Abnormal Spontaneous Gamma Power Is Associated With Verbal Learning and Memory Dysfunction in Schizophrenia

White matter microstructural integrity as a key to effective propagation of gamma entrainment in humans

Gamma entrainment through sensory stimulation has the potential to reduce the pathology of Alzheimer's disease in mouse models. However, clinical trials in Alzheimer's disease (AD) patients have yielded inconsistent results, necessitating further investigation. This single-center pre-post intervention study aims to explore the influence of white matter microstructural integrity on gamma rhythm propagation from the visual cortex to AD-affected regions in 31 cognitively normal volunteers aged ≥ 65. Gamma rhythm propagation induced by optimal FLS was measured. Diffusion tensor imaging was employed to assess the integrity of white matter tracts of interest. After excluding 5 participants with a deficit in steady-state visually evoked potentials, 26 participants were included in the final analysis. In the linear regression analyses, gamma entrainment was identified as a significant predictor of gamma propagation (p < 0.001). Furthermore, the study identified white matter microstructural integrity as a significant predictor of gamma propagation by flickering light stimulation (p < 0.05), which was specific to tracts that connect occipital and temporal or frontal regions. These findings indicate that, despite robust entrainment of gamma rhythms in the visual cortex, their propagation to other regions may be impaired if the microstructural integrity of the white matter tracts connecting the visual cortex to other areas is compromised. Consequently, our findings have expanded our understanding of the prerequisites for effective gamma entrainment and suggest that future clinical trials utilizing visual stimulation for gamma entrainment should consider white matter tract microstructural integrity for candidate selection and outcome analysis.

Therapeutic potential of gamma entrainment using sensory stimulation for cognitive symptoms associated with schizophrenia

Schizophrenia is a complex neuropsychiatric disorder with significant morbidity. Treatment options that address the spectrum of symptoms are limited, highlighting the need for innovative therapeutic approaches. Gamma Entrainment Using Sensory Stimulation (GENUS) is an emerging treatment for neuropsychiatric disorders that uses sensory stimulation to entrain impaired oscillatory network activity and restore brain function. Aberrant oscillatory activity often underlies the symptoms experienced by patients with schizophrenia. We propose that GENUS has therapeutic potential for schizophrenia. This paper reviews the current status of schizophrenia treatment and explores the use of sensory stimulation as an adjunctive treatment, specifically through gamma entrainment. Impaired gamma frequency entrainment is observed in patients, particularly in response to auditory and visual stimuli. Thus, sensory stimulation, such as music listening, may have therapeutic potential for individuals with schizophrenia. GENUS holds novel therapeutic potential to improve the lives of individuals with schizophrenia, but further research is required to determine the efficacy of GENUS, optimize its delivery and therapeutic window, and develop strategies for its implementation in specific patient populations.

Assessment of memory deficits in psychiatric disorders: A systematic literature review

Memory deficits are observed across psychiatric disorders ranging from the prodrome of psychosis to common mental disorders such as anxiety, depression, and dissociative disorders. Memory deficits among patients recovering from psychiatric disorders could be directly related to the primary illness or secondary to the adverse effect of a treatment such as Electroconvulsive Therapy (ECT). The trouble in the meaningful integration of working-memory and episodic memory is the most commonly affected domain that requires routine assessments. An update on the recent trends of methods of assessment of memory deficits is the first step towards understanding and correcting these deficits to target optimum recovery. A systematic literature search was conducted from October 2018 to October 2022 to review the recent methods of assessment of memory deficits in psychiatric disorders. The definition of 'Memory deficit' was operationalized as 'selective processes of memory, commonly required for activities of daily living, and affected among psychiatric disorders resulting in subjective distress and dysfunction'. We included 110 studies, most of them being conducted in western countries on patients with schizophrenia. Other disorders included dementia and mild cognitive impairment. Brief Assessment of Cognition in Schizophrenia, Cambridge Automated Neuropsychological Test Battery, California Verbal Learning Test, Trail Making Test Part A and B, Rey Auditory Verbal Learning Test, Wechsler Memory Scale, Wechsler Adults Intelligence Scale-IV were the most common neuropsychological assessments used. Mini-Mental State Examination and Montreal Cognitive Assessment were the most common bedside assessment tools used while Squire Subjective Memory Questionnaire was commonly used to measure ECT-related memory deficits. The review highlights the recent developments in the field of assessment of memory deficits in psychiatric disorders. Findings recommend and emphasize routine assessment of memory deficits among psychiatric disorders in developing countries especially severe mental illnesses. It remains interesting to see the role of standardized assessments in diagnostic systems given more than a decade of research on memory deficits in psychiatric disorders.

Rodents' visual gamma as a biomarker of pathological neural conditions

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

Gamma Oscillations and Potassium Channel Modulation in Schizophrenia: Targeting GABAergic Dysfunction

Impairments in gamma-aminobutyric acid (GABAergic) interneuron function lead to gamma power abnormalities and are thought to underlie symptoms in people with schizophrenia. Voltage-gated potassium 3.1 (Kv3.1) and 3.2 (Kv3.2) channels on GABAergic interneurons are critical to the generation of gamma oscillations suggesting that targeting Kv3.1/3.2 could augment GABAergic function and modulate gamma oscillation generation. Here, we studied the effect of a novel potassium Kv3.1/3.2 channel modulator, AUT00206, on resting state frontal gamma power in people with schizophrenia. We found a significant positive correlation between frontal resting gamma (35-45 Hz) power (n = 22, r = 0.613, P < .002) and positive and negative syndrome scale (PANSS) positive symptom severity. We also found a significant reduction in frontal gamma power (t13 = 3.635, P = .003) from baseline in patients who received AUT00206. This provides initial evidence that the Kv3.1/3.2 potassium channel modulator, AUT00206, may address gamma oscillation abnormalities in schizophrenia.

Use of Quantitative Electroencephalography to Inform Age- and Sex-Related Differences in NMDA Receptor Function Following MK-801 Administration

Sex- and age-related differences in symptom prevalence and severity have been widely reported in patients with schizophrenia, yet the underlying mechanisms contributing to these differences are not well understood. N-methyl-D-aspartate (NMDA) receptor hypofunction contributes to schizophrenia pathology, and preclinical models often use NMDA receptor antagonists, including MK-801, to model all symptom clusters. Quantitative electroencephalography (qEEG) represents a translational approach to measure neuronal activity, identify targetable biomarkers in neuropsychiatric disorders and evaluate possible treatments. Abnormalities in gamma power have been reported in patients with schizophrenia and correspond to psychosis and cognitive impairment. Further, as gamma power reflects cortical glutamate and GABA signaling, it is highly sensitive to changes in NMDA receptor function, and NMDA receptor antagonists aberrantly increase gamma power in rodents and humans. To evaluate the role of sex and age on NMDA receptor function, MK-801 (0.03-0.3 mg/kg, SC) was administered to 3- and 9-month-old male and female Sprague-Dawley rats that were implanted with wireless EEG transmitters to measure cortical brain function. MK-801-induced elevations in gamma power were observed in 3-month-old male and female and 9-month-old male rats. In contrast, 9-month-old female rats demonstrated blunted maximal elevations across a wide dose range. Importantly, MK-801-induced hyperlocomotor effects, a common behavioral screen used to examine antipsychotic-like activity, were similar across all groups. Overall, sex-by-age-related differences in gamma power support using qEEG as a translational tool to evaluate pathological progression and predict treatment response across a heterogeneous population.

Differential Effects of Aripiprazole on Electroencephalography-Recorded Gamma-Band Auditory Steady-State Response, Spontaneous Gamma Oscillations and Behavior in a Schizophrenia Rat Model

The available antipsychotics for schizophrenia (SZ) only reduce positive symptoms and do not significantly modify SZ neurobiology. This has raised the question of the robustness and translational value of methods employed during drug development. Electroencephalography (EEG)-based measures like evoked and spontaneous gamma oscillations are considered robust translational biomarkers as they can be recorded in both patients and animal models to probe a key mechanism underlying all SZ symptoms: the excitation/inhibition imbalance mediated by N-methyl-D-aspartate receptor (NMDAr) hypofunction. Understanding the effects of commercialized atypical antipsychotics on such measures could therefore contribute to developing better therapies for SZ. Yet, the effects of such drugs on these EEG readouts are unknown. Here, we studied the effect of the atypical antipsychotic aripiprazole on the gamma-band auditory steady-state response (ASSR), spontaneous gamma oscillations and behavioral features in a SZ rat model induced by the NMDAr antagonist MK-801. Interestingly, we found that aripiprazole could not normalize MK-801-induced abnormalities in ASSR, spontaneous gamma oscillations or social interaction while it still improved MK-801-induced hyperactivity. Suggesting that aripiprazole is unable to normalize electrophysiological features underlying SZ symptoms, our results might explain aripiprazole's inefficacy towards the social interaction deficit in our model but also its limited efficacy against social symptoms in patients.

Brain-region-specific changes in neurons and glia and dysregulation of dopamine signaling in Grin2a mutant mice

A genetically valid animal model could transform our understanding of schizophrenia (SCZ) disease mechanisms. Rare heterozygous loss-of-function (LoF) mutations in GRIN2A, encoding a subunit of the NMDA receptor, greatly increase the risk of SCZ. By transcriptomic, proteomic, and behavioral analyses, we report that heterozygous Grin2a mutant mice show (1) large-scale gene expression changes across multiple brain regions and in neuronal (excitatory and inhibitory) and non-neuronal cells (astrocytes and oligodendrocytes), (2) evidence of hypoactivity in the prefrontal cortex (PFC) and hyperactivity in the hippocampus and striatum, (3) an elevated dopamine signaling in the striatum and hypersensitivity to amphetamine-induced hyperlocomotion (AIH), (4) altered cholesterol biosynthesis in astrocytes, (5) a reduction in glutamatergic receptor signaling proteins in the synapse, and (6) an aberrant locomotor pattern opposite of that induced by antipsychotic drugs. These findings reveal potential pathophysiologic mechanisms, provide support for both the "hypo-glutamate" and "hyper-dopamine" hypotheses of SCZ, and underscore the utility of Grin2a-deficient mice as a genetic model of SCZ.

Differential Effects of Clozapine and Haloperidol on the 40 Hz Auditory Steady State Response-mediated Phase Resetting in the Prefrontal Cortex of the Female Sprague Dawley Rat

BACKGROUND

Neural synchrony at gamma frequency (~40 Hz) is important for information processing and is disrupted in schizophrenia. From a drug development perspective, molecules that can improve local gamma synchrony are promising candidates for therapeutic development.

HYPOTHESIS

Given their differentiated clinical profile, clozapine, and haloperidol may have distinct effects on local gamma synchrony engendered by 40 Hz click trains, the so-called auditory steady-state response (ASSR).

STUDY DESIGN

Clozapine and haloperidol at doses known to mimic clinically relevant D2 receptor occupancy were evaluated using the ASSR in separate cohorts of female SD rats.

RESULTS

Clozapine (2.5-10 mg/kg, sc) robustly increased intertrial phase coherence (ITC), across all doses. Evoked response increased but less consistently. Background gamma activity, unrelated to the stimulus, showed a reduction at all doses. Closer scrutiny of the data indicated that clozapine accelerated gamma phase resetting. Thus, clozapine augmented auditory information processing in the gamma frequency range by reducing the background gamma, accelerating the gamma phase resetting and improving phase precision and signal power. Modest improvements in ITC were seen with Haloperidol (0.08 and 0.24 mg/kg, sc) without accelerating phase resetting. Evoked power was unaffected while background gamma was reduced at high doses only, which also caused catalepsy.

CONCLUSIONS

Using click-train evoked gamma synchrony as an index of local neural network function, we provide a plausible neurophysiological basis for the superior and differentiated profile of clozapine. These observations may provide a neurophysiological template for identifying new drug candidates with a therapeutic potential for treatment-resistant schizophrenia.

Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment

Cognitive deficits are a core feature of schizophrenia, account for much of the impaired functioning associated with the disorder and are not responsive to existing treatments. In this review, we first describe the clinical presentation and natural history of these deficits. We then consider aetiological factors, highlighting how a range of similar genetic and environmental factors are associated with both cognitive function and schizophrenia. We then review the pathophysiological mechanisms thought to underlie cognitive symptoms, including the role of dopamine, cholinergic signalling and the balance between GABAergic interneurons and glutamatergic pyramidal cells. Finally, we review the clinical management of cognitive impairments and candidate novel treatments.

Ketamine as a pharmacological tool for the preclinical study of memory deficit in schizophrenia

Schizophrenia is a serious neuropsychiatric disorder characterized by the presence of positive symptoms (hallucinations, delusions, and disorganization of thought and language), negative symptoms (abulia, alogia, and affective flattening), and cognitive impairment (attention deficit, impaired declarative memory, and deficits in social cognition). Dopaminergic hyperactivity seems to explain the positive symptoms, but it does not completely clarify the appearance of negative and cognitive clinical manifestations. Preclinical data have demonstrated that acute and subchronic treatment with NMDA receptor antagonists such as ketamine (KET) represents a useful model that resembles the schizophrenia symptomatology, including cognitive impairment. This latter has been explained as a hypofunction of NMDA receptors located on the GABA parvalbumin-positive interneurons (near to the cortical pyramidal cells), thus generating an imbalance between the inhibitory and excitatory activity in the corticomesolimbic circuits. The use of behavioral models to explore alterations in different domains of memory is vital to learn more about the neurobiological changes that underlie schizophrenia. Thus, to better understand the neurophysiological mechanisms involved in cognitive impairment related to schizophrenia, the purpose of this review is to analyze the most recent findings regarding the effect of KET administration on these processes.

Mouse mutants in schizophrenia risk genes GRIN2A and AKAP11 show EEG abnormalities in common with schizophrenia patients

Schizophrenia is a heterogeneous psychiatric disorder with a strong genetic basis, whose etiology and pathophysiology remain poorly understood. Exome sequencing studies have uncovered rare, loss-of-function variants that greatly increase risk of schizophrenia [1], including loss-of-function mutations in GRIN2A (aka GluN2A or NR2A, encoding the NMDA receptor subunit 2A) and AKAP11 (A-Kinase Anchoring Protein 11). AKAP11 and GRIN2A mutations are also associated with bipolar disorder [2], and epilepsy and developmental delay/intellectual disability [1, 3, 4], respectively. Accessible in both humans and rodents, electroencephalogram (EEG) recordings offer a window into brain activity and display abnormal features in schizophrenia patients. Does loss of Grin2a or Akap11 in mice also result in EEG abnormalities? We monitored EEG in heterozygous and homozygous knockout Grin2a and Akap11 mutant mice compared with their wild-type littermates, at 3- and 6-months of age, across the sleep/wake cycle and during auditory stimulation protocols. Grin2a and Akap11 mutants exhibited increased resting gamma power, attenuated auditory steady-state responses (ASSR) at gamma frequencies, and reduced responses to unexpected auditory stimuli during mismatch negativity (MMN) tests. Sleep spindle density was reduced in a gene dose-dependent manner in Akap11 mutants, whereas Grin2a mutants showed increased sleep spindle density. The EEG phenotypes of Grin2a and Akap11 mutant mice show a variety of abnormal features that overlap considerably with human schizophrenia patients, reflecting systems-level changes caused by Grin2a and Akap11 deficiency. These neurophysiologic findings further substantiate Grin2a and Akap11 mutants as genetic models of schizophrenia and identify potential biomarkers for stratification of schizophrenia patients.

The effect of ketamine and D-cycloserine on the high frequency resting EEG spectrum in humans

RATIONALE

Preclinical studies indicate that high-frequency oscillations, above 100 Hz (HFO:100-170 Hz), are a potential translatable biomarker for pharmacological studies, with the rapid acting antidepressant ketamine increasing both gamma (40-100 Hz) and HFO.

OBJECTIVES

To assess the effect of the uncompetitive NMDA antagonist ketamine, and of D-cycloserine (DCS), which acts at the glycine site on NMDA receptors on HFO in humans.

METHODS

We carried out a partially double-blind, 4-way crossover study in 24 healthy male volunteers. Each participant received an oral tablet and an intravenous infusion on each of four study days. The oral treatment was either DCS (250 mg or 1000 mg) or placebo. The infusion contained 0.5 mg/kg ketamine or saline placebo. The four study conditions were therefore placebo-placebo, 250 mg DCS-placebo, 1000 mg DCS-placebo, or placebo-ketamine.

RESULTS

Compared with placebo, frontal midline HFO magnitude was increased by ketamine (p = 0.00014) and 1000 mg DCS (p = 0.013). Frontal gamma magnitude was also increased by both these treatments. However, at a midline parietal location, only HFO were increased by DCS, and not gamma, whilst ketamine increased both gamma and HFO at this location. Ketamine induced psychomimetic effects, as measured by the PSI scale, whereas DCS did not increase the total PSI score. The perceptual distortion subscale scores correlated with the posterior low gamma to frontal high beta ratio.

CONCLUSIONS

Our results suggest that, at high doses, a partial NMDA agonist (DCS) has similar effects on fast neural oscillations as an NMDA antagonist (ketamine). As HFO were induced without psychomimetic effects, they may prove a useful drug development target.

Regulation of the E/I-balance by the neural matrisome

In the mammalian cortex a proper excitatory/inhibitory (E/I) balance is fundamental for cognitive functions. Especially γ-aminobutyric acid (GABA)-releasing interneurons regulate the activity of excitatory projection neurons which form the second main class of neurons in the cortex. During development, the maturation of fast-spiking parvalbumin-expressing interneurons goes along with the formation of net-like structures covering their soma and proximal dendrites. These so-called perineuronal nets (PNNs) represent a specialized form of the extracellular matrix (ECM, also designated as matrisome) that stabilize structural synapses but prevent the formation of new connections. Consequently, PNNs are highly involved in the regulation of the synaptic balance. Previous studies revealed that the formation of perineuronal nets is accompanied by an establishment of mature neuronal circuits and by a closure of critical windows of synaptic plasticity. Furthermore, it has been shown that PNNs differentially impinge the integrity of excitatory and inhibitory synapses. In various neurological and neuropsychiatric disorders alterations of PNNs were described and aroused more attention in the last years. The following review gives an update about the role of PNNs for the maturation of parvalbumin-expressing interneurons and summarizes recent findings about the impact of PNNs in different neurological and neuropsychiatric disorders like schizophrenia or epilepsy. A targeted manipulation of PNNs might provide an interesting new possibility to indirectly modulate the synaptic balance and the E/I ratio in pathological conditions.

The contribution of gamma bursting to spontaneous gamma activity in schizophrenia

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

Excitatory Dysfunction Drives Network and Calcium Handling Deficits in 16p11.2 Duplication Schizophrenia Induced Pluripotent Stem Cell-Derived Neurons

BACKGROUND

Schizophrenia (SCZ) is a debilitating psychiatric disorder with a large genetic contribution; however, its neurodevelopmental substrates remain largely unknown. Modeling pathogenic processes in SCZ using human induced pluripotent stem cell-derived neurons (iNs) has emerged as a promising strategy. Copy number variants confer high genetic risk for SCZ, with duplication of the 16p11.2 locus increasing the risk 14.5-fold.

METHODS

To dissect the contribution of induced excitatory neurons (iENs) versus GABAergic (gamma-aminobutyric acidergic) neurons (iGNs) to SCZ pathophysiology, we induced iNs from CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 isogenic and SCZ patient-derived induced pluripotent stem cells and analyzed SCZ-related phenotypes in iEN monocultures and iEN/iGN cocultures.

RESULTS

In iEN/iGN cocultures, neuronal firing and synchrony were reduced at later, but not earlier, stages of in vitro development. These were fully recapitulated in iEN monocultures, indicating a primary role for iENs. Moreover, isogenic iENs showed reduced dendrite length and deficits in calcium handling. iENs from 16p11.2 duplication-carrying patients with SCZ displayed overlapping deficits in network synchrony, dendrite outgrowth, and calcium handling. Transcriptomic analysis of both iEN cohorts revealed molecular markers of disease related to the glutamatergic synapse, neuroarchitecture, and calcium regulation.

CONCLUSIONS

Our results indicate the presence of 16p11.2 duplication-dependent alterations in SCZ patient-derived iENs. Transcriptomics and cellular phenotyping reveal overlap between isogenic and patient-derived iENs, suggesting a central role of glutamatergic, morphological, and calcium dysregulation in 16p11.2 duplication-mediated pathogenesis. Moreover, excitatory dysfunction during early neurodevelopment is implicated as the basis of SCZ pathogenesis in 16p11.2 duplication carriers. Our results support network synchrony and calcium handling as outcomes directly linked to this genetic risk variant.

Altered gamma oscillations and beta-gamma coupling in drug-naive first-episode major depressive disorder: Association with sleep and cognitive disturbance

OBJECTIVE

Gamma oscillations contribute to the pathogenesis mechanisms of major depressive disorder (MDD) have been proposed, but gamma activity is not well characterized. This study is the first attempt to investigate the altered gamma oscillations in first-episode MDD, particularly the beta-gamma coupling, and to determine the potential symptomatic relationship with the identified gamma dysregulation.

METHODS

Resting electroencephalography was recorded for 43 drug-naive first-episode MDD and 57 healthy control (HC) subjects. Integrated analysis of relative spectral power, weighted phase lag index, and phase-amplitude coupling (PAC) were utilized to reveal the alterations of gamma activities. Pearson's correlation was implemented to identify the relationship between altered gamma activities and the clinical depressive symptoms, which were categorized into four factors: anxiety somatization, retardation, cognitive disturbance, and sleep disturbance.

RESULTS

Compared with HC subjects, MDD patients showed not only significantly decreased gamma powers in the left temporal and the bilateral occipital regions but also weakened gamma connectivity between the left hemisphere and the right frontal region. Furthermore, attenuated beta-gamma PAC of MDD patients was observed in the left temporal regions. Importantly, the suppression of left occipital mid- and high gamma oscillations were negatively correlated with sleep disturbance, while the deficits in left temporal beta-mid-gamma PAC and beta-high gamma PAC showed negative correlations with cognitive disturbance.

LIMITATIONS

Important limitations are the small sample size and the possible inclusion of bipolar depression in the MDD group.

CONCLUSIONS

Our findings provide the first evidence that in first-episode MDD, aberrant gamma powers and beta-gamma coupling are associated with sleep and cognitive impairments, respectively, deepening our understanding of the physiological mechanisms underlying sleep and cognitive symptoms in first-episode MDD. Altered gamma oscillations emerge as promising biomarkers for diagnosing MDD.

Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review

Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.

Effects of the glycine transporter-1 inhibitor iclepertin (BI 425809) on sensory processing, neural network function, and cognition in animal models related to schizophrenia

N-methyl-D-aspartate (NMDA) receptor hypofunction leading to neural network dysfunction is thought to play an important role in the pathophysiology of cognitive impairment associated with schizophrenia (CIAS). Increasing extracellular concentrations of the NMDA receptor co-agonist glycine through inhibition of glycine transporter-1 (GlyT1) has the potential to treat CIAS by improving cortical network function through enhanced glutamatergic signaling. Indeed, the novel GlyT1 inhibitor iclepertin (BI 425809) improved cognition in a recent clinical study in patients with schizophrenia. The present study tested the ability of iclepertin to reverse MK-801-induced deficits in auditory sensory processing and cortical network function using electroencephalography (EEG) to measure auditory event-related potentials (AERP) and 40 Hz auditory steady-state response (ASSR). In addition, improvements in memory performance with iclepertin were evaluated using the T-maze spontaneous alternation test in MK-801-treated mice and the social recognition test in naïve rats. Iclepertin reversed MK-801-induced deficits in the AERP readouts N1 amplitude and N1 gating, as well as 40 Hz ASSR power and inter-trial coherence. Additionally, iclepertin significantly attenuated an MK-801-induced increase in basal gamma power. Furthermore, iclepertin reversed MK-801-induced working memory deficits in mice and improved social recognition memory performance in rats. Overall, this study demonstrates that inhibition of GlyT1 is sufficient to attenuate MK-801-induced deficits in translatable EEG parameters relevant to schizophrenia. Moreover, iclepertin showed memory-enhancing effects in rodent cognition tasks, further demonstrating the potential for GlyT1 inhibition to treat CIAS. Significance Statement Despite the significant patient burden caused by cognitive impairment associated with schizophrenia, there are currently no approved pharmacotherapies. In this preclinical study, the novel glycine transporter inhibitor iclepertin (BI 425809) reversed sensory processing deficits and neural network dysfunction evoked by inhibition of N-methyl-D-aspartate (NMDA) receptors, and enhanced working memory performance and social recognition in rodents. These findings support previous clinical evidence for the pro-cognitive effects of iclepertin.

Combination of Group Singular Value Decomposition and eLORETA Identifies Human EEG Networks and Responses to Transcranial Photobiomodulation

Transcranial Photobiomodulation (tPBM) has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram (EEG) networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm². In data processing, a novel methodology by combining group singular value decomposition (gSVD) with the exact low-resolution brain electromagnetic tomography (eLORETA) was implemented and performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components (PCs) projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band (delta, theta, alpha, beta and gamma) were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes.

High-power gamma-related delta phase alteration in schizophrenia patients at rest

AIM

Information processing is supported by the cortico-cortical transmission of neural oscillations across brain regions. Recent studies have demonstrated that the rhythmic firing of neural populations is not random but is governed by interactions with other frequency bands. Specifically, the amplitude of gamma-band oscillations is associated with the phase of lower frequency oscillations in support of short and long-range communications among networks. This cross-frequency relation is thought to reflect the temporal coordination of neural communication. While schizophrenia patients show abnormal oscillatory responses across multiple frequencies at rest, it is unclear whether the functional relationships among frequency bands are intact. This study aimed to characterize the lower frequency (delta/theta, 1-8 Hz) phase and the amplitude of gamma oscillations in healthy subjects and schizophrenia patients at rest.

METHODS

Low frequency-phase (delta- and theta- band) angles and gamma-band amplitude relationships were assessed in 142 schizophrenia patients and 128 healthy subjects.

RESULTS

Significant low-frequency phase alteration related to high-power gamma was detected across broadly distributed scalp regions in both healthy subjects and patients. In patients, delta phase synchronization related to high-power gamma was significantly decreased at the frontocentral, right middle temporal, and left temporoparietal electrodes but significantly increased at the left parietal electrode.

CONCLUSIONS

High-power gamma-related delta phase alteration may reflect a core pathophysiologic abnormality in schizophrenia. Data-driven measures of functional relationships among frequency bands may prove useful in the development of novel therapeutics. Future studies are needed to determine whether these alterations are specific to schizophrenia or appear in other neuropsychiatric patient populations.

Detection of Schizophrenia Cases From Healthy Controls With Combination of Neurocognitive and Electrophysiological Features

BACKGROUND

The search for a method that utilizes biomarkers to identify patients with schizophrenia from healthy individuals has occupied researchers for decades. However, no single indicator can be employed to achieve the good in clinical practice. We aim to develop a comprehensive machine learning pipeline based on neurocognitive and electrophysiological combined features for distinguishing schizophrenia patients from healthy people.

METHODS

In the present study, 69 patients with schizophrenia and 50 healthy controls participated. Neurocognitive (contains seven specific domains of cognition) and electrophysiological [prepulse inhibition, electroencephalography (EEG) power spectrum, detrended fluctuation analysis, and fractal dimension (FD)] features were collected, all these features were taken together to generate the identification models of schizophrenia by applying logistics, random forest, and extreme gradient boosting algorithm. The classification capabilities of these models were also evaluated.

RESULTS

Both the neurocognitive and electrophysiological feature sets showed a good classification effect with the highest accuracy greater than 85% and AUC greater than 90%. Specifically, the performances of the combined neurocognitive and electrophysiological feature sets achieved the highest accuracy of 93.28% and AUC of 97.91%. The extreme gradient boosting algorithm as a whole presented more stably and precisely in classification efficiency.

CONCLUSION

The highest classification accuracy of 93.28% by combination of neurocognitive and electrophysiological features shows that both measurements are appropriate indicators to be used in discriminating schizophrenia patients and healthy individuals. Also, among three algorithms, extreme gradient boosting had better classified performances than logistics and random forest algorithms.

Benefits in Alzheimer's Disease of Sensory and Multisensory Stimulation

Alzheimer's disease (AD) is a serious neurodegenerative disease, which seriously affects the behavior, cognition, and memory of patients. Studies have shown that sensory stimulation can effectively improve the cognition and memory of AD patients, and its role in brain plasticity and neural regulation is initially revealed. This paper aims to review the effect of various sensory stimulation and multisensory stimulation for AD, and to explain the possible mechanism, so as to provide some new ideas for further research in this field. We searched the Web of Science and PubMed databases (from 2000 to October 27, 2020) for literature on the treatment of AD with sensory and multisensory stimulation, including music therapy, aromatherapy, rhythmic (e.g., visual or acoustic) stimulation, light therapy, multisensory stimulation, and virtual reality assisted therapy, then conducted a systematic analysis. Results show these sensory and multisensory stimulations can effectively ameliorate the pathology of AD, arouse memory, and improve cognition and behaviors. What's more, it can cause brain nerve oscillation, enhance brain plasticity, and regulate regional cerebral blood flow. Sensory and multisensory stimulation are very promising therapeutic methods, and they play an important role in the improvement and treatment of AD, but their potential mechanism and stimulation parameters need to be explored and improved.

Abnormal phase discontinuity of alpha- and theta-frequency oscillations in schizophrenia

BACKGROUND

Schizophrenia patients have abnormal electroencephalographic (EEG) power over multiple frequency bands, even at rest, though the primary neural generators and spatiotemporal dynamics of these abnormalities are largely unknown. Disturbances in the precise synchronization of oscillations within and across cortical sources may underlie abnormal resting-state EEG activity in schizophrenia patients.

METHODS

A novel assessment method was applied to identify the independent contributing sources of resting-state EEG and assess the phase discontinuity in schizophrenia patients (N = 148) and healthy subjects (N = 143).

RESULTS

A network of 11 primary contributing sources of scalp EEG was identified in both groups. Schizophrenia patients showed abnormal elevations of EEG power in the temporal region in the theta, beta, and gamma-bands, as well as the posterior cingulate gyrus in the delta, theta, alpha, and beta-bands. The higher theta-band power in the middle temporal gyrus was significantly correlated with verbal memory impairment in patients. The peak frequency of alpha was lower in patients in the cingulate and temporal regions. Furthermore, patients showed a higher rate of alpha phase discontinuity in the temporal region as well as a lower rate of theta phase discontinuity in the temporal and posterior cingulate regions.

CONCLUSIONS

Abnormal rates of phase discontinuity of alpha- and theta-band, abnormal elevations of EEG power in multiple bands, and a lower peak frequency of alpha were identified in schizophrenia patients at rest. Clarification of the mechanistic substrates of abnormal phase discontinuity may clarify core pathophysiologic abnormalities of schizophrenia and contribute to the development of novel biomarkers for therapeutic interventions.

A Comprehensive Review of Computer-Aided Diagnosis of Major Mental and Neurological Disorders and Suicide: A Biostatistical Perspective on Data Mining

The World Health Organization (WHO) suggests that mental disorders, neurological disorders, and suicide are growing causes of morbidity. Depressive disorders, schizophrenia, bipolar disorder, Alzheimer's disease, and other dementias account for 1.84%, 0.60%, 0.33%, and 1.00% of total Disability Adjusted Life Years (DALYs). Furthermore, suicide, the 15th leading cause of death worldwide, could be linked to mental disorders. More than 68 computer-aided diagnosis (CAD) methods published in peer-reviewed journals from 2016 to 2021 were analyzed, among which 75% were published in the year 2018 or later. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was adopted to select the relevant studies. In addition to the gold standard, the sample size, neuroimaging techniques or biomarkers, validation frameworks, the classifiers, and the performance indices were analyzed. We further discussed how various performance indices are essential based on the biostatistical and data mining perspective. Moreover, critical information related to the Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines was analyzed. We discussed how balancing the dataset and not using external validation could hinder the generalization of the CAD methods. We provided the list of the critical issues to consider in such studies.

Do NMDA-R antagonists re-create patterns of spontaneous gamma-band activity in schizophrenia? A systematic review and perspective

NMDA-R hypofunctioninig is a core pathophysiological mechanism in schizophrenia. However, it is unclear whether the physiological changes observed following NMDA-R antagonist administration are consistent with gamma-band alterations in schizophrenia. This systematic review examined the effects of NMDA-R antagonists on the amplitude of spontaneous gamma-band activity and functional connectivity obtained from preclinical (n = 24) and human (n = 9) studies and compared these data to resting-state EEG/MEG-measurements in schizophrenia patients (n = 27). Overall, the majority of preclinical and human studies observed increased gamma-band power following acute administration of NMDA-R antagonists. However, the direction of gamma-band power alterations in schizophrenia were inconsistent, which involved upregulation (n = 10), decreases (n = 7), and no changes (n = 8) in spectral power. Five out of 6 preclinical studies observed increased connectivity, while in healthy controls receiving Ketamine and in schizophrenia patients the direction of connectivity results was also inconsistent. Accordingly, the effects of NMDA-R hypofunctioning on gamma-band oscillations are different than pathophysiological signatures observed in schizophrenia. The implications of these findings for current E/I balance models of schizophrenia are discussed.

Gamma oscillations predict pro-cognitive and clinical response to auditory-based cognitive training in schizophrenia

Cognitive impairments are pervasive and disabling features of schizophrenia. Targeted cognitive training (TCT) is a "bottom-up" cognitive remediation intervention with efficacy for neurocognitive outcomes in schizophrenia, yet individual responses are variable. Gamma oscillatory measures are leading candidate biomarkers in the development of biologically informed pro-cognitive therapeutics. Forty-two schizophrenia patients were recruited from a long-term residential treatment facility. Participants were randomized to receive either 1 h of cognitive training (TCT, n = 21) or computer games (TAU, n = 21). All participants received standard-of-care treatment; the TCT group additionally completed 30 h of cognitive training. The auditory steady-state response paradigm was used to elicit gamma oscillatory power and synchrony during electroencephalogram recordings. Detailed clinical and cognitive assessments were collected at baseline and after completion of the study. Baseline gamma power predicted cognitive gains after a full course of TCT (MCCB, R² = 0.31). A change in gamma power after 1-h TCT exposure predicted improvement in both positive (SAPS, R² = 0.40) and negative (SANS, R² = 0.30) symptoms. These relationships were not observed in the TAU group (MCCB, SAPS, and SANS, all R² < 0.06). The results indicate that the capacity to support gamma oscillations, as well as the plasticity of the underlying ASSR circuitry after acute exposure to 1 h of TCT, reflect neural mechanisms underlying the efficacy of TCT, and may be used to predict individualized treatment outcomes. These findings suggest that gamma oscillatory biomarkers applied within the context of experimental medicine designs can be used to personalize individual treatment options for pro-cognitive interventions in patients with schizophrenia.

Neurophysiologic Characterization of Resting State Connectivity Abnormalities in Schizophrenia Patients

Background: Patients with schizophrenia show abnormal spontaneous oscillatory activity in scalp-level electroencephalographic (EEG) responses across multiple frequency bands. While oscillations play an essential role in the transmission of information across neural networks, few studies have assessed the frequency-specific dynamics across cortical source networks at rest. Identification of the neural sources and their dynamic interactions may improve our understanding of core pathophysiologic abnormalities associated with the neuropsychiatric disorders. Methods: A novel multivector autoregressive modeling approach for assessing effective connectivity among cortical sources was developed and applied to resting-state EEG recordings obtained from n = 139 schizophrenia patients and n = 126 healthy comparison subjects. Results: Two primary abnormalities in resting-state networks were detected in schizophrenia patients. The first network involved the middle frontal and fusiform gyri and a region near the calcarine sulcus. The second network involved the cingulate gyrus and the Rolandic operculum (a region that includes the auditory cortex). Conclusions: Schizophrenia patients show widespread patterns of hyper-connectivity across a distributed network of the frontal, temporal, and occipital brain regions. Results highlight a novel approach for characterizing alterations in connectivity in the neuropsychiatric patient populations. Further mechanistic characterization of network functioning is needed to clarify the pathophysiology of neuropsychiatric and neurological diseases.