A Neurophysiological Perspective on a Preventive Treatment against Schizophrenia Using Transcranial Electric Stimulation of the Corticothalamic Pathway

Early cognitive comorbidities before disease onset: A common symptom towards prevention of related brain diseases?

Brain diseases are very heterogeneous; however they also display multiple common risk factors and comorbidities. With a paucity of disease-modifying therapies, prevention became a health priority. Towards prevention, one strategy is to focus on similar symptoms of brain diseases occurring before disease onset. Cognitive deficits are a promising candidate as they occur across brain diseases before disease onset. Based on recent research, this review highlights the similarity of brain diseases and discusses how early cognitive deficits can be exploited to tackle disease prevention. After briefly introducing common risk factors, I review common comorbidities across brain diseases, with a focus on cognitive deficits before disease onset, reporting both experimental and clinical findings. Next, I describe network abnormalities associated with early cognitive deficits and discuss how these abnormalities can be targeted to prevent disease onset. A scenario on brain disease etiology with the idea that early cognitive deficits may constitute a common symptom of brain diseases is proposed.

Mathematical Model Insights into EEG Origin under Transcranial Direct Current Stimulation (tDCS) in the Context of Psychosis

Schizophrenia is a psychotic disease that develops progressively over years with a transition from prodromal to psychotic state associated with a disruption in brain activity. Transcranial Direct Current Stimulation (tDCS), known to alleviate pharmaco-resistant symptoms in patients suffering from schizophrenia, promises to prevent such a psychotic transition. To understand better how tDCS affects brain activity, we propose a neural cortico-thalamo-cortical (CTC) circuit model involving the Ascending Reticular Arousal System (ARAS) that permits to describe major impact features of tDCS, such as excitability for short-duration stimulation and electroencephalography (EEG) power modulation for long-duration stimulation. To this end, the mathematical model relates stimulus duration and Long-Term Plasticity (LTP) effect, in addition to describing the temporal LTP decay after stimulus offset. This new relation promises to optimize future stimulation protocols. Moreover, we reproduce successfully EEG-power modulation under tDCS in a ketamine-induced psychosis model and confirm the N-methyl-d-aspartate (NMDA) receptor hypofunction hypothesis in the etiopathophysiology of schizophrenia. The model description points to an important role of the ARAS and the δ-rhythm synchronicity in CTC circuit in early-stage psychosis.

Thalamic circuits for independent control of prefrontal signal and noise

Interactions between the mediodorsal thalamus and the prefrontal cortex are critical for cognition. Studies in humans indicate that these interactions may resolve uncertainty in decision-making¹, but the precise mechanisms are unknown. Here we identify two distinct mediodorsal projections to the prefrontal cortex that have complementary mechanistic roles in decision-making under uncertainty. Specifically, we found that a dopamine receptor (D2)-expressing projection amplifies prefrontal signals when task inputs are sparse and a kainate receptor (GRIK4) expressing-projection suppresses prefrontal noise when task inputs are dense but conflicting. Collectively, our data suggest that there are distinct brain mechanisms for handling uncertainty due to low signals versus uncertainty due to high noise, and provide a mechanistic entry point for correcting decision-making abnormalities in disorders that have a prominent prefrontal component^2–6.

Two different cell types in the mediodorsal thalamus have complementary roles in decision-making, with one type of mediodorsal projection amplifying prefrontal activity under low signal levels and one type suppressing it under high noise levels.

Frontoparietal anodal tDCS reduces ketamine-induced oscillopathies

During the prodromal phase of schizophrenia with its complex and insidious clinical picture, electroencephalographic recordings detect widespread oscillation disturbances (or oscillopathies) during the wake-sleep cycle. Neural oscillations are electrobiomarkers of the connectivity state within systems. A single-systemic administration of ketamine, a non-competitive NMDA glutamate receptor antagonist, transiently reproduces the oscillopathies with a clinical picture reminiscent of the psychosis prodrome. This acute pharmacological model may help the research and development of innovative treatments against psychotic transition. Transcranial electrical stimulation is recognized as an appropriate non-invasive therapeutic modality since it can increase cognitive performance and modulate neural oscillations with little or no side effects. Therefore, our objective was to set up, in the sedated adult rat, a stimulation method that is able to normalize ketamine-induced increase in gamma-frequency (30-80 Hz) oscillations and decrease in sigma-frequency (10-17 Hz) oscillations. Unilateral and bipolar frontoparietal (FP), transcranial anodal stimulation by direct current (<+1 mA) was applied in ketamine-treated rats. A concomitant bilateral electroencephalographic recording of the parietal cortex measured the stimulation effects on its spontaneously occurring oscillations. A 5 min FP anodal tDCS immediately and quickly reduced, significantly with an intensity-effect relationship, the ketamine-induced gamma hyperactivity, and sigma hypoactivity at least in the bilateral parietal cortex. A duration effect was also recorded. The tDCS also tended to diminish the ketamine-induced delta hypoactivity. These preliminary neurophysiological findings are promising for developing a therapeutic proof-of-concept against neuropsychiatric disorders.

Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup

Multi‐institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure‐based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI—rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure‐based analysis showed widespread DTI abnormalities in FEP and rs‐fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof‐of‐concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub‐groups.

Reduced sleep spindle density in adolescent patients with early-onset schizophrenia compared to major depressive disorder and healthy controls

OBJECTIVES

During adolescence schizophrenia and major depressive disorder (MDD) increasingly emerge. Overlapping symptomatology during first presentation challenges the diagnostic process. Reduced sleep spindle density (SSD) was suggested as a biomarker in adults, discerning patients with schizophrenia from patients with depression or healthy controls (HC). We aimed to compare SSD in early-onset schizophrenia (EOS), with MDD, and HC, and to analyse associations of SSD with symptomatology and neurocognitive measures.

METHODS

Automatic sleep spindle detection was performed on all-night high-density EEG (128 electrodes) data of 12 EOS, 19 MDD, and 57 HC (age range 9.8-19), allowing an age- and sex-matching of 1:2 (patients vs. HC). Severity of current symptoms and neurocognitive variables were assessed in all patients.

RESULTS

SSD was defined between 13.75 and 14.50 Hz as within this frequency range SSD differed between EOS vs. HC in bin by bin analyses (12-15 Hz). In EOS, SSD was lower over 27 centro-temporal electrodes compared to HC and over 9 central electrodes compared to MDD. Reduced SSD in EOS compared to MDD and HC was accompanied by a high variability of SSD in all adolescents. SSD did not differ between MDD and HC. In the pooled sample of patients, lower SSD was associated with more severe Positive and Negative Symptoms Scale total score, more impaired memory consolidation and processing speed.

CONCLUSION

A high variability of SSD in all adolescents may reflect the evolving character of SSD. The association of reduced SSD with the symptom dimension of impaired cognition cuts across diagnostical entities.

Thalamic reticular nucleus in the thalamocortical loop

Dynamic binding of different brain areas is critical for various cognitive functions. The thalamic reticular nucleus (TRN) is a GABAergic nucleus that constrains information flow through thalamocortical loop by providing inhibitory innervation to the thalamus. In this review, I summarize anatomical and single-cell-level physiological studies of the rodent TRN. Diversity and heterogeneity of TRN neurons in terms of axonal innervation, molecular expression, and physiological characteristics are described. I also outline thalamocortical and cortico-cortical connections with emphasis on interaction with the TRN. In summary, it is proposed that functional connectivity among brain regions are modulated with gating of transthalamic information flow by the TRN.

Thalamic Reticular Nucleus Parvalbumin Neurons Regulate Sleep Spindles and Electrophysiological Aspects of Schizophrenia in Mice

The thalamic reticular nucleus (TRN) is implicated in schizophrenia pathology. However, it remains unclear whether alterations of TRN activity can account for abnormal electroencephalographic activity observed in patients, namely reduced spindles (10-15 Hz) during sleep and increased delta (0.5-4 Hz) and gamma-band activity (30-80 Hz) during wakefulness. Here, we utilized optogenetic and reverse-microdialysis approaches to modulate activity of the major subpopulation of TRN GABAergic neurons, which express the calcium-binding protein parvalbumin (PV), and are implicated in schizophrenia dysfunction. An automated algorithm with enhanced efficiency and reproducibility compared to manual detection was used for sleep spindle assessment. A novel, low power, waxing-and-waning optogenetic stimulation paradigm preferentially induced spindles that were indistinguishable from spontaneously occurring sleep spindles without altering the behavioral state, when compared to a single pulse laser stimulation used by us and others. Direct optogenetic inhibition of TRN-PV neurons was ineffective in blocking spindles but increased both wakefulness and cortical delta/gamma activity, as well as impaired the 40 Hz auditory steady-state response. For the first time we demonstrate that spindle density is markedly reduced by (i) optogenetic stimulation of a major GABA/PV inhibitory input to TRN arising from basal forebrain parvalbumin neurons (BF-PV) and; (ii) localized pharmacological inhibition of low-threshold calcium channels, implicated as a genetic risk factor for schizophrenia. Together with clinical findings, our results support impaired TRN-PV neuron activity as a potential cause of schizophrenia-linked abnormalities in cortical delta, gamma, and spindle activity. Modulation of the BF-PV input to TRN may improve these neural abnormalities.

MEG resting-state oscillations and their relationship to clinical symptoms in schizophrenia

Neuroimaging studies suggest that schizophrenia is characterized by disturbances in oscillatory activity, although at present it remains unclear whether these neural abnormalities are driven by dimensions of symptomatology. Examining different subgroups of patients based on their symptomatology is thus very informative in understanding the role of neural oscillation patterns in schizophrenia. In the present study we examined whether neural oscillations in the delta, theta, alpha, beta and gamma bands correlate with positive and negative symptoms in individuals with schizophrenia (SZ) during rest. Resting-state brain activity of 39 SZ and 25 neurotypical controls was recorded using magnetoencephalography. Patients were categorized based on the severity of their positive and negative symptoms. Spectral analyses of beamformer data revealed that patients high in positive symptoms showed widespread low alpha power, and alpha power was negatively correlated with positive symptoms. In contrast, patients high in negative symptoms showed greater beta power in left hemisphere regions than those low in negative symptoms, and beta power was positively correlated with negative symptoms. We further discuss these findings and suggest that different neural mechanisms may underlie positive and negative symptoms in schizophrenia.

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

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