Patterns of spontaneous magnetoencephalographic activity in patients with schizophrenia

Neural Mechanism of 5-HT4R-Mediated Memory Enhancement in Hippocampal-Prefrontal Circuits in a Mouse Model of Schizophrenia

We investigated the cellular and neurophysiological mechanisms underlying the pro-cognitive effects of 5-HT4R activation in hippocampal-prefrontal pathways. Our findings show that, in addition to pyramidal neurons, 30-60% of parvalbumin+ interneurons in the CA1, CA3, and dentate gyrus (DG) of the hippocampus and the anterior cingulate (ACC), prelimbic (PL), and infralimbic (IL) regions of the prefrontal cortex co-express 5-HT4Rs. Additionally, 15% of somatostatin+ interneurons in CA1 and CA3 express 5-HT4Rs. Partial 5-HT4R agonist RS-67333 (1 mg/kg, i.p.) exerted anxiolytic effects and ameliorated short-term (3-min) and long-term (24-h) memory deficits in a mouse model of schizophrenia-like cognitive impairment induced by sub-chronic phencyclidine (sPCP) but did not enhance memory in healthy mice. At the neurophysiological level, RS-67333 normalized sPCP-induced disruptions in hippocampal-prefrontal neural dynamics while having no effect in healthy animals. Specifically, sPCP increased delta oscillations in CA1 and PL, leading to aberrant delta-high-frequency coupling in CA1 and delta-high-gamma coupling in PL. RS-67333 administration attenuated this abnormal delta synchronization without altering phase coherence or signal directionality within the circuit. Collectively, these results highlight the therapeutic potential of 5-HT4R activation in pyramidal, parvalbumin+, and somatostatin+ neurons of hippocampal-prefrontal pathways for mitigation of cognitive and negative symptoms associated with schizophrenia.

Spectral decomposition of resting state electroencephalogram reveals unique theta/alpha activity in schizophrenia

Resting state electroencephalographic (EEG) activity in schizophrenia (SZ) is frequently characterised by increased power at slow frequencies and/or a reduction of peak alpha frequency. Here we investigated the nature of these effects. As most studies to date have been limited by reliance on a priori frequency bands which impose an assumed structure on the data, we performed a data-driven analysis of resting EEG recorded in SZ patients and healthy controls (HC). The sample consisted of 39 chronic SZ and 36 matched HC. The EEG was recorded with a dense electrode array. Power spectral densities were decomposed via Varimax-rotated principal component analysis (PCA) over all participants and for each group separately. Spectral PCA was repeated at the cortical level on cortical current source density computed from standardised low resolution brain electromagnetic tomography. There was a trend for power in the theta/alpha range to be increased in SZ compared to HC, and peak alpha frequency was significantly reduced in SZ. PCA revealed that this frequency shift was because of the presence of a spectral component in the theta/alpha range (6-9 Hz) that was unique to SZ. The source distribution of the SZ > HC theta/alpha effect involved mainly prefrontal and parahippocampal areas. Abnormal low frequency resting EEG activity in SZ was accounted for by a unique theta/alpha oscillation. Other reports have described a similar phenomenon suggesting that the neural circuits oscillating in this range are relevant to SZ pathophysiology.

The hidden link: Investigating functional connectivity of rarely explored sub-regions of thalamus and superior temporal gyrus in Schizophrenia

Functional magnetic resonance imaging (fMRI) stands as a pivotal tool in advancing our comprehension of Schizophrenia, offering insights into functional segregations and integrations. Previous investigations employing either task-based or resting-state fMRI primarily focused on large main regions of interest (ROI), revealing the thalamus and superior temporal gyrus (STG) as prominently affected areas. Recent studies, however, unveiled the cytoarchitectural intricacies within these regions, prompting a more nuanced exploration. In this study, resting-state fMRI was conducted on 72 schizophrenic patients and 74 healthy controls to discern whether distinct thalamic nuclei and STG sub-regions exhibit varied functional integrational connectivity to main networks and to identify the most affected sub-regions in Schizophrenia. Employing seed-based analysis, six sub-ROIs - four in the thalamus and two in the STG - were selected. Our findings unveiled heightened positive functional connectivity in Schizophrenic patients, particularly toward the anterior STG (aSTG) and posterior STG (pSTG). Notably, positive connectivity emerged between the medial division of mediodorsal thalamic nuclei (MDm) and the visual network, while increased functional connectivity linked the ventral lateral nucleus of the thalamus with aSTG. This accentuated functional connectivity potentially influences these sub-regions, contributing to dysfunctions and manifesting symptoms such as language and learning difficulties alongside hallucinations. This study underscores the importance of delineating sub-regional dynamics to enhance our understanding of the nuanced neural alterations in Schizophrenia, paving the way for more targeted interventions and therapeutic approaches.

Simultaneous Knockouts of the Oxytocin and Vasopressin 1b Receptors in Hippocampal CA2 Impair Social Memory

Oxytocin (Oxt) and vasopressin (Avp) are two neuropeptides with many central actions related to social cognition. The oxytocin (Oxtr) and vasopressin 1b (Avpr1b) receptors are co-expressed in the pyramidal neurons of the hippocampal subfield CA2 and are known to play a critical role in social memory formation. How the neuropeptides perform this function in this region is not fully understood. Here, we report the behavioral effects of a life-long conditional removal (knockout, KO) of either the Oxtr alone or both Avpr1b and Oxtr from the pyramidal neurons of CA2 as well as the resultant changes in synaptic transmission within the different fields of the hippocampus. Surprisingly, the removal of both receptors results in mice that are unable to habituate to a familiar female presented for short duration over short intervals but are able to recognize and discriminate females when presented for a longer duration over a longer interval. Importantly, these double KO mice were unable to discriminate between a male littermate and a novel male. Synaptic transmission between CA3 and CA2 is enhanced in these mice, suggesting a compensatory mechanism is activated to make up for the loss of the receptors. Overall, our results demonstrate that co-expression of the receptors in CA2 is necessary to allow intact social memory processing.

The iPSC perspective on schizophrenia

Over a decade of schizophrenia research using human induced pluripotent stem cell (iPSC)-derived neural models has provided substantial data describing neurobiological characteristics of the disorder in vitro. Simultaneously, translation of the results into general mechanistic concepts underlying schizophrenia pathophysiology has been trailing behind. Given that modeling brain function using cell cultures is challenging, the gap between the in vitro models and schizophrenia as a clinical disorder has remained wide. In this review, we highlight reproducible findings and emerging trends in recent schizophrenia-related iPSC studies. We illuminate the relevance of the results in the context of human brain development, with a focus on processes coinciding with critical developmental periods for schizophrenia.

A Case for Thalamic Mechanisms of Schizophrenia: Perspective From Modeling 22q11.2 Deletion Syndrome

Schizophrenia is a severe, chronic psychiatric disorder that devastates the lives of millions of people worldwide. The disease is characterized by a constellation of symptoms, ranging from cognitive deficits, to social withdrawal, to hallucinations. Despite decades of research, our understanding of the neurobiology of the disease, specifically the neural circuits underlying schizophrenia symptoms, is still in the early stages. Consequently, the development of therapies continues to be stagnant, and overall prognosis is poor. The main obstacle to improving the treatment of schizophrenia is its multicausal, polygenic etiology, which is difficult to model. Clinical observations and the emergence of preclinical models of rare but well-defined genomic lesions that confer substantial risk of schizophrenia (e.g., 22q11.2 microdeletion) have highlighted the role of the thalamus in the disease. Here we review the literature on the molecular, cellular, and circuitry findings in schizophrenia and discuss the leading theories in the field, which point to abnormalities within the thalamus as potential pathogenic mechanisms of schizophrenia. We posit that synaptic dysfunction and oscillatory abnormalities in neural circuits involving projections from and within the thalamus, with a focus on the thalamocortical circuits, may underlie the psychotic (and possibly other) symptoms of schizophrenia.

Disorganization of Oscillatory Activity in Animal Models of Schizophrenia

Schizophrenia is a chronic, debilitating disorder with diverse symptomatology, including disorganized cognition and behavior. Despite considerable research effort, we have only a limited understanding of the underlying brain dysfunction. In this article, we review the potential role of oscillatory circuits in the disorder with a particular focus on the hippocampus, a region that encodes sequential information across time and space, as well as the frontal cortex. Several mechanistic explanations of schizophrenia propose that a loss of oscillatory synchrony between and within these brain regions may underlie some of the symptoms of the disorder. We describe how these oscillations are affected in several animal models of schizophrenia, including models of genetic risk, maternal immune activation (MIA) models, and models of NMDA receptor hypofunction. We then critically discuss the evidence for disorganized oscillatory activity in these models, with a focus on gamma, sharp wave ripple, and theta activity, including the role of cross-frequency coupling as a synchronizing mechanism. Finally, we focus on phase precession, which is an oscillatory phenomenon whereby individual hippocampal place cells systematically advance their firing phase against the background theta oscillation. Phase precession is important because it allows sequential experience to be compressed into a single 120 ms theta cycle (known as a 'theta sequence'). This time window is appropriate for the induction of synaptic plasticity. We describe how disruption of phase precession could disorganize sequential processing, and thereby disrupt the ordered storage of information. A similar dysfunction in schizophrenia may contribute to cognitive symptoms, including deficits in episodic memory, working memory, and future planning.

Effects of repetitive transcranial magnetic and deep brain stimulation on long-range synchrony of oscillatory activity in a rat model of developmental schizophrenia

Aberrant neuronal network activity likely resulting from disturbed interactions of excitatory and inhibitory systems may be a major cause of cognitive deficits in neuropsychiatric diseases, like within the spectrum of schizophrenic phenotypes. In particular, the synchrony and pattern of oscillatory brain activity appears to be disturbed within limbic networks, e.g. between prefrontal cortex and hippocampus. In a rat model of maternal immune activation (MIA), we compared the acute effects of deep brain stimulation within either medial prefrontal cortex or ventral hippocampus with the effects of repetitive transcranial magnetic stimulation (rTMS), using the intermittent theta-burst protocol (iTBS), on oscillatory activity within limbic structures. Simultaneous local field potential recordings were made from medial prefrontal cortex, ventral hippocampus, nucleus accumbens and rostral part of ventral tegmental area before and after deep brain stimulation in anaesthetized rats previously (~3 h) treated with sham or verum rTMS. We found a waxing and waning pattern of theta and gamma activity in all structures which was less synchronous in particular between medial prefrontal cortex and ventral hippocampus in MIA offspring. Deep brain stimulation in medial prefrontal cortex and pre-treatment with iTBS-rTMS partly improved this pattern. Gamma-theta cross-frequency coupling was stronger in MIA offspring and could partly be reduced by deep brain stimulation in medial prefrontal cortex. We can confirm aberrant limbic network activity in a rat MIA model, and at least acute normalizing effects of the neuromodulatory methods. It has to be proven whether these procedures can have chronic effects suitable for therapeutic purposes.

Transcranial alternating current stimulation (tACS): from basic mechanisms towards first applications in psychiatry

Transcranial alternating current stimulation (tACS) is a unique form of non-invasive brain stimulation. Sinusoidal alternating electric currents are delivered to the scalp to affect mostly cortical neurons. tACS is supposed to modulate brain function and, in turn, cognitive processes by entraining brain oscillations and inducing long-term synaptic plasticity. Therefore, tACS has been investigated in cognitive neuroscience, but only recently, it has been also introduced in psychiatric clinical trials. This review describes current concepts and first findings of applying tACS as a potential therapeutic tool in the field of psychiatry. The current understanding of its mechanisms of action is explained, bridging cellular neuronal activity and the brain network mechanism. Revisiting the relevance of altered brain oscillations found in six major psychiatric disorders, putative targets for the management of mental disorders using tACS are discussed. A systematic literature search on PubMed was conducted to report findings of the clinical studies applying tACS in patients with psychiatric conditions. In conclusion, the initial results may support the feasibility of tACS in clinical psychiatric populations without serious adverse events. Moreover, these results showed the ability of tACS to reset disturbed brain oscillations, and thus to improve behavioural outcomes. In addition to its potential therapeutic role, the reactivity of the brain circuits to tACS could serve as a possible tool to determine the diagnosis, classification or prognosis of psychiatric disorders. Future double-blind randomised controlled trials are necessary to answer currently unresolved questions. They may aim to detect response predictors and control for various confounding factors.

Spectral features based convolutional neural network for accurate and prompt identification of schizophrenic patients

Schizophrenia is a fatal mental disorder, which affects millions of people globally by the disturbance in their thinking, feeling and behaviour. In the age of the internet of things assisted with cloud computing and machine learning techniques, the computer-aided diagnosis of schizophrenia is essentially required to provide its patients with an opportunity to own a better quality of life. In this context, the present paper proposes a spectral features based convolutional neural network (CNN) model for accurate identification of schizophrenic patients using spectral analysis of multichannel EEG signals in real-time. This model processes acquired EEG signals with filtering, segmentation and conversion into frequency domain. Then, given frequency domain segments are divided into six distinct spectral bands like delta, theta-1, theta-2, alpha, beta and gamma. The spectral features including mean spectral amplitude, spectral power and Hjorth descriptors (Activity, Mobility and Complexity) are extracted from each band. These features are independently fed to the proposed spectral features-based CNN and long short-term memory network (LSTM) models for classification. This work also makes use of raw time-domain and frequency-domain EEG segments for classification using temporal CNN and spectral CNN models of same architectures respectively. The overall analysis of simulation results of all models exhibits that the proposed spectral features based CNN model is an efficient technique for accurate and prompt identification of schizophrenic patients among healthy individuals with average classification accuracies of 94.08% and 98.56% for two different datasets with optimally small classification time.

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.

Test-Retest Reliability of Magnetoencephalography Resting-State Functional Connectivity in Schizophrenia

The reliability of magnetoencephalography (MEG) resting-state functional connectivity in schizophrenia (SZ) is unknown as previous research has focused on healthy controls (HC). Here, we examined reliability in 26 participants (13-SZ, 13-HC). Eyes opened and eyes closed resting-state data were collected on 4 separate occasions during 2 visits, 1 week apart. For source modeling, we used minimum norm software to apply dynamic statistical parametric mapping. Source analyses compared the following functional connectivity metrics from each data run: coherence (coh), imaginary coherence (imcoh), pairwise phase consistency (ppc), phase-locking value (plv), phase lag index (pli), weighted phase lag index (wpli), and weighted phase lag index debiased (wpli2). Intraclass correlation coefficients (ICCs) were calculated for whole brain, network, and network pair averages. For reliability, ICCs above 0.75 = excellent, above 0.60 = good, above 0.40 = fair, and below 0.40 = poor reliability. We found the reliability of these metrics varied greatly depending on frequency band, network, network pair, and participant group examined. Broadband (1-58 Hz) whole brain averages in both HC and SZ showed excellent reliability for wpli2, and good to fair reliability for ppc, plv, and coh. Broadband network averages showed excellent to good reliability across 1 hour and 1 week for coh, imcoh, ppc, plv, wpli within default mode, cognitive control, and visual networks in HC, while the same metrics had excellent to fair reliability in SZ. Regional network pair averages showed good to fair reliability for coh, ppc, plv within default mode, cognitive control and visual network pairs in HC and SZ. In general, HC had higher reliability compared to SZ, and the default mode, cognitive control, and visual networks had higher reliability compared to somatosensory and auditory networks. Similar reliability levels occurred for both eyes opened and eyes closed resting-states for most metrics. The functional connectivity metrics of coh, ppc, and plv performed best across 1 hour and 1 week in HC and SZ. We also found that SZ had reduced coh, plv, and ppc in the dmn average and pair values indicating dysconnectivity in SZ. These findings encourage collecting both eyes opened and eyes closed resting-state MEG, while demonstrating that clinical populations may differ in reliability.

Reduced parietal alpha power and psychotic symptoms: Test-retest reliability of resting-state magnetoencephalography in schizophrenia and healthy controls

BACKGROUND

Despite increased reporting of resting-state magnetoencephalography (MEG), reliability of those measures remains scarce and predominately reported in healthy controls (HC). As such, there is limited knowledge on MEG resting-state reliability in schizophrenia (SZ).

METHODS

To address test-retest reliability in psychosis, a reproducibility study of 26 participants (13-SZ, 13-HC) was performed. We collected eyes open and eyes closed resting-state data during 4 separate instances (2 Visits, 2 runs per visit) to estimate spectral power reliability (power, normalized power, alpha reactivity) across one hour and one week. Intraclass correlation coefficients (ICCs) were calculated. For source modeling, we applied an anatomically constrained linear estimation inverse model known as dynamic statistical parametric mapping (MNE dSPM) and source-based connectivity using the weighted phase lag index.

RESULTS

Across one week there was excellent test-retest reliability in global spectral measures in theta-gamma bands (HC ICC_Avg = 0.87, SZ ICC_Avg = 0.87), regional spectral measures in all bands (HC ICC_Avg = 0.86, SZ ICC_Avg = 0.80), and parietal alpha measures (HC ICC_Avg = 0.90, SZ ICC_Avg = 0.84). Conversely, functional connectivity had poor reliability, as did source spectral power across one hour for SZ. Relative to HC, SZ also had reduced parietal alpha normalized power during eyes closed only, reduced alpha reactivity, and an association between higher PANSS positive scores and lower parietal alpha power.

CONCLUSIONS

There was excellent to good test-retest reliability in most MEG spectral measures with a few exceptions in the schizophrenia patient group. Overall, these findings encourage the use of resting-state MEG while emphasizing the importance of determining reliability in clinical populations.

The Role of GluN2C-Containing NMDA Receptors in Ketamine's Psychotogenic Action and in Schizophrenia Models

The NMDA receptor (NMDAR) hypofunction hypothesis of schizophrenia is supported by multiple lines of evidence. Notably, administration of the NMDAR antagonist, ketamine, to healthy human subjects has psychotogenic action, producing both positive and negative symptoms associated with schizophrenia. NMDARs have multiple subtypes, but the subtypes through which ketamine produces its psychotogenic effects are not known. Here we address this question using quantitative data that characterize ketamine's ability to block different NMDAR subtypes. Our calculations indicate that, at a concentration that has psychotogenic action in humans, ketamine blocks a substantial fraction of GluN2C subunit-containing receptors but has less effect on GluN2A-, GluN2B-, and GluN2D-containing receptors. Thus, GluN2C-containing receptors may have preferential involvement in psychotic states produced by ketamine. A separate line of experiments also points to a special role for GluN2C. That work demonstrates the ability of NMDAR antagonists to mimic the elevation in the awake-state δ frequency EEG power that occurs in schizophrenia. Physiological experiments in rodents show that NMDAR antagonists generate δ oscillations by their action on the GluN2C-containing NMDARs that are prevalent in the thalamus. Optogenetic experiments suggest that such oscillations could contribute to symptoms of schizophrenia.

Aberrant Network Activity in Schizophrenia

Brain dynamic changes associated with schizophrenia are largely equivocal, with interpretation complicated by many factors, such as the presence of therapeutic agents and the complex nature of the syndrome itself. Evidence for a brain-wide change in individual network oscillations, shared by all patients, is largely equivocal, but stronger for lower (delta) than for higher (gamma) bands. However, region-specific changes in rhythms across multiple, interdependent, nested frequencies may correlate better with pathology. Changes in synaptic excitation and inhibition in schizophrenia disrupt delta rhythm-mediated cortico-cortical communication, while enhancing thalamocortical communication in this frequency band. The contrasting relationships between delta and higher frequencies in thalamus and cortex generate frequency mismatches in inter-regional connectivity, leading to a disruption in temporal communication between higher-order brain regions associated with mental time travel.

Toward understanding thalamocortical dysfunction in schizophrenia through computational models of neural circuit dynamics

The thalamus is implicated in the neuropathology of schizophrenia, and multiple modalities of noninvasive neuroimaging provide converging evidence for altered thalamocortical dynamics in the disorder, such as functional connectivity and oscillatory power. However, it remains a challenge to link these neuroimaging biomarkers to underlying neural circuit mechanisms. One potential path forward is a "Computational Psychiatry" approach that leverages computational models of neural circuits to make predictions for the dynamical impact dynamical impact on specific thalamic disruptions hypothesized to occur in the pathophysiology of schizophrenia. Here we review biophysically-based computational models of neural circuit dynamics for large-scale resting-state networks which have been applied to schizophrenia, and for thalamic oscillations. As a key aspect of thalamocortical dysconnectivity in schizophrenia is its regional specificity, it is important to consider potential sources of intrinsic heterogeneity of cellular and circuit properties across cortical and thalamic structures.

Potential synergistic action of 19 schizophrenia risk genes in the thalamus

A goal of current schizophrenia (SZ) research is to understand how multiple risk genes work together with environmental factors to produce the disease. In schizophrenia, there is elevated delta frequency EEG power in the awake state, an elevation that can be mimicked in rodents by N-methyl-d-aspartate receptor (NMDAR) antagonist action in the thalamus. This thalamic delta can be blocked by dopamine D2 receptor antagonists, agents known to be therapeutic in SZ. Experiments suggest that these oscillations can interfere with brain function and may thus be causal in producing psychosis. Here we evaluate the question of whether well-established schizophrenia risk genes may interact to affect the delta generation process. We identify 19 risk genes that can plausibly work in a synergistic fashion to generate delta oscillations.

Abnormal Coupling Between Default Mode Network and Delta and Beta Band Brain Electric Activity in Psychotic Patients

Common-phase synchronization of neuronal oscillations is a mechanism by which distributed brain regions can be integrated into transiently stable networks. Based on the hypothesis that schizophrenia is characterized by deficits in functional integration within neuronal networks, this study aimed to explore whether psychotic patients exhibit differences in brain regions involved in integrative mechanisms. We report an electroencephalography (EEG)-informed functional magnetic resonance imaging analysis of eyes-open resting-state data collected from patients and healthy controls at two study sites. Global field synchronization (GFS) was chosen as an EEG measure indicating common-phase synchronization across electrodes. Several brain clusters appeared to be coupled to GFS differently in patients and controls. Activation in brain areas belonging to the default mode network was negatively associated to GFS delta (1-3.5 Hz) and positively to GFS beta (13-30 Hz) bands in patients, whereas controls showed an opposite pattern for both GFS frequency bands in those regions; activation in the extrastriate visual cortex was inversely related to GFS alpha1 (8.5-10.5 Hz) band in healthy controls, while patients had a tendency toward a positive relationship. Taken together, the GFS measure might be useful for detecting additional aspects of deficient functional network integration in psychosis.

Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence

Despite being the object of a thriving field of clinical research, the investigation of intrinsic brain network alterations in psychiatric illnesses is still in its early days. Because the pathological alterations are predominantly probed using functional magnetic resonance imaging (fMRI), many questions about the electrophysiological bases of resting-state alterations in psychiatric disorders, particularly among mood disorder patients, remain unanswered. Alongside important research using electroencephalography (EEG), the specific recent contributions and future promise of magnetoencephalography (MEG) in this field are not fully recognized and valued. Here, we provide a critical review of recent findings from MEG resting-state connectivity within major depressive disorder (MDD) and bipolar disorder (BD). The clinical MEG resting-state results are compared with those previously reported with fMRI and EEG. Taken together, MEG appears to be a promising but still critically underexploited technique to unravel the neurophysiological mechanisms that mediate abnormal (both hyper- and hypo-) connectivity patterns involved in MDD and BD. In particular, a major strength of MEG is its ability to provide source-space estimations of neuromagnetic long-range rhythmic synchronization at various frequencies (i.e., oscillatory coupling). The reviewed literature highlights the relevance of probing local and interregional rhythmic synchronization to explore the pathophysiological underpinnings of each disorder. However, before we can fully take advantage of MEG connectivity analyses in psychiatry, several limitations inherent to MEG connectivity analyses need to be understood and taken into account. Thus, we also discuss current methodological challenges and outline paths for future research. MEG resting-state studies provide an important window onto perturbed spontaneous oscillatory brain networks and hence supply an important complement to fMRI-based resting-state measurements in psychiatric populations.

Electroencephalographic characteristics of Iranian schizophrenia patients

Schizophrenia is a prevalent psychiatric disease with heterogeneous causes that is diagnosed based on history and mental status examination. Applied electrophysiology is a non-invasive method to investigate the function of the involved brain areas. In a previously understudied population, we examined acute phase electroencephalography (EEG) records along with pertinent Positive and Negative Syndrome Scale (PANSS) and Mini Mental State Examination (MMSE) scores for each patient. Sixty-four hospitalized patients diagnosed to have schizophrenia in Ebn-e-Sina Hospital were included in this study. PANSS and MMSE were completed and EEG tracings for every patient were recorded. Also, EEG tracings were recorded for 64 matched individuals of the control group. Although the predominant wave pattern in both patients and controls was alpha, theta waves were almost exclusively found in eight (12.5 %) patients with schizophrenia. Pathological waves in schizophrenia patients were exclusively found in the frontal brain region, while identified pathological waves in controls were limited to the temporal region. No specific EEG finding supported laterality in schizophrenia patients. PANSS and MMSE scores were significantly correlated with specific EEG parameters (all P values <0.04). Patients with schizophrenia demonstrate specific EEG patterns and show a clear correlation between EEG parameters and PANSS and MMSE scores. These characteristics are not observed in all patients, which imply that despite an acceptable specificity, they are not applicable for the majority of schizophrenia patients. Any deduction drawn based on EEG and scoring systems is in need of larger studies incorporating more patients and using better functional imaging techniques for the brain.

Consciousness, awareness of insight and neural mechanisms of schizophrenia

According to recent research, disturbances of self-awareness and conscious experience have a critical role in the pathophysiology of schizophrenia, and in this context, schizophrenia is currently understood as a disorder characterized by distortions of acts of awareness, self-consciousness, and self-monitoring. Together, these studies suggest that the processes of disrupted awareness and conscious disintegration in schizophrenia might be related and represented by similar disruptions on the brain level, which, in principle, could be explained by various levels of disturbed connectivity and information disintegration that may negatively affect usual patterns of synchronous activity constituting adaptive integrative functions of consciousness. On the other hand, mental integration based on self-awareness and insight may significantly increase information integration and directly influence neural mechanisms underlying basic pathophysiological processes in schizophrenia.

Decoding Advances in Psychiatric Genetics: A Focus on Neural Circuits in Rodent Models

Appropriately powered genome-wide association studies combined with deep-sequencing technologies offer the prospect of real progress in revealing the complex biological underpinnings of schizophrenia and other psychiatric disorders. Meanwhile, recent developments in genome engineering, including CRISPR, constitute better tools to move forward with investigating these genetic leads. This review aims to assess how these advances can inform the development of animal models for psychiatric disease, with a focus on schizophrenia and in vivo electrophysiological circuit-level measures with high potential as disease biomarkers.

Delta frequency optogenetic stimulation of the thalamic nucleus reuniens is sufficient to produce working memory deficits: relevance to schizophrenia

BACKGROUND

Low-frequency (delta/theta) oscillations in the thalamocortical system are elevated in schizophrenia during wakefulness and are also induced in the N-methyl-D-asparate receptor hypofunction rat model. To determine whether abnormal delta oscillations might produce functional deficits, we used optogenetic methods in awake rats. We illuminated channelrhodopsin-2 in the thalamic nucleus reuniens (RE) at delta frequency and measured the effect on working memory (WM) performance (the RE is involved in WM, a process affected in schizophrenia [SZ]).

METHODS

We injected RE with adeno-associated virus to transduce cells with channelrhodopsin-2. An optical fiber was implanted just dorsal to the hippocampus in order to illuminate RE axon terminals.

RESULTS

During optogenetic delta frequency stimulation, rats displayed a strong WM deficit. On the following day, performance was normal if illumination was omitted.

CONCLUSIONS

The optogenetic experiments show that delta frequency stimulation of a thalamic nucleus is sufficient to produce deficits in WM. This result supports the hypothesis that delta frequency bursting in particular thalamic nuclei has a causal role in producing WM deficits in SZ. The action potentials in these bursts may "jam" communication through the thalamus, thereby interfering with behaviors dependent on WM. Studies in thalamic slices using the N-methyl-D-asparate receptor hypofunction model show that delta frequency bursting is dependent on T-type Ca(2+) channels, a result that we confirmed here in vivo. These channels, which are strongly implicated in SZ by genome-wide association studies, may thus be a therapeutic target for treatment of SZ.

Multivariate genetic determinants of EEG oscillations in schizophrenia and psychotic bipolar disorder from the BSNIP study

Schizophrenia (SZ) and psychotic bipolar disorder (PBP) are disabling psychiatric illnesses with complex and unclear etiologies. Electroencephalogram (EEG) oscillatory abnormalities in SZ and PBP probands are heritable and expressed in their relatives, but the neurobiology and genetic factors mediating these abnormalities in the psychosis dimension of either disorder are less explored. We examined the polygenic architecture of eyes-open resting state EEG frequency activity (intrinsic frequency) from 64 channels in 105 SZ, 145 PBP probands and 56 healthy controls (HCs) from the multisite BSNIP (Bipolar-Schizophrenia Network on Intermediate Phenotypes) study. One million single-nucleotide polymorphisms (SNPs) were derived from DNA. We assessed eight data-driven EEG frequency activity derived from group-independent component analysis (ICA) in conjunction with a reduced subset of 10,422 SNPs through novel multivariate association using parallel ICA (para-ICA). Genes contributing to the association were examined collectively using pathway analysis tools. Para-ICA extracted five frequency and nine SNP components, of which theta and delta activities were significantly correlated with two different gene components, comprising genes participating extensively in brain development, neurogenesis and synaptogenesis. Delta and theta abnormality was present in both SZ and PBP, while theta differed between the two disorders. Theta abnormalities were also mediated by gene clusters involved in glutamic acid pathways, cadherin and synaptic contact-based cell adhesion processes. Our data suggest plausible multifactorial genetic networks, including novel and several previously identified (DISC1) candidate risk genes, mediating low frequency delta and theta abnormalities in psychoses. The gene clusters were enriched for biological properties affecting neural circuitry and involved in brain function and/or development.

Cortical parvalbumin and somatostatin GABA neurons express distinct endogenous modulators of nicotinic acetylcholine receptors

BACKGROUND

Inhibition from GABAergic interneurons in brain circuits is a critical component of cognitive function. This inhibition is regulated through a diverse network of neuromodulation. A number of recent studies suggest that one of the major regulators of interneuron function is nicotinic acetylcholinergic transmission and dysregulation of both systems is common in psychiatric conditions. However, how nicotinic modulation impacts specific subpopulations of diverse GABAergic interneurons remains in question. One potential way of conferring specificity to the convergence of GABAergic and nicotinic signaling is through the expression of a unique family of nicotinic acetycholine receptor modulators, the Lynx family. The present study sought to identify members of the Lynx family enriched in cortical interneurons and to elucidate subpopulations of GABAergic neurons that express unique nicotinic modulators.

RESULTS

We utilize double fluorescence in situ hybridization to examine the interneuronal expression of the Lynx family in adult mouse visual cortex. We find that two of the Lynx family members, Lynx1 and Lypd6, are enriched in interneuron populations in cortex. Nearly all parvalbumin interneurons express Lynx1 but we did not detect Lypd6 in this population. Conversely, in somatostatin interneurons Lypd6 was found in a subset localized to deep cortical layers but no somatostatin neurons show detectable levels of Lynx1. Using a combination of genetic and viral manipulations we further show that a subpopulation of deep-layer cortico-cortical long-range somatostatin neurons also express Lypd6.

CONCLUSIONS

This work shows that distinct subpopulations of GABAergic interneurons express unique Lynx family members. The pattern of expression of Lynx family members within interneurons places them in a unique position to potentially regulate the convergence of GABAergic and nicotinic systems, dysfunction of which are characteristic of psychiatric disorders.

Losing your inhibition: linking cortical GABAergic interneurons to schizophrenia

GABAergic interneurons of the cerebral cortex (cINs) play crucial roles in many aspects of cortical function. The diverse types of cINs are classified into subgroups according to their morphology, intrinsic physiology, neurochemical markers and synaptic targeting. Recent advances in mouse genetics, imaging and electrophysiology techniques have greatly advanced our efforts to understand the role of normal cIN function and its dysfunction in neuropsychiatric disorders. In schizophrenia (SCZ), a wealth of data suggests that cIN function is perturbed, and that interneuron dysfunction may underlie key symptoms of the disease. In this review, we discuss the link between cINs and SCZ, focusing on the evidence for GABAergic signaling deficits from both SCZ patients and mouse models.

Hierarchical organization of gamma and theta oscillatory dynamics in schizophrenia

BACKGROUND

Schizophrenia patients have deficits across a broad range of important cognitive and clinical domains. Synchronization of oscillations in the gamma frequency range (~40 Hz) is associated with many normal cognitive functions and underlies at least some of the deficits observed in schizophrenia patients. Recent studies have demonstrated that gamma oscillations are modulated by the phase of theta waves, and this cross-frequency coupling indicates that a complex and hierarchical organization governs neural oscillatory dynamics. The aims of the present study were to determine if schizophrenia patients have abnormalities in the amplitude, synchrony, and cross-frequency coupling of gamma and theta oscillations in response to gamma-frequency steady-state stimulation and if abnormal neural oscillatory dynamics are associated with cognitive deficits in schizophrenia.

METHODS

Schizophrenia patients (n = 234) and healthy control subjects (n = 188) underwent electroencephalography testing in response to 40-Hz auditory steady-state stimulation. Cognitive functions were assessed with a battery of neuropsychological tests.

RESULTS

Schizophrenia patients had significantly reduced gamma intertrial phase coherence, increased theta amplitude, and intact cross-frequency coupling relative to healthy control subjects. In schizophrenia patients, increased theta amplitude was associated with poor verbal memory performance.

CONCLUSIONS

Results suggest that schizophrenia patients have specific alterations in both gamma and theta oscillations, but these deficits occur in the context of an intact hierarchical organization of their cross-frequency modulation in response to 40-Hz steady-state stimulation. Cortical oscillatory dynamics may be useful for understanding the neural mechanisms that underlie the disparate cognitive and functional impairments of schizophrenia.

Post traumatic stress disorder, neuroscience, and the law

Post-Traumatic Stress Disorder (PTSD) is a complex psychiatric condition, the effects of which can be seriously debilitating. As it originates from a specific traumatic event, it often impacts soldiers and victims of violent crime. It is currently one of the most frequently litigated mental diseases. Neuroscience is slowly discovering the neural bases of PTSD and other psychiatric ailments and is building tests to distinguish actual patients from non-suffering individuals. We examine the current state of neuroscientific research on PTSD and its biomarkers, focusing on a recent experiment by Apostolos Georgopoulos and coworkers. Then we analyze the legal consequences of these scientific advances, both in civil and criminal law, from a comparative perspective. Neuro-technology is likely to provide courts with a new kind of evidence, which will not replace but add to older behavioral evidence. Furthermore, it will weaken the so far standing distinction between physical and emotional harm. However, even extremely sensitive tests (>95%) can have insufficient accuracy if the prevalence of a condition in the tested population is low. Therefore, the law ought to take into account the prevalence of PTSD and other psychiatric conditions when the decision whether to admit neuro-evidence in courts or not is made.

Circuits and brain rhythms in schizophrenia: a wealth of convergent targets

Few common neurological illnesses trace back to single molecular disturbances. Many disparate putative causes may co-associate with a single disease state. However, uncovering functional, hierarchical networks of underlying mechanisms can provide a framework in which many primary pathologies converge on more complex, single higher level correlates of disease. This article focuses on cognitive deficits associated with schizophrenia to illustrate: a) How non-invasive EEG biomarkers of cognitive function constitute such a 'higher level correlate' of underlying pathologies. b) How derangement of multiple, cell-specific, molecular processes can converge on such EEG-visible, correlates of disrupted cognitive function. This approach suggests that evidence-based design of multi-target therapies may take advantage of hierarchical patterns of convergence to improve both efficacy and selectivity of disease-intervention.

Excitation, inhibition, local oscillations, or large-scale loops: what causes the symptoms of schizophrenia?

What causes the positive, negative, and cognitive symptoms of schizophrenia? The importance of circuits is underscored by the finding that no single gene contributes strongly to the disease. Thus, some circuit abnormality to which many proteins can contribute is the likely cause. There are several major hypotheses regarding the circuitry involved: first, a change in the balance of excitation/inhibition in the prefrontal cortex (PFC); second, abnormal EEG oscillations in the gamma range; third, an increase in theta/delta EEG power related to changes in the thalamus (particularly midline nuclei); fourth, hyperactivity in the hippocampus and consequent dopamine hyperfunction; and fifth, deficits in corollary discharge. Evidence for these hypotheses will be reviewed.

Imaging of thalamocortical dysrhythmia in neuropsychiatry

Abnormal brain activity dynamics, in the sense of a thalamocortical dysrhythmia (TCD), has been proposed as the underlying mechanism for a subset of disorders that bridge the traditional delineations of neurology and neuropsychiatry. In order to test this proposal from a psychiatric perspective, a study using magnetoencephalography (MEG) was implemented in subjects with schizophrenic spectrum disorder (n = 14), obsessive–compulsive disorder (n = 10), or depressive disorder (n = 5) and in control individuals (n = 18). Detailed CNS electrophysiological analysis of these patients, using MEG, revealed the presence of abnormal theta range spectral power with typical TCD characteristics, in all cases. The use of independent component analysis and minimum-norm-based methods localized such TCD to ventromedial prefrontal and temporal cortices. The observed mode of oscillation was spectrally equivalent but spatially distinct from that of TCD observed in other related disorders, including Parkinson's disease, central tinnitus, neuropathic pain, and autism. The present results indicate that the functional basis for much of these pathologies may relate most fundamentally to the category of calcium channelopathies and serve as a model for the cellular substrate for low-frequency oscillations present in these psychiatric disorders, providing a basis for therapeutic strategies.

High vs low frequency neural oscillations in schizophrenia

There is growing recognition that neural oscillations are important in a wide range of perceptual and cognitive functions. One of the key issues in electrophysiological studies of schizophrenia is whether high or low frequency oscillations, or both, are related to schizophrenia because many brain functions are modulated with frequency specificities. Many recent electrophysiological studies of schizophrenia have focused on high frequency oscillations at gamma band and in general support gamma band dysfunction in schizophrenia. We discuss the concept that gamma oscillation abnormalities in schizophrenia often occur in the background of oscillation abnormalities of lower frequencies. The review discusses the basic neurobiology for the emergence of oscillations of all frequency bands in association with networks of inhibitory interneurons and the convergence and divergence of such mechanisms in generating high vs low frequency oscillations. We then review the literature of oscillatory frequency abnormalities identified in each frequency band in schizophrenia. By describing some of the key functional roles exerted by gamma, low frequencies, and their cross-frequency coupling, we conceptualize that even isolated alterations in gamma or low frequency oscillations may impact the interactions of high and low frequency bands that are involved in key cognitive functions. The review concludes that studying the full spectrum and the interaction of gamma and low frequency oscillations may be critical for deciphering the complex electrophysiological abnormalities observed in schizophrenia patients.