Computational models of schizophrenia and dopamine modulation in the prefrontal cortex

Hearing voices in the resting brain: A review of intrinsic functional connectivity research on auditory verbal hallucinations

Resting state networks (RSNs) are thought to reflect the intrinsic functional connectivity of brain regions. Alterations to RSNs have been proposed to underpin various kinds of psychopathology, including the occurrence of auditory verbal hallucinations (AVH). This review outlines the main hypotheses linking AVH and the resting state, and assesses the evidence for alterations to intrinsic connectivity provided by studies of resting fMRI in AVH. The influence of hallucinations during data acquisition, medication confounds, and movement are also considered. Despite a large variety of analytic methods and designs being deployed, it is possible to conclude that resting connectivity in the left temporal lobe in general and left superior temporal gyrus in particular are disrupted in AVH. There is also preliminary evidence of atypical connectivity in the default mode network and its interaction with other RSNs. Recommendations for future research include the adoption of a common analysis protocol to allow for more overlapping datasets and replication of intrinsic functional connectivity alterations.

Improper activation of D1 and D2 receptors leads to excess noise in prefrontal cortex

The dopaminergic system has been shown to control the amount of noise in the prefrontal cortex (PFC) and likely plays an important role in working memory and the pathophysiology of schizophrenia. We developed a model that takes into account the known receptor distributions of D1 and D2 receptors, the changes these receptors have on neuron response properties, as well as identified circuitry involved in working memory. Our model suggests that D1 receptor under-stimulation in supragranular layers gates internal noise into the PFC leading to cognitive symptoms as has been proposed in attention disorders, while D2 over-stimulation gates noise into the PFC by over-activation of cortico-striatal projecting neurons in infragranular layers. We apply this model in the context of a memory-guided saccade paradigm and show deficits similar to those observed in schizophrenic patients. We also show set-shifting impairments similar to those observed in rodents with D1 and D2 receptor manipulations. We discuss how the introduction of noise through changes in D1 and D2 receptor activation may account for many of the symptoms of schizophrenia depending on where this dysfunction occurs in the PFC.

Smoking restores impaired LTD-like plasticity in schizophrenia: a transcranial direct current stimulation study

Impaired neuroplastic responses following noninvasive brain stimulation have been reported repeatedly in schizophrenia patients. These findings have been associated with deficits in GABAergic, glutamatergic, and cholinergic neurotransmission. Although various neurophysiological studies have indicated a relationship between nicotine and neuroplasticity in healthy individuals, the present study is the first investigation into the impact of nicotine on LTD-like plasticity in patients with schizophrenia. Cortical excitability and cortical plasticity were explored in 30 schizophrenia patients (17 smoker, 13 nonsmoker) and 45 healthy controls (13 smoker, 32 nonsmoker) by using single-pulse transcranial magnetic stimulation (TMS) before and following cathodal transcranial direct current stimulation (tDCS) applied to the left primary motor cortex. Our analysis revealed abolished LTD-like plasticity in nonsmoking schizophrenia patients. However, these plasticity deficits were not present in smoking schizophrenia patients. In healthy controls, significant MEP reductions following cathodal tDCS were observed in nonsmoking individuals, but only trend-level reductions in smokers. In smoking schizophrenia patients, the severity of negative symptoms correlated positively with reduced neuroplasticity, whereas nonsmoking patients displayed the opposite effect. Taken together, the data of our study support the notion of an association between chronic smoking and the restitution of impaired LTD-like plasticity in schizophrenia patients. Although replication and further research are needed to better understand this relationship, our findings indicate that nicotine intake might stabilize the impaired inhibition-facilitation balance in the schizophrenic brain through a complex interaction between cortical plasticity, and GABAergic and cholinergic neurotransmission, and might explain the reduced prevalence of negative symptoms in this population.

Clozapine induces chloride channel-4 expression through PKA activation and modulates CDK5 expression in SH-SY5Y and U87 cells

OBJECTIVES

Second-generation antipsychotic drugs, such as clozapine, were reported to enhance neurite outgrowth by nerve growth factor in PC12 cells. The authors previously showed that chloride channel 4 (CLC-4) is responsible for nerve growth factor-induced neurite outgrowth in neuronal cells. In this study, we examined whether clozapine induces CLC-4 in neuroblastoma and glioma cells.

METHODS

The effect of clozapine on CLC-4 expression was examined in neuroblastoma (SH-SY5Y) and glioma (U87) cells. To investigate the signaling pathway responsible for clozapine-induced CLC-4 expression, the phosphorylation of cAMP response element-binding protein (CREB), which binds CRE in the promoter of the human CLC-4 gene, was examined. To identify the target of clozapine induced CLC-4, CLC-4 siRNA was introduced to neuroblastoma and glioma cells for functional knockdown.

RESULTS

We observed that clozapine increased CLC-4 expression in both SH-SY5Y and U87 cells. Clozapine induced CREB phosphorylation, but in the presence of inhibitor of protein kinase A (an upstream kinase of CREB) clozapine-induced CLC-4 expression was suppressed. Finally, we found that CLC-4 knockdown suppressed clozapine-induced cyclin-dependent kinase 5 (CDK5) expression in SH-SY5Y and U-87 cells suggesting CDK5 as potential molecular target of clozapine induced CLC-4 expression.

CONCLUSIONS

The results of the present study suggest that clozapine's therapeutic effect may include the induction of CLC-4 which is dependent on CREB activation via PKA. We also found that functional knockdown of CLC-4 resulted in reduction of CDK5 expression, which may also be implicated in clozapine's therapeutic effect.

Circuit to construct mapping: a mathematical tool for assisting the diagnosis and treatment in major depressive disorder

Major depressive disorder (MDD) is a serious condition with a lifetime prevalence exceeding 16% worldwide. MDD is a heterogeneous disorder that involves multiple behavioral symptoms on the one hand and multiple neuronal circuits on the other hand. In this review, we integrate the literature on cognitive and physiological biomarkers of MDD with the insights derived from mathematical models of brain networks, especially models that can be used for fMRI datasets. We refer to the recent NIH research domain criteria initiative, in which a concept of "constructs" as functional units of mental disorders is introduced. Constructs are biomarkers present at multiple levels of brain functioning - cognition, genetics, brain anatomy, and neurophysiology. In this review, we propose a new approach which we called circuit to construct mapping (CCM), which aims to characterize causal relations between the underlying network dynamics (as the cause) and the constructs referring to the clinical symptoms of MDD (as the effect). CCM involves extracting diagnostic categories from behavioral data, linking circuits that are causal to these categories with use of clinical neuroimaging data, and modeling the dynamics of the emerging circuits with attractor dynamics in order to provide new, neuroimaging-related biomarkers for MDD. The CCM approach optimizes the clinical diagnosis and patient stratification. It also addresses the recent demand for linking circuits to behavior, and provides a new insight into clinical treatment by investigating the dynamics of neuronal circuits underneath cognitive dimensions of MDD. CCM can serve as a new regime toward personalized medicine, assisting the diagnosis and treatment of MDD.

Stochastic cortical neurodynamics underlying the memory and cognitive changes in aging

The relatively random spiking times of individual neurons provide a source of noise in the brain. We show how this noise interacting with altered depth in the basins of attraction of networks involved in short-term memory, attention, and episodic memory provide an approach to understanding some of the cognitive changes in normal aging. The effects of the neurobiological changes in aging that are considered include reduced synaptic modification and maintenance during learning produced in part through reduced acetylcholine in normal aging, reduced dopamine which reduces NMDA-receptor mediated effects, reduced noradrenaline which increases cAMP and thus shunts excitatory synaptic inputs, and the effects of a reduction in acetylcholine in increasing spike frequency adaptation. Using integrate-and-fire simulations of an attractor network implementing memory recall and short-term memory, it is shown that all these changes associated with aging reduce the firing rates of the excitatory neurons, which in turn reduce the depth of the basins of attraction, resulting in a much decreased probability in maintaining in short-term memory what has been recalled from the attractor network. This stochastic dynamics approach opens up new ways to understand and potentially treat the effects of normal aging on memory and cognitive functions.

Computational psychiatry

Psychiatric disorders such as autism and schizophrenia, arise from abnormalities in brain systems that underlie cognitive, emotional, and social functions. The brain is enormously complex and its abundant feedback loops on multiple scales preclude intuitive explication of circuit functions. In close interplay with experiments, theory and computational modeling are essential for understanding how, precisely, neural circuits generate flexible behaviors and their impairments give rise to psychiatric symptoms. This Perspective highlights recent progress in applying computational neuroscience to the study of mental disorders. We outline basic approaches, including identification of core deficits that cut across disease categories, biologically realistic modeling bridging cellular and synaptic mechanisms with behavior, and model-aided diagnosis. The need for new research strategies in psychiatry is urgent. Computational psychiatry potentially provides powerful tools for elucidating pathophysiology that may inform both diagnosis and treatment. To achieve this promise will require investment in cross-disciplinary training and research in this nascent field.

Relationships between divided attention and working memory impairment in people with schizophrenia

Recent studies suggest that people with schizophrenia (PSZ) have difficulty distributing their attention broadly. Other research suggests that PSZ have reduced working memory (WM) capacity. This study tested whether these findings reflect a common underlying deficit. We measured the ability to distribute attention by means of the Useful Field of View (UFOV) task, in which participants must distribute attention so that they can discriminate a foveal target and simultaneously localize a peripheral target. Participants included 50 PSZ and 52 healthy control subjects. We found that PSZ exhibited severe impairments in UFOV performance, that UFOV performance was highly correlated with WM capacity in PSZ (r = -.61), and that UFOV impairments could not be explained by either impaired low-level processing or a generalized deficit. These results suggest that a common mechanism explains deficits in the ability to distribute attention broadly, reduced WM capacity, and other aspects of impaired cognition in schizophrenia. We hypothesize that this mechanism may involve abnormal local circuit dynamics that cause a hyperfocusing of resources onto a small number of internal representations.

Hyperfocusing in schizophrenia: Evidence from interactions between working memory and eye movements

Recent research suggests that processing resources are focused more narrowly but more intensely in people with schizophrenia (PSZ) than in healthy control subjects (HCS), possibly reflecting local cortical circuit abnormalities. This hyperfocusing hypothesis leads to the counterintuitive prediction that, although PSZ cannot store as much information in working memory as HCS, the working memory representations that are present in PSZ may be more intense than those in HCS. To test this hypothesis, we used a task in which participants make a saccadic eye movement to a peripheral target and avoid a parafoveal nontarget while they are holding a color in working memory. Previous research with this task has shown that the parafoveal nontarget is more distracting when it matches the color being held in working memory. This effect should be enhanced in PSZ if their working memory representations are more intense. Consistent with this prediction, we found that the effect of a match between the distractor color and the memory color was larger in PSZ than in HCS. We also observed evidence that PSZ hyperfocused spatially on the region surrounding the fixation point. These results provide further evidence that some aspects of cognitive dysfunction in schizophrenia may be a result of a narrower and more intense focusing of processing resources.

Antipsychotic treatment modulates glutamate transport and NMDA receptor expression

Schizophrenia patients often suffer from treatment-resistant cognitive and negative symptoms, both of which are influenced by glutamate neurotransmission. Innovative therapeutic strategies such as agonists at metabotropic glutamate receptors or glycin reuptake inhibitors try to modulate the brain's glutamate network. Interactions of amino acids with monoamines have been described on several levels, and first- and second-generation antipsychotic agents (FGAs, SGAs) are known to exert modulatory effects on the glutamatergic system. This review summarizes the current knowledge on effects of FGAs and SGAs on glutamate transport and receptor expression derived from pharmacological studies. Such studies serve as a control for molecular findings in schizophrenia brain tissue and are clinically relevant. Moreover, they may validate animal models for psychosis, foster basic research on antipsychotic substances and finally lead to a better understanding of how monoaminergic and amino acid neurotransmissions are intertwined. In the light of these results, important differences dependent on antipsychotic substances, dosage and duration of treatment became obvious. While some post-mortem findings might be confounded with multifold drug effects, others are unlikely to be influenced by antipsychotic treatment and could represent important markers of schizophrenia pathophysiology. In similarity to the convergence of toxic and psychotomimetic effects of dopaminergic, serotonergic and anti-glutamatergic substances, the therapeutic mechanisms of SGAs might merge on a yet to be defined molecular level. In particular, serotonergic effects of SGAs, such as an agonism at 5HT1A receptors, represent important targets for further clinical research.

A mathematical model of dysfunction of the thalamo-cortical loop in schizophrenia

BACKGROUND

Recent experimental results suggest that impairment of auditory information processing in the thalamo-cortical loop is crucially related to schizophrenia. Large differences between schizophrenia patients and healthy controls were found in the cortical EEG signals.

METHODS

We derive a phenomenological mathematical model, based on coupled phase oscillators with continuously distributed frequencies to describe the neural activity of the thalamo-cortical loop. We examine the influence of the bidirectional coupling strengths between the thalamic and the cortical area with regard to the phase-locking effects observed in the experiments. We extend this approach to a model consisting of a thalamic area coupled to two cortical areas, each comprising a set of nonidentical phase oscillators. In the investigations of our model, we applied the Ott-Antonsen theory and the Pikovsky-Rosenblum reduction methods to the original system.

RESULTS

The results derived from our mathematical model satisfactorily reproduce the experimental data obtained by EEG measurements. Furthermore, they show that modifying the coupling strength from the thalamic region to a cortical region affects the duration of phase synchronization, while a change in the feedback to the thalamus affects the strength of synchronization in the cortex. In addition, our model provides an explanation in terms of nonlinear dynamics as to why brain waves desynchronize after a given phase reset.

CONCLUSION

Our model can explain functional differences seen between EEG records of healthy subjects and schizophrenia patients on a system theoretic basis. Because of this and its predictive character, the model may be considered to pave the way towards an early and reliable clinical detection of schizophrenia that is dependent on the interconnections between the thalamic and cortical regions. In particular, the model parameter that describes the strength of this connection can be used for a diagnostic classification of schizophrenia patients.

Altered functional connectivity links in neuroleptic-naïve and neuroleptic-treated patients with schizophrenia, and their relation to symptoms including volition

In order to analyze functional connectivity in untreated and treated patients with schizophrenia, resting-state fMRI data were obtained for whole-brain functional connectivity analysis from 22 first-episode neuroleptic-naïve schizophrenia (NNS), 61 first-episode neuroleptic-treated schizophrenia (NTS) patients, and 60 healthy controls (HC). Reductions were found in untreated and treated patients in the functional connectivity between the posterior cingulate gyrus and precuneus, and this was correlated with the reduction in volition from the Positive and Negative Symptoms Scale (PANSS), that is in the willful initiation, sustenance, and control of thoughts, behavior, movements, and speech, and with the general and negative symptoms. In addition in both patient groups interhemispheric functional connectivity was weaker between the orbitofrontal cortex, amygdala and temporal pole. These functional connectivity changes and the related symptoms were not treated by the neuroleptics. Differences between the patient groups were that there were more strong functional connectivity links in the NNS patients (including in hippocampal, frontal, and striatal circuits) than in the NTS patients. These findings with a whole brain analysis in untreated and treated patients with schizophrenia provide evidence on some of the brain regions implicated in the volitional, other general, and negative symptoms, of schizophrenia that are not treated by neuroleptics so have implications for the development of other treatments; and provide evidence on some brain systems in which neuroleptics do alter the functional connectivity.

A Tradeoff Between Accuracy and Flexibility in a Working Memory Circuit Endowed with Slow Feedback Mechanisms

Recent studies have shown that reverberation underlying mnemonic persistent activity must be slow, to ensure the stability of a working memory system and to give rise to long neural transients capable of accumulation of information over time. Is the slower the underlying process, the better? To address this question, we investigated 3 slow biophysical mechanisms that are activity-dependent and prominently present in the prefrontal cortex: Depolarization-induced suppression of inhibition (DSI), calcium-dependent nonspecific cationic current (ICAN), and short-term facilitation. Using a spiking network model for spatial working memory, we found that these processes enhance the memory accuracy by counteracting noise-induced drifts, heterogeneity-induced biases, and distractors. Furthermore, the incorporation of DSI and ICAN enlarges the range of network's parameter values required for working memory function. However, when a progressively slower process dominates the network, it becomes increasingly more difficult to erase a memory trace. We demonstrate this accuracy-flexibility tradeoff quantitatively and interpret it using a state-space analysis. Our results supports the scenario where N-methyl-d-aspartate receptor-dependent recurrent excitation is the workhorse for the maintenance of persistent activity, whereas slow synaptic or cellular processes contribute to the robustness of mnemonic function in a tradeoff that potentially can be adjusted according to behavioral demands.

Working memory in schizophrenia: behavioral and neural evidence for reduced susceptibility to item-specific proactive interference

BACKGROUND

Susceptibility to item-specific proactive interference (PI) contributes to interindividual differences in working memory (WM) capacity and complex cognition relying on WM. Although WM deficits are a well-recognized impairment in schizophrenia, the underlying pathophysiological effects on specific WM control functions, such as the ability to resist item-specific PI, remain unknown. Moreover, opposing hypotheses on increased versus reduced PI susceptibility in schizophrenia are both justifiable by the extant literature.

METHODS

To provide first insights into the behavioral and neural correlates of PI-related WM control in schizophrenia, a functional magnetic resonance imaging experiment was conducted in a sample of 20 patients and 20 well-matched control subjects. Demands on item-specific PI were experimentally manipulated in a recent-probes task (three runs, 64 trials each) requiring subjects to encode and maintain a set of four target items per trial.

RESULTS

Compared with healthy control subjects, schizophrenia patients showed a significantly reduced PI susceptibility in both accuracy and latency measures. Notably, reduced PI susceptibility in schizophrenia was not associated with overall WM impairments and thus constituted an independent phenomenon. In addition, PI-related activations in inferior frontal gyrus and anterior insula, typically assumed to support PI resistance, were reduced in schizophrenia, thus ruling out increased neural efforts as a potential cause of the patients' reduced PI susceptibility.

CONCLUSIONS

The present study provides first evidence for a diminished vulnerability of schizophrenia patients to item-specific PI, which is presumably a consequence of the patients' more efficient clearing of previously relevant WM traces and the accordingly reduced likelihood for item-specific PI to occur.

Biases in facial and vocal emotion recognition in chronic schizophrenia

There has been extensive research on impaired emotion recognition in schizophrenia in the facial and vocal modalities. The literature points to biases toward non-relevant emotions for emotional faces but few studies have examined biases in emotional recognition across different modalities (facial and vocal). In order to test emotion recognition biases, we exposed 23 patients with stabilized chronic schizophrenia and 23 healthy controls (HCs) to emotional facial and vocal tasks asking them to rate emotional intensity on visual analog scales. We showed that patients with schizophrenia provided higher intensity ratings on the non-target scales (e.g., surprise scale for fear stimuli) than HCs for the both tasks. Furthermore, with the exception of neutral vocal stimuli, they provided the same intensity ratings on the target scales as the HCs. These findings suggest that patients with chronic schizophrenia have emotional biases when judging emotional stimuli in the visual and vocal modalities. These biases may stem from a basic sensorial deficit, a high-order cognitive dysfunction, or both. The respective roles of prefrontal-subcortical circuitry and the basal ganglia are discussed.

Generation and characterization of humanized mice carrying COMT158 Met/Val alleles

The Val158Met polymorphism of human catechol-o-methyltransferase (COMT) is one of the most well-studied single-nucleotide polymorphisms in neuropsychiatry; however, findings are inconsistent due to human genetic heterogeneity. We created the first 'humanized' COMTVal158Met mouse lines, which carry either human COMT Val or Met alleles via gene targeting. The 'humanized' mouse model enables strict comparison of the physiological functions of the two alleles. Consistent with human observation, Met/Met mice exhibited a 30% reduction in enzymatic activity compared with Val/Val mice. On the basis of the reported differences in human Met and Val carriers across working memory, fear processes and sensorimotor gating, we examined these functions between sibling Met/Met and Val/Val mice. Val/Val mice exhibited robust reductions in spatial working memory compared with Met/Met mice in both sexes, with tolcapone treatment significantly reversing the Val/Val alternation deficits. Sex effects were observed in other behaviors, with male Val/Val mice exhibited lower prepulse inhibition compared with Met/Met mice, whereas female mice exhibited the opposite phenotype. Female but not male Met/Met mice exhibited reduced contextual fear, increased cued fear, and reduced extinction recall. Thus, these mice (1) support the argument that human COMT Val158Met polymorphism modulates behavioral functions and most importantly (2) exhibit the expected treatment effects supporting the 'inverted U shaped' dose response of catecholamine signaling on cognitive function. This model will be invaluable for understanding the effects of human COMT Val158Met polymorphism on cortical development and behavioral functions, and how this polymorphism modulates treatment response.

Computational psychiatry: the brain as a phantastic organ

In this Review, we discuss advances in computational neuroscience that relate to psychiatry. We review computational psychiatry in terms of the ambitions of investigators, emerging domains of application, and future work. Our focus is on theoretical formulations of brain function that put subjective beliefs and behaviour within formal (computational) frameworks-frameworks that can be grounded in neurophysiology down to the level of synaptic mechanisms. Understanding the principles that underlie the brain's functional architecture might be essential for an informed phenotyping of psychopathology in terms of its pathophysiological underpinnings. We focus on active (Bayesian) inference and predictive coding. Specifically, we show how basic principles of neuronal computation can be used to explain psychopathology, ranging from impoverished theory of mind in autism to abnormalities of smooth pursuit eye movements in schizophrenia.

Reduced binding potential of GABA-A/benzodiazepine receptors in individuals at ultra-high risk for psychosis: an [18F]-fluoroflumazenil positron emission tomography study

BACKGROUND

Altered transmission of gamma-aminobutyric acid (GABA), a major inhibitory neurotransmitter, may contribute to the development of schizophrenia. The purpose of the present study was to investigate the presence of GABA-A/benzodiazepine (BZ) receptor binding abnormalities in individuals at ultra-high risk (UHR) for psychosis in comparison with normal controls using [(18)F]-fluoroflumazenil (FFMZ) positron emission tomography (PET). In particular, we set regions of interest in the striatum (caudate, putamen, and nucleus accumbens) and medial temporal area (hippocampus and parahippocampal gyrus).

METHODS

Eleven BZ-naive people at UHR and 15 normal controls underwent PET scanning using [(18)F]-FFMZ to measure GABA-A/BZ receptor binding potential. The regional group differences between UHR individuals and normal controls were analyzed using Statistical Parametric Mapping 8 software. Participants were evaluated using the structured interview for prodromal syndromes and neurocognitive function tasks.

RESULTS

People at UHR demonstrated significantly reduced binding potential of GABA-A/BZ receptors in the right caudate.

CONCLUSIONS

Altered GABAergic transmission and/or the imbalance of inhibitory and excitatory systems in the striatum may be present at the putative prodromal stage and play a pivotal role in the pathophysiology of psychosis.

Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia

Although a number of recent studies have examined functional connectivity at rest, few have assessed differences between connectivity both during rest and across active task paradigms. Therefore, the question of whether cortical connectivity patterns remain stable or change with task engagement continues to be unaddressed. We collected multi-scan fMRI data on healthy controls (N=53) and schizophrenia patients (N=42) during rest and across paradigms arranged hierarchically by sensory load. We measured functional network connectivity among 45 non-artifactual distinct brain networks. Then, we applied a novel analysis to assess cross paradigm connectivity patterns applied to healthy controls and patients with schizophrenia. To detect these patterns, we fit a group by task full factorial ANOVA model to the group average functional network connectivity values. Our approach identified both stable (static effects) and state-based differences (dynamic effects) in brain connectivity providing a better understanding of how individuals' reactions to simple sensory stimuli are conditioned by the context within which they are presented. Our findings suggest that not all group differences observed during rest are detectable in other cognitive states. In addition, the stable differences of heightened connectivity between multiple brain areas with thalamus across tasks underscore the importance of the thalamus as a gateway to sensory input and provide new insight into schizophrenia.

Diagnostic specificity and familiality of early versus late evoked potentials to auditory paired stimuli across the schizophrenia-bipolar psychosis spectrum

Disrupted sensory processing is a core feature of psychotic disorders. Auditory paired stimuli (PS) evoke a complex neural response, but it is uncertain which aspects reflect shared and/or distinct liability for the most common severe psychoses, schizophrenia (SZ) and psychotic bipolar disorder (BDP). Evoked time-voltage/time-frequency domain responses quantified with EEG during a typical PS paradigm (S1-S2) were compared among proband groups (SZ [n = 232], BDP [181]), their relatives (SZrel [259], BDPrel [220]), and healthy participants (H [228]). Early S1-evoked responses were reduced in SZ and BDP, while later/S2 abnormalities showed SZ/SZrel and BDP/BDPrel specificity. Relatives' effects were absent/small despite significant familiality of the entire auditorineural response. This pattern suggests general and divergent biological pathways associated with psychosis, yet may reflect complications with conditioning solely on clinical phenomenology.

Nonhuman gamblers: lessons from rodents, primates, and robots

The search for neuronal and psychological underpinnings of pathological gambling in humans would benefit from investigating related phenomena also outside of our species. In this paper, we present a survey of studies in three widely different populations of agents, namely rodents, non-human primates, and robots. Each of these populations offers valuable and complementary insights on the topic, as the literature demonstrates. In addition, we highlight the deep and complex connections between relevant results across these different areas of research (i.e., cognitive and computational neuroscience, neuroethology, cognitive primatology, neuropsychiatry, evolutionary robotics), to make the case for a greater degree of methodological integration in future studies on pathological gambling.

Connectivity, pharmacology, and computation: toward a mechanistic understanding of neural system dysfunction in schizophrenia

Neuropsychiatric diseases such as schizophrenia and bipolar illness alter the structure and function of distributed neural networks. Functional neuroimaging tools have evolved sufficiently to reliably detect system-level disturbances in neural networks. This review focuses on recent findings in schizophrenia and bipolar illness using resting-state neuroimaging, an advantageous approach for biomarker development given its ease of data collection and lack of task-based confounds. These benefits notwithstanding, neuroimaging does not yet allow the evaluation of individual neurons within local circuits, where pharmacological treatments ultimately exert their effects. This limitation constitutes an important obstacle in translating findings from animal research to humans and from healthy humans to patient populations. Integrating new neuroscientific tools may help to bridge some of these gaps. We specifically discuss two complementary approaches. The first is pharmacological manipulations in healthy volunteers, which transiently mimic some cardinal features of psychiatric conditions. We specifically focus on recent neuroimaging studies using the NMDA receptor antagonist, ketamine, to probe glutamate synaptic dysfunction associated with schizophrenia. Second, we discuss the combination of human pharmacological imaging with biophysically informed computational models developed to guide the interpretation of functional imaging studies and to inform the development of pathophysiologic hypotheses. To illustrate this approach, we review clinical investigations in addition to recent findings of how computational modeling has guided inferences drawn from our studies involving ketamine administration to healthy subjects. Thus, this review asserts that linking experimental studies in humans with computational models will advance to effort to bridge cellular, systems, and clinical neuroscience approaches to psychiatric disorders.

Reinforcement learning and dopamine in schizophrenia: dimensions of symptoms or specific features of a disease group?

Abnormalities in reinforcement learning are a key finding in schizophrenia and have been proposed to be linked to elevated levels of dopamine neurotransmission. Behavioral deficits in reinforcement learning and their neural correlates may contribute to the formation of clinical characteristics of schizophrenia. The ability to form predictions about future outcomes is fundamental for environmental interactions and depends on neuronal teaching signals, like reward prediction errors. While aberrant prediction errors, that encode non-salient events as surprising, have been proposed to contribute to the formation of positive symptoms, a failure to build neural representations of decision values may result in negative symptoms. Here, we review behavioral and neuroimaging research in schizophrenia and focus on studies that implemented reinforcement learning models. In addition, we discuss studies that combined reinforcement learning with measures of dopamine. Thereby, we suggest how reinforcement learning abnormalities in schizophrenia may contribute to the formation of psychotic symptoms and may interact with cognitive deficits. These ideas point toward an interplay of more rigid versus flexible control over reinforcement learning. Pronounced deficits in the flexible or model-based domain may allow for a detailed characterization of well-established cognitive deficits in schizophrenia patients based on computational models of learning. Finally, we propose a framework based on the potentially crucial contribution of dopamine to dysfunctional reinforcement learning on the level of neural networks. Future research may strongly benefit from computational modeling but also requires further methodological improvement for clinical group studies. These research tools may help to improve our understanding of disease-specific mechanisms and may help to identify clinically relevant subgroups of the heterogeneous entity schizophrenia.

Increased firing irregularity as an emergent property of neural-state transition in monkey prefrontal cortex

Flexible behaviors are organized by complex neural networks in the prefrontal cortex. Recent studies have suggested that such networks exhibit multiple dynamical states, and can switch rapidly from one state to another. In many complex systems such as the brain, the early-warning signals that may predict whether a critical threshold for state transitions is approaching are extremely difficult to detect. We hypothesized that increases in firing irregularity are a crucial measure for predicting state transitions in the underlying neuronal circuits of the prefrontal cortex. We used both experimental and theoretical approaches to test this hypothesis. Experimentally, we analyzed activities of neurons in the prefrontal cortex while monkeys performed a maze task that required them to perform actions to reach a goal. We observed increased firing irregularity before the activity changed to encode goal-to-action information. Theoretically, we constructed theoretical generic neural networks and demonstrated that changes in neuronal gain on functional connectivity resulted in a loss of stability and an altered state of the networks, accompanied by increased firing irregularity. These results suggest that assessing the temporal pattern of neuronal fluctuations provides important clues regarding the state stability of the prefrontal network. We also introduce a novel scheme that the prefrontal cortex functions in a metastable state near the critical point of bifurcation. According to this scheme, firing irregularity in the prefrontal cortex indicates that the system is about to change its state and the flow of information in a flexible manner, which is essential for executive functions. This metastable and/or critical dynamical state of the prefrontal cortex may account for distractibility and loss of flexibility in the prefrontal cortex in major mental illnesses such as schizophrenia.

Abrupt and gradual transitions between low and hyperexcited firing frequencies in neuronal models with fast synaptic excitation: a comparative study

Hyperexcitability of neuronal networks is one of the hallmarks of epileptic brain seizure generation, and results from a net imbalance between excitation and inhibition that promotes excessive abnormal firing frequencies. The transition between low and high firing frequencies as the levels of recurrent AMPA excitation change can occur either gradually or abruptly. We used modeling, numerical simulations, and dynamical systems tools to investigate the biophysical and dynamic mechanisms that underlie these two identified modes of transition in recurrently connected neurons via AMPA excitation. We compare our results and demonstrate that these two modes of transition are qualitatively different and can be linked to different intrinsic properties of the participating neurons.

Dopaminergic control of long-term depression/long-term potentiation threshold in prefrontal cortex

Long-term memory in the prefrontal cortex is a necessary component of adaptive executive control and is strongly modulated by dopamine. However, the functional significance of this dopaminergic modulation remains elusive. In vitro experimental results on dopamine-dependent shaping of prefrontal long-term plasticity often appear inconsistent and, altogether, draw a complicated picture. It is also generally difficult to relate these findings to in vivo observations given strong differences between the two experimental conditions. This study presents a unified view of the functional role of dopamine in the prefrontal cortex by framing it within the Bienenstock-Cooper-Munro theory of cortical plasticity. We investigate dopaminergic modulation of long-term plasticity through a multicompartment Hodgkin-Huxley model of a prefrontal pyramidal neuron. Long-term synaptic plasticity in the model is governed by a calcium- and dopamine-dependent learning rule, in which dopamine exerts its action via D1 and D2 dopamine receptors in a concentration-dependent manner. Our results support a novel function of dopamine in the prefrontal cortex, namely that it controls the synaptic modification threshold between long-term depression and potentiation in pyramidal neurons. The proposed theoretical framework explains a wide range of experimental results and provides a link between in vitro and in vivo studies of dopaminergic plasticity modulation. It also suggests that dopamine may constitute a new player in metaplastic and homeostatic processes in the prefrontal cortex.

Dopamine regulates two classes of primate prefrontal neurons that represent sensory signals

The lateral prefrontal cortex (PFC), a hub of higher-level cognitive processing, is strongly modulated by midbrain dopamine (DA) neurons. The cellular mechanisms have been comprehensively studied in the context of short-term memory, but little is known about how DA regulates sensory inputs to PFC that precede and give rise to such memory activity. By preparing recipient cortical circuits for incoming signals, DA could be a powerful determinant of downstream cognitive processing. Here, we tested the hypothesis that prefrontal DA regulates the representation of sensory signals that are required for perceptual decisions. In rhesus monkeys trained to report the presence or absence of visual stimuli at varying levels of contrast, we simultaneously recorded extracellular single-unit activity and applied DA to the immediate vicinity of the neurons by micro-iontophoresis. We found that DA modulation of prefrontal neurons is not uniform but tailored to specialized neuronal classes. In one population of neurons, DA suppressed activity with high temporal precision but preserved signal/noise ratio. Neurons in this group had short visual response latencies and comprised all recorded narrow-spiking, putative interneurons. In a distinct population, DA increased excitability and enhanced signal/noise ratio by reducing response variability. These neurons had longer visual response latencies and were composed exclusively of broad-spiking, putative pyramidal neurons. By gating sensory inputs to PFC and subsequently strengthening the representation of sensory signals, DA might play an important role in shaping how the PFC initiates appropriate behavior in response to changes in the sensory environment.

Urbanicity, social adversity and psychosis

In recent years, there has been increasing interest in research on geographical variation in the incidence of schizophrenia and other psychoses. In this paper, we review the evidence on variation in incidence of schizophrenia and other psychoses in terms of place, as well as the individual- and area-level factors that account for this variation. We further review findings on potential mechanisms that link adverse urban environment and psychosis. There is evidence from earlier and more recent studies that urbanicity is associated with an increased incidence of schizophrenia and non-affective psychosis. In addition, considerable variation in incidence across neighbourhoods has been observed for these disorders. Findings suggest it is unlikely that social drift alone can fully account for geographical variation in incidence. Evidence further suggests that the impact of adverse social contexts - indexed by area-level exposures such as population density, social fragmentation and deprivation - on risk of psychosis is explained (confounding) or modified (interaction) by environmental exposures at the individual level (i.e., cannabis use, social adversity, exclusion and discrimination). On a neurobiological level, several studies suggest a close link between social adversity, isolation and stress on the one hand, and monoamine dysfunction on the other, which resembles findings in schizophrenia patients. However, studies directly assessing correlations between urban stress or discrimination and neurobiological alterations in schizophrenia are lacking to date.

Necessity of noise in physiology and medicine

Noise is omnipresent in biomedical systems and signals. Conventional views assume that its presence is detrimental to systems' performance and accuracy. Hence, various analytic approaches and instrumentation have been designed to remove noise. On the contrary, recent contributions have shown that noise can play a beneficial role in biomedical systems. The results of this literature review indicate that noise is an essential part of biomedical systems and often plays a fundamental role in the performance of these systems. Furthermore, in preliminary work, noise has demonstrated therapeutic potential to alleviate the effects of various diseases. Further research into the role of noise and its applications in medicine is likely to lead to novel approaches to the treatment of diseases and prevention of disability.

Charles Bonnet syndrome: evidence for a generative model in the cortex?

Several theories propose that the cortex implements an internal model to explain, predict, and learn about sensory data, but the nature of this model is unclear. One condition that could be highly informative here is Charles Bonnet syndrome (CBS), where loss of vision leads to complex, vivid visual hallucinations of objects, people, and whole scenes. CBS could be taken as indication that there is a generative model in the brain, specifically one that can synthesise rich, consistent visual representations even in the absence of actual visual input. The processes that lead to CBS are poorly understood. Here, we argue that a model recently introduced in machine learning, the deep Boltzmann machine (DBM), could capture the relevant aspects of (hypothetical) generative processing in the cortex. The DBM carries both the semantics of a probabilistic generative model and of a neural network. The latter allows us to model a concrete neural mechanism that could underlie CBS, namely, homeostatic regulation of neuronal activity. We show that homeostatic plasticity could serve to make the learnt internal model robust against e.g. degradation of sensory input, but overcompensate in the case of CBS, leading to hallucinations. We demonstrate how a wide range of features of CBS can be explained in the model and suggest a potential role for the neuromodulator acetylcholine. This work constitutes the first concrete computational model of CBS and the first application of the DBM as a model in computational neuroscience. Our results lend further credence to the hypothesis of a generative model in the brain.

The cerebral cortex is central to many aspects of cognition and intelligence in humans and other mammals, but our scientific understanding of the computational principles underlying cortical processing is still limited. We might gain insights by considering visual hallucinations, specifically in a pathology known as Charles Bonnet syndrome, where patients suffering from visual impairment experience hallucinatory images that rival the vividness and complexity of normal seeing. Such generation of rich internal imagery could naturally be accounted for by theories that posit that the cortex implements an internal generative model of sensory input. Perception then could entail the synthesis of internal explanations that are evaluated by testing whether what they predict is consistent with actual sensory input. Here, we take an approach from artificial intelligence that is based on similar ideas, the deep Boltzmann machine, use it as a model of generative processing in the cortex, and examine various aspects of Charles Bonnet syndrome in computer simulations. In particular, we explain why the synthesis of internal explanations, which is so useful for perception, goes astray in the syndrome as neurons overcompensate for the lack of sensory input by increasing spontaneous activity.

Noise as a mechanism of anomalous face processing among persons with Schizophrenia

There is substantial evidence that people with Schizophrenia (SCZ) have altered visual perception and cognition, including impaired face processing. However, the mechanism(s) underlying this observation are not yet known. Eye movement studies have found that people with SCZ do not direct their gaze to the most informative regions of the face (e.g., the eyes). This suggests that SCZ patients may be less able to extract the most relevant face information and therefore have decreased calculation efficiency. In addition, research with non-face stimuli indicates that SCZ is associated with increased levels of internal noise. Importantly, both calculation efficiency and internal noise have been shown to underpin face perception among healthy observers. Therefore, the current study applies noise masking to upright and inverted faces to determine if face processing deficits among those with SCZ are the result of changes in calculation efficiency, internal noise, or both. Consistent with previous results, SCZ participants exhibited higher contrast thresholds in order to identify masked target faces. However, higher thresholds were associated with increases in internal noise but unrelated to changes in calculation efficiency. These results suggest that SCZ-related face processing deficits are the result of a decreased noise-to-signal ratio. The source of increased processing noise among these patients is unclear, but may emanate from abnormal neural dynamics.

A quantitative theory of the functions of the hippocampal CA3 network in memory

A quantitative computational theory of the operation of the hippocampal CA3 system as an autoassociation or attractor network used in episodic memory system is described. In this theory, the CA3 system operates as a single attractor or autoassociation network to enable rapid, one-trial, associations between any spatial location (place in rodents, or spatial view in primates) and an object or reward, and to provide for completion of the whole memory during recall from any part. The theory is extended to associations between time and object or reward to implement temporal order memory, also important in episodic memory. The dentate gyrus (DG) performs pattern separation by competitive learning to produce sparse representations suitable for setting up new representations in CA3 during learning, producing for example neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells produce by the very small number of mossy fiber (MF) connections to CA3 a randomizing pattern separation effect important during learning but not recall that separates out the patterns represented by CA3 firing to be very different from each other, which is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path (pp) input to CA3 is quantitatively appropriate to provide the cue for recall in CA3, but not for learning. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described, and support the theory.

Aripiprazole differentially regulates the expression of Gad67 and γ-aminobutyric acid transporters in rat brain

The molecular etiology of schizophrenia comprises abnormal neurotransmission of the amino acid GABA (γ-aminobutyric acid). Neuropathological studies convincingly revealed reduced expression of glutamic acid decarboxylase (Gad67) in GABAergic interneurons. Several antipsychotics influence the expression of GABAergic genes, but aripiprazole (APZ), a partial dopaminergic and serotonergic receptor agonist, has not been involved into these studies so far. We treated Sprague-Dawley rats for 4 weeks or 4 months with APZ suspended in drinking water and doses of 10 and 40 mg per kg body weight. Gene expression of Gad67, the vesicular GABA transporter Slc32a1 (solute carrier family, Vgat), the transmembrane transporters Slc6a1 (Gat1) and Slc6a11 (Gat3) was assessed by semiquantitative radioactive in situ hybridization. APZ treatment resulted in time- and dose-dependent effects with qualitative differences between brain regions. In the 10-mg group, Slc6a1 was strongly induced after 4 weeks in the hippocampus, amygdala, and cerebral cortex, followed by an induction of Gad67 in the same regions after 4 months, while frontocortical regions as well as basal ganglia showed dose-dependent reductions of Gad67 expression after 4 months. In several frontocortical and subcortical regions, we observed a decrease of Slc32a1 and an increase of Slc6a11 expression. In conclusion, APZ modulates gene expression of GABAergic marker genes involved into pathogenetic theories of schizophrenia. APZ only partially mirrors the effects of other antipsychotics with some important differences regarding brain regions. The findings might be explained by regulatory connections between serotonergic, GABAergic, and dopaminergic neurotransmission and should be validated in behavioral animal models of psychotic disorders.

GABA levels in the dorsal anterior cingulate cortex associated with difficulty ignoring smoking-related cues in tobacco-dependent volunteers

Substance abusers have difficulty ignoring drug-related cues, which is associated with relapse vulnerability. This 'attentional bias' towards drug cues translates into an inability to ignore drug-related stimuli and may reflect deficits in the brain regions, such as the dorsal anterior cingulate cortex (dACC)-a key region in cognitive control and adaptive decision making. Quantifying relationships between attentional biases to drug cues and dACC neurochemistry could aid in identifying neurobiological mechanisms associated with increased relapse vulnerability precipitated by drug cues. As gamma-aminobutyric acid (GABA) deficits have been linked to impaired cognition and addictive disorders, we hypothesized that reduced GABA in the dACC would be associated with increased attentional biases towards smoking-related cues. We confirmed this hypothesis among nicotine-dependent tobacco smokers by combining an offline behavioral measure of attentional bias with magnetic resonance spectroscopy. Smokers with the greatest attentional bias also experienced more negative affect during early nicotine withdrawal. Findings revealed a relationship between heightened reactivity to drug cues, and both decreasing dACC GABA and early withdrawal symptoms. Because reduced GABA function in frontal brain regions disrupt cognitive function, our findings suggest that smokers with diminished dACC GABA may lack the cognitive resources to successfully ignore highly salient distractors such as tobacco-related stimuli and therefore might be more prone to cue-induced relapse. This newly discovered relationship between dACC GABA and attentional bias provides evidence for a neurochemical target, which may aid smoking cessation in highly cue-reactive individuals.

Holding multiple items in short term memory: a neural mechanism

Human short term memory has a capacity of several items maintained simultaneously. We show how the number of short term memory representations that an attractor network modeling a cortical local network can simultaneously maintain active is increased by using synaptic facilitation of the type found in the prefrontal cortex. We have been able to maintain 9 short term memories active simultaneously in integrate-and-fire simulations where the proportion of neurons in each population, the sparseness, is 0.1, and have confirmed the stability of such a system with mean field analyses. Without synaptic facilitation the system can maintain many fewer memories active in the same network. The system operates because of the effectively increased synaptic strengths formed by the synaptic facilitation just for those pools to which the cue is applied, and then maintenance of this synaptic facilitation in just those pools when the cue is removed by the continuing neuronal firing in those pools. The findings have implications for understanding how several items can be maintained simultaneously in short term memory, how this may be relevant to the implementation of language in the brain, and suggest new approaches to understanding and treating the decline in short term memory that can occur with normal aging.

Updating the mild encephalitis hypothesis of schizophrenia

Schizophrenia seems to be a heterogeneous disorder. Emerging evidence indicates that low level neuroinflammation (LLNI) may not occur infrequently. Many infectious agents with low overall pathogenicity are risk factors for psychoses including schizophrenia and for autoimmune disorders. According to the mild encephalitis (ME) hypothesis, LLNI represents the core pathogenetic mechanism in a schizophrenia subgroup that has syndromal overlap with other psychiatric disorders. ME may be triggered by infections, autoimmunity, toxicity, or trauma. A 'late hit' and gene-environment interaction are required to explain major findings about schizophrenia, and both aspects would be consistent with the ME hypothesis. Schizophrenia risk genes stay rather constant within populations despite a resulting low number of progeny; this may result from advantages associated with risk genes, e.g., an improved immune response, which may act protectively within changing environments, although they are associated with the disadvantage of increased susceptibility to psychotic disorders. Specific schizophrenic symptoms may arise with instances of LLNI when certain brain functional systems are involved, in addition to being shaped by pre-existing liability factors. Prodrome phase and the transition to a diseased status may be related to LLNI processes emerging and varying over time. The variability in the course of schizophrenia resembles the varying courses of autoimmune disorders, which result from three required factors: genes, the environment, and the immune system. Preliminary criteria for subgrouping neurodevelopmental, genetic, ME, and other types of schizophrenias are provided. A rare example of ME schizophrenia may be observed in Borna disease virus infection. Neurodevelopmental schizophrenia due to early infections has been estimated by others to explain approximately 30% of cases, but the underlying pathomechanisms of transition to disease remain in question. LLNI (e.g. from reactivation related to persistent infection) may be involved and other pathomechanisms including dysfunction of the blood-brain barrier or the blood-CSF barrier, CNS-endogenous immunity and the volume transmission mode balancing wiring transmission (the latter represented mainly by synaptic transmission, which is often described as being disturbed in schizophrenia). Volume transmission is linked to CSF signaling; and together could represent a common pathogenetic link for the distributed brain dysfunction, dysconnectivity, and brain structural abnormalities observed in schizophrenia. In addition, CSF signaling may extend into peripheral tissues via the CSF outflow pathway along brain nerves and peripheral nerves, and it may explain the peripheral topology of neuronal dysfunctions found, like in olfactory dysfunction, dysautonomia, and even in peripheral tissues, i.e., the muscle lesions that were found in 50% of cases. Modulating factors in schizophrenia, such as stress, hormones, and diet, are also modulating factors in the immune response. Considering recent investigations of CSF, the ME schizophrenia subgroup may constitute approximately 40% of cases.

Development of antipsychotic medications with novel mechanisms of action based on computational modeling of hippocampal neuropathology

A large number of cellular level abnormalities have been identified in the hippocampus of schizophrenic subjects. Nonetheless, it remains uncertain how these pathologies interact at a system level to create clinical symptoms, and this has hindered the development of more effective antipsychotic medications. Using a 72-processor supercomputer, we created a tissue level hippocampal simulation, featuring multicompartmental neuron models with multiple ion channel subtypes and synaptic channels with realistic temporal dynamics. As an index of the schizophrenic phenotype, we used the specific inability of the model to attune to 40 Hz (gamma band) stimulation, a well-characterized abnormality in schizophrenia. We examined several possible combinations of putatively schizophrenogenic cellular lesions by systematically varying model parameters representing NMDA channel function, dendritic spine density, and GABA system integrity, conducting 910 trials in total. Two discrete “clusters” of neuropathological changes were identified. The most robust was characterized by co-occurring modest reductions in NMDA system function (-30%) and dendritic spine density (-30%). Another set of lesions had greater NMDA hypofunction along with low level GABA system dysregulation. To the schizophrenic model, we applied the effects of 1,500 virtual medications, which were implemented by varying five model parameters, independently, in a graded manner; the effects of known drugs were also applied. The simulation accurately distinguished agents that are known to lack clinical efficacy, and identified novel mechanisms (e.g., decrease in AMPA conductance decay time constant, increase in projection strength of calretinin-positive interneurons) and combinations of mechanisms that could re-equilibrate model behavior. These findings shed light on the mechanistic links between schizophrenic neuropathology and the gamma band oscillatory abnormalities observed in the illness. As such, they generate specific falsifiable hypotheses, which can guide postmortem and other laboratory research. Significantly, this work also suggests specific non-obvious targets for potential pharmacologic agents.

Increased intrinsic brain activity in the striatum reflects symptom dimensions in schizophrenia

Striatal dysfunction is thought to be a fundamental element in schizophrenia. Striatal dopamine dysfunction impacts on reward processing and learning and is present even at rest. Here, we addressed the question whether and how spontaneous neuronal activity in the striatum is altered in schizophrenia. We therefore assessed intrinsic striatal activity and its relation with disorder states and symptom dimensions in patients with schizophrenia. We performed resting-state functional (rs-fMRI) and structural magnetic resonance imaging as well as psychometric assessment in 21 schizophrenic patients during psychosis. On average 9 months later, we acquired follow-up data during psychotic remission and with comparable levels of antipsychotic medication. Twenty-one age- and sex-matched healthy controls were included in the study. Independent component analysis of fMRI data yielded spatial maps and time-courses of coherent ongoing blood-oxygen-level-dependent signal fluctuations, which were used for group comparisons and correlation analyses with scores of the positive and negative syndrome scale. During psychosis, coherent intrinsic activity of the striatum was increased in the dorsal part and correlated with positive symptoms such as delusion and hallucination. In psychotic remission of the same patients, activity of the ventral striatum was increased and correlated with negative symptoms such as emotional withdrawal and blunted affect. Results were controlled for volumetric and medication effects. These data provide first evidence that in schizophrenia intrinsic activity is changed in the striatum and corresponds to disorder states and symptom dimensions.

Long-range temporal correlations in the subthalamic nucleus of patients with Parkinson's disease

Neuronal activity in the subthalamic nucleus (STN) of patients with Parkinson's disease (PD) is characterised by excessive neuronal synchronization, particularly in the beta frequency range. However, less is known about the temporal dynamics of neuronal oscillations in PD. In this respect long-range temporal correlations (LRTC) are of special interest as they quantify the neuronal dynamics on different timescales and have been shown to be relevant for optimal information processing in the brain. While the presence of LRTC has been demonstrated in cortical data, their existence in deep brain structures remains an open question. We investigated (i) whether LRTC are present in local field potentials (LFP) recorded bilaterally from the STN at wakeful rest in ten patients with PD after overnight withdrawal of levodopa (OFF) and (ii) whether LRTC can be modulated by levodopa treatment (ON). Detrended fluctuation analysis was utilised in order to quantify the temporal dynamics in the amplitude fluctuations of LFP oscillations. We demonstrated for the first time the presence of LRTC (extending up to 50 s) in the STN. Importantly, the ON state was characterised by significantly stronger LRTC than the OFF state, both in beta (13-35 Hz) and high-frequency (> 200 Hz) oscillations. The existence of LRTC in subcortical structures such as STN provides further evidence for their ubiquitous nature in the brain. The weaker LRTC in the OFF state might indicate limited information processing in the dopamine-depleted basal ganglia. The present results implicate LRTC as a potential biomarker of pathological neuronal processes in PD.

Working memory encoding and maintenance deficits in schizophrenia: neural evidence for activation and deactivation abnormalities

Substantial evidence implicates working memory (WM) as a core deficit in schizophrenia (SCZ), purportedly due to primary deficits in dorsolateral prefrontal cortex functioning. Recent findings suggest that SCZ is also associated with abnormalities in suppression of certain regions during cognitive engagement--namely the default mode system--that may further contribute to WM pathology. However, no study has systematically examined activation and suppression abnormalities across both encoding and maintenance phases of WM in SCZ. Twenty-eight patients and 24 demographically matched healthy subjects underwent functional magnetic resonance imaging at 3T while performing a delayed match-to-sample WM task. Groups were accuracy matched to rule out performance effects. Encoding load was identical across subjects to facilitate comparisons across WM phases. We examined activation differences using an assumed model approach at the whole-brain level and within meta-analytically defined WM areas. Despite matched performance, we found regions showing less recruitment during encoding and maintenance for SCZ subjects. Furthermore, we identified 2 areas closely matching the default system, which SCZ subjects failed to deactivate across WM phases. Lastly, activation in prefrontal regions predicted the degree of deactivation for healthy but not SCZ subjects. Current results replicate and extend prefrontal recruitment abnormalities across WM phases in SCZ. Results also indicate deactivation abnormalities across WM phases, possibly due to inefficient prefrontal recruitment. Such regional deactivation may be critical for suppressing sources of interference during WM trace formation. Thus, deactivation deficits may constitute an additional source of impairments, which needs to be further characterized for a complete understanding of WM pathology in SCZ.

Schizotypal people stick longer to their first choices

Many studies have reported that schizophrenic patients show a Bias Against Disconfirmatory Evidence (BADE). This cognitive bias has been related to the formation and maintenance of delusion. The aim of this paper was to study whether BADE was present in healthy people displaying psychometric schizotypy, and to compare a closure task, which has been used for schizophrenia, with a new chronometric paradigm. Results with the new paradigm showed that the high-schizotypy group maintained their initial hypotheses longer than the low-schizotypy group. This finding corroborated the similarities between schizophrenic disorder and schizotypal traits, in this case with respect to the BADE. Research of this kind could facilitate the study of cognition in the schizophrenic spectrum without the difficulties of working with schizophrenic patients for some tasks and the assessment and early intervention in at-risk populations.

Immunization with DAT fragments is associated with long-term striatal impairment, hyperactivity and reduced cognitive flexibility in mice

Background

Possible interactions between nervous and immune systems in neuro-psychiatric disorders remain elusive. Levels of brain dopamine transporter (DAT) have been implicated in several impulse-control disorders, like attention deficit / hyperactivity disorder (ADHD) and obsessive-compulsive disorder (OCD). Here, we assessed the interplay between DAT auto-immunity and behavioural / neurochemical phenotype.

Methods

Male CD-1 mice were immunized with DAT peptide fragments (DAT-i), or vehicle alone (VEH), to generate elevated circulating levels of DAT auto-antibodies (aAbs). Using an operant delay-of-reward task (20 min daily sessions; timeout 25 sec), mice had a choice between either an immediate small amount of food (SS), or a larger amount of food after a delay (LL), which increased progressively across sessions (from 0 to 150 sec).

Results

DAT-i mice exhibited spontaneous hyperactivity (2 h-longer wake-up peak; a wake-up attempt during rest). Two sub-populations differing in behavioural flexibility were identified in the VEH control group: they showed either a clear-cut decision to select LL or clear-cut shifting towards SS, as expected. Compared to VEH controls, choice-behaviour profile of DAT-i mice was markedly disturbed, together with long-lasting alterations of the striatal monoamines. Enhanced levels of DA metabolite HVA in DAT-i mice came along with slower acquisition of basal preferences and with impaired shifting; elevation also in DOPAC levels was associated with incapacity to change a rigid selection strategy. This scarce flexibility of performance is indicative of a poor adaptation to task contingencies.

Conclusions

Hyperactivity and reduced cognitive flexibility are patterns of behaviour consistent with enduring functional impairment of striatal regions. It is yet unclear how anti-DAT antibodies could enter or otherwise affect these brain areas, and which alterations in DAT activity exactly occurred after immunization. Present neuro-behavioural alterations, coming along with an experimentally-induced rise of circulating DAT-directed aAbs, open the issue of a potential role for auto-immunity in vulnerability to impulse-control disorders.

Spreading activation in an attractor network with latching dynamics: automatic semantic priming revisited

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assume a synaptic depression mechanism leading to autonomous transitions between encoded memory patterns (latching dynamics), which account for the major characteristics of automatic semantic priming in humans. Using computer simulations, we demonstrated how findings that challenged attractor-based networks in the past, such as mediated and asymmetric priming, are a natural consequence of our present model's dynamics. Puzzling results regarding backward priming were also given a straightforward explanation. In addition, the current model addresses some of the differences between semantic and associative relatedness and explains how these differences interact with stimulus onset asynchrony in priming experiments.

Smooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia

This paper introduces a model of oculomotor control during the smooth pursuit of occluded visual targets. This model is based upon active inference, in which subjects try to minimise their (proprioceptive) prediction error based upon posterior beliefs about the hidden causes of their (exteroceptive) sensory input. Our model appeals to a single principle – the minimisation of variational free energy – to provide Bayes optimal solutions to the smooth pursuit problem. However, it tries to accommodate the cardinal features of smooth pursuit of partially occluded targets that have been observed empirically in normal subjects and schizophrenia. Specifically, we account for the ability of normal subjects to anticipate periodic target trajectories and emit pre-emptive smooth pursuit eye movements – prior to the emergence of a target from behind an occluder. Furthermore, we show that a single deficit in the postsynaptic gain of prediction error units (encoding the precision of posterior beliefs) can account for several features of smooth pursuit in schizophrenia: namely, a reduction in motor gain and anticipatory eye movements during visual occlusion, a paradoxical improvement in tracking unpredicted deviations from target trajectories and a failure to recognise and exploit regularities in the periodic motion of visual targets. This model will form the basis of subsequent (dynamic causal) models of empirical eye tracking measurements, which we hope to validate, using psychopharmacology and studies of schizophrenia.

Dexamphetamine reduces auditory P3 delta power and phase-locking while increasing gamma power

Auditory P3 amplitude reduction is one of the most robust and replicated findings in schizophrenia. Recent evidence suggests that these reductions are due to reductions in both power and phase-locking at delta and theta frequencies. We have previously shown that the auditory, but not visual, P3 is reduced in healthy participants given the catecholamine releasing agent dexamphetamine. Our aim was to determine whether the auditory P3 amplitude reduction induced by dexamphetamine has similar power and phase locking characteristics to that seen in schizophrenia. Forty-four healthy participants were given 0.45 mg/kg dexamphetamine and placebo, in a double-blinded, placebo-controlled, cross-over design. The task was a three-stimulus auditory odd-ball task, target stimuli were the major stimuli of interest. Individual target trials underwent wavelet analysis to give power and phase-locking of delta (3 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (13-30 Hz) and gamma (30-50 Hz) frequencies for a 50 ms time window centred around the peak of the target P3. Delta power around the P3 peak was significantly reduced when participants were given dexamphetamine. Delta phase-locking was also reduced but only when analysis was targeted at the location of the peak P3 amplitude. In contrast, theta power and phase-locking were not affected by dexamphetamine. These findings suggest that increased catecholamine activity may be responsible for the power and phase-locking reductions of the auditory P3 delta component in patients with schizophrenia. Interestingly, dexamphetamine significantly increased gamma power around the P3 peak. We attempt to link this finding with the gamma alterations that have been found in patients with schizophrenia.