitability after stimulation, such that neurons fired more readily to the same stimulus. In other words, neurons maintained a cellular memory of having been stimulated. The authors conclude that ensembles form because connected neurons become more excitable, which in turn, may strengthen connections of the circuit at a later stage.

These results provide fresh insights about the neural circuits underpinning learning and memory. In time, the findings could also help to understand disorders such as Alzheimer’s disease and schizophrenia, which are characterised by memory impairments and disordered thinking.

Long-term in vivo imaging of mouse spinal cord through an optically cleared intervertebral window

The spinal cord accounts for the main communication pathway between the brain and the peripheral nervous system. Spinal cord injury is a devastating and largely irreversible neurological trauma, and can result in lifelong disability and paralysis with no available cure. In vivo spinal cord imaging in mouse models without introducing immunological artifacts is critical to understand spinal cord pathology and discover effective treatments. We developed a minimally invasive intervertebral window by retaining the ligamentum flavum to protect the underlying spinal cord. By introducing an optical clearing method, we achieve repeated two-photon fluorescence and stimulated Raman scattering imaging at subcellular resolution with up to 15 imaging sessions over 6-167 days and observe no inflammatory response. Using this optically cleared intervertebral window, we study neuron-glia dynamics following laser axotomy and observe strengthened contact of microglia with the nodes of Ranvier during axonal degeneration. By enabling long-term, repetitive, stable, high-resolution and inflammation-free imaging of mouse spinal cord, our method provides a reliable platform in the research aiming at interpretation of spinal cord physiology and pathology.

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.