Brain rhythms connect impaired inhibition to altered cognition in schizophrenia

A neural modeling approach to study mechanisms underlying the heterogeneity of visual spatial frequency sensitivity in schizophrenia

Patients with schizophrenia exhibit abnormalities in spatial frequency sensitivity, and it is believed that these abnormalities indicate more widespread dysfunction and dysregulation of bottom-up processing. The early visual system, including the first-order Lateral Geniculate Nucleus of the thalamus (LGN) and the primary visual cortex (V1), are key contributors to spatial frequency sensitivity. Medicated and unmedicated patients with schizophrenia exhibit contrasting changes in spatial frequency sensitivity, thus making it a useful probe for examining potential effects of the disorder and antipsychotic medications in neural processing. We constructed a parameterized, rate-based neural model of on-center/off-surround neurons in the early visual system to investigate the impacts of changes to the excitatory and inhibitory receptive field subfields. By incorporating changes in both the excitatory and inhibitory subfields that are associated with pathophysiological findings in schizophrenia, the model successfully replicated perceptual data from behavioral/functional studies involving medicated and unmedicated patients. Among several plausible mechanisms, our results highlight the dampening of excitation and/or increase in the spread and strength of the inhibitory subfield in medicated patients and the contrasting decreased spread and strength of inhibition in unmedicated patients. Given that the model was successful at replicating results from perceptual data under a variety of conditions, these elements of the receptive field may be useful markers for the imbalances seen in patients with schizophrenia.

Diverging functional connectivity timescales: Capturing distinct aspects of cognitive performance in early psychosis

Background

Psychosis spectrum disorders (PSDs) are marked by cognitive impairments, the neurobiological correlates of which remain poorly understood. Here, we investigate the entropy of time-varying functional connectivity (TVFC) patterns from resting-state fMRI (rfMRI) as potential biomarker for cognitive performance in PSDs. By combining our results with multimodal reference data, we hope to generate new insights into the mechanisms underlying cognitive dysfunction in PSDs. We hypothesized that low-entropy TVFC patterns (LEN) would be more behaviorally informative than high-entropy TVFC patterns (HEN), especially for tasks that require extensive integration across diverse cognitive subdomains.

Methods

rfMRI and behavioral data from 97 patients in the early phases of psychosis and 53 controls were analyzed. Positron-Emission Tomography (PET) and magnetoencephalography (MEG) data were taken from a public repository (Hansen et al., 2022). Multivariate analyses were conducted to examine relationships between TVFC patterns at multiple spatial scales and cognitive performance in patients.

Results

Compared to HEN, LEN explained significantly more cognitive variance on average in PSD patients, driven by superior encoding of information on psychometrically more integrated tasks. HEN better captured information in specific subdomains of executive functioning. Nodal HEN-LEN transitions were spatially aligned with neurobiological gradients reflecting monoaminergic transporter densities and MEG beta power. Exploratory analyses revealed a close statistical relationship between LEN and positive PSD symptoms.

Conclusion

Our entropy-based analysis of TVFC patterns dissociates distinct aspects of cognition in PSDs. By linking topographies of neurotransmission and oscillatory dynamics with cognitive performance, it enhances our understanding of the mechanisms underlying cognitive deficits in PSDs.

CRediT Authorship Contribution Statement

Fabian Hirsch: Conceptualization, Methodology, Software, Formal analysis, Writing - Original Draft, Writing - Review & Editing, Visualization; Ângelo Bumanglag: Methodology, Software, Formal analysis, Writing - Review & Editing; Yifei Zhang: Methodology, Software, Formal analysis, Writing - Review & Editing; Afra Wohlschlaeger: Methodology, Writing - Review & Editing, Supervision, Project administration.

Mean-field analysis of synaptic alterations underlying deficient cortical gamma oscillations in schizophrenia

Deficient gamma oscillations in the prefrontal cortex (PFC) of individuals with schizophrenia (SZ) are proposed to arise from alterations in the excitatory drive to fast-spiking interneurons ( E → I ) and in the inhibitory drive from these interneurons to excitatory neurons ( I → E ) . Consistent with this idea, prior postmortem studies showed lower levels of molecular and structural markers for the strength of E → I and I → E synapses and also greater variability in E → I synaptic strength in PFC of SZ. Moreover, simulating these alterations in a network of quadratic integrate-and-fire (QIF) neurons revealed a synergistic effect of their interactions on reducing gamma power. In this study, we aimed to investigate the dynamical nature of this synergistic interaction at macroscopic level by deriving a mean-field description of the QIF model network that consists of all-to-all connected excitatory neurons and fast-spiking interneurons. Through a series of numerical simulations and bifurcation analyses, findings from our mean-field model showed that the macroscopic dynamics of gamma oscillations are synergistically disrupted by the interactions among lower strength of E → I and I → E synapses and greater variability in E → I synaptic strength. Furthermore, the two-dimensional bifurcation analyses showed that this synergistic interaction is primarily driven by the shift in Hopf bifurcation due to lower E → I synaptic strength. Together, these simulations predict the nature of dynamical mechanisms by which multiple synaptic alterations interact to robustly reduce PFC gamma power in SZ, and highlight the utility of mean-field model to study macroscopic neural dynamics and their alterations in the illness.

A neural modeling approach to study mechanisms underlying the heterogeneity of visual spatial frequency sensitivity in schizophrenia

Patients with schizophrenia exhibit abnormalities in spatial frequency sensitivity, and it is believed that these abnormalities indicate more widespread dysfunction and dysregulation of bottom-up processing. The early visual system, including the first-order Lateral Geniculate Nucleus of the thalamus (LGN) and the primary visual cortex (V1), are key contributors to spatial frequency sensitivity. Medicated and unmedicated patients with schizophrenia exhibit contrasting changes in spatial frequency sensitivity, thus making it a useful probe for examining potential effects of the disorder and antipsychotic medications in neural processing. We constructed a parameterized, rate-based neural model of on-center/off-surround neurons in the early visual system to investigate the impacts of changes to the excitatory and inhibitory receptive field subfields. By incorporating changes in both the excitatory and inhibitory subfields that are associated with pathophysiological findings in schizophrenia, the model successfully replicated perceptual data from behavioral/functional studies involving medicated and unmedicated patients. Among several plausible mechanisms, our results highlight the dampening of excitation and/or increase in the spread and strength of the inhibitory subfield in medicated patients and the contrasting decreased spread and strength of inhibition in unmedicated patients. Given that the model was successful at replicating results from perceptual data under a variety of conditions, these elements of the receptive field may be useful markers for the imbalances seen in patients with schizophrenia.

Dopamine D4 Receptor Agonist Drastically Increases Delta Activity in the Thalamic Nucleus Reuniens: Potential Role in Communication between Prefrontal Cortex and Hippocampus

Network oscillations are essential for all cognitive functions. Oscillatory deficits are well established in psychiatric diseases and are recapitulated in animal models. They are significantly and specifically affected by pharmacological interventions using psychoactive compounds. Dopamine D4 receptor (D4R) activation was shown to enhance gamma rhythm in freely moving rats and to specifically affect slow delta and theta oscillations in the urethane-anesthetized rat model. The goal of this study was to test the effect of D4R activation on slow network oscillations at delta and theta frequencies during wake states, potentially supporting enhanced functional connectivity during dopamine-induced attention and cognitive processing. Network activity was recorded in the prefrontal cortex (PFC), hippocampus (HC) and nucleus reuniens (RE) in control conditions and after injecting the D4R agonist A-412997 (3 and 5 mg/kg; systemic administration). We found that A-412997 elicited a lasting (~40 min) wake state and drastically enhanced narrow-band delta oscillations in the PFC and RE in a dose-dependent manner. It also preferentially enhanced delta synchrony over theta coupling within the PFC-RE-HC circuit, strongly strengthening PFC-RE coupling. Thus, our findings indicate that the D4R may contribute to cognitive processes, at least in part, through acting on wake delta oscillations and that the RE, providing an essential link between the PFC and HC, plays a prominent role in this mechanism.

Resting-State EEG Connectivity at High-Frequency Bands and Attentional Performance Dysfunction in Stabilized Schizophrenia Patients

Background and Objectives: Attentional dysfunction has long been viewed as one of the fundamental underlying cognitive deficits in schizophrenia. There is an urgent need to understand its neural underpinning and develop effective treatments. In the process of attention, neural oscillation has a central role in filtering information and allocating resources to either stimulus-driven or goal-relevant objects. Here, we asked if resting-state EEG connectivity correlated with attentional performance in schizophrenia patients. Materials and Methods: Resting-state EEG recordings were obtained from 72 stabilized patients with schizophrenia. Lagged phase synchronization (LPS) was used to measure whole-brain source-based functional connectivity between 84 intra-cortical current sources determined by eLORETA (exact low-resolution brain electromagnetic tomography) for five frequencies. The Conners' Continuous Performance Test-II (CPT-II) was administered for evaluating attentional performance. Linear regression with a non-parametric permutation randomization procedure was used to examine the correlations between the whole-brain functional connectivity and the CPT-II measures. Results: Greater beta-band right hemispheric fusiform gyrus (FG)-lingual gyrus (LG) functional connectivity predicted higher CPT-II variability scores (r = 0.44, p < 0.05, corrected), accounting for 19.5% of variance in the CPT-II VAR score. Greater gamma-band right hemispheric functional connectivity between the cuneus (Cu) and transverse temporal gyrus (TTG) and between Cu and the superior temporal gyrus (STG) predicted higher CPT-II hit reaction time (HRT) scores (both r = 0.50, p < 0.05, corrected), accounting for 24.6% and 25.1% of variance in the CPT-II HRT score, respectively. Greater gamma-band right hemispheric Cu-TTG functional connectivity predicted higher CPT-II HRT standard error (HRTSE) scores (r = 0.54, p < 0.05, corrected), accounting for 28.7% of variance in the CPT-II HRTSE score. Conclusions: Our study indicated that increased right hemispheric resting-state EEG functional connectivity at high frequencies was correlated with poorer focused attention in schizophrenia patients. If replicated, novel approaches to modulate these networks may yield selective, potent interventions for improving attention deficits in schizophrenia.

Development of network oscillations through adolescence in male and female rats

The primary aim of this research was to study the developmental trajectory of oscillatory synchronization in neural networks of normal healthy rats during adolescence, corresponding to the vulnerable age of schizophrenia prodrome in human. To monitor the development of oscillatory networks through adolescence we used a "pseudo-longitudinal" design. Recordings were performed in terminal experiments under urethane anesthesia, every day from PN32 to PN52 using rats-siblings from the same mother, to reduce individual innate differences between subjects. We found that hippocampal theta power decreased and delta power in prefrontal cortex increased through adolescence, indicating that the oscillations in the two different frequency bands follow distinct developmental trajectories to reach the characteristic oscillatory activity found in adults. Perhaps even more importantly, theta rhythm showed age-dependent stabilization toward late adolescence. Furthermore, sex differences was found in both networks, more prominent in the prefrontal cortex compared with hippocampus. Delta increase was stronger in females and theta stabilization was completed earlier in females, in postnatal days PN41-47, while in males it was only completed in late adolescence. Our finding of a protracted maturation of theta-generating networks in late adolescence is overall consistent with the findings of longitudinal studies in human adolescents, in which oscillatory networks demonstrated a similar pattern of maturation.

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

The Relationship Between Cannabinoids and Neural Oscillations: How Cannabis Disrupts Sensation, Perception, and Cognition

Disruptions in neural oscillations are believed to be one critical mechanism by which cannabinoids, such as delta-9-tetrahyrdrocannabinol (THC; the primary psychoactive constituent of cannabis), perturbs brain function. Here we briefly review the role of synchronized neural activity, particularly in the gamma (30-80 Hz) and theta (4-7 Hz) frequency range, in sensation, perception, and cognition. This is followed by a review of clinical studies utilizing electroencephalography (EEG) which have demonstrated that both chronic and acute cannabinoid exposure disrupts neural oscillations in humans. We also offer a hypothetical framework through which endocannabinoids modulate neural synchrony at the network level. This also includes speculation on how both chronic and acute cannabinoids disrupt functionally relevant neural oscillations by altering the fine tuning of oscillations and the inhibitory/excitatory balance of neural circuits. Finally, we highlight important clinical implications of such oscillatory disruptions, such as the potential relationship between cannabis use, altered neural synchrony, and disruptions in sensation, perception, and cognition, which are perturbed in disorders such as schizophrenia.

A systematic review of the neural correlates of multisensory integration in schizophrenia

Multisensory integration (MSI), in which sensory signals from different modalities are unified, is necessary for our comprehensive perception of and effective adaptation to the objects and events around us. However, individuals with schizophrenia suffer from impairments in MSI, which could explain typical symptoms like hallucination and reality distortion. Because the neural correlates of aberrant MSI in schizophrenia help us understand the physiognomy of this psychiatric disorder, we performed a systematic review of the current research on this subject. The literature search concerned investigated MSI in diagnosed schizophrenia patients compared to healthy controls using brain imaging. Seventeen of 317 identified studies were finally included. To assess risk of bias, the Newcastle-Ottawa quality assessment was used, and the review was written according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA). The results indicated that multisensory processes in schizophrenia are associated with aberrant, mainly reduced, neural activity in several brain regions, as measured by event-related potentials, oscillations, activity and connectivity. The conclusion is that a fronto-temporal region, comprising the frontal inferior gyrus, middle temporal gyrus and superior temporal gyrus/sulcus, along with the fusiform gyrus and dorsal visual stream in the occipital-parietal lobe are possible key regions of deficient MSI in schizophrenia.

Noise effect on the temporal patterns of neural synchrony

Neural synchrony in the brain is often present in an intermittent fashion, i.e., there are intervals of synchronized activity interspersed with intervals of desynchronized activity. A series of experimental studies showed that this kind of temporal patterning of neural synchronization may be very specific and may be correlated with behaviour (even if the average synchrony strength is not changed). Prior studies showed that a network with many short desynchronized intervals may be functionally different from a network with few long desynchronized intervals as it may be more sensitive to synchronizing input signals. In this study, we investigated the effect of channel noise on the temporal patterns of neural synchronization. We employed a small network of conductance-based model neurons that were mutually connected via excitatory synapses. The resulting dynamics of the network was studied using the same time-series analysis methods as used in prior experimental and computational studies. While it is well known that synchrony strength generally degrades with noise, we found that noise also affects the temporal patterning of synchrony. Noise, at a sufficient intensity (yet too weak to substantially affect synchrony strength), promotes dynamics with predominantly short (although potentially very numerous) desynchronizations. Thus, channel noise may be one of the mechanisms contributing to the short desynchronization dynamics observed in multiple experimental studies.

Temporal patterns of synchrony in a pyramidal-interneuron gamma (PING) network

Synchronization in neural systems plays an important role in many brain functions. Synchronization in the gamma frequency band (30-100 Hz) is involved in a variety of cognitive phenomena; abnormalities of the gamma synchronization are found in schizophrenia and autism spectrum disorder. Frequently, the strength of synchronization is not high, and synchronization is intermittent even on short time scales (few cycles of oscillations). That is, the network exhibits intervals of synchronization followed by intervals of desynchronization. Neural circuit dynamics may show different distributions of desynchronization durations even if the synchronization strength is fixed. We use a conductance-based neural network exhibiting pyramidal-interneuron gamma rhythm to study the temporal patterning of synchronized neural oscillations. We found that changes in the synaptic strength (as well as changes in the membrane kinetics) can alter the temporal patterning of synchrony. Moreover, we found that the changes in the temporal pattern of synchrony may be independent of the changes in the average synchrony strength. Even though the temporal patterning may vary, there is a tendency for dynamics with short (although potentially numerous) desynchronizations, similar to what was observed in experimental studies of neural synchronization in the brain. Recent studies suggested that the short desynchronizations dynamics may facilitate the formation and the breakup of transient neural assemblies. Thus, the results of this study suggest that changes of synaptic strength may alter the temporal patterning of the gamma synchronization as to make the neural networks more efficient in the formation of neural assemblies and the facilitation of cognitive phenomena.

Anticholinergic Burden and Cognitive Performance in Patients With Schizophrenia: A Systematic Literature Review

Objective: Cognitive impairment in schizophrenia forms the key cause of the disease's disability, leading to serious functional, and socioeconomic implications. Dopaminergic-cholinergic balance is considered essential to cognitive performance in schizophrenia and patients are often treated with many drugs with anticholinergic properties. This study aims to examine the cognitive impact of anticholinergic burden in patients with schizophrenia. Methods: A systematic literature review was performed on English-language studies published on PubMed, Embase, and Web of Science, from inception to June 2021, to identify research studies that examined the effect of anticholinergic load on cognition in clinically stable patients with schizophrenia. No restrictions on study design, age of participants, or geographical distribution were applied. Two researchers performed independently the screening and shortlisting of the eligible articles. A narrative synthesis of the main characteristics and findings of studies included was reported. Results: In total, 17 articles of varying methodological design met the inclusion criteria. Three of them found statistically significant improvement in cognition after anticholinergic tapering without adverse effects. Thirteen studies found a statistically significant association between high anticholinergic burden and cognitive impairment (neurocognitive composite scores and individual cognitive domains such as learning and memory, executive function, processing speed), apart from a study, related to the specific characteristics of clozapine. Conclusions: Medication with increased anticholinergic load has been found in most of the studies to negatively affect neurocognitive performance of patients with schizophrenia. However, the clinical and methodological heterogeneity of studies included limit our interpretation and conclusions.

In silico hippocampal modeling for multi-target pharmacotherapy in schizophrenia

Treatment of schizophrenia has had limited success in treating core cognitive symptoms. The evidence of multi-gene involvement suggests that multi-target therapy may be needed. Meanwhile, the complexity of schizophrenia pathophysiology and psychopathology, coupled with the species-specificity of much of the symptomatology, places limits on analysis via animal models, in vitro assays, and patient assessment. Multiscale computer modeling complements these traditional modes of study. Using a hippocampal CA3 computer model with 1200 neurons, we examined the effects of alterations in NMDAR, HCN (Ih current), and GABAAR on information flow (measured with normalized transfer entropy), and in gamma activity in local field potential (LFP). We found that altering NMDARs, GABAAR, Ih, individually or in combination, modified information flow in an inverted-U shape manner, with information flow reduced at low and high levels of these parameters. Theta-gamma phase-amplitude coupling also had an inverted-U shape relationship with NMDAR augmentation. The strong information flow was associated with an intermediate level of synchrony, seen as an intermediate level of gamma activity in the LFP, and an intermediate level of pyramidal cell excitability. Our results are consistent with the idea that overly low or high gamma power is associated with pathological information flow and information processing. These data suggest the need for careful titration of schizophrenia pharmacotherapy to avoid extremes that alter information flow in different ways. These results also identify gamma power as a potential biomarker for monitoring pathology and multi-target pharmacotherapy.

Altered parahippocampal gyrus activation and its connectivity with resting-state network areas in schizophrenia: An EEG study

Synchronized and coherent activity in resting-networks during normal brain functioning could be altered in disconnection syndrome like schizophrenia. Study of neural oscillations as assessed by EEG appears to be a promising proposition to understand the pathophysiology of schizophrenia in patients and their first-degree relatives, where disturbances in neural oscillations point towards genetic predisposition. Therefore, present study aims at establishing EEG based biomarkers for early detection and management strategies. Thirty-two patients with schizophrenia, 28 first-degree relatives and 31 healthy controls (HC) participated in the study. Resting brain activity was recorded using 128-channel electroencephalography. After pre-processing and independent component analysis (ICA), an equivalent current dipole was estimated for each IC. Total of 1551 independent and localizable EEG components across all groups were used in subsequent analysis. Power spectral density and source coherence between IC clusters were computed. Patients and first-degree relatives displayed significantly higher power spectral density (PSD) than HC for all frequency bands in left parahippocampal gyrus (PHG) (-7, -26, 8; BA 27). Another region within left deep PHG (-4, -28, 1), however, distinguished patients from first-degree relatives and HC in terms of significantly lower PSD in higher frequency bands. Functional connectivity (FC) was found to be lower in patients and higher in relatives compared to HC between different resting-state network areas. In patients, connectivity was lower compared to first-degree relatives. Altered activity within left PHG and FC of primarily this with other areas in resting-state network can serve as state and trait markers of schizophrenia.

Spike-Timing Dependent Plasticity Effect on the Temporal Patterning of Neural Synchronization

Neural synchrony in the brain at rest is usually variable and intermittent, thus intervals of predominantly synchronized activity are interrupted by intervals of desynchronized activity. Prior studies suggested that this temporal structure of the weakly synchronous activity might be functionally significant: many short desynchronizations may be functionally different from few long desynchronizations even if the average synchrony level is the same. In this study, we used computational neuroscience methods to investigate the effects of spike-timing dependent plasticity (STDP) on the temporal patterns of synchronization in a simple model. We employed a small network of conductance-based model neurons that were connected via excitatory plastic synapses. The dynamics of this network was subjected to the time-series analysis methods used in prior experimental studies. We found that STDP could alter the synchronized dynamics in the network in several ways, depending on the time scale that plasticity acts on. However, in general, the action of STDP in the simple network considered here is to promote dynamics with short desynchronizations (i.e., dynamics reminiscent of that observed in experimental studies). Complex interplay of the cellular and synaptic dynamics may lead to the activity-dependent adjustment of synaptic strength in such a way as to facilitate experimentally observed short desynchronizations in the intermittently synchronized neural activity.

Aerobic exercise improves memory and prevents cognitive deficits of relevance to schizophrenia in an animal model

INTRODUCTION AND OBJECTIVES

Cognitive impairment associated with schizophrenia (CIAS) greatly reduces patients' functionality, and remains an unmet clinical need. The sub-chronic phencyclidine (scPCP) rat model is commonly employed in studying CIAS. We have previously shown that voluntary exercise reverses impairments in novel object recognition (NOR) induced by scPCP. However, there has not been a longitudinal study investigating the potential protective effects of exercise in a model of CIAS. This study aimed to investigate the pro-cognitive and protective effects of exercise on CIAS using the translational NOR and attentional set-shifting tasks (ASST).

METHODS

Female Lister Hooded rats were either exercised (wheel running for one hour per day, five days per week, for six weeks; n=20) or not (n=20) and then tested in a natural-forgetting NOR test. Rats in each group were then administered either PCP (2 mg/kg intraperitoneally (i.p.)) or saline solution (1 mL/kg i.p.) for seven days, followed by seven days washout. Three NOR tests were conducted immediately and two and nine weeks after washout, and a natural-forgetting NOR test was carried out again eight weeks post washout. Rats were trained and tested in ASST from week 6 to week 10 post washout.

RESULTS

Non-exercised rats displayed a deficit in both of the natural-forgetting NOR tests, whereas exercised rats did not. The scPCP exercise group did not show the expected deficit in NOR at any time point, and had a significantly ameliorated deficit in the ASST compared to the scPCP control group.

CONCLUSION

Voluntary exercise has long-lasting pro-cognitive and protective effects in two cognitive domains. Exercise improves cognition and could provide protection against CIAS.

[Neurophysiological characteristics of juvenile schizophrenia patients examined at the very remote follow up stage]

OBJECTIVE

To determine neurophysiological characteristics of patients with long-term follow up (>20 years) and to find correlations between neurophysiological parameters and clinical features of schizophrenia.

MATERIAL AND METHODS

The patients were divided into three groups: with predomination of personality changes (group 1, n=17), with negative disorders (group 2, n=23) and with positive and negative disorders (group 3, n=40). A psychopathological method and electroencephalography with evoked potentials testing were used.

RESULTS AND CONCLUSION

In group 3, the statistically significant higher frequencies of theta-rhythm and lower of alpha-rhythm were found. Also, theta frequency correlated with PANSS positive scores. The significant intergroup differences by auditory oddball P300 were lacked. The findings are discussed in view of the hypothesis of theta-rhythm as a marker of hippocampal-prefrontal connectivity.

Relationship between resting-state theta phase-gamma amplitude coupling and neurocognitive functioning in patients with first-episode psychosis

BACKGROUND

Although cognitive dysfunction is a core element of schizophrenia, the neurobiological underpinnings of the pathophysiology are not yet sufficiently understood. Because the resting state is crucial for cognitive functioning and electroencephalography (EEG) can reflect instantaneous neural activity, we investigated theta phase-gamma amplitude coupling (TGC) of resting-state EEG and its relationship with cognitive function in patients with first-episode psychosis (FEP) to reveal the neural correlates of cognitive dysfunction.

METHODS

A total of 59 FEP patients and 50 healthy controls (HCs) underwent resting-state, eyes-closed EEG recordings and performed the Trail Making Test Part A (TMT-A) and Part B (TMT-B) and California Verbal Learning Test (CVLT). TGC from the source signal of the resting-state EEG in default mode network (DMN)-related brain regions was compared between groups. Correlation analyses were performed between TGC and cognitive function test performance in FEP patients.

RESULTS

Mean resting-state TGC was larger for the FEP patients than for the HCs. Patients with FEP showed increased TGC in the left posterior cingulate cortex, which was correlated with better performance on the TMT-A and TMT-B and on immediate and delayed recall in the CVLT.

CONCLUSIONS

These results suggest that patients with FEP show compensatory hyperactivation of resting-state TGC in DMN-related brain regions, which may be related to the reallocation of cognitive resources to prepare for successful cognitive execution. This study not only highlights the neural underpinnings of cognitive dysfunction in FEP patients but also provides useful background to support the development of treatments for cognitive dysfunction in schizophrenia.

Oscillotherapeutics - Time-targeted interventions in epilepsy and beyond

Oscillatory brain activities support many physiological functions from motor control to cognition. Disruptions of the normal oscillatory brain activities are commonly observed in neurological and psychiatric disorders including epilepsy, Parkinson's disease, Alzheimer's disease, schizophrenia, anxiety/trauma-related disorders, major depressive disorders, and drug addiction. Therefore, these disorders can be considered as common oscillation defects despite having distinct behavioral manifestations and genetic causes. Recent technical advances of neuronal activity recording and analysis have allowed us to study the pathological oscillations of each disorder as a possible biomarker of symptoms. Furthermore, recent advances in brain stimulation technologies enable time- and space-targeted interventions of the pathological oscillations of both neurological disorders and psychiatric disorders as possible targets for regulating their symptoms.

Whole brain polarity regime dynamics are significantly disrupted in schizophrenia and correlate strongly with network connectivity measures

From a large clinical blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) study, we report several interrelated findings involving transient supra-network brainwide states characterized by a saturation phenomenon we are referring to as "polarization." These are whole-brain states in which the voxelwise-normalized BOLD (vn-BOLD) activation of a large proportion of voxels is simultaneously either very high or very low. The presence of such states during a resting-state fMRI (rs-fMRI) scan is significantly anti-correlated with diagnosed schizophrenia, significantly anti-correlated with connectivity between subcortical networks and auditory, visual and sensorimotor networks and also significantly anti-correlated with contemporaneous occupancy of transient functional network connectivity states featuring broad disconnectivity or strong inhibitory connections between the default mode and other networks. Conversely, the presence of highly polarized vn-BOLD states is significantly correlated with connectivity strength between auditory, visual and sensorimotor networks and with contemporaneous occupancy of transient whole-brain patterns of strongly modularized network connectivity and diffuse hyperconnectivity. Despite their consistency with well-documented effects of schizophrenia on static and time-varying functional network connectivity, the observed relationships between polarization and network connectivity are with very few exceptions unmediated by schizophrenia diagnosis. Many differences observed between patients and controls are echoed within the patient population itself in the effect patterns of positive symptomology (e.g. hallucinations, delusions, grandiosity). Our findings highlight a particular whole-brain spatiotemporal BOLD activation phenomenon that differs markedly between healthy subjects and schizophrenia patients, one that also strongly informs time-resolved network connectivity patterns that are associated with this serious clinical disorder.

White matter neuron biology and neuropathology in schizophrenia

Schizophrenia is considered a neurodevelopmental disorder as it often manifests before full brain maturation and is also a cerebral cortical disorder where deficits in GABAergic interneurons are prominent. Whilst most neurons are located in cortical and subcortical grey matter regions, a smaller population of neurons reside in white matter tracts of the primate and to a lesser extent, the rodent brain, subjacent to the cortex. These interstitial white matter neurons (IWMNs) have been identified with general markers for neurons [e.g., neuronal nuclear antigen (NeuN)] and with specific markers for neuronal subtypes such as GABAergic neurons. Studies of IWMNs in schizophrenia have primarily focused on their density underneath cortical areas known to be affected in schizophrenia such as the dorsolateral prefrontal cortex. Most of these studies of postmortem brains have identified increased NeuN+ and GABAergic IWMN density in people with schizophrenia compared to healthy controls. Whether IWMNs are involved in the pathogenesis of schizophrenia or if they are increased because of the cortical pathology in schizophrenia is unknown. We also do not understand how increased IWMN might contribute to brain dysfunction in the disorder. Here we review the literature on IWMN pathology in schizophrenia. We provide insight into the postulated functional significance of these neurons including how they may contribute to the pathophysiology of schizophrenia.

Posterior Parietal Cortex Dysfunction Is Central to Working Memory Storage and Broad Cognitive Deficits in Schizophrenia

PFC dysfunction is widely believed to underlie working memory (WM) deficits in people with schizophrenia (PSZ), but few studies have focused on measures of WM storage devoid of manipulation. Research in neurotypical individuals has shown that storage capacity is more closely related to posterior parietal cortex (PPC) than PFC, suggesting that reductions in WM storage capacity in schizophrenia that are associated with broad cognitive deficits may be related to neural activity in PPC. In the present human neuroimaging study, 37 PSZ and 37 matched healthy control subjects of either sex completed a change detection task with varying set sizes while undergoing fMRI. The task was designed to emphasize WM storage with minimal top-down control demands. Whole-brain analysis identified areas in which BOLD activity covaried with the number of items maintained in WM (K), as derived from task performance at a given set size. Across groups, K values independent of set size predicted BOLD activity in PPC, including superior and inferior parietal lobules and intraparietal sulcus, and middle occipital gyrus. Whole-brain interaction analysis found significantly less K-dependent signal modulation in PSZ than healthy control subjects in left PPC, a phenomenon that could not be explained by a narrower K value range. The slope between K and PPC activation statistically accounted for 43.4% of the between-group differences in broad cognitive function. These results indicate that PPC dysfunction is central to WM storage deficits in PSZ and may play a key role in the broad cognitive deficits associated with schizophrenia.SIGNIFICANCE STATEMENT People with schizophrenia exhibit cognitive deficits across a wide range of tasks. Explaining these impairments in terms of a small number of core deficits with clearly defined neural correlates would advance the understanding of the disorder and promote treatment development. We show that a substantial portion of broad cognitive deficits in schizophrenia can be explained by a failure to flexibly modulate posterior parietal cortex activity as a function of the amount of information currently stored in working memory. Working memory deficits have long been considered central to schizophrenia-related cognitive deficits, but the focus has been on paradigms involving some form of top-down control rather than pure storage of information, which may have unduly narrowed the focus on prefrontal dysfunction.

Subunit-specific NMDAR antagonism dissociates schizophrenia subtype-relevant oscillopathies associated with frontal hypofunction and hippocampal hyperfunction

NMDAR antagonism alters mesolimbic, hippocampal, and cortical function, acutely reproducing the positive, cognitive, and negative symptoms of schizophrenia. These physiological and behavioral effects may depend differentially on NMDAR subtype- and region-specific effects. The dramatic electrophysiological signatures of NMDAR blockade in rodents include potentiated high frequency oscillations (HFOs, ∼140 Hz), likely generated in mesolimbic structures, and increased HFO phase-amplitude coupling (PAC), a phenomenon related to goal-directed behavior and dopaminergic tone. This study examined the impact of subtype-specific NMDAR antagonism on HFOs and PAC. We found that positive-symptom-associated NR2A-preferring antagonism (NVP-AAM077), but not NR2B-specific antagonism (Ro25-6985) or saline control, replicated increases in HFO power seen with nonspecific antagonism (MK-801). However, PAC following NR2A-preferring antagonism was distinct from all other conditions. While θ-HFO PAC was prominent or potentiated in other conditions, NVP-AAM077 increased δ-HFO PAC and decreased θ-HFO PAC. Furthermore, active wake epochs exhibiting narrowband frontal δ oscillations, and not broadband sleep-associated δ, selectively exhibited δ-HFO coupling, while paradoxical sleep epochs having a high CA1 θ to frontal δ ratio selectively exhibited θ-HFO coupling. Our results suggest: (1) NR2A-preferring antagonism induces oscillopathies reflecting frontal hyperfunction and hippocampal hypofunction; and (2) HFO PAC indexes cortical vs. hippocampal control of mesolimbic circuits.

Parvalbumin-containing GABA cells and schizophrenia: experimental model based on targeted gene delivery through adeno-associated viruses

Understanding the contribution of transmitter systems in behavioural pharmacology has a long tradition. Multiple techniques such as transmitter-specific lesions, and also localized administration of pharmacological toxins including agonists and antagonists of selected receptors have been applied. More recently, modern genetic tools have permitted cell-type selective interferences, for example by expression of light-sensitive channels followed by optogenetic stimulation in behaviourally meaningful settings or by engineered channels termed DREADDS that respond to peripherally administered drugs. We here took a similar approach and employed a Cre recombinase-dependent viral delivery system (adeno-associated virus) to express tetanus toxin light chain (TeLc) and thus, block neural transmission specifically in parvalbumin-positive (PV+) neurons of the limbic and infralimbic prefrontal circuitry. PV-TeLc cohorts presented with normal circadian activity as recorded in PhenoTyper home cages, but a reproducible increase in anxiety was extracted in both the open field and light-dark box. Interestingly, working memory assessed in a spontaneous alternation Y-maze task was impaired in PV-TeLc mice. We also recorded local field potentials from a separate cohort and found no global changes in brain activity, but found a behaviourally relevant lack of modulation in the gamma spectral band. These anomalies are reminiscent of endophenotypes of schizophrenia and appear to be critically dependent on GABAergic signalling through PV neurones. At the same time, these observations validate the use of viral vector delivery and its expression in Cre-lines as a useful tool for understanding the role of selective components of the brain in behaviour and the underpinning physiology.

The N-Methyl d-Aspartate Glutamate Receptor Antagonist Ketamine Disrupts the Functional State of the Corticothalamic Pathway

The non-competitive N-methyl d-aspartate glutamate receptor (NMDAR) antagonist ketamine elicits a brain state resembling high-risk states for developing psychosis and early stages of schizophrenia characterized by sensory and cognitive deficits and aberrant ongoing gamma (30-80 Hz) oscillations in cortical and subcortical structures, including the thalamus. The underlying mechanisms are unknown. The goal of the present study was to determine whether a ketamine-induced psychotic-relevant state disturbs the functional state of the corticothalamic (CT) pathway. Multisite field recordings were performed in the somatosensory CT system of the sedated rat. Baseline activity was challenged by activation of vibrissa-related prethalamic inputs. The sensory-evoked thalamic response was characterized by a short-latency (∼4 ms) prethalamic-mediated negative sharp potential and a longer latency (∼10 ms) CT-mediated negative potential. Following a single subcutaneous injection of ketamine (2.5 mg/kg), spontaneously occurring and sensory-evoked thalamic gamma oscillations increased and decreased in power, respectively. The power of the sensory-related gamma oscillations was positively correlated with both the amplitude and the area under the curve of the corresponding CT potential but not with the prethalamic potential. The present results show that the layer VI CT pathway significantly contributes in thalamic gamma oscillations, and they support the hypothesis that reduced NMDAR activation disturbs the functional state of CT and corticocortical networks.

Oscillatory Synchronous Inhibition in the Basolateral Amygdala and its Primary Dependence on NR2A-containing NMDA Receptors

Synchronous, rhythmic firing of GABAergic interneurons is a fundamental mechanism underlying the generation of brain oscillations, and evidence suggests that NMDA receptors (NMDARs) play a key role in oscillatory activity by regulating the activity of interneurons. Consistent with this, derangement of brain rhythms in certain neuropsychiatric disorders, notably schizophrenia and autism, is associated with NMDAR hypofunction and loss of inhibitory interneurons. In the basolateral amygdala (BLA)-dysfunction of which is involved in a host of neuropsychiatric diseases-, principal neurons display spontaneous, rhythmic "bursts" of inhibitory activity, which could potentially be involved in the orchestration of oscillations in the BLA network; here, we investigated the role of NMDARs in these inhibitory oscillations. Rhythmic bursts of spontaneous IPSCs (0.5 Hz average burst frequency) recorded from rat BLA principal cells were blocked or significantly suppressed by D-AP5, and could be driven by NMDAR activation alone. BLA interneurons generated spontaneous bursts of suprathreshold EPSCs at a similar frequency, which were also blocked or reduced by D-AP5. PEAQX (GluN2A-NMDAR antagonist; 0.4 μM) or Ro-25-6981 (GluN2B-NMDAR antagonist; 5 μM) suppressed the IPSC and EPSC bursts; suppression by PEAQX was significantly greater than that by Ro-25-6981. Immunohistochemical labeling revealed the presence of both GluN2A- and GluN2B-NMDARs on GABAergic BLA interneurons, while, functionally, GluN2A-NMDARs have the dominant role, as suggested by a greater reduction of NMDA-evoked currents by PEAQX versus Ro-25-6981. Entrainment of BLA principal neurons in an oscillatory generation of inhibitory activity depends primarily on activation of GluN2A-NMDARs, and interneuronal GluN2A-NMDARs may play a significant role.

Deconstructing Schizophrenia: Advances in Preclinical Models for Biomarker Identification

Schizophrenia is considered to develop as a consequence of genetic and environmental factors impacting on brain neural systems and circuits during vulnerable neurodevelopmental periods, thereby resulting in symptoms in early adulthood. Understanding of the impact of schizophrenia risk factors on brain biology and behaviour can help in identifying biologically relevant pathways that are attractive for informing clinical studies and biomarker development. In this chapter, we emphasize the importance of adopting a reciprocal forward and reverse translation approach that is iteratively updated when additional new information is gained, either preclinically or clinically, for offering the greatest opportunity for discovering panels of biomarkers for the diagnosis, prognosis and treatment of schizophrenia. Importantly, biomarkers for identifying those at risk may inform early intervention strategies prior to the development of schizophrenia.Given the emerging nature of this approach in the field, this review will highlight recent research of preclinical biomarkers in schizophrenia that show the most promise for informing clinical needs with an emphasis on relevant imaging, electrophysiological, cognitive behavioural and biochemical modalities. The implementation of this reciprocal translational approach is exemplified firstly by the production and characterization of preclinical models based on the glutamate hypofunction hypothesis, genetic and environmental risk factors for schizophrenia (reverse translation), and then the recent clinical recognition of the thalamic reticular thalamus (TRN) as an important locus of brain dysfunction in schizophrenia as informed by preclinical findings (forward translation).

Abnormal cortical neural synchrony during working memory in schizophrenia

OBJECTIVE

To better understand the origins of working memory (WM) impairment in schizophrenia we investigated cortical oscillatory activity in people with schizophrenia (PSZ) while they performed a WM task requiring encoding, maintenance, and retrieval/manipulation processes of spatial information.

METHODS

We examined time-frequency synchronous energy of cortical source signals that were derived from magnetoencephalography (MEG) localized to cortical regions using WM-related hemodynamic responses and individualized structural head-models.

RESULTS

Compared to thirteen healthy controls (HC), twelve PSZ showed performance deficits regardless of WM-load or duration. During encoding, PSZ had early theta and delta event-related synchrony (ERS) deficits in prefrontal and visual cortices which worsened with greater memory load and predicted WM performance. During prolonged maintenance of material, PSZ showed deficient beta event-related desynchrony (ERD) in dorsolateral prefrontal, posterior parietal, and visual cortices. In retrieval, PSZ showed reduced delta/theta ERS in the anterior prefrontal and ventral visual cortices and diminished gamma ERS in the premotor and posterior parietal cortices.

CONCLUSIONS

Although beta/gamma cortical neural oscillatory deficits for maintenance/retrieval are evident during WM, the abnormal prefrontal theta-frequency ERS for encoding is most predictive of poor WM in schizophrenia.

SIGNIFICANCE

Time-frequency-spatial analysis identified process- and frequency-specific neural synchrony abnormalities underlying WM deficits in schizophrenia.

Neuronal correlates of ketamine and walking induced gamma oscillations in the medial prefrontal cortex and mediodorsal thalamus

Alterations in the function of the medial prefrontal cortex (mPFC) and its major thalamic source of innervation, the mediodorsal (MD) thalamus, have been hypothesized to contribute to the symptoms of schizophrenia. The NMDAR antagonist ketamine, used to model schizophrenia, elicits a brain state resembling early stage schizophrenia characterized by cognitive deficits and increases in cortical low gamma (40-70 Hz) power. Here we sought to determine how ketamine differentially affects spiking and gamma local field potential (LFP) activity in the rat mPFC and MD thalamus. Additionally, we investigated the ability of drugs targeting the dopamine D4 receptor (D4R) to modify the effects of ketamine on gamma activity as a measure of potential cognitive therapeutic efficacy. Rats were trained to walk on a treadmill to reduce confounds related to hyperactivity after ketamine administration (10 mg/kg s.c.) while recordings were obtained from electrodes chronically implanted in the mPFC and MD thalamus. Ketamine increased gamma LFP power in mPFC and MD thalamus in a similar frequency range, yet did not increase thalamocortical synchronization. Ketamine also increased firing rates and spike synchronization to gamma oscillations in the mPFC but decreased both measures in MD thalamus. Conversely, walking alone increased both firing rates and spike-gamma LFP correlations in both mPFC and MD thalamus. The D4R antagonist alone (L-745,870) had no effect on gamma LFP power during treadmill walking, although it reversed increases induced by the D4R agonist (A-412997) in both mPFC and MD thalamus. Neither drug altered ketamine-induced changes in gamma power or firing rates in the mPFC. However, in MD thalamus, the D4R agonist increased ketamine-induced gamma power and prevented ketamine's inhibitory effect on firing rates. Results provide new evidence that ketamine differentially modulates spiking and gamma power in MD thalamus and mPFC, supporting a potential role for both areas in contributing to ketamine-induced schizophrenia-like symptoms.

Attenuation of ketamine-induced impairment in verbal learning and memory in healthy volunteers by the AMPA receptor potentiator PF-04958242

There is a need to develop treatments for cognitive impairment associated with schizophrenia (CIAS). The significant role played by N-methyl-d-aspartate receptors (NMDARs) in both the pathophysiology of schizophrenia and in neuronal plasticity suggests that facilitation of NMDAR function might ameliorate CIAS. One strategy to correct NMDAR hypofunction is to stimulate α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) as AMPAR and NMDAR functioning are coupled and interdependent. In rats and nonhuman primates (NHP), AMPAR potentiators reduce spatial working memory deficits caused by the nonselective NMDAR antagonist ketamine. The current study assessed whether the AMPAR potentiator PF-04958242 would attenuate ketamine-induced deficits in verbal learning and memory in humans. Healthy male subjects (n=29) participated in two randomized treatment periods of daily placebo or PF-04958242 for 5 days separated by a washout period. On day 5 of each treatment period, subjects underwent a ketamine infusion for 75 min during which the effects of PF-04958242/placebo were assessed on ketamine-induced: (1) impairments in verbal learning and recall measured by the Hopkins Verbal Learning Test; (2) impairments in working memory on a CogState battery; and (3) psychotomimetic effects measured by the Positive and Negative Syndrome Scale and Clinician-Administered Dissociative Symptoms Scale. PF-04958242 significantly reduced ketamine-induced impairments in immediate recall and the 2-Back and spatial working memory tasks (CogState Battery), without significantly attenuating ketamine-induced psychotomimetic effects. There were no pharmacokinetic interactions between PF-04958242 and ketamine. Furthermore, PF-04958242 was well tolerated. 'High-impact' AMPAR potentiators like PF-04958242 may have a role in the treatment of the cognitive symptoms, but not the positive or negative symptoms, associated with schizophrenia. The excellent concordance between the preclinical (rat, NHP) and human studies with PF-04958242, and in silico modeling of AMPAR-NMDAR interactions in the hippocampus, highlights the translational value of this study.

Disrupted cholinergic modulation can underlie abnormal gamma rhythms in schizophrenia and auditory hallucination

The pathophysiology of auditory hallucination, a common symptom of schizophrenia, has yet been understood, but during auditory hallucination, primary auditory cortex (A1) shows paradoxical responses. When auditory stimuli are absent, A1 becomes hyperactive, while A1 responses to auditory stimuli are reduced. Such activation pattern of A1 responses during auditory hallucination is consistent with aberrant gamma rhythms in schizophrenia observed during auditory tasks, raising the possibility that the pathology underlying abnormal gamma rhythms can account for auditory hallucination. Moreover, A1 receives top-down signals in the gamma frequency band from an adjacent association area (Par2), and cholinergic modulation regulates interactions between A1 and Par2. In this study, we utilized a computational model of A1 to ask if disrupted cholinergic modulation could underlie abnormal gamma rhythms in schizophrenia. Furthermore, based on our simulation results, we propose potential pathology by which A1 can directly contribute to auditory hallucination.

Aberrant alpha and gamma oscillations ex vivo after single application of the NMDA receptor antagonist MK-801

Clinical symptoms of schizophrenia are associated with altered cortical neuronal oscillations in multiple frequency bands such as alpha (7-13Hz) and gamma (30-90Hz) rhythms. NMDA receptor antagonists induce psychotic symptoms in humans and a schizophrenia-like phenotype in animals, suggesting NMDA receptor dysfunction is involved in the generation of many symptoms of the disorder. We investigated the effects of a single intraperitoneal injection of the NMDA receptor antagonist MK-801 in rats, a model of first-episode schizophrenia, on network oscillations recorded ex vivo in the hippocampus and prefrontal cortex. We found that spontaneous gamma oscillations in hippocampal slices of MK-801-treated animals had a higher peak frequency, but that their rate of occurrence, peak power and Q factor (ratio of peak frequency to half bandwidth) were not affected. Hippocampal gamma oscillations induced by application of acetylcholine displayed a higher peak power, a reduced peak frequency and a shortened induction latency, whereas the Q factor did not change. In the prefrontal cortex, co-application of carbachol and kainate induced two types of network activity in sham animals: continuous gamma oscillations and alternating alpha/gamma oscillations. In MK-801-treated animals, the alternating pattern completely disappeared, and only continuous gamma oscillations could be detected, possessing an increased peak power, decreased peak frequency and decreased Q factor. Alpha oscillations recorded in MK-801-treated animals also had a significantly lower Q factor. In conclusion, our data suggest that NMDA receptor antagonists fundamentally alter the power, peak frequency, dynamics and periodicity of neuronal oscillations in the alpha and gamma frequency band.

Potential Mechanisms and Functions of Intermittent Neural Synchronization

Neural synchronization is believed to play an important role in different brain functions. Synchrony in cortical and subcortical circuits is frequently variable in time and not perfect. Few long intervals of desynchronized dynamics may be functionally different from many short desynchronized intervals although the average synchrony may be the same. Recent analysis of imperfect synchrony in different neural systems reported one common feature: neural oscillations may go out of synchrony frequently, but primarily for a short time interval. This study explores potential mechanisms and functional advantages of this short desynchronizations dynamics using computational neuroscience techniques. We show that short desynchronizations are exhibited in coupled neurons if their delayed rectifier potassium current has relatively large values of the voltage-dependent activation time-constant. The delayed activation of potassium current is associated with generation of quickly-rising action potential. This “spikiness” is a very general property of neurons. This may explain why very different neural systems exhibit short desynchronization dynamics. We also show how the distribution of desynchronization durations may be independent of the synchronization strength. Finally, we show that short desynchronization dynamics requires weaker synaptic input to reach a pre-set synchrony level. Thus, this dynamics allows for efficient regulation of synchrony and may promote efficient formation of synchronous neural assemblies.

Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders

Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions.

Differences of temporal dynamics and signal complexity of gamma band oscillations in first-episode psychosis during a working memory task

Gamma band oscillations participate in the temporal binding needed to synchronize cortical networks, involved in early sensory and short term memory processes. In earlier studies, alterations of these neurophysiological parameters have been found in psychotic disorders. To date no study has explored the temporal dynamics and signal complexity of gamma band oscillations in first episode psychosis (FEP). To address this issue, gamma band analysis was performed in 15 FEP patients and 18 healthy controls who successfully performed an adapted 2-back working memory task. Multiple linear and logistic regression models were computed to explore the relationship between the cognitive status and gamma oscillation changes over time. Based on regression model results, phase diagrams were constructed and their complexity was estimated using fractal dimension, a mathematical tool that describes shapes as numeric values. When adjusted for gamma values at time lags -3 to -4 ms and -15 to -16 ms, FEP patients displayed significantly higher time-dependent changes than controls, independently of the nature of the task. The present results are consistent with a discoordination of the activity of cortical generators engaged by the stimulus apparition in FEP patients, leading to a global binding deficit. In addition, fractal analysis showing higher complexity of gamma signal, confirmed this deficit. Our results provide evidence for recruitment of supplementary cortical generators as compensating mechanisms and yield further understanding for the pathophysiology cognitive impairments in FEP.

Cannabinoids as hippocampal network administrators

Extensive pioneering studies performed in the hippocampus have greatly contributed to our knowledge of an endogenous cannabinoid system comprised of the molecular machinery necessary to process endocannabinoid lipid messengers and their associated cannabinoid receptors. Moreover, a foundation of knowledge regarding the function of hippocampal circuits, and its role in supporting synaptic plasticity has facilitated our understanding of the roles cannabinoids play in the diverse behaviors in which the hippocampus participates, in both normal and pathological states. In this review, we present an historical overview of research pertaining to the hippocampal cannabinoid system to provide context in which to understand the participation of the hippocampus in cognition, behavior, and epilepsy. We also examine potential roles for the hippocampal formation in mediating dysfunctional behavior, and assert that these phenomena reflect disordered physiological activity within the hippocampus and its interactions with other brain regions after exposure to synthetic cannabinoids, and the phytocannabinoids found in marijuana, such as Δ⁹-THC and cannabidiol. In this regard, we examine contemporary hypotheses concerning the hippocampal endocannabinoid system's participation in psychotic disorders, schizophrenia, and epilepsy, and examine cannabinoid-sensitive cellular mechanisms contributing to coherent network oscillations as potential contributors to these disorders. This article is part of the Special Issue entitled "A New Dawn in Cannabinoid Neurobiology".

Differential modulation of global and local neural oscillations in REM sleep by homeostatic sleep regulation

Homeostatic rebound in rapid eye movement (REM) sleep normally occurs after acute sleep deprivation, but REM sleep rebound settles on a persistently elevated level despite continued accumulation of REM sleep debt during chronic sleep restriction (CSR). Using high-density EEG in mice, we studied how this pattern of global regulation is implemented in cortical regions with different functions and network architectures. We found that across all areas, slow oscillations repeated the behavioral pattern of persistent enhancement during CSR, whereas high-frequency oscillations showed progressive increases. This pattern followed a common rule despite marked topographic differences. The findings suggest that REM sleep slow oscillations may translate top-down homeostatic control to widely separated brain regions whereas fast oscillations synchronizing local neuronal ensembles escape this global command. These patterns of EEG oscillation changes are interpreted to reconcile two prevailing theories of the function of sleep, synaptic homeostasis and sleep dependent memory consolidation.

An in Silico, Biomarker-Based Method for the Evaluation of Virtual Neuropsychiatric Drug Effects

The recent explosion in neuroscience research has markedly increased our understanding of the neurobiological correlates of many psychiatric illnesses, but this has unfortunately not translated into more effective pharmacologic treatments for these conditions. At the same time, researchers have increasingly sought out biological markers, or biomarkers, as a way to categorize psychiatric illness, as these are felt to be closer to underlying genetic and neurobiological vulnerabilities. While biomarker-based drug discovery approaches have tended to employ in vivo (e.g., rodent) or in vitro test systems, relatively little attention has been paid to the potential of computational, or in silico, methodologies. Here we describe such a methodology, using as an example a biophysically detailed computational model of hippocampus that is made to generate putative schizophrenia biomarkers by the inclusion of a number of neuropathological changes that have been associated with the illness (NMDA system deficit, decreased neural connectivity, hyperdopaminergia). We use the specific inability to attune to gamma band (40 Hz) auditory stimulus as our illness biomarker. We expose this system to a large number of virtual medications, defined by systematic variation of model parameters corresponding to five cellular-level effects. The potential efficacy of virtual medications is determined by a wellness metric (WM) that we have developed. We identify a number of virtual agents that consist of combinations of mechanisms, which are not simply reversals of the causative lesions. The manner in which this methodology could be extended to other neuropsychiatric conditions, such as Alzheimer's disease, autism, and fragile X syndrome, is discussed.

Beta/Gamma Oscillations and Event-Related Potentials Indicate Aberrant Multisensory Processing in Schizophrenia

Recent behavioral and neuroimaging studies have suggested multisensory processing deficits in patients with schizophrenia (SCZ). Thus far, the neural mechanisms underlying these deficits are not well understood. Previous studies with unisensory stimulation have shown altered neural oscillations in SCZ. As such, altered oscillations could contribute to aberrant multisensory processing in this patient group. To test this assumption, we conducted an electroencephalography (EEG) study in 15 SCZ and 15 control participants in whom we examined neural oscillations and event-related potentials (ERPs) in the sound-induced flash illusion (SIFI). In the SIFI multiple auditory stimuli that are presented alongside a single visual stimulus can induce the illusory percept of multiple visual stimuli. In SCZ and control participants we compared ERPs and neural oscillations between trials that induced an illusion and trials that did not induce an illusion. On the behavioral level, SCZ (55.7%) and control participants (55.4%) did not significantly differ in illusion rates. The analysis of ERPs revealed diminished amplitudes and altered multisensory processing in SCZ compared to controls around 135 ms after stimulus onset. Moreover, the analysis of neural oscillations revealed altered 25–35 Hz power after 100 to 150 ms over occipital scalp for SCZ compared to controls. Our findings extend previous observations of aberrant neural oscillations in unisensory perception paradigms. They suggest that altered ERPs and altered occipital beta/gamma band power reflect aberrant multisensory processing in SCZ.

Bridging the Gap between Genes and Language Deficits in Schizophrenia: An Oscillopathic Approach

Schizophrenia is characterized by marked language deficits, but it is not clear how these deficits arise from the alteration of genes related to the disease. The goal of this paper is to aid the bridging of the gap between genes and schizophrenia and, ultimately, give support to the view that the abnormal presentation of language in this condition is heavily rooted in the evolutionary processes that brought about modern language. To that end we will focus on how the schizophrenic brain processes language and, particularly, on its distinctive oscillatory profile during language processing. Additionally, we will show that candidate genes for schizophrenia are overrepresented among the set of genes that are believed to be important for the evolution of the human faculty of language. These genes crucially include (and are related to) genes involved in brain rhythmicity. We will claim that this translational effort and the links we uncover may help develop an understanding of language evolution, along with the etiology of schizophrenia, its clinical/linguistic profile, and its high prevalence among modern populations.

Language deficits in schizophrenia and autism as related oscillatory connectomopathies: An evolutionary account

Schizophrenia (SZ) and autism spectrum disorders (ASD) are characterised by marked language deficits, but it is not clear how these arise from gene mutations associated with the disorders. Our goal is to narrow the gap between SZ and ASD and, ultimately, give support to the view that they represent abnormal (but related) ontogenetic itineraries for the human faculty of language. We will focus on the distinctive oscillatory profiles of the SZ and ASD brains, in turn using these insights to refine our understanding of how the brain implements linguistic computations by exploring a novel model of linguistic feature-set composition. We will argue that brain rhythms constitute the best route to interpreting language deficits in both conditions and mapping them to neural dysfunction and risk alleles of the genes. Importantly, candidate genes for SZ and ASD are overrepresented among the gene sets believed to be important for language evolution. This translational effort may help develop an understanding of the aetiology of SZ and ASD and their high prevalence among modern populations.

Implicit Timing as the Missing Link between Neurobiological and Self Disorders in Schizophrenia?

Disorders of consciousness and the self are at the forefront of schizophrenia symptomatology. Patients are impaired in feeling themselves as the authors of their thoughts and actions. In addition, their flow of consciousness is disrupted, and thought fragmentation has been suggested to be involved in the patients' difficulties in feeling as being one unique, unchanging self across time. Both impairments are related to self disorders, and both have been investigated at the experimental level. Here we review evidence that both mechanisms of motor control and the temporal structure of signal processing are impaired in schizophrenia patients. Based on this review, we propose that the sequencing of action and perception plays a key role in the patients' impairments. Furthermore, the millisecond time scale of the disorders, as well as the impaired sequencing, highlights the cooperation between brain networks including the cerebellum, as proposed by Andreasen (1999). We examine this possibility in the light of recent knowledge on the anatomical and physiological properties of the cerebellum, its role in timing, and its involvement in known physiological impairments in patients with schizophrenia, e.g., resting states and brain dynamics. A disruption in communication between networks involving the cerebellum, related to known impairments in dopamine, glutamate and GABA transmission, may help to better explain why patients experience reduced attunement with the external world and possibly with themselves.

It's All in the Rhythm: The Role of Cannabinoids in Neural Oscillations and Psychosis

Evidence has accumulated over the past several decades suggesting that both exocannabinoids and endocannabinoids play a role in the pathophysiology of schizophrenia. The current article presents evidence suggesting that one of the mechanisms whereby cannabinoids induce psychosis is through the alteration in synchronized neural oscillations. Neural oscillations, particularly in the gamma (30-80 Hz) and theta (4-7 Hz) ranges, are disrupted in schizophrenia and are involved in various areas of perceptual and cognitive function. Regarding cannabinoids, preclinical evidence from slice and local field potential recordings has shown that central cannabinoid receptor (cannabinoid receptor type 1) agonists decrease the power of neural oscillations, particularly in the gamma and theta bands. Further, the administration of cannabinoids during critical stages of neural development has been shown to disrupt the brain's ability to generate synchronized neural oscillations in adulthood. In humans, studies examining the effects of chronic cannabis use (utilizing electroencephalography) have shown abnormalities in neural oscillations in a pattern similar to those observed in schizophrenia. Finally, recent studies in humans have also shown disruptions in neural oscillations after the acute administration of delta-9-tetrahydrocannabinol, the primary psychoactive constituent in cannabis. Taken together, these data suggest that both acute and chronic cannabinoids can disrupt the ability of the brain to generate synchronized oscillations at functionally relevant frequencies. Hence, this may represent one of the primary mechanisms whereby cannabinoids induce disruptions in attention, working memory, sensory-motor integration, and many other psychosis-related behavioral effects.