An Integrative Perspective on the Role of Dopamine in Schizophrenia

NMDAR dysfunction and the regulation of dopaminergic transmission in schizophrenia

A substantial body of evidence implicates dysfunction in N-methyl-d-aspartate receptors (NMDARs) in the pathophysiology of schizophrenia. This article illustrates how NMDAR dysfunction may give rise to many of the neurobiological phenomena frequently associated with schizophrenia with a particular focus on how NMDAR dysfunction affects the thalamic reticular nucleus (nRT) and pedunculopontine tegmental nucleus (PPTg). Furthermore, this article presents a model for schizophrenia illustrating how dysfunction in the nRT may interrupt prefrontal regulation of midbrain dopaminergic neurons, and how dysfunction in the PPTg may drive increased, irregular burst firing.

Behind the heterogeneity in the long-term course of first-episode psychosis: Different psychotic symptom trajectories are associated with different patterns of cannabis and stimulant use

BACKGROUND

Data-driven classification of long-term psychotic symptom trajectories and identification of associated risk factors could assist treatment planning and improve long-term outcomes in psychosis. However, few studies have used this approach, and knowledge about underlying mechanisms is limited. Here, we identify long-term psychotic symptom trajectories and investigate the role of illness-concurrent cannabis and stimulant use.

METHODS

192 participants with first-episode psychosis were followed up after 10 years. Psychotic symptom trajectories were estimated using growth mixture modeling and tested for associations with baseline characteristics and cannabis and stimulant use during the follow-up (FU) period.

RESULTS

Four trajectories emerged: (1) Stable Psychotic Remission (54.2 %), (2) Delayed Psychotic Remission (15.6 %), (3) Psychotic Relapse (7.8 %), (4) Persistent Psychotic Symptoms (22.4 %). At baseline, all unfavorable trajectories (2-4) were characterized by more schizophrenia diagnoses, higher symptom severity, and longer duration of untreated psychosis. Compared to the Stable Psychotic Remission trajectory, unstable trajectories (2,3) showed distinct associations with cannabis/stimulant use during the FU-period, with dose-dependent effects for cannabis but not stimulants (Delayed Psychotic Remission: higher rates of frequent cannabis and stimulant use during the first 5 FU-years; Psychotic Relapse: higher rates of sporadic stimulant use throughout the entire FU-period). The Persistent Psychosis trajectory was less clearly linked to substance use during the FU-period.

CONCLUSIONS

The risk for an adverse long-term course could be mitigated by treatment of substance use, where particular attention should be devoted to preventing the use of stimulants while the use reduction of cannabis may already yield positive effects.

A biophysical model for dopamine modulating working memory through reward system in obsessive-compulsive disorder

Dopamine modulates working memory in the prefrontal cortex (PFC) and is crucial for obsessive-compulsive disorder (OCD). However, the mechanism is unclear. Here we establish a biophysical model of the effect of dopamine (DA) in PFC to explain the mechanism of how high dopamine concentrations induce persistent neuronal activities with the network plunging into a deep, stable attractor state. The state develops a defect in working memory and tends to obsession and compulsion. Weakening the reuptake of dopamine acts on synaptic plasticity according to Hebbian learning rules and reward learning, which in turn affects the strength of neuronal synaptic connections, resulting in the tendency of compulsion and learned obsession. In addition, we elucidate the potential mechanisms of dopamine antagonists in OCD, indicating that dopaminergic drugs might be available for treatment, even if the abnormality is a consequence of glutamate hypermetabolism rather than dopamine. The theory highlights the significance of early intervention and behavioural therapies for obsessive-compulsive disorder. It potentially offers new approaches to dopaminergic pharmacotherapy and psychotherapy for OCD patients.

Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

Short-term antipsychotic treatment reduces functional connectivity of the striatum in first-episode drug-naïve early-onset schizophrenia

BACKGROUND

The striatum is thought to play a critical role in the pathophysiology and antipsychotic treatment of schizophrenia. Previous studies have revealed abnormal functional connectivity (FC) of the striatum in early-onset schizophrenia (EOS) patients. However, no prior studies have examined post-treatment changes of striatal FC in EOS patients.

METHODS

We recruited 49 first-episode drug-naïve EOS patients to have resting-state functional magnetic resonance imaging scans at baseline and after 8 weeks of treatment with antipsychotics, along with baseline scanning of 34 healthy controls (HCs) for comparison purposes. We examined the FC values between each seed in striatal subregion and the rest of the brain. The Positive and Negative Syndrome Scale (PANSS) was applied to measure psychiatric symptoms in patients.

RESULTS

Compared with HCs at baseline, EOS patients exhibited weaker FC of striatal subregions with several brain regions of the salience network and default mode network. Meanwhile, FC between the dorsal caudal putamen (DCP) and left supplementary motor area, as well as between the DCP and right postcentral gyrus, was negatively correlated with PANSS negative scores. Furthermore, after 8 weeks of treatment, EOS patients showed decreased FC between subregions of the putamen and the triangular part of inferior frontal gyrus, middle frontal gyrus, supramarginal gyrus and inferior parietal lobule.

CONCLUSIONS

Decreased striatal FC is evident, even in the early stages of schizophrenia, and enhance our understanding of the neurodevelopmental abnormalities in schizophrenia. The findings also demonstrate that reduced striatal FC occurs after antipsychotic therapy, indicating that antipsychotic effects need to be accounted for when considering striatal FC abnormalities in schizophrenia.

Psychosis as a disorder of muscarinic signalling: psychopathology and pharmacology

Dopaminergic receptor antagonism is a crucial component of all licensed treatments for psychosis, and dopamine dysfunction has been central to pathophysiological models of psychotic symptoms. Some clinical trials, however, indicate that drugs that act through muscarinic receptor agonism can also be effective in treating psychosis, potentially implicating muscarinic abnormalities in the pathophysiology of psychosis. Here, we discuss understanding of the central muscarinic system, and we examine preclinical, behavioural, post-mortem, and neuroimaging evidence for its involvement in psychosis. We then consider how altered muscarinic signalling could contribute to the genesis and maintenance of psychotic symptoms, and we review the clinical evidence for muscarinic agents as treatments. Finally, we discuss future research that could clarify the relationship between the muscarinic system and psychotic symptoms.

Exploring causal mechanisms of psychosis risk

Robust epidemiological evidence of risk and protective factors for psychosis is essential to inform preventive interventions. Previous evidence syntheses have classified these risk and protective factors according to their strength of association with psychosis. In this critical review we appraise the distinct and overlapping mechanisms of 25 key environmental risk factors for psychosis, and link these to mechanistic pathways that may contribute to neurochemical alterations hypothesised to underlie psychotic symptoms. We then discuss the implications of our findings for future research, specifically considering interactions between factors, exploring universal and subgroup-specific factors, improving understanding of temporality and risk dynamics, standardising operationalisation and measurement of risk and protective factors, and developing preventive interventions targeting risk and protective factors.

Selective dopaminergic neurotoxicity modulated by inherent cell-type specific neurobiology

Parkinson's disease (PD) is a debilitating neurodegenerative disease affecting millions of individuals worldwide. Hallmark features of PD pathology are the formation of Lewy bodies in neuromelanin-containing dopaminergic (DAergic) neurons of the substantia nigra pars compacta (SNpc), and the subsequent irreversible death of these neurons. Although genetic risk factors have been identified, around 90 % of PD cases are sporadic and likely caused by environmental exposures and gene-environment interaction. Mechanistic studies have identified a variety of chemical PD risk factors. PD neuropathology occurs throughout the brain and peripheral nervous system, but it is the loss of DAergic neurons in the SNpc that produce many of the cardinal motor symptoms. Toxicology studies have found specifically the DAergic neuron population of the SNpc exhibit heightened sensitivity to highly variable chemical insults (both in terms of chemical structure and mechanism of neurotoxic action). Thus, it has become clear that the inherent neurobiology of nigral DAergic neurons likely underlies much of this neurotoxic response to broad insults. This review focuses on inherent neurobiology of nigral DAergic neurons and how such neurobiology impacts the primary mechanism of neurotoxicity. While interactions with a variety of other cell types are important in disease pathogenesis, understanding how inherent DAergic biology contributes to selective sensitivity and primary mechanisms of neurotoxicity is critical to advancing the field. Specifically, key biological features of DAergic neurons that increase neurotoxicant susceptibility.

Neuromelanin-Sensitive MRI as Candidate Marker for Treatment Resistance in First-Episode Schizophrenia

OBJECTIVE

Markers for treatment resistance in schizophrenia are needed to reduce delays in effective treatment. Nigrostriatal hyperdopaminergic function plays a critical role in the pathology of schizophrenia, yet antipsychotic nonresponders do not show increased dopamine function. Neuromelanin-sensitive MRI (NM-MRI), which indirectly measures dopamine function in the substantia nigra, has potential as a noninvasive marker for nonresponders. Increased NM-MRI signal has been shown in psychosis, but has not yet been assessed in nonresponders. In this study, the authors investigated whether nonresponders show lower NM-MRI signal than responders.

METHODS

NM-MRI scans were acquired in 79 patients with first-episode psychosis and 20 matched healthy control subjects. Treatment response was assessed at a 6-month follow-up. An a priori voxel-wise analysis within the substantia nigra tested the relation between NM-MRI signal and treatment response in patients.

RESULTS

Fifteen patients were classified as nonresponders and 47 patients as responders. Seventeen patients were excluded, primarily because of medication nonadherence or change in diagnosis. Voxel-wise analysis revealed 297 significant voxels in the ventral tier of the substantia nigra that were negatively associated with treatment response. Nonresponders and healthy control subjects had significantly lower NM-MRI signal than responders. Receiver operating characteristic curve analysis showed that NM-MRI signal separated nonresponders with areas under the curve between 0.62 and 0.85. In addition, NM-MRI signal in patients did not change over 6 months.

CONCLUSIONS

These findings provide further evidence for dopaminergic differences between medication responders and nonresponders and support the potential of NM-MRI as a clinically applicable marker for treatment resistance in schizophrenia.

Antipsychotic drugs selectively decorrelate long-range interactions in deep cortical layers

Psychosis is characterized by a diminished ability of the brain to distinguish externally driven activity patterns from self-generated activity patterns. Antipsychotic drugs are a class of small molecules with relatively broad binding affinity for a variety of neuromodulator receptors that, in humans, can prevent or ameliorate psychosis. How these drugs influence the function of cortical circuits, and in particular their ability to distinguish between externally and self-generated activity patterns, is still largely unclear. To have experimental control over self-generated sensory feedback, we used a virtual reality environment in which the coupling between movement and visual feedback can be altered. We then used widefield calcium imaging to determine the cell type-specific functional effects of antipsychotic drugs in mouse dorsal cortex under different conditions of visuomotor coupling. By comparing cell type-specific activation patterns between locomotion onsets that were experimentally coupled to self-generated visual feedback and locomotion onsets that were not coupled, we show that deep cortical layers were differentially activated in these two conditions. We then show that the antipsychotic drug clozapine disrupted visuomotor integration at locomotion onsets also primarily in deep cortical layers. Given that one of the key components of visuomotor integration in cortex is long-range cortico-cortical connections, we tested whether the effect of clozapine was detectable in the correlation structure of activity patterns across dorsal cortex. We found that clozapine as well as two other antipsychotic drugs, aripiprazole and haloperidol, resulted in a strong reduction in correlations of layer 5 activity between cortical areas and impaired the spread of visuomotor prediction errors generated in visual cortex. Our results are consistent with the interpretation that a major functional effect of antipsychotic drugs is a selective alteration of long-range layer 5-mediated communication.

65 years of research on dopamine's role in classical fear conditioning and extinction: A systematic review

Dopamine, a catecholamine neurotransmitter, has historically been associated with the encoding of reward, whereas its role in aversion has received less attention. Here, we systematically gathered the vast evidence of the role of dopamine in the simplest forms of aversive learning: classical fear conditioning and extinction. In the past, crude methods were used to augment or inhibit dopamine to study its relationship with fear conditioning and extinction. More advanced techniques such as conditional genetic, chemogenic and optogenetic approaches now provide causal evidence for dopamine's role in these learning processes. Dopamine neurons encode conditioned stimuli during fear conditioning and extinction and convey the signal via activation of D1-4 receptor sites particularly in the amygdala, prefrontal cortex and striatum. The coordinated activation of dopamine receptors allows for the continuous formation, consolidation, retrieval and updating of fear and extinction memory in a dynamic and reciprocal manner. Based on the reviewed literature, we conclude that dopamine is crucial for the encoding of classical fear conditioning and extinction and contributes in a way that is comparable to its role in encoding reward.

Quantifying the effects of practicing a semantic task according to subclinical schizotypy

The learning ability of individuals within the schizophrenia spectrum is crucial for their psychosocial rehabilitation. When selecting a treatment, it is thus essential to consider the impact of medications on practice effects, an important type of learning ability. To achieve this end goal, a pre-treatment test has to be developed and tested in healthy participants first. This is the aim of the current work, which takes advantage of the schizotypal traits present in these participants to preliminary assess the test's validity for use among patients. In this study, 47 healthy participants completed the Schizotypal Personality Questionnaire (SPQ) and performed a semantic categorization task twice, with a 1.5-hour gap between sessions. Practice was found to reduce reaction times (RTs) in both low- and high-SPQ scorers. Additionally, practice decreased the amplitudes of the N400 event-related brain potentials elicited by semantically matching words in low SPQ scorers only, which shows the sensitivity of the task to schizotypy. Across the two sessions, both RTs and N400 amplitudes had good test-retest reliability. This task could thus be a valuable tool. Ongoing studies are currently evaluating the impact of fully deceptive placebos and of real antipsychotic medications on these practice effects. This round of research should subsequently assist psychiatrists in making informed decisions about selecting the most suitable medication for the psychosocial rehabilitation of a patient.

Temporal imprecision of phase coherence in schizophrenia and psychosis-dynamic mechanisms and diagnostic marker

Schizophrenia (SCZ) is a complex disorder in which various pathophysiological models have been postulated. Brain imaging studies using EEG/MEG and fMRI show altered amplitude and, more recently, decrease in phase coherence in response to external stimuli. What are the dynamic mechanisms of such phase incoherence, and can it serve as a differential-diagnostic marker? Addressing this gap in our knowledge, we uniquely combine a review of previous findings, novel empirical data, and computational-dynamic simulation. The main findings are: (i) the review shows decreased phase coherence in SCZ across a variety of different tasks and frequencies, e.g., task- and frequency-unspecific, which is further supported by our own novel data; (ii) our own data demonstrate diagnostic specificity of decreased phase coherence for SCZ as distinguished from major depressive disorder; (iii) simulation data exhibit increased phase offset in SCZ leading to a precision index, in the millisecond range, of the phase coherence relative to the timing of the external stimulus. Together, we demonstrate the key role of temporal imprecision in phase coherence of SCZ, including its mechanisms (phase offsets, precision index) on the basis of which we propose a phase-based temporal imprecision model of psychosis (PTP). The PTP targets a deeper dynamic layer of a basic disturbance. This converges well with other models of psychosis like the basic self-disturbance and time-space experience changes, as discussed in phenomenological and spatiotemporal psychopathology, as well as with the models of aberrant predictive coding and disconnection as in computational psychiatry. Finally, our results show that temporal imprecision as manifest in decreased phase coherence is a promising candidate biomarker for clinical differential diagnosis of SCZ, and more broadly, psychosis.

Cognitive Control in Schizophrenia: Advances in Computational Approaches

Psychiatric research is undergoing significant advances in an emerging subspeciality of computational psychiatry, building upon cognitive neuroscience research by expanding to neurocomputational modeling. Here, we illustrate some research trends in this domain using work on proactive cognitive control deficits in schizophrenia as an example. We provide a selective review of formal modeling approaches to understanding cognitive control deficits in psychopathology, focusing primarily on biologically plausible connectionist-level models as well as mathematical models that generate parameter estimates of putatively dissociable psychological or neural processes. We illustrate some of the advantages of these models in terms of understanding both cognitive control deficits in schizophrenia and the potential roles of effort and motivation. Further, we highlight critical future directions for this work, including a focus on establishing psychometric properties, additional work modeling psychotic symptoms and their interaction with cognitive control, and the need to expand both behavioral and neural modeling to samples that include individuals with different mental health conditions, allowing for the examination of dissociable neural or psychological substrates for seemingly similar cognitive impairments across disorders.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

Targeted Treatment of Schizophrenia Symptoms as They Manifest, or Continuous Treatment to Reduce the Risk of Psychosis Recurrence

Current pharmacological treatment of schizophrenia employs drugs that interfere with dopamine neurotransmission, aiming to suppress acute exacerbation of psychosis and maintenance treatment to reduce the risk of psychosis recurrence. According to this treatment scheme, available psychotropic drugs intended to treat negative symptoms, cognitive impairment, or anxiety are administered as add-ons to treatment with antipsychotics. However, an alternative treatment scheme proposes a targeted or intermittent treatment approach, by which antipsychotic drugs are administered upon psychosis exacerbation and discontinued upon remission or stabilization, while negative symptoms, cognitive impairment, or anxiety are treated with specific psychotropics as monotherapy. Along these lines, antipsychotics are renewed only in the event of recurrence of psychotic symptoms. This 50-year-old debate between targeted and continuous treatment schemes arises from disagreements about interpreting scientific evidence and discordant views regarding benefit/risk assessment. Among the debate's questions are: (1) what is the percentage of individuals who can maintain stability without antipsychotic maintenance treatment, and what is the percentage of those who exacerbate despite antipsychotic treatment? (2) how to interpret results of placebo-controlled 9- to 18-month-long maintenance trials in a life-long chronic disorder, and how to interpret results of the targeted trials, some of which are open label or not randomized; (3) how to weigh the decreased risk for psychotic recurrence vs the almost certainty of adverse effects on patient's quality of life. Patients' profiles, preferences, and circumstances of the care provision should be considered as the targeted vs continuous treatment options are considered.

Reduced Reward Processing in Schizophrenia: A Comprehensive EEG Event-Related Oscillation Study

It is well known that abnormal reward processing is a characteristic feature of various psychopathologies including schizophrenia (SZ). Reduced reward anticipation has been suggested as a core symptom of SZ. The present study aims to evaluate the event-related oscillations (EROs) delta, theta, alpha, beta, and gamma in patients with SZ during the Monetary Incentive Delay (MID) task, which elicits the neural activity of reward processing. Twenty-one patients with SZ and twenty-two demographically matched healthy controls were included in the study. EROs were compared between groups and correlation analyses were conducted to determine a possible relationship between clinical scores and ERO values. Compared with healthy controls, the SZ group had reduced (1) delta and theta amplitudes in the reward condition (2) total beta and non-incentive cue-related beta amplitudes, and (3) incentive cue-related frontal gamma amplitudes. These reductions can be interpreted as impaired dopaminergic neurotransmission and disrupted cognitive functioning in the reward processing of SZ. In contrast, SZ patients showed higher incentive cue-related theta and occipital gamma amplitudes compared to controls. These increments may reflect negative symptoms in SZ. Moreover, theta amplitudes showed a negative correlation with Calgary Depression Scale for Schizophrenia scores and a positive correlation with attentional impulsivity. This is the first study showing the impairments of SZ patients in EROs from delta to gamma frequency bands compared with healthy controls during reward anticipation. Being the first comprehensive study, our results can be interpreted as providing evidence for disrupted brain dynamics in the reward processing of SZ studied by EROs. It may become possible to help patients' wellness by improving our understanding of reward processing in schizophrenia and developing innovative rehabilitation treatments based on these findings.

The cognitive (lateral) hypothalamus

Despite the physiological complexity of the hypothalamus, its role is typically restricted to initiation or cessation of innate behaviors. For example, theories of lateral hypothalamus argue that it is a switch to turn feeding 'on' and 'off' as dictated by higher-order structures that render when feeding is appropriate. However, recent data demonstrate that the lateral hypothalamus is critical for learning about food-related cues. Furthermore, the lateral hypothalamus opposes learning about information that is neutral or distal to food. This reveals the lateral hypothalamus as a unique arbitrator of learning capable of shifting behavior toward or away from important events. This has relevance for disorders characterized by changes in this balance, including addiction and schizophrenia. Generally, this suggests that hypothalamic function is more complex than increasing or decreasing innate behaviors.

Resolving the Delusion Paradox

BACKGROUND AND HYPOTHESIS

The neurocomputational framework of predictive processing (PP) provides a promising approach to explaining delusions, a key symptom of psychotic disorders. According to PP, the brain makes inferences about the world by weighing prior beliefs against the available sensory data. Mismatches between prior beliefs and sensory data result in prediction errors that may update the brain's model of the world. Psychosis has been associated with reduced weighting of priors relative to the sensory data. However, delusional beliefs are highly resistant to change, suggesting increased rather than decreased weighting of priors. We propose that this "delusion paradox" can be resolved within a hierarchical PP model: Reduced weighting of prior beliefs at low hierarchical levels may be compensated by an increased influence of higher-order beliefs represented at high hierarchical levels, including delusional beliefs. This may sculpt perceptual processing into conformity with delusions and foster their resistance to contradictory evidence.

STUDY DESIGN

We review several lines of experimental evidence on low- and high-level processes, and their neurocognitive underpinnings in delusion-related phenotypes and link them to predicted processing.

STUDY RESULTS

The reviewed evidence supports the notion of decreased weighting of low-level priors and increased weighting of high-level priors, in both delusional and delusion-prone individuals. Moreover, we highlight the role of prefrontal cortex as a neural basis for the increased weighting of high-level prior beliefs and discuss possible clinical implications of the proposed hierarchical predictive-processing model.

CONCLUSIONS

Our review suggests the delusion paradox can be resolved within a hierarchical PP model.

The Atypical Dopamine Transporter Inhibitor CE-158 Enhances Dopamine Neurotransmission in the Prefrontal Cortex of Male Rats: A Behavioral, Electrophysiological, and Microdialysis Study

BACKGROUND

Dopamine plays a key role in several physiological functions such as motor control, learning and memory, and motivation and reward. The atypical dopamine transporter inhibitor S,S stereoisomer of 5-(((S)-((S)-(3-bromophenyl)(phenyl)methyl)sulfinyl)methyl)thiazole (CE-158) has been recently reported to promote behavioral flexibility and restore learning and memory in aged rats.

METHODS

Adult male rats were i.p. administered for 1 or 10 days with CE-158 at the dose of 1 or 10 mg/kg and tested for extracellular dopamine in the medial prefrontal cortex by means of intracerebral microdialysis and single unit cell recording in the same brain area. Moreover, the effects of acute and chronic CE-158 on exploratory behavior, locomotor activity, prepulse inhibition, working memory, and behavioral flexibility were also investigated.

RESULTS

CE-158 dose-dependently potentiated dopamine neurotransmission in the medial prefrontal cortex as assessed by intracerebral microdialysis. Moreover, repeated exposure to CE-158 at 1 mg/kg was sufficient to increase the number of active pyramidal neurons and their firing frequency in the same brain area. In addition, CE-158 at the dose of 10 mg/kg stimulates exploratory behavior to the same extent after acute or chronic treatment. Noteworthy, the chronic treatment at both doses did not induce any behavioral alterations suggestive of abuse potential (e.g., motor behavioral sensitization) or pro-psychotic-like effects such as disruption of sensorimotor gating or impairments in working memory and behavioral flexibility as measured by prepulse inhibition and Y maze.

CONCLUSIONS

Altogether, these findings confirm CE-158 as a promising pro-cognitive agent and contribute to assessing its preclinical safety profile in a chronic administration regimen for further translational testing.

Fronto-striato-thalamic circuit connectivity and neuromelanin in schizophrenia: an fMRI and neuromelanin-MRI study

Changes in dopamine and fronto-striato-thalamic (FST) circuit functional connectivity are prominent in schizophrenia. Dopamine is thought to underlie connectivity changes, but experimental evidence for this hypothesis is lacking. Previous studies examined the association in some of the connections using positron emission tomography (PET) and functional MRI (fMRI); however, PET has disadvantages in scanning patients, such as invasiveness. Excessive dopamine induces neuromelanin (NM) accumulation, and NM-MRI is suggested as a noninvasive proxy measure of dopamine function. We aimed to investigate the association between NM and FST circuit connectivity at the network level in patients with schizophrenia. We analysed substantia nigra NM-MRI and resting-state fMRI data from 29 schizophrenia patients and 63 age- and sex-matched healthy controls (HCs). We identified the FST subnetwork with abnormal connectivity found in schizophrenia patients compared to that of HCs and investigated the relationship between constituting connectivity and NM-MRI signal. We found a higher NM signal (t = -2.12, p = 0.037) and a hypoconnected FST subnetwork (FWER-corrected p = 0.014) in schizophrenia patients than in HCs. In the hypoconnected subnetwork of schizophrenia patients, lower left supplementary motor area-left caudate connectivity was associated with a higher NM signal (β = -0.38, p = 0.042). We demonstrated the association between NM and FST circuit connectivity. Considering that the NM-MRI signal reflects dopamine function, our results suggest that dopamine underlies changes in FST circuit connectivity, which supports the dopamine hypothesis. In addition, this study reveals implications for the future use of NM-MRI in investigations of the dopamine system.

Increasing dopamine synthesis in nigrostriatal circuits increases phasic dopamine release and alters dorsal striatal connectivity: implications for schizophrenia

One of the most robust neurochemical abnormalities reported in patients with schizophrenia is an increase in dopamine (DA) synthesis and release, restricted to the dorsal striatum (DS). This hyper functionality is strongly associated with psychotic symptoms and progresses in those who later transition to schizophrenia. To understand the implications of this progressive neurobiology on brain function, we have developed a model in rats which we refer to as EDiPs (Enhanced Dopamine in Prodromal schizophrenia). The EDiPs model features a virally mediated increase in dorsal striatal (DS) DA synthesis capacity across puberty and into adulthood. This protocol leads to progressive changes in behaviour and neurochemistry. Our aim in this study was to explore if increased DA synthesis capacity alters the physiology of DA release and DS connectivity. Using fast scan cyclic voltammetry to assess DA release we show that evoked/phasic DA release is increased in the DS of EDiPs rats, whereas tonic/background levels of DA remain unaffected. Using quantitative immunohistochemistry methods to quantify DS synaptic architecture we show a presynaptic marker for DA release sites (Bassoon) was elevated within TH axons specifically within the DS, consistent with the increased phasic DA release in this region. Alongside changes in DA systems, we also show increased density of vesicular glutamate transporter 1 (VGluT1) synapses in the EDiPs DS suggesting changes in cortical connectivity. Our data may prove relevant in understanding the long-term implications for DS function in response to the robust and prolonged increases in DA synthesis uptake and release reported in schizophrenia.

Neonatal phencyclidine as a model of sex-biased schizophrenia symptomatology in adolescent mice

Sex-biased differences in schizophrenia are evident in several features of the disease, including symptomatology and response to pharmacological treatments. As a neurodevelopmental disorder, these differences might originate early in life and emerge later during adolescence. Considering that the disruption of the glutamatergic system during development is known to contribute to schizophrenia, we hypothesized that the neonatal phencyclidine model could induce sex-dependent behavioral and neurochemical changes associated with this disorder during adolescence. C57BL/6 mice received either saline or phencyclidine (5, 10, or 20 mg/kg) on postnatal days (PN) 7, 9, and 11. Behavioral assessment occurred in late adolescence (PN48-50), when mice were submitted to the open field, social interaction, and prepulse inhibition tests. Either olanzapine or saline was administered before each test. The NMDAR obligatory GluN1 subunit and the postsynaptic density protein 95 (PSD-95) were evaluated in the frontal cortex and hippocampus at early (PN30) and late (PN50) adolescence. Neonatal phencyclidine evoked dose-dependent deficits in all analyzed behaviors and males were more susceptible. Males also had reduced GluN1 expression in the frontal cortex at PN30. There were late-emergent effects at PN50. Cortical GluN1 was increased in both sexes, while phencyclidine increased cortical and decreased hippocampal PSD-95 in females. Olanzapine failed to mitigate most phencyclidine-evoked alterations. In some instances, this antipsychotic aggravated the deficits or potentiated subthreshold effects. These results lend support to the use of neonatal phencyclidine as a sex-biased neurodevelopmental preclinical model of schizophrenia. Olanzapine null effects and deleterious outcomes suggest that its use during adolescence should be further evaluated.

Altered Brain Dynamics Across Bipolar Disorder and Schizophrenia During Rest and Task Switching Revealed by Overlapping Brain States

BACKGROUND

Individuals with bipolar disorder (BD) and schizophrenia (SCZ) show aberrant brain dynamics (i.e., altered recruitment or traversal through different brain states over time). Existing investigations of brain dynamics typically assume that one dominant brain state characterizes each time point. However, as multiple brain states likely are engaged at any given moment, this approach can obscure alterations in less prominent but critical brain states. Here, we examined brain dynamics in BD and SCZ by implementing a novel framework that simultaneously assessed the engagement of multiple brain states.

METHODS

Four recurring brain states were identified by applying nonlinear manifold learning and k-means clustering to the Human Connectome Project task-based functional magnetic resonance imaging data. We then assessed moment-to-moment state engagement in 2 independent samples of healthy control participants and patients with BD or SCZ using resting-state (N = 336) or task-based (N = 217) functional magnetic resonance imaging data. Relative state engagement and state engagement variability were extracted and compared across groups using multivariate analysis of covariance, controlling for site, medication, age, and sex.

RESULTS

Our framework identified dynamic alterations in BD and SCZ, while a state discretization approach revealed no significant group differences. Participants with BD or SCZ showed reduced state engagement variability, but not relative state engagement, across multiple brain states during resting-state and task-based functional magnetic resonance imaging. We found decreased state engagement variability in older participants and preliminary evidence suggesting an association with avolition.

CONCLUSIONS

Assessing multiple brain states simultaneously can reflect the complexity of aberrant brain dynamics in BD and SCZ, providing a more comprehensive understanding of the neural mechanisms underpinning these conditions.

Evidence for functional improvement in reward anticipation in recent onset schizophrenia after one year of coordinated specialty care

BACKGROUND

Motivational impairment associated with deficits in processing the anticipation of future reward is hypothesized to be a cardinal feature of schizophrenia spectrum disorders (SZ). Evidence from short-term follow-up (6-week post-treatment) studies suggests that these deficits may improve or be reversed with treatment, although longer-term outcomes are unknown. Here we examined the one-year trajectory of functional activation in brain circuitry associated with reward anticipation in people with recent onset SZ who participated in coordinated specialty care (CSC) treatment, hypothesizing normalization of brain response mirroring previous short-term findings in first-episode individuals.

METHOD

Blood oxygen level-dependent (BOLD) response in the dorsal anterior cingulate cortex, anterior insula, and ventral striatum (VS) associated with reward anticipation during the Incentivized Control Engagement Task (ICE-T) was analyzed in a baseline sample of 49 healthy controls (HCs) and 52 demographically matched people with SZ, with follow-up data available for 35 HCs and 17 people with SZ.

RESULTS

In agreement with our hypothesis, significant time × diagnosis interactions were observed across all regions, in which reward anticipation-associated BOLD response increased in SZ to above baseline HC levels at follow-up. Increased VS activation was associated with decreased reality distortion symptoms over the follow-up period. Baseline reward anticipation-associated BOLD response in the right anterior insula was associated with improvement in reality distortion symptoms.

CONCLUSIONS

These findings suggest that functional deficits in reward anticipation may be reversed after one year of CSC in recent onset participants with SZ, and that this improvement is associated with reduced positive symptoms in the illness.

Dopamine regulates decision thresholds in human reinforcement learning in males

Dopamine fundamentally contributes to reinforcement learning, but recent accounts also suggest a contribution to specific action selection mechanisms and the regulation of response vigour. Here, we examine dopaminergic mechanisms underlying human reinforcement learning and action selection via a combined pharmacological neuroimaging approach in male human volunteers (n = 31, within-subjects; Placebo, 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist Haloperidol). We found little credible evidence for previously reported beneficial effects of L-dopa vs. Haloperidol on learning from gains and altered neural prediction error signals, which may be partly due to differences experimental design and/or drug dosages. Reinforcement learning drift diffusion models account for learning-related changes in accuracy and response times, and reveal consistent decision threshold reductions under both drugs, in line with the idea that lower dosages of D2 receptor antagonists increase striatal DA release via an autoreceptor-mediated feedback mechanism. These results are in line with the idea that dopamine regulates decision thresholds during reinforcement learning, and may help to bridge action selection and response vigor accounts of dopamine.

10 Hz repetitive transcranial magnetic stimulation (rTMS) may improve cognitive function: An exploratory study of schizophrenia patients with auditory hallucinations

Objectives

Cognitive impairment in schizophrenia patients with auditory hallucinations is more prominent compared to those without. Our study aimed to investigate the cognitive improvement effects of 10 Hz repetitive transcranial magnetic stimulation (rTMS) over the left dorsolateral prefrontal cortex (DLPFC) in schizophrenia with auditory hallucinations.

Methods

A total of 60 schizophrenic patients with auditory hallucinations in this study were randomly assigned to sham or active group. Both groups received 10 Hz or sham rTMS targeted in left DLPFC for 20 sessions. The Positive and Negative Syndrome Scale (PANSS), the Auditory Hallucination Rating Scale (AHRS), the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and the Udvalg for Kliniske Under-sogelser (UKU) side effect scale were used to measure psychiatric symptoms, auditory hallucinations, cognition, and side reaction, respectively.

Results

Our results indicated that the active group experienced greater improvements in RBANS-total score (P = 0.043) and immediate memory subscale score (P = 0.001). Additionally, the PANSS-total score, negative and positive subscale score were obviously lower in the active group compared to the sham group (all P < 0.050). Furthermore, our study found that the improvement of RBANS-total score was positively associated with the decline of positive factor score, and the improvement of language score in RBANS was positively associated with the reduction in PANSS-total scale, negative and positive subscale score in the real stimulation group (all P < 0.050).

Conclusion

Our results demonstrated that a four-week intervention of 10 Hz rTMS over the left DLPFC can improve cognition (particularly immediate memory) among schizophrenia patients with auditory hallucinations. Future studies with larger sample size are needful to verify our preliminary findings.

Primary states of consciousness: A review of historical and contemporary developments

Primary states of consciousness are conceived as phylogenetically older states of consciousness as compared to secondary states governed by sociocultural inhibition. The historical development of the concept in psychiatry and neurobiology is reviewed, along with its relationship to theories of consciousness. We suggest that primary states of consciousness are characterized by a temporary breakdown of self-control accompanied by a merging of action, communication, and emotion (ACE fusion), ordinarily segregated in human adults. We examine the neurobiologic basis of this model, including its relation to the phenomenon of neural dedifferentiation, the loss of modularity during altered states of consciousness, and increased corticostriatal connectivity. By shedding light on the importance of primary states of consciousness, this article provides a novel perspective on the role of consciousness as a mechanism of differentiation and control. We discuss potential differentiators underlying a gradient from primary to secondary state of consciousness, suggesting changes in thalamocortical interactions and arousal function. We also propose a set of testable, neurobiologically plausible working hypotheses to account for their distinct phenomenological and neural signatures.

Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia

Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.

From Computation to Clinic

Theory-driven and data-driven computational approaches to psychiatry have enormous potential for elucidating mechanism of disease and providing translational linkages between basic science findings and the clinic. These approaches have already demonstrated utility in providing clinically relevant understanding, primarily via back translation from clinic to computation, revealing how specific disorders or symptoms map onto specific computational processes. Nonetheless, forward translation, from computation to clinic, remains rare. In addition, consensus regarding specific barriers to forward translation-and on the best strategies to overcome these barriers-is limited. This perspective review brings together expert basic and computationally trained researchers and clinicians to 1) identify challenges specific to preclinical model systems and clinical translation of computational models of cognition and affect, and 2) discuss practical approaches to overcoming these challenges. In doing so, we highlight recent evidence for the ability of computational approaches to predict treatment responses in psychiatric disorders and discuss considerations for maximizing the clinical relevance of such models (e.g., via longitudinal testing) and the likelihood of stakeholder adoption (e.g., via cost-effectiveness analyses).

Explainable drug side effect prediction via biologically informed graph neural network

Early detection of potential side effects (SE) is a critical and challenging task for drug discovery and patient care. In-vitro or in-vivo approach to detect potential SEs is not scalable for many drug candidates during the preclinical stage. Recent advances in explainable machine learning may facilitate detecting potential SEs of new drugs before market release and elucidating the critical mechanism of biological actions. Here, we leverage multi-modal interactions among molecules to develop a biologically informed graph-based SE prediction model, called HHAN-DSI. HHAN-DSI predicted frequent and even uncommon SEs of the unseen drug with higher or comparable accuracy against benchmark methods. When applying HHAN-DSI to the central nervous system, the organs with the largest number of SEs, the model revealed diverse psychiatric medications' previously unknown but probable SEs, together with the potential mechanisms of actions through a network of genes, biological functions, drugs, and SEs.

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.

Belief updating in psychosis, depression and anxiety disorders: A systematic review across computational modelling approaches

Alterations in belief updating are proposed to underpin symptoms of psychiatric illness, including psychosis, depression, and anxiety. Key parameters underlying belief updating can be captured using computational modelling techniques, aiding the identification of unique and shared deficits, and improving diagnosis and treatment. We systematically reviewed research that applied computational modelling to probabilistic tasks measuring belief updating in stable and volatile (changing) environments, across clinical and subclinical psychosis (n = 17), anxiety (n = 9), depression (n = 9) and transdiagnostic samples (n = 9). Depression disorders related to abnormal belief updating in response to the valence of rewards, evidenced in both stable and volatile environments. Whereas psychosis and anxiety disorders were associated with difficulties adapting to changing contingencies specifically, indicating an inflexibility and/or insensitivity to environmental volatility. Higher-order learning models revealed additional difficulties in the estimation of overall environmental volatility across psychosis disorders, showing increased updating to irrelevant information. These findings stress the importance of investigating belief updating in transdiagnostic samples, using homogeneous experimental and computational modelling approaches.

Maladaptive explore/exploit trade-offs in schizophrenia

Schizophrenia is a complex disorder that remains poorly understood, particularly at the systems level. In this opinion article we argue that the explore/exploit trade-off concept provides a holistic and ecologically valid framework to resolve some of the apparent paradoxes that have emerged within schizophrenia research. We review recent evidence suggesting that fundamental explore/exploit behaviors may be maladaptive in schizophrenia during physical, visual, and cognitive foraging. We also describe how theories from the broader optimal foraging literature, such as the marginal value theorem (MVT), could provide valuable insight into how aberrant processing of reward, context, and cost/effort evaluations interact to produce maladaptive responses.

Reward disturbances in antipsychotic-naïve patients with first-episode psychosis and their association to glutamate levels

BACKGROUND

Aberrant anticipation of motivational salient events and processing of outcome evaluation in striatal and prefrontal regions have been suggested to underlie psychosis. Altered glutamate levels have likewise been linked to schizophrenia. Glutamatergic abnormalities may affect the processing of motivational salience and outcome evaluation. It remains unresolved, whether glutamatergic dysfunction is associated with the coding of motivational salience and outcome evaluation in antipsychotic-naïve patients with first-episode psychosis.

METHODS

Fifty-one antipsychotic-naïve patients with first-episode psychosis (22 ± 5.2 years, female/male: 31/20) and 52 healthy controls (HC) matched on age, sex, and parental education underwent functional magnetic resonance imaging and magnetic resonance spectroscopy (3T) in one session. Brain responses to motivational salience and negative outcome evaluation (NOE) were examined using a monetary incentive delay task. Glutamate levels were estimated in the left thalamus and anterior cingulate cortex using LCModel.

RESULTS

Patients displayed a positive signal change to NOE in the caudate (p = 0.001) and dorsolateral prefrontal cortex (DLPFC; p = 0.003) compared to HC. No group difference was observed in motivational salience or in levels of glutamate. There was a different association between NOE signal in the caudate and DLPFC and thalamic glutamate levels in patients and HC due to a negative correlation in patients (caudate: p = 0.004, DLPFC: p = 0.005) that was not seen in HC.

CONCLUSIONS

Our findings confirm prior findings of abnormal outcome evaluation as a part of the pathophysiology of schizophrenia. The results also suggest a possible link between thalamic glutamate and NOE signaling in patients with first-episode psychosis.

Perimenopausal Effects of Estradiol on Anhedonia and Psychosis Study (PEEPs): study protocol for a neural and molecular mechanistic clinical trial

BACKGROUND

The perimenopausal transition is accompanied by psychiatric symptoms in over 10% of women. Symptoms commonly include depressed mood and anhedonia and less commonly include psychosis. Psychiatric symptoms have been linked to the depletion and/or variability of circulating estradiol, and estradiol treatment reduces perimenopausal anhedonia and psychosis in some women. Estrogen fluctuations may disrupt function in the mesolimbic reward system in some women, leading to psychiatric symptoms like anhedonia or psychosis. The Perimenopausal Effects of Estradiol on Anhedonia and Psychosis Study (PEEPs) is a mechanistic clinical trial that aims to (1) identify relationships between perimenopausal-onset anhedonia and psychosis and neuromolecular markers of mesolimbic reward responses and (2) determine the extent to which estradiol treatment-induced changes in mesolimbic reward responses are associated with alleviation of perimenopausal onset anhedonia or psychosis.

METHODS

This study will recruit 100 unmedicated women ages 44-55 in the late-stage perimenopausal transition, sampling across the range of mild-to-high anhedonia and absent-to-moderate psychosis symptoms. Patients will be randomized to receive either estradiol or placebo treatment for 3 weeks. Clinical outcome measures will include symptoms of anhedonia (measured with Snaith-Hamilton Pleasure Scale; SHAPS) and psychosis (measured with Brief Psychiatric Rating Scale; BPRS psychosis subscale) as well as neural markers of mesolimbic reward system functioning, including reward-related fMRI activation and PET-derived measure of striatal dopamine binding. Pre-treatment associations between (1) SHAPS/BPRS scores and (2) reward-related striatal dopamine binding/BOLD activation will be examined. Furthermore, longitudinal mixed models will be used to estimate (1) symptom and neuromolecular trajectories as a function of estradiol vs. placebo treatment and (2) how changes in reward-related striatal dopamine binding and BOLD activation predict variability in symptom trajectories in response to estradiol treatment.

DISCUSSION

This clinical trial will be the first to characterize neural and molecular mechanisms by which estradiol treatment ameliorates anhedonia and psychosis symptoms during the perimenopausal transition, thus laying the groundwork for future biomarker research to predict susceptibility and prognosis and develop targeted treatments for perimenopausal psychiatric symptoms. Furthermore, in alignment with the National Institute for Mental Health Research Domain Criteria initiative, this trial will improve our understanding of a range of disorders characterized by anhedonia, psychosis, and reward system dysfunction.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05282277.

Nanosystems for Brain Targeting of Antipsychotic Drugs: An Update on the Most Promising Nanocarriers for Increased Bioavailability and Therapeutic Efficacy

Orally administered antipsychotic drugs are the first-line treatment for psychotic disorders, such as schizophrenia and bipolar disorder. Nevertheless, adverse drug reactions jeopardize clinical outcomes, resulting in patient non-compliance. The design formulation strategies for enhancing brain drug delivery has been a major challenge, mainly due to the restrictive properties of the blood-brain barrier. However, recent pharmacokinetic and pharmacodynamic in vivo assays confirmed the advantage of the intranasal route when compared to oral and intravenous administration, as it allows direct nose-to-brain drug transport via neuronal pathways, reducing systemic side effects and maximizing therapeutic outcomes. In addition, the incorporation of antipsychotic drugs into nanosystems such as polymeric nanoparticles, polymeric mixed micelles, solid lipid nanoparticles, nanostructured lipid carriers, nanoemulsions, nanoemulgels, nanosuspensions, niosomes and spanlastics, has proven to be quite promising. The developed nanosystems, having a small and homogeneous particle size (ideal for nose-to-brain delivery), high encapsulation efficiency and good stability, resulted in improved brain bioavailability and therapeutic-like effects in animal models. Hence, although it is essential to continue research in this field, the intranasal delivery of nanosystems for the treatment of schizophrenia, bipolar disorder and other related disorders has proven to be quite promising, opening a path for future therapies with higher efficacy.

Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum

Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.

Understanding cingulotomy's therapeutic effect in OCD through computer models

Cingulotomy is therapeutic in OCD, but what are the possible mechanisms? Computer models that formalize cortical OCD abnormalities and anterior cingulate cortex (ACC) function can help answer this. At the neural dynamics level, cortical dynamics in OCD have been modeled using attractor networks, where activity patterns resistant to change denote the inability to switch to new patterns, which can reflect inflexible thinking patterns or behaviors. From that perspective, cingulotomy might reduce the influence of difficult-to-escape ACC attractor dynamics on other cortical areas. At the functional level, computer formulations based on model-free reinforcement learning (RL) have been used to describe the multitude of phenomena ACC is involved in, such as tracking the timing of expected outcomes and estimating the cost of exerting cognitive control and effort. Different elements of model-free RL models of ACC could be affected by the inflexible cortical dynamics, making it challenging to update their values. An agent can also use a world model, a representation of how the states of the world change, to plan its actions, through model-based RL. OCD has been hypothesized to be driven by reduced certainty of how the brain's world model describes changes. Cingulotomy might improve such uncertainties about the world and one's actions, making it possible to trust the outcomes of these actions more and thus reduce the urge to collect more sensory information in the form of compulsions. Connecting the neural dynamics models with the functional formulations can provide new ways of understanding the role of ACC in OCD, with potential therapeutic insights.

Adaptive control of synaptic plasticity integrates micro- and macroscopic network function

Synaptic plasticity configures interactions between neurons and is therefore likely to be a primary driver of behavioral learning and development. How this microscopic-macroscopic interaction occurs is poorly understood, as researchers frequently examine models within particular ranges of abstraction and scale. Computational neuroscience and machine learning models offer theoretically powerful analyses of plasticity in neural networks, but results are often siloed and only coarsely linked to biology. In this review, we examine connections between these areas, asking how network computations change as a function of diverse features of plasticity and vice versa. We review how plasticity can be controlled at synapses by calcium dynamics and neuromodulatory signals, the manifestation of these changes in networks, and their impacts in specialized circuits. We conclude that metaplasticity-defined broadly as the adaptive control of plasticity-forges connections across scales by governing what groups of synapses can and can't learn about, when, and to what ends. The metaplasticity we discuss acts by co-opting Hebbian mechanisms, shifting network properties, and routing activity within and across brain systems. Asking how these operations can go awry should also be useful for understanding pathology, which we address in the context of autism, schizophrenia and Parkinson's disease.

Action selection in early stages of psychosis: an active inference approach

BACKGROUND

To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls.

METHODS

Twenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification.

RESULTS

We found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures.

LIMITATIONS

The sample size is moderate.

CONCLUSION

Active inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis.

Strong Binding of Phytochemicals to the Catalytic Domain of Tyrosine Hydroxylase as a Trojan Horse Decreases Dopamine in Dopaminergic Cells: Pharmaceutical Considerations in Schizophrenia and Parkinson's Disease

BACKGROUND

Imbalances in dopamine levels result in neurological and psychological disorders such as elevated dopamine in Parkinson's disease.

OBJECTIVE

Despite a considerable number of advertisements claiming Aloe-vera's effectiveness in PD treatment, it has hidden long-term disadvantages for healthy people and PD patients.

METHODS

In the present investigation, the impacts of Aloe-vera on dopaminergic cells were evaluated.

RESULTS

The results indicated that the focal adhesion kinase (FAK) enhancement was in line with the Bax/Bcl2 ratio decrement, reactive oxygen specious (ROS) production, and nonsignificant alteration in the sub-G1phase of the cell cycle. It led to glial cell-derived neurotrophic factor (GDNF) upregulation but did not significantly change the BDNF level involved in depression and motor impairment recovery. These events apparently resulted in the enhancement in dopaminergic cell viability and neurite length and attenuated PI+ cells. However, it also induced neuronal nitric oxide synthase (nNOS) overexpression and nitric oxide (NO) and lactate dehydrogenase (LDH) production. Notably, docking results of the catalytic domain in tyrosine hydroxylase (TH) with the Aloe-vera constituents showed strong binding of most Aloe-vera constituents with the catalytic domain of TH, even stronger than L-tyrosine as an original substrate. Following the docking results, Aloe-vera downregulated TH protein and attenuated dopamine.

CONCLUSION

It can be hypothesized that Aloe-vera improves PD symptoms through enhancement in antiapoptotic markers and neurotrophic factors, while it suppresses TH and dopamine in the form of a Trojan horse, later resulting in the future deterioration of the disease symptoms. The results provide cues to pharmaceutical companies to use the active components of Aloe-vera as putative agents in neurological and psychiatric disorders and diseases to decrease dopamine in patients with enhanced dopamine levels.

Computational reinforcement learning, reward (and punishment), and dopamine in psychiatric disorders

In the DSM-5, psychiatric diagnoses are made based on self-reported symptoms and clinician-identified signs. Though helpful in choosing potential interventions based on the available regimens, this conceptualization of psychiatric diseases can limit basic science investigation into their underlying causes. The reward prediction error (RPE) hypothesis of dopamine neuron function posits that phasic dopamine signals encode the difference between the rewards a person expects and experiences. The computational framework from which this hypothesis was derived, temporal difference reinforcement learning (TDRL), is largely focused on reward processing rather than punishment learning. Many psychiatric disorders are characterized by aberrant behaviors, expectations, reward processing, and hypothesized dopaminergic signaling, but also characterized by suffering and the inability to change one's behavior despite negative consequences. In this review, we provide an overview of the RPE theory of phasic dopamine neuron activity and review the gains that have been made through the use of computational reinforcement learning theory as a framework for understanding changes in reward processing. The relative dearth of explicit accounts of punishment learning in computational reinforcement learning theory and its application in neuroscience is highlighted as a significant gap in current computational psychiatric research. Four disorders comprise the main focus of this review: two disorders of traditionally hypothesized hyperdopaminergic function, addiction and schizophrenia, followed by two disorders of traditionally hypothesized hypodopaminergic function, depression and post-traumatic stress disorder (PTSD). Insights gained from a reward processing based reinforcement learning framework about underlying dopaminergic mechanisms and the role of punishment learning (when available) are explored in each disorder. Concluding remarks focus on the future directions required to characterize neuropsychiatric disorders with a hypothesized cause of underlying dopaminergic transmission.

Variables influencing conditioning-evoked hallucinations: overview and future applications

Hallucinations occur in the absence of sensory stimulation and result in vivid perceptual experiences of nonexistent events that manifest across a range of sensory modalities. Approaches from the field of experimental and cognitive psychology have leveraged the idea that associative learning experiences can evoke conditioning-induced hallucinations in both animals and humans. In this review, we describe classical and contemporary findings and highlight the variables eliciting these experiences. We also provide an overview of the neurobiological mechanisms, along with the associative and computational factors that may explain hallucinations that are generated by representation-mediated conditioning phenomena. Through the integration of animal and human research, significant advances into the psychobiology of hallucinations are possible, which may ultimately translate to more effective clinical applications.

Cognitive [Computational] Neuroscience Test Reliability and Clinical Applications for Serious Mental Illness (CNTRaCS) Consortium: Progress and Future Directions

The development of treatments for impaired cognition in schizophrenia has been characterized as the most important challenge facing psychiatry at the beginning of the twenty-first century. The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) project was designed to build on the potential benefits of using tasks and tools from cognitive neuroscience to better understanding and treat cognitive impairments in psychosis. These benefits include: (1) the use of fine-grained tasks that measure discrete cognitive processes; (2) the ability to design tasks that distinguish between specific cognitive domain deficits and poor performance due to generalized deficits resulting from sedation, low motivation, poor test taking skills, etc.; and (3) the ability to link cognitive deficits to specific neural systems, using animal models, neuropsychology, and functional imaging. CNTRICS convened a series of meetings to identify paradigms from cognitive neuroscience that maximize these benefits and identified the steps need for translation into use in clinical populations. The Cognitive Neuroscience Test Reliability and Clinical Applications for Schizophrenia (CNTRaCS) Consortium was developed to help carry out these steps. CNTRaCS consists of investigators at five different sites across the country with diverse expertise relevant to a wide range of the cognitive systems identified as critical as part of CNTRICs. This work reports on the progress and current directions in the evaluation and optimization carried out by CNTRaCS of the tasks identified as part of the original CNTRICs process, as well as subsequent extensions into the Positive Valence systems domain of Research Domain Criteria (RDoC). We also describe the current focus of CNTRaCS, which involves taking a computational psychiatry approach to measuring cognitive and motivational function across the spectrum of psychosis. Specifically, the current iteration of CNTRaCS is using computational modeling to isolate parameters reflecting potentially more specific cognitive and visual processes that may provide greater interpretability in understanding shared and distinct impairments across psychiatric disorders.

Delayed improvements in visual memory task performance among chronic schizophrenia patients after high-frequency repetitive transcranial magnetic stimulation

BACKGROUND

Cognitive impairments are core characteristics of schizophrenia, but are largely resistant to current treatments. Several recent studies have shown that high-frequency repetitive transcranial magnetic stimulation (rTMS) of the left dor-solateral prefrontal cortex (DLPFC) can reduce negative symptoms and improve certain cognitive deficits in schizophrenia patients. However, results are inconsistent across studies.

AIM

To examine if high-frequency rTMS of the DLPFC can improve visual memory deficits in patients with schizophrenia.

METHODS

Forty-seven chronic schizophrenia patients with severe negative symptoms on stable treatment regimens were randomly assigned to receive active rTMS to the DLPFC (n = 25) or sham stimulation (n = 22) on weekdays for four consecutive weeks. Patients performed the pattern recognition memory (PRM) task from the Cambridge Neuropsychological Test Automated Battery at baseline, at the end of rTMS treatment (week 4), and 4 wk after rTMS treatment (week 8). Clinical symptoms were also measured at these same time points using the Scale for the Assessment of Negative Symptoms (SANS) and the Positive and Negative Syndrome Scale (PANSS).

RESULTS

There were no significant differences in PRM performance metrics, SANS total score, SANS subscores, PANSS total score, and PANSS subscores between active and sham rTMS groups at the end of the 4-wk treatment period, but PRM performance metrics (percent correct and number correct) and changes in these metrics from baseline were significantly greater in the active rTMS group at week 8 compared to the sham group (all P < 0.05). Active rTMS treatment also significantly reduced SANS score at week 8 compared to sham treatment. Moreover, the improvement in visual memory was correlated with the reduction in negative symptoms at week 8. In contrast, there were no between-group differences in PANSS total score and subscale scores at either week 4 or week 8 (all P > 0.05).

CONCLUSION

High-frequency transcranial magnetic stimulation improves visual memory and reduces negative symptoms in schizophrenia, but these effects are delayed, potentially due to the requirement for extensive neuroplastic changes within DLPFC networks.

Comparing adaptive coding of reward in bipolar I disorder and schizophrenia

Deficits in neural processing of reward have been described in both bipolar disorder (BD) and schizophrenia (SZ), but it remains unclear to what extent these deficits are caused by similar mechanisms. Efficient reward processing relies on adaptive coding which allows representing large input spans by limited neuronal encoding ranges. Deficits in adaptive coding of reward have previously been observed across the SZ spectrum and correlated with total symptom severity. In the present work, we sought to establish whether adaptive coding is similarly affected in patients with BD. Twenty-five patients with BD, 27 patients with SZ and 25 healthy controls performed a variant of the Monetary Incentive Delay task during functional magnetic resonance imaging in two reward range conditions. Adaptive coding was impaired in the posterior part of the right caudate in BD and SZ (trend level). In contrast, BD did not show impaired adaptive coding in the anterior caudate and right precentral gyrus/insula, where SZ showed deficits compared to healthy controls. BD patients show adaptive coding deficits that are similar to those observed in SZ in the right posterior caudate. Adaptive coding in BD appeared more preserved as compared to SZ participants especially in the more anterior part of the right caudate and to a lesser extent also in the right precentral gyrus. Thus, dysfunctional adaptive coding could constitute a fundamental deficit in severe mental illnesses that extends beyond the SZ spectrum.

Analysis of individual differences in neurofeedback training illuminates successful self-regulation of the dopaminergic midbrain

The dopaminergic midbrain is associated with reinforcement learning, motivation and decision-making - functions often disturbed in neuropsychiatric disorders. Previous research has shown that dopaminergic midbrain activity can be endogenously modulated via neurofeedback. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we examine whether the activation of particular brain regions associates with successful regulation transfer when feedback is no longer available. Moreover, to elucidate mechanisms underlying effective self-regulation, we study the relation of successful transfer with learning (temporal difference coding) outside the midbrain during neurofeedback training and with individual reward sensitivity in a monetary incentive delay (MID) task. Fifty-nine participants underwent neurofeedback training either in standard (Study 1 N = 15, Study 2 N = 28) or control feedback group (Study 1, N = 16). We find that successful self-regulation is associated with prefrontal reward sensitivity in the MID task (N = 25), with a decreasing relation between prefrontal activity and midbrain learning signals during neurofeedback training and with increased activity within cognitive control areas during transfer. The association between midbrain self-regulation and prefrontal temporal difference and reward sensitivity suggests that reinforcement learning contributes to successful self-regulation. Our findings provide insights in the control of midbrain activity and may facilitate individually tailoring neurofeedback training.

Functional neuroimaging in psychiatry and the case for failing better

Psychiatric disorders encompass complex aberrations of cognition and affect and are among the most debilitating and poorly understood of any medical condition. Current treatments rely primarily on interventions that target brain function (drugs) or learning processes (psychotherapy). A mechanistic understanding of how these interventions mediate their therapeutic effects remains elusive. From the early 1990s, non-invasive functional neuroimaging, coupled with parallel developments in the cognitive neurosciences, seemed to signal a new era of neurobiologically grounded diagnosis and treatment in psychiatry. Yet, despite three decades of intense neuroimaging research, we still lack a neurobiological account for any psychiatric condition. Likewise, functional neuroimaging plays no role in clinical decision making. Here, we offer a critical commentary on this impasse and suggest how the field might fare better and deliver impactful neurobiological insights.