Theta-phase gamma-amplitude coupling as a neurophysiological marker in neuroleptic-naïve schizophrenia

High-Gamma Activity Is Coupled to Low-Gamma Oscillations in Precentral Cortices and Modulates with Movement and Speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger-flexion or word-reading tasks. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger movements or speaking words aloud. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Early adolescent psychological distress and cognition, correlates of resting-state EEG, interregional phase-amplitude coupling

Delineating neurobiological markers of youth mental health is crucial for early identification and treatment. One promising marker is phase-amplitude coupling (PAC), cross-frequency coupling between the phase of slower oscillatory activity and the amplitude of faster oscillatory activity in the brain. Prior research has demonstrated that PAC is associated with both cognition and mental health and can be modulated using neurostimulation. However, to date research investigating PAC has focused primarily on adults, and only within-region theta-gamma coupling in the context of mental health. We investigated associations between interregional resting-state PAC (posterior-anterior cortex), and cognition and psychological distress in N = 77 (M_age = 12.58 years, SD = 0.31; 51 % female) 12-year-olds. Firstly, while left theta-beta PAC showed a moderate positive correlation (r = 0.529, p < .01), right theta-gamma PAC showed a weak positive correlation, with psychological distress (r = 0.283, p < .05). In terms of cognition, moderate correlations were observed between: (i) increased left theta-beta PAC and increased psychomotor speed (r = -0.367, p < .05); (ii) increased left alpha-beta PAC and decreased attention (r = 0.355, p ≤0.01); and (iii) increased left alpha-beta PAC and decreased verbal learning and memory (r = -0.352, p < .01). Whereas weak associations were observed for: (i) increased left alpha-beta PAC and decreased executive functioning scores (r = 0.284, p < .05); and (ii) increased left alpha-gamma PAC and increased attention (r = -0.272, p < .05). The overall findings of this exploratory study are encouraging, although all the correlations were in the weak-to-moderate range and require replication. Further research may confirm interregional resting-state PAC as a biomarker that can help us better understand the link between mental health and cognition in adolescents and improve treatment of cognitive related deficits in mental illness.

Hippocampal-prefrontal theta coupling develops as mice become proficient in associative odorant discrimination learning

Learning and memory requires coordinated activity between different regions of the brain. Here we studied the interaction between infralimbic medial prefrontal cortex (mPFC) and hippocampal dorsal CA1 during associative odorant discrimination learning in the mouse. We found that as the animal learns to discriminate odorants in a go-no go task, the coupling of high frequency neural oscillations to the phase of theta oscillations (theta-referenced phase-amplitude coupling or tPAC) changes in a manner that results in divergence between rewarded and unrewarded odorant-elicited changes in the theta-phase referenced power (tPRP) for beta and gamma oscillations. In addition, in the proficient animal there was a decrease in the coordinated oscillatory activity between CA1 and mPFC in the presence of the unrewarded odorant. Furthermore, the changes in tPAC resulted in a marked increase in the accuracy for decoding contextual odorant identity from tPRP when the animal became proficient. Finally, we studied the role of Ca2+/calmodulin-dependent protein kinase II α (CaMKIIα), a protein involved in learning and memory, in oscillatory neural processing in this task. We find that the accuracy for decoding the contextual odorant identity from tPRP decreases in CaMKIIα knockout mice and that this accuracy correlates with behavioral performance. These results implicate a role for tPAC and CaMKIIα in olfactory go-no go associative learning in the hippocampal-prefrontal circuit.Significance statementCoupling of neural oscillations within and between hippocampal CA1 and medial prefrontal cortex (mPFC) is involved in spatial learning and memory, but the role of oscillation coupling for other learning tasks is not well understood. Here we performed local field potential recording in CA1 and mPFC in mice learning to differentiate rewarded from unrewarded odorants in an associative learning task. We find that odorant-elicited changes in the power of bursts of gamma oscillations at distinct phases of theta oscillations become divergent as the animal becomes proficient allowing decoding of contextual odorant identity. Finally, we find that the accuracy to decode contextual odorant identity decreases in mice deficient for the expression of Ca2+/calmodulin-dependent protein kinase II α, a protein involved in synaptic plasticity.

Phase-Amplitude Coupling Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder

In cognitive neuroscience, there is an increasing interest in identifying and understanding the synchronization of distinct neural oscillations with different frequencies that might support dynamic communication within the brain. This study explored the cross-frequency phase-amplitude coupling brain network characteristics of resting-state electroencephalograms between 30 children with attention-deficit/hyperactivity disorder (ADHD) and 30 age-matched typically developing children. Compared with control group, children with ADHD show increased coupling intensity and altered distribution patterns of dominant paired channels, especially in the δ-γ_H, θ-γ_H, α-γ_H, β_L-γ_H, and β_H-γ_H coupling networks. Regarding graph theory properties, the characteristic path length, the mean clustering coefficient, the global efficiency, and the mean local efficiency significant difference in many cross-frequency coupling networks, especially in the δ-γ_H, θ-γ_H, α-γ_H, β_L-γ_H, and β_H-γ_H coupling networks. The area under the receiver operating characteristic curve (AUC) in low-frequency coupling with a high-gamma frequency was larger than that in coupling with low-gamma frequency (AUC values of δ-γ_L, θ-γ_L, α-γ_L, β_L-γ_L, β_H-γ_L, δ-γ_H, θ-γ_H, α-γ_H, β_L-γ_H, and β_H-γ_H were 0.794, 0.722, 0.666, 0.570, 0.881, 0.992, 0.998, 0.998, 0.989, and 0.974, respectively). These findings demonstrate altered coupling intensity and disrupted topological organization of coupling networks, support the altered brain network theory in children with ADHD. The coupling intensity and graph theory properties of low-frequency coupling with high-gamma frequency were promising resting-state electroencephalogram biomarkers of ADHD in children.

Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness

The Research Domain Criteria (RDoC) initiative challenges researchers to build neurobehavioral models of psychiatric illness with the hope that such models identify better targets that will yield more effective treatment. However, a guide for building such models was not provided and symptom heterogeneity within Diagnostic Statistical Manual categories has hampered progress in identifying endophenotypes that underlie mental illness. We propose that the best chance to discover viable biomarkers and treatment targets for psychiatric illness is to investigate a triangle of relationships: severity of a specific psychiatric symptom that correlates to mental activity that correlates to a neural activity signature. We propose that this is the minimal model complexity required to advance the field of psychiatry. With an understanding of how neural activity relates to the experience of the patient, a genuine understanding for how treatment imparts its therapeutic effect is possible. After the discovery of this three-fold relationship, causal testing is required in which the neural activity pattern is directly enhanced or suppressed to provide causal, instead of just correlational, evidence for the biomarker. We suggest using non-invasive brain stimulation (NIBS) as these techniques provide tools to precisely manipulate spatial and temporal activity patterns. We detail how this approach enabled the discovery of two orthogonal electroencephalography (EEG) activity patterns associated with anhedonia and anxiosomatic symptoms in depression that can serve as future treatment targets. Altogether, we propose a systematic approach for building neurobehavioral models for dimensional psychiatry.

Cross-frequency coupling in psychiatric disorders: A systematic review

Cross-frequency coupling (CFC), an electrophysiologically derived measure of oscillatory coupling in the brain, is believed to play a critical role in neuronal computation, learning and communication. It has received much recent attention in the study of both health and disease. We searched for literature that studied CFC during resting state and task-related activities during electroencephalography and magnetoencephalography in psychiatric disorders. Thirty-eight studies were identified, which included attention-deficit hyperactivity disorder, Alzheimer's dementia, autism spectrum disorder, bipolar disorder, depression, obsessive compulsive disorder, social anxiety disorder and schizophrenia. The systematic review was registered with PROSPERO (ID#CRD42021224188). The current review indicates measurable differences exist between CFC in disease states vs. healthy controls. There was variance in CFC at different regions of the brain within the same psychiatric disorders, perhaps this could be explained by the mechanisms and functionality of CFC. There was heterogeneity in methodologies used, which may lead to spurious CFC analyses. Going forward, standardized methodologies need to be established and utilized in further research to understand the neuropathophysiology associated with psychiatric disorders.

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.

Thalamocortical dysrhythmia in patients with schizophrenia spectrum disorder and individuals at clinical high risk for psychosis

Thalamocortical dysrhythmia (TCD) is a model characterized by abnormal resting-state thalamic oscillatory patterns where the alpha rhythm is replaced by cross-frequency coupling of low- and high-frequency rhythms. Although disrupted thalamic function is a suggested important pathophysiological mechanism underlying schizophrenia, knowledge regarding the TCD model in schizophrenia spectrum disorder (SSD) patients and individuals at clinical high risk (CHR) for psychosis is limited. A total of 169 SSD patients, 106 individuals at CHR for psychosis, and 105 healthy controls (HCs) underwent resting-state electroencephalography recordings. We performed mean global field power (MGFP) spectral analysis between 1 and 49 Hz as well as source-level theta phase-gamma amplitude coupling (TGC) analysis and compared resting-state oscillatory patterns across groups. Correlations between altered TGC values and psychotic symptom severity in the patient group were investigated. Spectral MGFP of low- and high-frequencies was larger in the SSD and CHR groups than in the HC group. The TGC of SSD patients was greater than that of HCs in the right frontal, right parietal, and left and right limbic lobes. Greater TGC in the right frontal and limbic lobes was associated with positive symptom severity in SSD patients. However, TGC in the CHR group was comparable to that in the HCs and was smaller than that in the SSD group in widespread cortical regions. The TCD pattern may be apparent after frank psychotic disorder onset in tandem with overt positive symptoms. A psychosis-risk state without overt psychotic symptoms could be characterized by abnormally increased low- and high-frequency activities with relatively preserved TGC.

Monocyte chemoattractant protein-1 levels are associated with major depressive disorder

OBJECTIVES

Major depressive disorder (MDD) is a distressing condition characterized by persistent low mood, loss of interest in daily activities. Researchers consider several biological, psycho-social, and genetic factors are involved in depression. The present study aimed to investigate the serum levels of monocyte chemoattractant protein-1 (MCP-1) in MDD patients to explore its role in depression.

METHODS

This case-control study recruited 114 MDD patients and 106 healthy controls (HCs) matched by age and gender. A specialized psychiatrist diagnosed the cases and evaluated the controls based on the diagnostic and statistical manual for mental disorders, 5th edition. We quantified serum MCP-1 levels using commercially available enzyme-linked immune sorbent assay kits. Also, we applied the Hamilton depression rating scale (Ham-D) to measure the severity of depression.

RESULTS

We observed the decreased levels of serum MCP-1 in MDD patients compared to HCs. Also, we obtained a significant negative correlation between serum MCP-1 levels and Ham-D scores. Moreover, female MDD patients with higher Ham-D scores exhibited lower serum MCP-1 levels. The receiver operating characteristic analysis demonstrated the good diagnostic value of MCP-1 with the area under the curve at 0.837.

CONCLUSIONS

The depression-related alteration of serum MCP-1 may be more complicated than the current assumption and depends on the characteristics of the individual patients. Our study suggests that the serum MCP-1 levels might involve in the pathophysiology and mechanism of MDD. The present findings, along with the diagnostic evaluation, might be used to evaluate depressive patients.

Automatic classification of schizophrenia patients using resting-state EEG signals

Schizophrenia is one of the serious mental disorders, which can suspend the patient from all aspects of life. In this paper we introduced a new method based on the adaptive neuro fuzzy inference system (ANFIS) to classify recorded electroencephalogram (EEG) signals from 14 schizophrenia patients and 14 age-matched control participants. Sixteen EEG channels from 19 main channels that had the most discriminatory information were selected. Possible artifacts of these channels were eliminated with the second-order Butterworth filter. Four features, Shannon entropy, spectral entropy, approximate entropy, and the absolute value of the highest slope of autoregressive coefficients (AVLSAC) were extracted from each selected EEG channel in 5 frequency sub-bands, Delta, Theta, Alpha, Beta, and Gamma. Forty-six features were introduced among the 640 possible ones, and the results included accuracies of near 100%, 98.89%, and 95.59% for classifiers of ANFIS, support vector machine (SVM), and artificial neural network (ANN), respectively. Also, our results show that channels of alpha of O1, theta and delta of Fz and F8, and gamma of Fp1 have the most discriminatory information between the two groups. The performance of our proposed model was also compared with the recently published approaches. This study led to presenting a new decision support system (DSS) that can receive a person's EEG signal and separates the schizophrenia patient and healthy subjects with high accuracy.

The Role of Quantitative Electroencephalogram in the Diagnosis and Subgrouping of Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.

EEG microstate features for schizophrenia classification

Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes in brain state in neuropsychiatric diseases. However, previous studies have only reported differences in each microstate feature and have not determined whether microstate features are suitable for schizophrenia classification. Therefore, it is necessary to validate microstate features for schizophrenia classification. Nineteen microstate features, including duration, occurrence, and coverage as well as thirty-one conventional EEG features, including statistical, frequency, and temporal characteristics were obtained from resting-state EEG recordings of 14 patients diagnosed with schizophrenia and from 14 healthy (control) subjects. Machine-learning based multivariate analysis was used to evaluate classification performance. EEG recordings of patients and controls showed different microstate features. More importantly, when differentiating among patients and controls, EEG microstate features outperformed conventional EEG ones. The performance of the microstate features exceeded that of conventional EEG, even after optimization using recursive feature elimination. EEG microstate features applied with conventional EEG features also showed better classification performance than conventional EEG features alone. The current study is the first to validate the use of microstate features to discriminate schizophrenia, suggesting that EEG microstate features are useful for schizophrenia classification.

Phase-Amplitude Coupling, Mental Health and Cognition: Implications for Adolescence

Identifying biomarkers of developing mental disorder is crucial to improving early identification and treatment-a key strategy for reducing the burden of mental disorders. Cross-frequency coupling between two different frequencies of neural oscillations is one such promising measure, believed to reflect synchronization between local and global networks in the brain. Specifically, in adults phase-amplitude coupling (PAC) has been shown to be involved in a range of cognitive processes, including working and long-term memory, attention, language, and fluid intelligence. Evidence suggests that increased PAC mediates both temporary and lasting improvements in working memory elicited by transcranial direct-current stimulation and reductions in depressive symptoms after transcranial magnetic stimulation. Moreover, research has shown that abnormal patterns of PAC are associated with depression and schizophrenia in adults. PAC is believed to be closely related to cortico-cortico white matter (WM) microstructure, which is well established in the literature as a structural mechanism underlying mental health. Some cognitive findings have been replicated in adolescents and abnormal patterns of PAC have also been linked to ADHD in young people. However, currently most research has focused on cross-sectional adult samples. Whereas initial hypotheses suggested that PAC was a state-based measure due to an early focus on cognitive, task-based research, current evidence suggests that PAC has both state-based and stable components. Future longitudinal research focusing on PAC throughout adolescent development could further our understanding of the relationship between mental health and cognition and facilitate the development of new methods for the identification and treatment of youth mental health.

Neurotrophin receptor activation rescues cognitive and synaptic abnormalities caused by hemizygosity of the psychiatric risk gene Cacna1c

Genetic variation in CACNA1C, which encodes the alpha-1 subunit of Ca_V1.2 L-type voltage-gated calcium channels, is strongly linked to risk for psychiatric disorders including schizophrenia and bipolar disorder. To translate genetics to neurobiological mechanisms and rational therapeutic targets, we investigated the impact of mutations of one copy of Cacna1c on rat cognitive, synaptic and circuit phenotypes implicated by patient studies. We show that rats hemizygous for Cacna1c harbour marked impairments in learning to disregard non-salient stimuli, a behavioural change previously associated with psychosis. This behavioural deficit is accompanied by dys-coordinated network oscillations during learning, pathway-selective disruption of hippocampal synaptic plasticity, attenuated Ca²⁺ signalling in dendritic spines and decreased signalling through the Extracellular-signal Regulated Kinase (ERK) pathway. Activation of the ERK pathway by a small-molecule agonist of TrkB/TrkC neurotrophin receptors rescued both behavioural and synaptic plasticity deficits in Cacna1c^+/- rats. These results map a route through which genetic variation in CACNA1C can disrupt experience-dependent synaptic signalling and circuit activity, culminating in cognitive alterations associated with psychiatric disorders. Our findings highlight targeted activation of neurotrophin signalling pathways with BDNF mimetic drugs as a genetically informed therapeutic approach for rescuing behavioural abnormalities in psychiatric disorder.

Serum interferon-gamma level is associated with drug-naïve major depressive disorder

Objectives:

Major depressive disorder is a leading heterogeneous psychiatric illness manifested by persistent low mood, a feeling of sadness, and diminished interest in daily activities. Many biological, genetic, and social factors are thought to be linked with depression. But any suitable early risk assessment markers are absent for this illness. Therefore, we aimed to investigate the serum levels of IFN-γ in major depressive disorder patients to further investigate the association between serum levels of this cytokine and major depression.

Methods:

This prospective case-control study enrolled 120 major depressive disorder patients and 100 healthy controls matched by age, sex, and body mass index. A qualified psychiatrist diagnosed the major depressive disorder patients and evaluated healthy controls according to the Diagnostic and Statistical Manual of Mental Health Disorders (5th ed.; DSM-5). The Hamilton depression rating scale was applied for all the study participants to measure the severity of depression. Serum IFN-γ levels were measured by a commercially available enzyme-linked immunosorbent assay kit (Boster Biological Technology, Pleasanton, CA, USA).

Results:

This study observed that serum IFN-γ levels were significantly decreased in major depressive disorder patients compared to healthy controls. A significant negative correlation (r = −0.375; p < 0.001) was obtained between serum IFN-γ levels and Hamilton depression scores. Receiver operating characteristic analysis showed good diagnostic performance of lowered serum IFN-γ levels in depression with an area under the curve at 0.790.

Conclusion:

We suggest the altered serum IFN-γ levels are associated with the pathophysiology of depression. The reduced levels of serum IFN-γ might be used as an early risk assessment tool for major depression.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Neurobiological Mechanisms of Metacognitive Therapy - An Experimental Paradigm

INTRODUCTION

The neurobiological mechanisms underlying the clinical effects of psychotherapy are scarcely understood. In particular, the modifying effects of psychotherapy on neuronal activity are largely unknown. We here present data from an innovative experimental paradigm using the example of a patient with treatment resistant obsessive-compulsive disorder (trOCD) who underwent implantation of bilateral electrodes for deep brain stimulation (DBS). The aim of the paradigm was to examine the short term effect of metacognitive therapy (MCT) on neuronal local field potentials (LFP) before and after 5 MCT sessions.

METHODS

DBS electrodes were implanted bilaterally with stereotactic guidance in the bed nucleus of the stria terminalis/ internal capsule (BNST/IC). The period between implantation of the electrodes and the pacemaker was used for the experimental paradigm. DBS electrodes were externalized via extension cables, yielding the opportunity to record LFP directly from the BNST/IC. The experimental paradigm was designed as follows: (a) baseline recording of LFP from the BNST/IC, (b) application of 5 MCT sessions over 3 days, (c) post-MCT recording from the BNST/IC. The Obsessive-Compulsive Disorder- scale (OCD-S) was used to evaluate OCD symptoms.

RESULTS

OCD symptoms decreased after MCT. These reductions were accompanied by a decrease of the relative power of theta band activity, while alpha, beta, and gamma band activity was significantly increased after MCT. Further, analysis of BNST/IC LFP and frontal cortex EEG coherence showed that MCT decreased theta frequency band synchronization.

DISCUSSION

Implantation of DBS electrodes for treating psychiatric disorders offers the opportunity to gather data from neuronal circuits, and to compare effects of therapeutic interventions. Here, we demonstrate direct effects of MCT on neuronal oscillatory behavior, which may give possible cues for the neurobiological changes associated with psychotherapy.

The dynamics of disordered dialogue: Prefrontal, hippocampal and thalamic miscommunication underlying working memory deficits in schizophrenia

The prefrontal cortex is central to the orchestrated brain network communication that gives rise to working memory and other cognitive functions. Accordingly, working memory deficits in schizophrenia are increasingly thought to derive from prefrontal cortex dysfunction coupled with broader network disconnectivity. How the prefrontal cortex dynamically communicates with its distal network partners to support working memory and how this communication is disrupted in individuals with schizophrenia remain unclear. Here we review recent evidence that prefrontal cortex communication with the hippocampus and thalamus is essential for normal spatial working memory, and that miscommunication between these structures underlies spatial working memory deficits in schizophrenia. We focus on studies using normal rodents and rodent models designed to probe schizophrenia-related pathology to assess the dynamics of neural interaction between these brain regions. We also highlight recent preclinical work parsing roles for long-range prefrontal cortex connections with the hippocampus and thalamus in normal and disordered spatial working memory. Finally, we discuss how emerging rodent endophenotypes of hippocampal- and thalamo-prefrontal cortex dynamics in spatial working memory could translate into richer understanding of the neural bases of cognitive function and dysfunction in humans.