Computational models of schizophrenia and dopamine modulation in the prefrontal cortex

Age-related changes in the ease of dynamical transitions in human brain activity

Executive functions, a set of cognitive processes that enable flexible behavioral control, are known to decay with aging. Because such complex mental functions are considered to rely on the dynamic coordination of functionally different neural systems, the age-related decline in executive functions should be underpinned by alteration of large-scale neural dynamics. However, the effects of age on brain dynamics have not been firmly formulated. Here, we investigate such age-related changes in brain dynamics by applying "energy landscape analysis" to publicly available functional magnetic resonance imaging data from healthy younger and older human adults. We quantified the ease of dynamical transitions between different major patterns of brain activity, and estimated it for the default mode network (DMN) and the cingulo-opercular network (CON) separately. We found that the two age groups shared qualitatively the same trajectories of brain dynamics in both the DMN and CON. However, in both of networks, the ease of transitions was significantly smaller in the older than the younger group. Moreover, the ease of transitions was associated with the performance in executive function tasks in a doubly dissociated manner: for the younger adults, the ability of executive functions was mainly correlated with the ease of transitions in the CON, whereas that for the older adults was specifically associated with the ease of transitions in the DMN. These results provide direct biological evidence for age-related changes in macroscopic brain dynamics and suggest that such neural dynamics play key roles when individuals carry out cognitively demanding tasks.

Dorsal Forebrain-Specific Deficiency of Reelin-Dab1 Signal Causes Behavioral Abnormalities Related to Psychiatric Disorders

Reelin-Dab1 signaling is involved in brain development and neuronal functions. The abnormalities in the signaling through either reduction of Reelin and Dab1 gene expressions or the genomic mutations in the brain have been reported to be associated with psychiatric disorders. However, it has not been clear if the deficiency in Reelin-Dab1 signaling is responsible for symptoms of the disorders. Here, to examine the function of Reelin-Dab1 signaling in the forebrain, we generated dorsal forebrain-specific Dab1 conditional knockout mouse (Dab1 cKO) and performed a behavioral test battery on the Dab1 cKO mice. Although conventional Dab1 null mutant mice exhibit cerebellar atrophy and cerebellar ataxia, the Dab1 cKO mice had normal cerebellum and showed no motor dysfunction. Dab1 cKO mice exhibited behavioral abnormalities, including hyperactivity, decreased anxiety-like behavior, and impairment of working memory, which are reminiscent of symptoms observed in patients with psychiatric disorders such as schizophrenia and bipolar disorder. These results suggest that deficiency of Reelin-Dab1 signal in the dorsal forebrain is involved in the pathogenesis of some symptoms of human psychiatric disorders.

Psychosis subgroups differ in intrinsic neural activity but not task-specific processing

Individuals with psychosis often show high levels of intrinsic, or nonspecific, neural activity, but attenuated stimulus-specific activity. Clementz et al. (2016) proposed that one subgroup of psychosis cases has accentuated intrinsic activity (Biotype-2's) and a different subgroup (Biotype-1's) has diminished intrinsic activity, with both groups exhibiting varying degrees of cognitive deficits. This model was studied by assessing neural activity in psychosis probands (N=105) during baseline and a 5second period in preparation for a pro-/anti-saccade task. Steady-state stimuli allowed real-time assessment of modulation of visuocortical investment to different target locations. Psychosis probands as a whole showed poor antisaccade performance. As expected, Biotype-1 showed diminished intrinsic neural activity and the worst behavior, and Biotype-2 showed accentuated intrinsic activity and less deviant behavior. Both of these groups also exhibited less dynamic oscillatory phase synchrony. Biotype-3 showed no neurophysiological differences from healthy individuals, despite a history of psychosis. Interestingly, all psychosis subgroups showed normal (i.e., not different from healthy) preparatory modulation of visuocortical investment as a function of cognitive demands, despite varying levels of task performance. Similar analyses conducted subgrouping cases by psychotic symptomatology revealed fewer and less consistent differences, including no intrinsic activity differences between any clinical subgroup and healthy individuals. This study illustrates that (i) differences in intrinsic neural activity may be a fundamental characteristic of psychosis and need to be evaluated separately from stimulus-specific responses, and (ii) grouping patients based on multidimensional classification using neurobiological data may have advantages for resolving heterogeneity and clarifying illness mechanisms relative to traditional psychiatric diagnoses.

Coupling of respiration and attention via the locus coeruleus: Effects of meditation and pranayama

The locus coeruleus (LC) has established functions in both attention and respiration. Good attentional performance requires optimal levels of tonic LC activity, and must be matched to task consistently. LC neurons are chemosensitive, causing respiratory phrenic nerve firing to increase frequency with higher CO₂ levels, and as CO₂ level varies with the phase of respiration, tonic LC activity should exhibit fluctuations at respiratory frequency. Top-down modulation of tonic LC activity from brain areas involved in attentional regulation, intended to optimize LC firing to suit task requirements, may have respiratory consequences as well, as increases in LC activity influence phrenic nerve firing. We hypothesize that, due to the physiological and functional overlaps of attentional and respiratory functions of the LC, this small neuromodulatory nucleus is ideally situated to act as a mechanism of synchronization between respiratory and attentional systems, giving rise to a low-amplitude oscillation that enables attentional flexibility, but may also contribute to unintended destabilization of attention. Meditative and pranayama practices result in attentional, emotional, and physiological enhancements that may be partially due to the LC's pivotal role as the nexus in this coupled system. We present original findings of synchronization between respiration and LC activity (via fMRI and pupil dilation) and provide evidence of a relationship between respiratory phase modulation and attentional performance. We also present a mathematical dynamical systems model of respiratory-LC-attentional coupling, review candidate neurophysiological mechanisms of changes in coupling dynamics, and discuss implications for attentional theory, meditation, and pranayama, and possible therapeutic applications.

A Perceptual Inference Mechanism for Hallucinations Linked to Striatal Dopamine

Hallucinations, a cardinal feature of psychotic disorders such as schizophrenia, are known to depend on excessive striatal dopamine. However, an underlying cognitive mechanism linking dopamine dysregulation and the experience of hallucinatory percepts remains elusive. Bayesian models explain perception as an optimal combination of prior expectations and new sensory evidence, where perceptual distortions such as illusions and hallucinations may occur if prior expectations are afforded excessive weight. Such excessive weight of prior expectations, in turn, could stem from a gain-control process controlled by neuromodulators such as dopamine. To test for such a dopamine-dependent gain-control mechanism of hallucinations, we studied unmedicated patients with schizophrenia with varying degrees of hallucination severity and healthy individuals using molecular imaging with a pharmacological manipulation of dopamine, structural imaging, and a novel task designed to measure illusory changes in the perceived duration of auditory stimuli under different levels of uncertainty. Hallucinations correlated with a perceptual bias, reflecting disproportional gain on expectations under uncertainty. This bias could be pharmacologically induced by amphetamine, strongly correlated with striatal dopamine release, and related to cortical volume of the dorsal anterior cingulate, a brain region involved in tracking environmental uncertainty. These findings outline a novel dopamine-dependent mechanism for perceptual modulation in physiological conditions and further suggest that this mechanism may confer vulnerability to hallucinations in hyper-dopaminergic states underlying psychosis.

Psilocybin disrupts sensory and higher order cognitive processing but not pre-attentive cognitive processing-study on P300 and mismatch negativity in healthy volunteers

RATIONALE

Disruption of auditory event-related evoked potentials (ERPs) P300 and mismatch negativity (MMN), electrophysiological markers of attentive and pre-attentive cognitive processing, is repeatedly described in psychosis and schizophrenia. Similar findings were observed in a glutamatergic model of psychosis, but the role of serotonergic 5-HT_2A receptors in information processing is less clear.

OBJECTIVES

We studied ERPs in a serotonergic model of psychosis, induced by psilocybin, a psychedelic with 5-HT_2A/C agonistic properties, in healthy volunteers.

METHODS

Twenty subjects (10M/10F) were given 0.26 mg/kg of psilocybin orally in a placebo-controlled, double-blind, cross-over design. ERPs (P300, MMN) were registered during the peak of intoxication. Correlations between measured electrophysiological variables and psilocin serum levels and neuropsychological effects were also analyzed.

RESULTS

Psilocybin induced robust psychedelic effects and psychotic-like symptoms, decreased P300 amplitude (p = 0.009) but did not affect the MMN. Psilocybin's disruptive effect on P300 correlated with the intensity of the psychedelic state, which was dependent on the psilocin serum levels. We also observed a decrease in N100 amplitude (p = 0.039) in the P300 paradigm and a negative correlation between P300 and MMN amplitude (p = 0.014).

CONCLUSIONS

Even though pre-attentive cognition (MMN) was not affected, processing at the early perceptual level (N100) and in higher-order cognition (P300) was significantly disrupted by psilocybin. Our results have implications for the role of 5-HT_2A receptors in altered information processing in psychosis and schizophrenia.

A Computational Model of Major Depression: the Role of Glutamate Dysfunction on Cingulo-Frontal Network Dynamics

Major depression disease (MDD) is associated with the dysfunction of multinode brain networks. However, converging evidence implicates the reciprocal interaction between midline limbic regions (typified by the ventral anterior cingulate cortex, vACC) and the dorso-lateral prefrontal cortex (dlPFC), reflecting interactions between emotions and cognition. Furthermore, growing evidence suggests a role for abnormal glutamate metabolism in the vACC, while serotonergic treatments (selective serotonin reuptake inhibitor, SSRI) effective for many patients implicate the serotonin system. Currently, no mechanistic framework describes how network dynamics, glutamate, and serotonin interact to explain MDD symptoms and treatments. Here, we built a biophysical computational model of 2 areas (vACC and dlPFC) that can switch between emotional and cognitive processing. MDD networks were simulated by slowing glutamate decay in vACC and demonstrated sustained vACC activation. This hyperactivity was not suppressed by concurrent dlPFC activation and interfered with expected dlPFC responses to cognitive signals, mimicking cognitive dysfunction seen in MDD. Simulation of clinical treatments (SSRI or deep brain stimulation) counteracted this aberrant vACC activity. Theta and beta/gamma oscillations correlated with network function, representing markers of switch-like operation in the network. The model shows how glutamate dysregulation can cause aberrant brain dynamics, respond to treatments, and be reflected in EEG rhythms as biomarkers of MDD.

Neuromodulatory Systems and Their Interactions: A Review of Models, Theories, and Experiments

Neuromodulatory systems, including the noradrenergic, serotonergic, dopaminergic, and cholinergic systems, track environmental signals, such as risks, rewards, novelty, effort, and social cooperation. These systems provide a foundation for cognitive function in higher organisms; attention, emotion, goal-directed behavior, and decision-making derive from the interaction between the neuromodulatory systems and brain areas, such as the amygdala, frontal cortex, hippocampus, and sensory cortices. Given their strong influence on behavior and cognition, these systems also play a key role in disease states and are the primary target of many current treatment strategies. The fact that these systems interact with each other either directly or indirectly, however, makes it difficult to understand how a failure in one or more systems can lead to a particular symptom or pathology. In this review, we explore experimental evidence, as well as focus on computational and theoretical models of neuromodulation. Better understanding of neuromodulatory systems may lead to the development of novel treatment strategies for a number of brain disorders.

Individual differences in schizophrenia

BACKGROUND

Whether there are distinct subtypes of schizophrenia is an important issue to advance understanding and treatment of schizophrenia.

AIMS

To understand and treat individuals with schizophrenia, the aim was to advance understanding of differences between individuals, whether there are discrete subtypes, and how first-episode patients (FEP) may differ from multiple episode patients (MEP).

METHOD

These issues were analysed in 687 FEP and 1880 MEP with schizophrenia using the Positive and Negative Syndrome Scale for (PANSS) schizophrenia before and after antipsychotic medication for 6 weeks.

RESULTS

The seven Negative Symptoms were correlated with each other and with P2 (conceptual disorganisation), G13 (disturbance of volition), and G7 (motor retardation). The main difference between individuals was in the cluster of seven negative symptoms, which had a continuous unimodal distribution. Medication decreased the PANSS scores for all the symptoms, which were similar in the FEP and MEP groups.

CONCLUSIONS

The negative symptoms are a major source of individual differences, and there are potential implications for treatment.

DECLARATION OF INTERESTS

L.P. received speaker fees from Otsuka Canada and educational grant from Janssen Canada in 2017.

COPYRIGHT AND USAGE

© The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

Protein Kinase A Deregulation in the Medial Prefrontal Cortex Impairs Working Memory in Murine Oligophrenin-1 Deficiency

Classical and systems genetics have identified wide networks of genes associated with cognitive and neurodevelopmental diseases. In parallel to deciphering the role of each of these genes in neuronal or synaptic function, evaluating the response of neuronal and molecular networks to gene loss of function could reveal some pathophysiological mechanisms potentially accessible to nongenetic therapies. Loss of function of the Rho-GAP oligophrenin-1 is associated with cognitive impairments in both human and mouse. Upregulation of both PKA and ROCK has been reported in Ophn1^-/y mice, but it remains unclear whether kinase hyperactivity contributes to the behavioral phenotypes. In this study, we thoroughly characterized a prominent perseveration phenotype displayed by Ophn1-deficient mice using a Y-maze spatial working memory (SWM) test. We report that Ophn1 deficiency in the mouse generated severe cognitive impairments, characterized by both a high occurrence of perseverative behaviors and a lack of deliberation during the SWM test. In vivo and in vitro pharmacological experiments suggest that PKA dysregulation in the mPFC underlies cognitive dysfunction in Ophn1-deficient mice, as assessed using a delayed spatial alternation task results. Functionally, mPFC neuronal networks appeared to be affected in a PKA-dependent manner, whereas hippocampal-PFC projections involved in SWM were not affected in Ophn1^-/y mice. Thus, we propose that discrete gene mutations in intellectual disability might generate "secondary" pathophysiological mechanisms, which are prone to become pharmacological targets for curative strategies in adult patients.SIGNIFICANCE STATEMENT Here we report that Ophn1 deficiency generates severe impairments in performance at spatial working memory tests, characterized by a high occurrence of perseverative behaviors and a lack of decision making. This cognitive deficit is consecutive to PKA deregulation in the mPFC that prevents Ophn1 KO mice to exploit a correctly acquired rule. Functionally, mPFC neuronal networks appear to be affected in a PKA-dependent manner, whereas behaviorally important hippocampal projections were preserved by the mutation. Thus, we propose that discrete gene mutations in intellectual disability can generate "secondary" pathophysiological mechanisms prone to become pharmacological targets for curative strategies in adults.

Pattern of gene expression in different stages of schizophrenia: Down-regulation of NPTX2 gene revealed by a meta-analysis of microarray datasets

Schizophrenia (SCZ) is a severe psychiatric disorder with a genetic susceptibility. Alterations in neurochemical signaling, as well as changes in brain structure and function, manifest during the course of SCZ and are likely causative of the symptoms shown by affected individuals. However, little is known about the timing of these changes, particularly in the pre-morbid and prodromal phases of SCZ. Here, we performed a gene-based and pathway-based meta-analysis of 5 microarray datasets from human induced pluripotent stem cells (hiPSCs)-derived neurons and post-mortem brain tissue from SCZ and healthy controls (HC), with the underlying assumption they might represent the neurobiological make-up of SCZ in the pre-morbid and chronic stages of illness, respectively. Thus, we identified 1 microarray expression profiling dataset of hiPSCs-derived neurons (GSE25673) and performed a systematic search of microarray expression profiling datasets from SCZ post-mortem brain publicly available on the Gene Expression Omnibus (GEO) repository. We selected 4 different SCZ post-mortem brain microarray expression profiling datasets (GSE17612, GSE21935, GSE12649, and GSE21338) according to specific inclusion and exclusion criteria. We downloaded raw data and performed quality controls, differential expression analysis, and gene-based, as well as pathway-based meta-analysis. Neuronal pentraxin 2 (NPTX2) gene was consistently down-regulated across all datasets, with highly significant association in the meta-analysis (FDR<1.0E-04). These results highlight the heuristic value of microarray meta-analysis and suggest a role of NPTX2 as a disease biomarker, provided that it achieves biological validation in future studies examining whether this down-regulation has predictive value with respect to the developmental trajectory of SCZ.

Comprehensive review: Computational modelling of schizophrenia

Computational modelling has been used to address: (1) the variety of symptoms observed in schizophrenia using abstract models of behavior (e.g. Bayesian models - top-down descriptive models of psychopathology); (2) the causes of these symptoms using biologically realistic models involving abnormal neuromodulation and/or receptor imbalance (e.g. connectionist and neural networks - bottom-up realistic models of neural processes). These different levels of analysis have been used to answer different questions (i.e. understanding behavioral vs. neurobiological anomalies) about the nature of the disorder. As such, these computational studies have mostly supported diverging hypotheses of schizophrenia's pathophysiology, resulting in a literature that is not always expanding coherently. Some of these hypotheses are however ripe for revision using novel empirical evidence. Here we present a review that first synthesizes the literature of computational modelling for schizophrenia and psychotic symptoms into categories supporting the dopamine, glutamate, GABA, dysconnection and Bayesian inference hypotheses respectively. Secondly, we compare model predictions against the accumulated empirical evidence and finally we identify specific hypotheses that have been left relatively under-investigated.

Latching dynamics in neural networks with synaptic depression

Prediction is the ability of the brain to quickly activate a target concept in response to a related stimulus (prime). Experiments point to the existence of an overlap between the populations of the neurons coding for different stimuli, and other experiments show that prime-target relations arise in the process of long term memory formation. The classical modelling paradigm is that long term memories correspond to stable steady states of a Hopfield network with Hebbian connectivity. Experiments show that short term synaptic depression plays an important role in the processing of memories. This leads naturally to a computational model of priming, called latching dynamics; a stable state (prime) can become unstable and the system may converge to another transiently stable steady state (target). Hopfield network models of latching dynamics have been studied by means of numerical simulation, however the conditions for the existence of this dynamics have not been elucidated. In this work we use a combination of analytic and numerical approaches to confirm that latching dynamics can exist in the context of a symmetric Hebbian learning rule, however lacks robustness and imposes a number of biologically unrealistic restrictions on the model. In particular our work shows that the symmetry of the Hebbian rule is not an obstruction to the existence of latching dynamics, however fine tuning of the parameters of the model is needed.

Altered Cortical Ensembles in Mouse Models of Schizophrenia

In schizophrenia, brain-wide alterations have been identified at the molecular and cellular levels, yet how these phenomena affect cortical circuit activity remains unclear. We studied two mouse models of schizophrenia-relevant disease processes: chronic ketamine (KET) administration and Df(16)A^+/-, modeling 22q11.2 microdeletions, a genetic variant highly penetrant for schizophrenia. Local field potential recordings in visual cortex confirmed gamma-band abnormalities similar to patient studies. Two-photon calcium imaging of local cortical populations revealed in both models a deficit in the reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altered single-neuron activity. This effect was present in ongoing and sensory-evoked activity and was not replicated by acute ketamine administration or pharmacogenetic parvalbumin-interneuron suppression. These results are consistent with the hypothesis that schizophrenia is an "attractor" disease and demonstrate that degraded neuronal ensembles are a common consequence of diverse genetic, cellular, and synaptic alterations seen in chronic schizophrenia.

Effect of clozapine on ketamine-induced deficits in attentional set shift task in mice

RATIONALE

Clozapine (CLZ) is an effective treatment for schizophrenia, producing improvements in both negative symptoms and cognitive impairments. Cognitive impairments can be modelled in animals by ketamine (KET) and assessed using the attentional set-shift task (ASST).

OBJECTIVE

Our first aim was to determine whether CLZ improves cognitive function and reverses KET-induced cognitive impairments using the ASST. Our second aim was to assess dose dependency of these effects.

RESULTS

Our findings demonstrate that acute as well as sub-chronic administration of KET cause cognitive deficits observed as increase in number of trails and errors to reach the criterion in the EDS phase. CLZ 0.3 mg/kg reversed the effects of both acute and sub-chronic KET, with no effects on locomotor activity. However, clozapine's effect after sub-chronic administration of dose 0.3 mg/kg was not as explicit as in the case of acute treatment. Moreover, administration of 1 mg/kg CLZ to KET-treated mice induced or enhanced deficits in the extra-dimensional shift phase compared to 1 mg/kg CLZ administration to mice not receiving KET. Locomotor activity test showed sedation effects of CLZ 1 mg/kg after acute treatment; therefore, effect of CLZ 1 mg/kg on KET-induced cognitive deficits was not evaluated in the attentional set-shift task (ASST) test.

CONCLUSIONS

The present findings support dose-dependent effects of CLZ to reverse KET-induced cognitive deficits. The observed dose dependency may be mediated by activation of different receptors, including monomers and/or heterodimers.

Structural brain changes are associated with response of negative symptoms to prefrontal repetitive transcranial magnetic stimulation in patients with schizophrenia

Impaired neural plasticity may be a core pathophysiological process underlying the symptomatology of schizophrenia. Plasticity-enhancing interventions, including repetitive transcranial magnetic stimulation (rTMS), may improve difficult-to-treat symptoms; however, efficacy in large clinical trials appears limited. The high variability of rTMS-related treatment response may be related to a comparably large variation in the ability to generate plastic neural changes. The aim of the present study was to determine whether negative symptom improvement in schizophrenia patients receiving rTMS to the left dorsolateral prefrontal cortex (DLPFC) was related to rTMS-related brain volume changes. A total of 73 schizophrenia patients with predominant negative symptoms were randomized to an active (n=34) or sham (n=39) 10-Hz rTMS intervention applied 5 days per week for 3 weeks to the left DLPFC. Local brain volume changes measured by deformation-based morphometry were correlated with changes in negative symptom severity using a repeated-measures analysis of covariance design. Volume gains in the left hippocampal, parahippocampal and precuneal cortices predicted negative symptom improvement in the active rTMS group (all r⩽-0.441, all P⩽0.009), but not the sham rTMS group (all r⩽0.211, all P⩾0.198). Further analyses comparing negative symptom responders (⩾20% improvement) and non-responders supported the primary analysis, again only in the active rTMS group (F_{(9, 207)}=2.72, P=0.005, partial η ²=0.106). Heterogeneity in clinical response of negative symptoms in schizophrenia to prefrontal high-frequency rTMS may be related to variability in capacity for structural plasticity, particularly in the left hippocampal region and the precuneus.

Neural Mechanisms of Cognitive Dissonance (Revised): An EEG Study

Cognitive dissonance theory suggests that our preferences are modulated by the mere act of choosing. A choice between two similarly valued alternatives creates psychological tension (cognitive dissonance) that is reduced by a postdecisional reevaluation of the alternatives. We measured EEG of human subjects during rest and free-choice paradigm. Our study demonstrates that choices associated with stronger cognitive dissonance trigger a larger negative frontocentral evoked response similar to error-related negativity, which has in turn been implicated in general performance monitoring. Furthermore, the amplitude of the evoked response is correlated with the reevaluation of the alternatives. We also found a link between individual neural dynamics (long-range temporal correlations) of the frontocentral cortices during rest and follow-up neural and behavioral effects of cognitive dissonance. Individuals with stronger resting-state long-range temporal correlations demonstrated a greater postdecisional reevaluation of the alternatives and larger evoked brain responses associated with stronger cognitive dissonance. Thus, our results suggest that cognitive dissonance is reflected in both resting-state and choice-related activity of the prefrontal cortex as part of the general performance-monitoring circuitry.

SIGNIFICANCE STATEMENT Contrary to traditional decision theory, behavioral studies repeatedly demonstrate that our preferences are modulated by the mere act of choosing. Difficult choices generate psychological (cognitive) dissonance, which is reduced by the postdecisional devaluation of unchosen options. We found that decisions associated with a higher level of cognitive dissonance elicited a stronger negative frontocentral deflection that peaked ∼60 ms after the response. This activity shares similar spatial and temporal features as error-related negativity, the electrophysiological correlate of performance monitoring. Furthermore, the frontocentral resting-state activity predicted the individual magnitude of preference change and the strength of cognitive dissonance-related neural activity.

Intrinsic neural activity differences among psychotic illnesses

Individuals with psychosis have been reported to show either reduced or augmented brain responses under seemingly similar conditions. It is likely that inconsistent baseline-adjustment methods are partly responsible for this discrepancy. Using steady-state stimuli during a pro/antisaccade task, this study addressed the relationship between nonspecific and stimulus-related neural activity, and how these activities are modulated as a function of cognitive demands. In 98 psychosis probands (schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis), neural activity was assessed during baseline and during a 5-s period in preparation for the pro/antisaccade task. To maximize the ability to identify meaningful differences between psychosis subtypes, analyses were conducted as a function of subgrouping probands by standard clinical diagnoses and neurobiological features. These psychosis "biotypes" were created using brain-based biomarkers, independent of symptomatology (Clementz et al., ). Psychosis probands as a whole showed poor antisaccade performance and diminished baseline oscillatory phase synchrony. Psychosis biotypes differed on both behavioral and brain measures, in ways predicted from Clementz et al. (). Two biotype groups showed similarly deficient behavior and baseline synchrony, despite diametrically opposed neural activity amplitudes. Another biotype subgroup was more similar to healthy individuals on behavioral and brain measures, despite the presence of psychosis. This study provides evidence that (a) consideration of baseline levels of activation and synchrony will be essential for a comprehensive understanding of neural response differences in psychosis, and (b) distinct psychosis subgroups exhibit reduced versus augmented intrinsic neural activity, despite cognitive performance and clinical similarities.

Electrophysiological Evidence for Hyperfocusing of Spatial Attention in Schizophrenia

A recently proposed hyperfocusing hypothesis of cognitive dysfunction in schizophrenia proposes that people with schizophrenia (PSZ) tend to concentrate processing resources more narrowly but more intensely than healthy control subjects (HCS). The present study tests a key prediction of this hypothesis, namely, that PSZ will hyperfocus on information presented at the center of gaze. This should lead to greater filtering of peripheral stimuli when the task requires focusing centrally but reduced filtering of central stimuli when the task requires attending broadly in the periphery. These predictions were tested in a double oddball paradigm, in which frequent standard stimuli and rare oddball stimuli were presented at central and peripheral locations while event-related potentials were recorded. Participants were instructed to discriminate between the standard and oddball stimuli at either the central location or at the peripheral locations. PSZ and HCS showed opposite patterns of spatial bias at the level of early sensory processing, as assessed with the P1 component: PSZ exhibited stronger sensory suppression of peripheral stimuli when the task required attending narrowly to the central location, whereas HCS exhibited stronger sensory suppression of central stimuli when the task required attending broadly to the peripheral locations. Moreover, PSZ exhibited a stronger stimulus categorization response than HCS, as assessed with the P3b component, for central stimuli when the task required attending to the peripheral region. These results provide strong evidence of hyperfocusing in PSZ, which may provide a unified mechanistic account of multiple aspects of cognitive dysfunction in schizophrenia.SIGNIFICANCE STATEMENT Schizophrenia clearly involves impaired attention, but attention is complex, and delineating the precise nature of attentional dysfunction in schizophrenia has been difficult. The present study tests a new hyperfocusing hypothesis, which proposes that people with schizophrenia (PSZ) tend to concentrate processing resources more intensely but more narrowly than healthy control subjects (HCS). Using electrophysiological measures of sensory and cognitive processing, we found that PSZ were actually superior to HCS in focusing attention at the point of gaze and filtering out peripheral distractors when the task required a narrow focusing of attention. This finding of superior filtering in PSZ supports the hyperfocusing hypothesis, which may provide the mechanism underlying a broad range of cognitive impairments in schizophrenia.

Genetic Feedback Regulation of Frontal Cortical Neuronal Ensembles Through Activity-Dependent Arc Expression and Dopaminergic Input

Mental functions involve coordinated activities of specific neuronal ensembles that are embedded in complex brain circuits. Aberrant neuronal ensemble dynamics is thought to form the neurobiological basis of mental disorders. A major challenge in mental health research is to identify these cellular ensembles and determine what molecular mechanisms constrain their emergence and consolidation during development and learning. Here, we provide a perspective based on recent studies that use activity-dependent gene Arc/Arg3.1 as a cellular marker to identify neuronal ensembles and a molecular probe to modulate circuit functions. These studies have demonstrated that the transcription of Arc is activated in selective groups of frontal cortical neurons in response to specific behavioral tasks. Arc expression regulates the persistent firing of individual neurons and predicts the consolidation of neuronal ensembles during repeated learning. Therefore, the Arc pathway represents a prototypical example of activity-dependent genetic feedback regulation of neuronal ensembles. The activation of this pathway in the frontal cortex starts during early postnatal development and requires dopaminergic (DA) input. Conversely, genetic disruption of Arc leads to a hypoactive mesofrontal dopamine circuit and its related cognitive deficit. This mutual interaction suggests an auto-regulatory mechanism to amplify the impact of neuromodulators and activity-regulated genes during postnatal development. Such a mechanism may contribute to the association of mutations in dopamine and Arc pathways with neurodevelopmental psychiatric disorders. As the mesofrontal dopamine circuit shows extensive activity-dependent developmental plasticity, activity-guided modulation of DA projections or Arc ensembles during development may help to repair circuit deficits related to neuropsychiatric disorders.

Dopamine Neuron-Specific Optogenetic Stimulation in Rhesus Macaques

Optogenetic studies in mice have revealed new relationships between well-defined neurons and brain functions. However, there are currently no means to achieve the same cell-type specificity in monkeys, which possess an expanded behavioral repertoire and closer anatomical homology to humans. Here, we present a resource for cell-type-specific channelrhodopsin expression in Rhesus monkeys and apply this technique to modulate dopamine activity and monkey choice behavior. These data show that two viral vectors label dopamine neurons with greater than 95% specificity. Infected neurons were activated by light pulses, indicating functional expression. The addition of optical stimulation to reward outcomes promoted the learning of reward-predicting stimuli at the neuronal and behavioral level. Together, these results demonstrate the feasibility of effective and selective stimulation of dopamine neurons in non-human primates and a resource that could be applied to other cell types in the monkey brain.

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Cell-type-specific promoter drives Cre-dependent ChR2 expression in monkey

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Optogenetically activated neurons had dopamine-like features and reward responses

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Dopamine neurons respond strongly to cues predicting optical stimulation

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Monkeys choose predicted optogenetic stimulation over no predicted stimulation

Cell-type-specific modulation of targets and distractors by dopamine D1 receptors in primate prefrontal cortex

The prefrontal cortex (PFC) is crucial for maintaining relevant information in working memory and resisting interference. PFC neurons are strongly regulated by dopamine, but it is unknown whether dopamine receptors are involved in protecting target memories from distracting stimuli. We investigated the prefrontal circuit dynamics and dopaminergic modulation of targets and distractors in monkeys trained to ignore interfering stimuli in a delayed-match-to-numerosity task. We found that dopamine D1 receptors (D1Rs) modulate the recovery of task-relevant information following a distracting stimulus. The direction of modulation is cell-type-specific: in putative pyramidal neurons, D1R inhibition enhances and D1R stimulation attenuates coding of the target stimulus after the interference, while the opposite pattern is observed in putative interneurons. Our results suggest that dopaminergic neuromodulation of PFC circuits regulates mental representations of behaviourally relevant stimuli that compete with task-irrelevant input and could play a central role for cognitive functioning in health and disease.

The Neurocognitive Cost of Enhancing Cognition with Methylphenidate: Improved Distractor Resistance but Impaired Updating

A balance has to be struck between supporting distractor-resistant representations in working memory and allowing those representations to be updated. Catecholamine, particularly dopamine, transmission has been proposed to modulate the balance between the stability and flexibility of working memory representations. However, it is unclear whether drugs that increase catecholamine transmission, such as methylphenidate, optimize this balance in a task-dependent manner or bias the system toward stability at the expense of flexibility (or vice versa). Here we demonstrate, using pharmacological fMRI, that methylphenidate improves the ability to resist distraction (cognitive stability) but impairs the ability to flexibly update items currently held in working memory (cognitive flexibility). These behavioral effects were accompanied by task-general effects in the striatum and opposite and task-specific effects on neural signal in the pFC. This suggests that methylphenidate exerts its cognitive enhancing and impairing effects through acting on the pFC, an effect likely associated with methylphenidate's action on the striatum. These findings highlight that methylphenidate acts as a double-edged sword, improving one cognitive function at the expense of another, while also elucidating the neurocognitive mechanisms underlying these paradoxical effects.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity.

SIGNIFICANCE STATEMENT

It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior.

Are Hallucinations Due to an Imbalance Between Excitatory and Inhibitory Influences on the Brain?

This review from the International Consortium on Hallucinations Research intends to question the pertinence of the excitatory-to-inhibitory (E/I) imbalance hypothesis as a model for hallucinations. A large number of studies suggest that subtle impairments of the E/I balance are involved in neurological and psychiatric conditions, such as schizophrenia. Emerging evidence also points to a role of the E/I balance in maintaining stable perceptual representations, suggesting it may be a plausible model for hallucinations. In support, hallucinations have been linked to inhibitory deficits as shown with impairment of gamma-aminobutyric acid transmission, N-methyl-d-aspartate receptor plasticity, reductions in gamma-frequency oscillations, hyperactivity in sensory cortices, and cognitive inhibition deficits. However, the mechanisms by which E/I dysfunctions at the cellular level might relate to clinical symptoms and cognitive deficits remain unclear. Given recent data advances in the field of clinical neuroscience, it is now possible to conduct a synthesis of available data specifically related to hallucinations. These findings are integrated with the latest computational frameworks of hallucinations, and recommendations for future research are provided.

Developmental analysis of the dopamine-containing neurons of the Drosophila brain

The Drosophila dopaminergic (DAergic) system consists of a relatively small number of neurons clustered throughout the brain and ventral nerve cord. Previous work shows that clusters of DA neurons innervate different brain compartments, which in part accounts for functional diversity of the DA system. We analyzed the association between DA neuron clusters and specific brain lineages, developmental and structural units of the Drosophila brain that provide a framework of connections that can be followed throughout development. The hatching larval brain contains six groups of primary DA neurons (born in the embryo), which we assign to six distinct lineages. We can show that all larval DA clusters persist into the adult brain. Some clusters increase in cell number during late larval stages, whereas others do not become DA positive until early pupa. Ablating neuroblasts with hydroxyurea (HU) prior to onset of larval proliferation (generates secondary neurons) confirms that these added DA clusters are primary neurons born in the embryo, rather than secondary neurons. A single cluster that becomes DA positive in the late pupa, PAM1/lineage DALcm1/2, forms part of a secondary lineage that can be ablated by larval HU application. By supplying lineage information for each DA cluster, our analysis promotes further developmental and functional analyses of this important system of neurons. J. Comp. Neurol. 525:363-379, 2017. © 2016 Wiley Periodicals, Inc.

Increased Nigral SLC6A3 Activity in Schizophrenia Patients: Findings From the Toronto-McLean Cohorts

SLC6A3, which encodes the primary regulator of extracellular dopamine (DA) concentration, the DA transporter, has been implicated in schizophrenia (SCZ). However, the details of its genetic effect on risk remain largely unknown. The purpose of this candidate gene study was to identify a specificSLC6A3activity associated with SCZ by using functional genetic approaches. We first examined gene activity in DA neurons isolated from case-control postmortem nigral tissue and found that the averageSLC6A3mRNA level in controls was only 0.37-fold of that in cases (P= .0034). To understand this expression difference, we examined the association of 10 genetic markers, mostly located in the promoter region, with SCZ in 1717 subjects collected from Toronto and McLean cohorts, including 881 controls and 836 cases and identified the 5' promoter SNP rs1478435 as having a significant association signal (uncorrectedPvalue: .00462; adjustedPvalue: .0319) in unrelated Caucasians. Allele T was over-represented in controls (OR = .75); T-carrier controls had decreased mRNA levels in nigral DA neurons, contributing to the reduced activity in the controls. In vitro functional analysis confirmed that T carriers displayed attenuated enhancement of promoter activity. These findings collectively suggest that increased nigralSLC6A3activity may be a risk factor for SCZ, and may help to explain high rates of comorbidity with substance abuse.

Opposing effects of acute and chronic d-amphetamine on decision-making in rats

Amphetamine and other drugs of abuse have both short-term and long-lasting effects on brain function, and drug sensitization paradigms often result in chronic impairments in behavioral flexibility. Here we show that acute amphetamine administration temporarily renders rats less sensitive to reward omission, as revealed by a decrease in lose-shift responding during a binary choice task. Intracerebral infusions of amphetamine into the ventral striatum did not affect lose-shift responding but did increase impulsive behavior in which rats chose to check both reward feeders before beginning the next trial. In contrast to acute systemic and intracerebral infusions, sensitization through repeated exposure induced long-lasting increased sensitivity to reward omission. These treatments did not affect choices on trials following reward delivery (i.e. win-stay responding), and sensitization increased spine density in the sensorimotor striatum. The dichotomous effects of amphetamine on short-term and long-term loss sensitivity, and the null effect on win-stay responding, are consistent with a shift of behavioral control to the sensorimotor striatum after drug sensitization. These data provide a new demonstration of such a shift in a novel task unrelated to drug administration, and suggests that the dominance of sensorimotor control persists over many hundreds of trials after sensitization.

Reduction of Pavlovian Bias in Schizophrenia: Enhanced Effects in Clozapine-Administered Patients

The negative symptoms of schizophrenia (SZ) are associated with a pattern of reinforcement learning (RL) deficits likely related to degraded representations of reward values. However, the RL tasks used to date have required active responses to both reward and punishing stimuli. Pavlovian biases have been shown to affect performance on these tasks through invigoration of action to reward and inhibition of action to punishment, and may be partially responsible for the effects found in patients. Forty-five patients with schizophrenia and 30 demographically-matched controls completed a four-stimulus reinforcement learning task that crossed action ("Go" or "NoGo") and the valence of the optimal outcome (reward or punishment-avoidance), such that all combinations of action and outcome valence were tested. Behaviour was modelled using a six-parameter RL model and EEG was simultaneously recorded. Patients demonstrated a reduction in Pavlovian performance bias that was evident in a reduced Go bias across the full group. In a subset of patients administered clozapine, the reduction in Pavlovian bias was enhanced. The reduction in Pavlovian bias in SZ patients was accompanied by feedback processing differences at the time of the P3a component. The reduced Pavlovian bias in patients is suggested to be due to reduced fidelity in the communication between striatal regions and frontal cortex. It may also partially account for previous findings of poorer "Go-learning" in schizophrenia where "Go" responses or Pavlovian consistent responses are required for optimal performance. An attenuated P3a component dynamic in patients is consistent with a view that deficits in operant learning are due to impairments in adaptively using feedback to update representations of stimulus value.

Frequency-specific disruptions of neuronal oscillations reveal aberrant auditory processing in schizophrenia

Individuals with schizophrenia exhibit abnormalities in evoked brain responses in oddball paradigms. These could result from (a) insufficient salience-related cortical signaling (P300), (b) insufficient suppression of irrelevant aspects of the auditory environment, or (c) excessive neural noise. We tested whether disruption of ongoing auditory steady-state responses at predetermined frequencies informed which of these issues contribute to auditory stimulus relevance processing abnormalities in schizophrenia. Magnetoencephalography data were collected for 15 schizophrenia and 15 healthy subjects during an auditory oddball paradigm (25% targets; 1-s interstimulus interval). Auditory stimuli (pure tones: 1 kHz standards, 2 kHz targets) were administered during four continuous background (auditory steady-state) stimulation conditions: (1) no stimulation, (2) 24 Hz, (3) 40 Hz, and (4) 88 Hz. The modulation of the auditory steady-state response (aSSR) and the evoked responses to the transient stimuli were quantified and compared across groups. In comparison to healthy participants, the schizophrenia group showed greater disruption of the ongoing aSSR by targets regardless of steady-state frequency, and reduced amplitude of both M100 and M300 event-related field components. During the no-stimulation condition, schizophrenia patients showed accentuation of left hemisphere 40 Hz response to both standard and target stimuli, indicating an effort to enhance local stimulus processing. Together, these findings suggest abnormalities in auditory stimulus relevance processing in schizophrenia patients stem from insufficient amplification of salient stimuli.

Integrating Insults: Using Fault Tree Analysis to Guide Schizophrenia Research across Levels of Analysis

The grand challenges of schizophrenia research are linking the causes of the disorder to its symptoms and finding ways to overcome those symptoms. We argue that the field will be unable to address these challenges within psychiatry's standard neo-Kraepelinian (DSM) perspective. At the same time the current corrective, based in molecular genetics and cognitive neuroscience, is also likely to flounder due to its neglect for psychiatry's syndromal structure. We suggest adopting a new approach long used in reliability engineering, which also serves as a synthesis of these approaches. This approach, known as fault tree analysis, can be combined with extant neuroscientific data collection and computational modeling efforts to uncover the causal structures underlying the cognitive and affective failures in people with schizophrenia as well as other complex psychiatric phenomena. By making explicit how causes combine from basic faults to downstream failures, this approach makes affordances for: (1) causes that are neither necessary nor sufficient in and of themselves; (2) within-diagnosis heterogeneity; and (3) between diagnosis co-morbidity.

Increased co-expression of genes harboring the damaging de novo mutations in Chinese schizophrenic patients during prenatal development

Schizophrenia is a heritable, heterogeneous common psychiatric disorder. In this study, we evaluated the hypothesis that de novo variants (DNVs) contribute to the pathogenesis of schizophrenia. We performed exome sequencing in Chinese patients (N = 45) with schizophrenia and their unaffected parents (N = 90). Forty genes were found to contain DNVs. These genes had enriched transcriptional co-expression profile in prenatal frontal cortex (Bonferroni corrected p < 9.1 × 10⁻³), and in prenatal temporal and parietal regions (Bonferroni corrected p < 0.03). Also, four prenatal anatomical subregions (VCF, MFC, OFC and ITC) have shown significant enrichment of connectedness in co-expression networks. Moreover, four genes (LRP1, MACF1, DICER1 and ABCA2) harboring the damaging de novo mutations are strongly prioritized as susceptibility genes by multiple evidences. Our findings in Chinese schizophrenic patients indicate the pathogenic role of DNVs, supporting the hypothesis that schizophrenia is a neurodevelopmental disease.

Stochastic Mesocortical Dynamics and Robustness of Working Memory during Delay-Period

The role of prefronto-mesoprefrontal system in the dopaminergic modulation of working memory during delayed response tasks is well-known. Recently, a dynamical model of the closed-loop mesocortical circuit has been proposed which employs a deterministic framework to elucidate the system's behavior in a qualitative manner. Under natural conditions, noise emanating from various sources affects the circuit's functioning to a great extent. Accordingly in the present study, we reformulate the model into a stochastic framework and investigate its steady state properties in the presence of constant background noise during delay-period. From the steady state distribution, global potential landscape and signal-to-noise ratio are obtained which help in defining robustness of the circuit dynamics. This provides insight into the robustness of working memory during delay-period against its disruption due to background noise. The findings reveal that the global profile of circuit's robustness is predominantly governed by the level of D1 receptor activity and high D1 receptor stimulation favors the working memory-associated sustained-firing state over the spontaneous-activity state of the system. Moreover, the circuit's robustness is further fine-tuned by the levels of excitatory and inhibitory activities in a way such that the robustness of sustained-firing state exhibits an inverted-U shaped profile with respect to D1 receptor stimulation. It is predicted that the most robust working memory is formed possibly at a subtle ratio of the excitatory and inhibitory activities achieved at a critical level of D1 receptor stimulation. The study also paves a way to understand various cognitive deficits observed in old-age, acute stress and schizophrenia and suggests possible mechanistic routes to the working memory impairments based on the circuit's robustness profile.

An integrated network model of psychotic symptoms

The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice.

Converging models of schizophrenia--Network alterations of prefrontal cortex underlying cognitive impairments

The prefrontal cortex (PFC) and its connections with other brain areas are crucial for cognitive function. Cognitive impairments are one of the core symptoms associated with schizophrenia, and manifest even before the onset of the disorder. Altered neural networks involving PFC contribute to cognitive impairments in schizophrenia. Both genetic and environmental risk factors affect the development of the local circuitry within PFC as well as development of broader brain networks, and make the system vulnerable to further insults during adolescence, leading to the onset of the disorder in young adulthood. Since spared cognitive functions correlate with functional outcome and prognosis, a better understanding of the mechanisms underlying cognitive impairments will have important implications for novel therapeutics for schizophrenia focusing on cognitive functions. Multidisciplinary approaches, from basic neuroscience to clinical studies, are required to link molecules, circuitry, networks, and behavioral phenotypes. Close interactions among such fields by sharing a common language on connectomes, behavioral readouts, and other concepts are crucial for this goal.

Doping the Mind: Dopaminergic Modulation of Prefrontal Cortical Cognition

The prefrontal cortex is the center of cognitive control. Processing in prefrontal cortical circuits enables us to direct attention to behaviorally relevant events; to memorize, structure, and categorize information; and to learn new concepts. The prefrontal cortex receives strong projections from midbrain neurons that use dopamine as a transmitter. In this article, we review the crucial role dopamine plays as a modulator of prefrontal cognitive functions, in the primate brain in particular. Following a summary of the anatomy and physiology of the midbrain dopamine system, we focus on recent studies that investigated dopaminergic effects in prefrontal cortex at the cellular level. We then discuss how unregulated prefrontal dopamine signaling could contribute to major disorders of cognition. The studies highlighted in this review demonstrate the powerful influence dopamine exerts on the mind.

Intraindividual neurophysiological variability in ultra-high-risk for psychosis and schizophrenia patients: single-trial analysis

Background:

Intraindividual variability in neurophysiological responses is an important factor in the study of schizophrenia. Interestingly, this variability strongly predicts individual differences in cognitive processing. Neurobiological abnormalities that present during the prodromal phase of schizophrenia are not well characterized. However, these symptoms may provide insight into the key circuits involved in the disorder.

Aims:

To investigate the variability in magnetoencephalographic responses at ultrahigh risk and schizophrenia patients.

Methods:

Twenty-four ultrahigh risk, 21 patients with schizophrenia and 28 healthy controls were evaluated. The intraindividual variability was estimated by calculating the s.d. of the across-trial amplitude in responses to deviant and standard stimuli. The degree of phase locking across trials was calculated by intertrial coherence.

Results:

Greater variability in the responses to deviant and standard tones was noted in the schizophrenia and ultrahigh risk groups compared with controls. Variability in response to standard stimuli was positively correlated with the amplitude for the standard stimuli in all of the groups. Moreover, schizophrenia patients displayed lower alpha and theta intertrial coherence compared with ultrahigh risk and controls. Mismatch negativity amplitude was correlated with the alpha intertrial coherence in all groups. Taken together, the augmented variability and reduced inter-trial coherence provide empirical evidence for increased amplitude and phase inconsistencies in schizophrenia and ultrahigh risk.

Conclusions:

The results implicate widespread dysfunction in amplitude modulation and phase concentration in schizophrenia and ultrahigh risk, as well as evidence for early amplitude and phase disruption. These finding suggest intraindividual variability and intertrial coherence appear to be important indicators of pathophysiological processing.

Interaction Between Functional Genetic Variation of DRD2 and Cannabis Use on Risk of Psychosis

Both cannabis use and the dopamine receptor (DRD2) gene have been associated with schizophrenia, psychosis-like experiences, and cognition. However, there are no published data investigating whether genetically determined variation in DRD2 dopaminergic signaling might play a role in individual susceptibility to cannabis-associated psychosis. We genotyped (1) a case-control study of 272 patients with their first episode of psychosis and 234 controls, and also from (2) a sample of 252 healthy subjects, for functional variation in DRD2, rs1076560. Data on history of cannabis use were collected on all the studied subjects by administering the Cannabis Experience Questionnaire. In the healthy subjects' sample, we also collected data on schizotypy and cognitive performance using the Schizotypal Personality Questionnaire and the N-back working memory task. In the case-control study, we found a significant interaction between the rs1076560 DRD2 genotype and cannabis use in influencing the likelihood of a psychotic disorder. Among cannabis users, carriers of the DRD2, rs1076560, T allele showed a 3-fold increased probability to suffer a psychotic disorder compared with GG carriers (OR = 3.07; 95% confidence interval [CI]: 1.22-7.63). Among daily users, T carrying subjects showed a 5-fold increase in the odds of psychosis compared to GG carriers (OR = 4.82; 95% CI: 1.39-16.71). Among the healthy subjects, T carrying cannabis users had increased schizotypy compared with T carrying cannabis-naïve subjects, GG cannabis users, and GG cannabis-naïve subjects (all P ≤ .025). T carrying cannabis users had reduced working memory accuracy compared with the other groups (all P ≤ .008). Thus, variation of the DRD2, rs1076560, genotype may modulate the psychosis-inducing effect of cannabis use.

The separate and combined effects of monoamine oxidase A inhibition and nicotine on the mismatch negativity event related potential

The mismatch negativity (MMN) auditory event-related potential (ERP) has been extensively studied as a potential biomarker for abnormal auditory processing in schizophrenia (SZ), a population which exhibits abnormally high smoking rates. The relationship between nicotinic activation and cognition in SZ may be related to underlying nicotinic and NMDA receptor dysfunction within the disease. However, transient cognitive improvements via smoking in patients may also result from monoamine oxidase (MAO) inhibition, achieved through tobacco smoke. In 24 healthy non-smoking males, we investigated the separate and combined effects of nicotine and MAO-A inhibition via moclobemide (75mg) on the optimal-5 variation of the MMN paradigm. No significant drug effects were observed in our total sample, however, stratification of individuals into low (N=12) and high (N=12) baseline MMN amplitude groups revealed increases in duration MMN amplitude relative to placebo by nicotine, as well as moclobemide, but not after the combination of the two. Because previous research has shown there was no effect of monoamine modulation on MMN, this study shows an unexpected effect of moclobemide on duration MMN.

Molecular underpinnings of prefrontal cortex development in rodents provide insights into the etiology of neurodevelopmental disorders

The prefrontal cortex (PFC), seat of the highest-order cognitive functions, constitutes a conglomerate of highly specialized brain areas and has been implicated to have a role in the onset and installation of various neurodevelopmental disorders. The development of a properly functioning PFC is directed by transcription factors, guidance cues and other regulatory molecules and requires the intricate and temporal orchestration of a number of developmental processes. Disturbance or failure of any of these processes causing neurodevelopmental abnormalities within the PFC may contribute to several of the cognitive deficits seen in patients with neurodevelopmental disorders. In this review, we elaborate on the specific processes underlying prefrontal development, such as induction and patterning of the prefrontal area, proliferation, migration and axonal guidance of medial prefrontal progenitors, and their eventual efferent and afferent connections. We furthermore integrate for the first time the available knowledge from genome-wide studies that have revealed genes linked to neurodevelopmental disorders with experimental molecular evidence in rodents. The integrated data suggest that the pathogenic variants in the neurodevelopmental disorder-associated genes induce prefrontal cytoarchitectonical impairments. This enhances our understanding of the molecular mechanisms of prefrontal (mis)development underlying the four major neurodevelopmental disorders in humans, that is, intellectual disability, autism spectrum disorders, attention deficit hyperactivity disorder and schizophrenia, and may thus provide clues for the development of novel therapies.

Multifactoriality in Psychiatric Disorders: A Computational Study of Schizophrenia

The search for biological causes of mental disorders has up to now met with limited success, leading to growing dissatisfaction with diagnostic classifications. However, it is questionable whether most clinical syndromes should be expected to correspond to specific microscale brain alterations, as multiple low-level causes could lead to similar symptoms in different individuals. In order to evaluate the potential multifactoriality of alterations related to psychiatric illness, we performed a parametric exploration of published computational models of schizophrenia. By varying multiple parameters simultaneously, such as receptor conductances, connectivity patterns, and background excitation, we generated 5625 different versions of an attractor-based network model of schizophrenia symptoms. Among networks presenting activity within valid ranges, 154 parameter combinations out of 3002 (5.1%) presented a phenotype reminiscent of schizophrenia symptoms as defined in the original publication. We repeated this analysis in a model of schizophrenia-related deficits in spatial working memory, building 3125 different networks, and found that 41 (4.9%) out of 834 networks with valid activity presented schizophrenia-like alterations. In isolation, none of the parameters in either model showed adequate sensitivity or specificity to identify schizophrenia-like networks. Thus, in computational models of schizophrenia, even simple network phenotypes related to the disorder can be produced by a myriad of causes at the molecular and circuit levels. This suggests that unified explanations for either the full syndrome or its behavioral and network endophenotypes are unlikely to be expected at the genetic and molecular levels.

Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease

Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this article, we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low-frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders-including Parkinson's disease, autism, depression, schizophrenia, and anxiety-are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural gray or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states or their treatment are a product of how these physical processes affect dynamic network communication.

Dysfunctional prefrontal gamma-band oscillations reflect working memory and other cognitive deficits in schizophrenia

Impairments in working memory (WM) and other cognitive functions are cardinal neuropsychological symptoms in schizophrenia (ScZ). The prefrontal cortex (PFC) is important for mediating and executing these functions. Functional neuroimaging and molecular studies have consistently shown PFC abnormalities in ScZ. In addition, recent studies have suggested that impairments in oscillatory activity, especially in the gamma band (approximately 30-80 Hz), reflect disturbed cortical information processing in this patient group. Here we review evidence that dysfunctional gamma-band responses (GBR) in the PFC could be a factor contributing to WM and other cognitive deficits in ScZ. We provide an overview of noninvasive electrophysiological studies reporting frontal GBR abnormalities in ScZ patients during WM and other cognitive tasks. In agreement with the often-reported hypofrontality in functional neuroimaging studies, the majority of reviewed studies revealed reduced amplitudes or reduced phase locking of GBR over frontal areas in this patient group. Clinical implications derived from these findings and possibilities to foster future studies on GBR abnormalities in ScZ patients, are discussed. Since oscillatory activity in the gamma band has previously been linked to a variety of neurotransmitters, such as the gamma-aminobutyric acid-ergic system, the study of prefrontal GBR could also have implications for pharmacologic approaches in the treatment of WM and other cognitive deficits in ScZ.

Stochastic Dynamics Underlying Cognitive Stability and Flexibility

Cognitive stability and flexibility are core functions in the successful pursuit of behavioral goals. While there is evidence for a common frontoparietal network underlying both functions and for a key role of dopamine in the modulation of flexible versus stable behavior, the exact neurocomputational mechanisms underlying those executive functions and their adaptation to environmental demands are still unclear. In this work we study the neurocomputational mechanisms underlying cue based task switching (flexibility) and distractor inhibition (stability) in a paradigm specifically designed to probe both functions. We develop a physiologically plausible, explicit model of neural networks that maintain the currently active task rule in working memory and implement the decision process. We simplify the four-choice decision network to a nonlinear drift-diffusion process that we canonically derive from a generic winner-take-all network model. By fitting our model to the behavioral data of individual subjects, we can reproduce their full behavior in terms of decisions and reaction time distributions in baseline as well as distractor inhibition and switch conditions. Furthermore, we predict the individual hemodynamic response timecourse of the rule-representing network and localize it to a frontoparietal network including the inferior frontal junction area and the intraparietal sulcus, using functional magnetic resonance imaging. This refines the understanding of task-switch-related frontoparietal brain activity as reflecting attractor-like working memory representations of task rules. Finally, we estimate the subject-specific stability of the rule-representing attractor states in terms of the minimal action associated with a transition between different rule states in the phase-space of the fitted models. This stability measure correlates with switching-specific thalamocorticostriatal activation, i.e., with a system associated with flexible working memory updating and dopaminergic modulation of cognitive flexibility. These results show that stochastic dynamical systems can implement the basic computations underlying cognitive stability and flexibility and explain neurobiological bases of individual differences.

In this work we develop a neurophysiologically inspired dynamical model that is capable of solving a complex behavioral task testing cognitive stability and flexibility. We can individually fit the behavior of each of 20 human subjects that conducted this stability-flexibility task during functional magnetic resonance imaging (fMRI). The physiological nature of our model allows us to estimate the energy consumption of the rule-representing module, which we use to predict the hemodynamic fMRI response. Through this model-based prediction, we localize the rule module to a frontoparietal network known to be required for cognitive stability and flexibility. In this way we both validate our model, which is based on noisy attractor dynamics, and specify the computational role of a cortical network that is well-established in human neuroimaging research. Additionally, we quantify the individual stability of the rule-representing states and relate this stability to individual differences in energy consumption during task switching versus distractor inhibition. Hereby we show that the activation of a thalamocorticostriatal network involved in the dopaminergic modulation of cognitive stability is modulated by the model-derived stability of the frontoparietal rule-representing network. Altogether, we show that noisy dynamic systems are likely to implement the basic computations underlying cognitive stability and flexibility.