Computational models of schizophrenia and dopamine modulation in the prefrontal cortex

Attractor cortical neurodynamics, schizophrenia, and depression

The local recurrent collateral connections between cortical neurons provide a basis for attractor neural networks for memory, attention, decision-making, and thereby for many aspects of human behavior. In schizophrenia, a reduction of the firing rates of cortical neurons, caused for example by reduced NMDA receptor function or reduced spines on neurons, can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention in the prefrontal cortex, contributing to the cognitive symptoms. Reduced NMDA receptor function in the orbitofrontal cortex by reducing firing rates may produce negative symptoms, by reducing reward, motivation, and emotion. Reduced functional connectivity between some brain regions increases the temporal variability of the functional connectivity, contributing to the reduced stability and more loosely associative thoughts. Further, the forward projections have decreased functional connectivity relative to the back projections in schizophrenia, and this may reduce the effects of external bottom-up inputs from the world relative to internal top-down thought processes. Reduced cortical inhibition, caused by a reduction of GABA neurotransmission, can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. In depression, the lateral orbitofrontal cortex non-reward attractor network system is over-connected and has increased sensitivity to non-reward, providing a new approach to understanding depression. This is complemented by under-sensitivity and under-connectedness of the medial orbitofrontal cortex reward system in depression.

Cortical ensembles selective for context

Neural processing of sensory information is strongly influenced by context. For instance, cortical responses are reduced to predictable stimuli, while responses are increased to novel stimuli that deviate from contextual regularities. Such bidirectional modulation based on preceding sensory context is likely a critical component or manifestation of attention, learning, and behavior, yet how it arises in cortical circuits remains unclear. Using volumetric two-photon calcium imaging and local field potentials in primary visual cortex (V1) from awake mice presented with visual "oddball" paradigms, we identify both reductions and augmentations of stimulus-evoked responses depending, on whether the stimulus was redundant or deviant, respectively. Interestingly, deviance-augmented responses were limited to a specific subset of neurons mostly in supragranular layers. These deviance-detecting cells were spatially intermixed with other visually responsive neurons and were functionally correlated, forming a neuronal ensemble. Optogenetic suppression of prefrontal inputs to V1 reduced the contextual selectivity of deviance-detecting ensembles, demonstrating a causal role for top-down inputs. The presence of specialized context-selective ensembles in primary sensory cortex, modulated by higher cortical areas, provides a circuit substrate for the brain's construction and selection of prediction errors, computations which are key for survival and deficient in many psychiatric disorders.

Detection of H3K4me3 Identifies NeuroHIV Signatures, Genomic Effects of Methamphetamine and Addiction Pathways in Postmortem HIV+ Brain Specimens that Are Not Amenable to Transcriptome Analysis

Human postmortem specimens are extremely valuable resources for investigating translational hypotheses. Tissue repositories collect clinically assessed specimens from people with and without HIV, including age, viral load, treatments, substance use patterns and cognitive functions. One challenge is the limited number of specimens suitable for transcriptional studies, mainly due to poor RNA quality resulting from long postmortem intervals. We hypothesized that epigenomic signatures would be more stable than RNA for assessing global changes associated with outcomes of interest. We found that H3K27Ac or RNA Polymerase (Pol) were not consistently detected by Chromatin Immunoprecipitation (ChIP), while the enhancer H3K4me3 histone modification was abundant and stable up to the 72 h postmortem. We tested our ability to use HeK4me3 in human prefrontal cortex from HIV+ individuals meeting criteria for methamphetamine use disorder or not (Meth +/-) which exhibited poor RNA quality and were not suitable for transcriptional profiling. Systems strategies that are typically used in transcriptional metadata were applied to H3K4me3 peaks revealing consistent genomic activity differences in regions where addiction and neuronal synapses pathway genes are represented, including genes of the dopaminergic system, as well as inflammatory pathways. The resulting comparisons mirrored previously observed effects of Meth on suppressing gene expression and provided insights on neurological processes affected by Meth. The results suggested that H3K4me3 detection in chromatin may reflect transcriptional patterns, thus providing opportunities for analysis of larger numbers of specimens from cases with substance use and neurological deficits. In conclusion, the detection of H3K4me3 in isolated chromatin can be an alternative to transcriptome strategies to increase the power of association using specimens with long postmortem intervals and low RNA quality.

Emulating Cued Recall of Abstract Concepts via Regulated Activation Networks

Abstract concepts play a vital role in decision-making or recall operations because the associations among them are essential for contextual processing. Abstract concepts are complex and difficult to represent (conceptually, formally, or computationally), leading to difficulties in their comprehension and recall. This contribution reports the computational simulation of the cued recall of abstract concepts by exploiting their learned associations. The cued recall operation is realized via a novel geometric back-propagation algorithm that emulates the recall of abstract concepts learned through regulated activation network (RAN) modeling. During recall operation, another algorithm uniquely regulates the activation of concepts (nodes) by injecting excitatory, neutral, and inhibitory signals to other concepts of the same level. A Toy-data problem is considered to illustrate the RAN modeling and recall procedure. The results display how regulation enables contextual awareness among abstract nodes during the recall process. The MNIST dataset is used to show how recall operations retrieve intuitive and non-intuitive blends of abstract nodes. We show that every recall process converges to an optimal image. With more cues, better images are recalled, and every intermediate image obtained during the recall iterations corresponds to the varying cognitive states of the recognition procedure.

Brain dynamics: the temporal variability of connectivity, and differences in schizophrenia and ADHD

We describe advances in the understanding of brain dynamics that are important for understanding the operation of the cerebral cortex in health and disease. In data from 1017 participants from the Human Connectome Project, we show that early visual and connected areas have low temporal variability of their functional connectivity. We show that a low temporal variability of the connectivity of cortical areas is related to high mean functional connectivity between those areas, and provide an account of how these dynamics arise. We then investigate how these concepts help to understand brain dynamics in mental disorders. We find that in both first episode and long-term schizophrenia, reduced functional connectivity of early visual and related temporal cortex areas is associated with increased temporal variability of the functional connectivity, consistent with decreased stability of attractor networks related to sensory processing. In ADHD, we find these functional connectivities are increased and their temporal variability is decreased, and relate this to increased engagement with visual sensory input as manifest in high screen time usage in ADHD. We further show that these differences in the dynamics of the cortex in schizophrenia, and ADHD can be related to differences in the functional connectivity of the specific sensory vs. association thalamic nuclei. These discoveries help to advance our understanding of cortical operation in health, and in some mental disorders.

Association between long-range temporal correlations in intrinsic EEG activity and subjective sense of identity

The long-range temporal correlation (LRTC) in resting-state intrinsic brain activity is known to be associated with temporal behavioral patterns, including decision making based on internal criteria such as self-knowledge. However, the association between the neuronal LRTC and the subjective sense of identity remains to be explored; in other words, whether our subjective sense of consistent self across time relates to the temporal consistency of neural activity. The present study examined the relationship between the LRTC of resting-state scalp electroencephalography (EEG) and a subjective sense of identity measured by the Erikson Psychosocial Stage Inventory (EPSI). Consistent with our prediction based on previous studies of neuronal-behavioral relationships, the frontocentral alpha LRTC correlated negatively with identity confusion. Moreover, from the descriptive analyses, centroparietal beta LRTC showed negative correlations with identity confusion, and frontal theta LRTC showed positive relationships with identity synthesis. These results suggest that more temporal consistency (reversely, less random noise) in intrinsic brain activity is associated with less confused and better-synthesized identity. Our data provide further evidence that the LRTC of intrinsic brain activity might serve as a noise suppression mechanism at the psychological level.

P2X7 Receptor-Dependent Layer-Specific Changes in Neuron-Microglia Reactivity in the Prefrontal Cortex of a Phencyclidine Induced Mouse Model of Schizophrenia

Background: It has been consistently reported that the deficiency of the adenosine triphosphate (ATP) sensitive purinergic receptor P2X7 (P2X7R) ameliorates symptoms in animal models of brain diseases.

Objective: This study aimed to investigate the role of P2X7R in rodent models of acute and subchronic schizophrenia based on phencyclidine (PCP) delivery in animals lacking or overexpressing P2X7R, and to identify the underlying mechanisms involved.

Methods: The psychotomimetic effects of acute i.p. PCP administration in C57Bl/6J wild-type, P2X7R knockout (P2rx7^−/−) and overexpressing (P2X7-EGFP) young adult mice were quantified. The medial prefrontal cortex (mPFC) of P2rx7^−/− and heterozygous P2X7-EGFP acutely treated animals was characterized through immunohistochemical staining. The prefrontal cortices of young adult P2rx7^−/− and P2rx7^tg/+ mice were examined with tritiated dopamine release experiments and the functional properties of the mPFC pyramidal neurons in layer V from P2rx7^−/− mice were assessed by patch-clamp recordings. P2rx7^−/− animals were subjected to a 7 days subchronic systemic PCP treatment. The animals working memory performance and PFC cytokine levels were assessed.

Results: Our data strengthen the hypothesis that P2X7R modulates schizophrenia-like positive and cognitive symptoms in NMDA receptor antagonist models in a receptor expression level-dependent manner. P2X7R expression leads to higher medial PFC susceptibility to PCP-induced circuit hyperactivity. The mPFC of P2X7R knockout animals displayed distinct alterations in the neuronal activation pattern, microglial organization, specifically around hyperactive neurons, and were associated with lower intrinsic excitability of mPFC neurons.

Conclusions: P2X7R expression exacerbated PCP-related effects in C57Bl/6J mice. Our findings suggest a pleiotropic role of P2X7R in the mPFC, consistent with the observed behavioral phenotype, regulating basal dopamine concentration, layer-specific neuronal activation, intrinsic excitability of neurons in the mPFC, and the interaction of microglia with hyperactive neurons. Direct measurements of P2X7R activity concerning microglial ramifications and dynamics could help to further elucidate the molecular mechanisms involved.

Patient, interrupted: MEG oscillation dynamics reveal temporal dysconnectivity in schizophrenia

Current theories of schizophrenia emphasize the role of altered information integration as the core dysfunction of this illness. While ample neuroimaging evidence for such accounts comes from investigations of spatial connectivity, understanding temporal disruptions is important to fully capture the essence of dysconnectivity in schizophrenia. Recent electrophysiology studies suggest that long-range temporal correlation (LRTC) in the amplitude dynamics of neural oscillations captures the integrity of transferred information in the healthy brain. Thus, in this study, 25 schizophrenia patients and 25 controls (8 females/group) were recorded during two five-minutes of resting-state magnetoencephalography (once with eyes-open and once with eyes-closed). We used source-level analyses to investigate temporal dysconnectivity in patients by characterizing LRTCs across cortical and sub-cortical brain regions. In addition to standard statistical assessments, we applied a machine learning framework using support vector machine to evaluate the discriminative power of LRTCs in identifying patients from healthy controls. We found that neural oscillations in schizophrenia patients were characterized by reduced signal memory and higher variability across time, as evidenced by cortical and subcortical attenuations of LRTCs in the alpha and beta frequency bands. Support vector machine significantly classified participants using LRTCs in key limbic and paralimbic brain areas, with decoding accuracy reaching 82%. Importantly, these brain regions belong to networks that are highly relevant to the symptomology of schizophrenia. These findings thus posit temporal dysconnectivity as a hallmark of altered information processing in schizophrenia, and help advance our understanding of this pathology.

Reduction in social learning and increased policy uncertainty about harmful intent is associated with pre-existing paranoid beliefs: Evidence from modelling a modified serial dictator game

Current computational models suggest that paranoia may be explained by stronger higher-order beliefs about others and increased sensitivity to environments. However, it is unclear whether this applies to social contexts, and whether it is specific to harmful intent attributions, the live expression of paranoia. We sought to fill this gap by fitting a computational model to data (n = 1754) from a modified serial dictator game, to explore whether pre-existing paranoia could be accounted by specific alterations to cognitive parameters characterising harmful intent attributions. We constructed a ‘Bayesian brain’ model of others’ intent, which we fitted to harmful intent and self-interest attributions made over 18 trials, across three different partners. We found that pre-existing paranoia was associated with greater uncertainty about other’s actions. It moderated the relationship between learning rates and harmful intent attributions, making harmful intent attributions less reliant on prior interactions. Overall, the magnitude of harmful intent attributions was directly related to their uncertainty, and importantly, the opposite was true for self-interest attributions. Our results explain how pre-existing paranoia may be the result of an increased need to attend to immediate experiences in determining intentional threat, at the expense of what is already known, and more broadly, they suggest that environments that induce greater probabilities of harmful intent attributions may also induce states of uncertainty, potentially as an adaptive mechanism to better detect threatening others. Importantly, we suggest that if paranoia were able to be explained exclusively by core domain-general alterations we would not observe differential parameter estimates underlying harmful-intent and self-interest attributions.

A great deal of work has tried to explain paranoia through general cognitive principles, although relatively little has tried to understand whether paranoia may be explained by specific changes to social learning processes. This question is crucial, as paranoia is inherently a social phenomenon, and requires mechanistic explanations to match with its dynamic phenomenology. In this paper we wanted to test whether pre-existing and live paranoid beliefs about others specifically altered how an individual attributed harmful intent–the live expression of paranoia–to partners over a series of live interactions. To do this we applied a novel computational model and network analysis to behavioural data from a large sample of participants in the general population that had played a modified Dictator game online, and required them to attribute whether the behaviour of their partner was due to their intent to harm, or their self-interest, on two mutually exclusive scales. Pre-existing paranoid beliefs about others reduced the value of new partner behaviours on evolving attributions of harmful intent. We suggest that both pre-existing paranoid beliefs and momentary paranoia may incur an adaptive cognitive state to better track potentially threatening others, and demonstrate phenomenological specificity associated with mechanisms of live paranoia.

Gene expression meta-analysis reveals the up-regulation of CREB1 and CREBBP in Brodmann Area 10 of patients with schizophrenia

Cognitive impairments characterize individuals with schizophrenia, and are correlated to the patients' functional outcome. The transcription factor Cyclic AMP-responsive element-binding protein-1 (CREB1) is involved in learning and memory processes. CREB1 and both CREB-binding protein (CREBBP) and E1A Binding Protein P300 (EP300), co-activators of CREB1, have been associated with schizophrenia. We performed a systematic meta-analysis of CREB1, CREBBP and EP300 differential expression in post mortem Brodmann Area 10 (BA10) samples of patients with schizophrenia vs. healthy controls, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Two microarray datasets met the inclusion criteria (overall 41 schizophrenia samples and 38 controls were analyzed). We detect up-regulation of CREB1 and CREBBP in BA10 samples of patients with schizophrenia, while EP300 wasn't differentially expressed. The integration of two independent datasets and the positive correlation between the expression patterns of CREB1 and CREBBP increase the validity of the results. The up-regulation of CREB1 and its co-activator CREBBP might relate to BA10 altered activation that has been shown in schizophrenia. As BA10 was shown to be involved in the cognitive impairments associated with schizophrenia, this suggests involvement of CREB1 and CREBBP in the cognitive symptoms that characterize the disease.

How Sequentially Changing Reward Prospect Modulates Meta-control: Increasing Reward Prospect Promotes Cognitive Flexibility

Meta-control is necessary to regulate the balance between cognitive stability and flexibility. Evidence from (voluntary) task switching studies suggests performance-contingent reward as one modulating factor. Depending on the immediate reward history, reward prospect seems to promote either cognitive stability or flexibility: Increasing reward prospect reduced switch costs and increased the voluntary switch rate, suggesting increased cognitive flexibility. In contrast, remaining high reward prospect increased switch costs and reduced the voluntary switch rate, suggesting increased cognitive stability. Recently we suggested that increasing reward prospect serves as a meta-control signal toward cognitive flexibility by lowering the updating threshold in working memory. However, in task switching paradigms with two tasks only, this could alternatively be explained by facilitated switching to the other of two tasks. To address this issue, a series of task switching experiments with uncued task switching between three univalent tasks was conducted. Results showed a reduction in reaction time (RT) switch costs to a nonsignificant difference and a high voluntary switch rate when reward prospect increased, whereas repetition RTs were faster, switch RTs slower, and voluntary switch rate was reduced when reward prospect remained high. That is, increasing reward prospect put participants in a state of equal readiness to respond to any target stimulus-be it a task repetition or a switch to one of the other two tasks. The study thus provides further evidence for the assumption that increasing reward prospect serves as a meta-control signal to increase cognitive flexibility, presumably by lowering the updating threshold in working memory.

Why Brain Criticality Is Clinically Relevant: A Scoping Review

The past 25 years have seen a strong increase in the number of publications related to criticality in different areas of neuroscience. The potential of criticality to explain various brain properties, including optimal information processing, has made it an increasingly exciting area of investigation for neuroscientists. Recent reviews on this topic, sometimes termed brain criticality, make brief mention of clinical applications of these findings to several neurological disorders such as epilepsy, neurodegenerative disease, and neonatal hypoxia. Other clinicallyrelevant domains - including anesthesia, sleep medicine, developmental-behavioral pediatrics, and psychiatry - are seldom discussed in review papers of brain criticality. Thorough assessments of these application areas and their relevance for clinicians have also yet to be published. In this scoping review, studies of brain criticality involving human data of all ages are evaluated for their current and future clinical relevance. To make the results of these studies understandable to a more clinical audience, a review of the key concepts behind criticality (e.g., phase transitions, long-range temporal correlation, self-organized criticality, power laws, branching processes) precedes the discussion of human clinical studies. Open questions and forthcoming areas of investigation are also considered.

Aberrant Cortical Ensembles and Schizophrenia-like Sensory Phenotypes in Setd1a+/- Mice

BACKGROUND

A breakdown of synchrony within neuronal ensembles leading to destabilization of network "attractors" could be a defining aspect of neuropsychiatric diseases such as schizophrenia, representing a common downstream convergence point for the diverse etiological pathways associated with the disease. Using a mouse genetic model, we demonstrated that altered ensembles are associated with pathological sensory cortical processing phenotypes resulting from loss of function mutations in the Setd1a gene, a recently identified rare risk genotype with very high penetrance for schizophrenia.

METHODS

We used fast two-photon calcium imaging of neuronal populations (calcium indicator GCaMP6s, 10 Hz, 100-250 cells, layer 2/3 of primary visual cortex, i.e., V1) in awake head-fixed mice (Setd1a^+/- vs. wild-type littermate control) during rest and visual stimulation with moving full-field square-wave gratings (0.04 cycles per degree, 2.0 cycles per second, 100% contrast, 12 directions). Multielectrode recordings were analyzed in the time-frequency domain to assess stimulus-induced oscillations and cross-layer phase synchrony.

RESULTS

Neuronal activity and orientation/direction selectivity were unaffected in Setd1a^+/- mice, but correlations between cell pairs in V1 showed altered distributions compared with wild-type mice, in both ongoing and visually evoked activity. Furthermore, population-wide "ensemble activations" in Setd1a^+/- mice were markedly less reliable over time during rest and visual stimulation, resulting in unstable encoding of basic visual information. This alteration of ensembles coincided with reductions in alpha and high-gamma band phase synchrony within and between cortical layers.

CONCLUSIONS

These results provide new evidence for an ensemble hypothesis of schizophrenia and highlight the utility of Setd1a^+/- mice for modeling sensory-processing phenotypes.

Testing Psychosis Phenotypes From Bipolar-Schizophrenia Network for Intermediate Phenotypes for Clinical Application: Biotype Characteristics and Targets

BACKGROUND

Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis.

METHODS

Doing this, the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated.

RESULTS

Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes.

CONCLUSIONS

In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.

Predicted DRD4 prefrontal gene expression moderates snack intake and stress perception in response to the environment in adolescents

Body weight is substantially determined by eating behaviors, which are themselves driven by biological factors interacting with the environment. Previous studies in young children suggest that genetic influences on dopamine function may confer differential susceptibility to the environment in such a way that increases behavioral obesity risk in a lower socioeconomic status (SES) environment but decreases it in a higher SES environment. We aimed to test if this pattern of effect could also be observed in adolescence, another critical period for development in brain and behavior, using a novel measure of predicted expression of the dopamine receptor 4 (DRD4) gene in prefrontal cortex. In a sample of 76 adolescents (37 boys and 39 girls from Baltimore, Maryland/US, aged 14-18y), we estimated individual levels of DRD4 gene expression (PredDRD4) in prefrontal cortex from individual genomic data using PrediXcan, and tested interactions with a composite SES score derived from their annual household income, maternal education, food insecurity, perceived resource availability, and receipt of public assistance. Primary outcomes were snack intake during a multi-item ad libitum meal test, and food-related impulsivity assessed using a food-adapted go/no-go task. A linear regression model adjusted for sex, BMI z-score, and genetic ethnicity demonstrated a PredDRD4 by composite SES score interaction for snack intake (p = 0.009), such that adolescents who had lower PredDRD4 levels exhibited greater snack intake in the lower SES group, but lesser snack intake in the higher SES group. Exploratory analysis revealed a similar pattern for scores on the Perceived Stress Scale (p = 0.001) such that the low PredDRD4 group reported higher stress in the lower SES group, but less stress in the higher SES group, suggesting that PredDRD4 may act in part by affecting perceptions of the environment. These results are consistent with a differential susceptibility model in which genes influencing environmental responsiveness interact with environments varying in obesogenicity to confer behavioral obesity risk in a less favorable environment, but behavioral obesity protection in a favorable one.

Memantine Effects on Electroencephalographic Measures of Putative Excitatory/Inhibitory Balance in Schizophrenia

BACKGROUND

Abnormalities in cortical excitation and inhibition (E/I) balance are thought to underlie sensory and information processing deficits in schizophrenia. Deficits in early auditory information processing mediate both neurocognitive and functional impairment and appear to be normalized by acute pharmacologic challenge with the NMDA antagonist memantine (MEM).

METHODS

Thirty-six subjects with a diagnosis of schizophrenia and 31 healthy control subjects underwent electroencephalographic recordings. Subjects ingested either placebo or MEM (10 or 20 mg) in a double-blind, within-subject, crossover, randomized design. The aperiodic, 1/f-like scaling property of the neural power spectra, which is thought to index relative E/I balance, was estimated using a robust linear regression algorithm.

RESULTS

Patients with schizophrenia had greater aperiodic components compared with healthy control subjects (p < .01, d = 0.64), which was normalized after 20 mg MEM. Analysis revealed a significant dose × diagnosis interaction (p < .0001, d = 0.82). Furthermore, the MEM effect (change in aperiodic component in MEM vs. placebo conditions) was associated with baseline attention and vigilance (r = .54, p < .05) and MEM-induced enhancements in gamma power (r = -.60, p < .01).

CONCLUSIONS

Findings confirmed E/I balance abnormalities in schizophrenia that were normalized with acute MEM administration and suggest that neurocognitive profiles may predict treatment response based on E/I sensitivity. These data provide proof-of-concept evidence for the utility of E/I balance indices as metrics of acute pharmacologic sensitivity for central nervous system therapeutics.

Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia

The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.

Neuronal mechanisms for sequential activation of memory items: Dynamics and reliability

In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions: activation of regular or irregular sequences. The switch between the two types of activation occurs through the modulation of biological parameters, without altering the connectivity matrix. Some of the parameters included in our model are neuronal gain, strength of inhibition, synaptic depression and noise. We investigate how these parameters enable the existence of sequences and influence the type of sequences observed. In particular we show that synaptic depression and noise drive the transitions from one memory item to the next and neuronal gain controls the switching between regular and irregular (random) activation.

Exploring Geometric Feature Hyper-Space in Data to Learn Representations of Abstract Concepts

The term concept has been a prominent part of investigations in psychology and neurobiology where, mostly, it is mathematically or theoretically represented. Concepts are also studied in the computational domain through their symbolic, distributed and hybrid representations. The majority of these approaches focused on addressing concrete concepts notion, but the view of the abstract concept is rarely explored. Moreover, most computational approaches have a predefined structure or configurations. The proposed method, Regulated Activation Network (RAN), has an evolving topology and learns representations of abstract concepts by exploiting the geometrical view of concepts, without supervision. In the article, first, a Toy-data problem was used to demonstrate the RANs modeling. Secondly, we demonstrate the liberty of concept identifier choice in RANs modeling and deep hierarchy generation using the IRIS dataset. Thirdly, data from the IoT’s human activity recognition problem is used to show automatic identification of alike classes as abstract concepts. The evaluation of RAN with eight UCI benchmarks and the comparisons with five Machine Learning models establishes the RANs credibility as a classifier. The classification operation also proved the RANs hypothesis of abstract concept representation. The experiments demonstrate the RANs ability to simulate psychological processes (like concept creation and learning) and carry out effective classification irrespective of training data size.

Cognition- and circuit-based dysfunction in a mouse model of 22q11.2 microdeletion syndrome: effects of stress

Genetic microdeletion at the 22q11 locus is associated with very high risk for schizophrenia. The 22q11.2 microdeletion (Df(h22q11)/+) mouse model shows cognitive deficits observed in this disorder, some of which can be linked to dysfunction of the prefrontal cortex (PFC). We used behavioral (n = 10 per genotype), electrophysiological (n = 7 per genotype per group), and neuroanatomical (n = 5 per genotype) techniques to investigate schizophrenia-related pathology of Df(h22q11)/+ mice, which showed a significant decrease in the total number of parvalbumin positive interneurons in the medial PFC. The Df(h22q11)/+ mice when tested on PFC-dependent behavioral tasks, including gambling tasks, perform significantly worse than control animals while exhibiting normal behavior on hippocampus-dependent tasks. They also show a significant decrease in hippocampus-medial Prefrontal cortex (H-PFC) synaptic plasticity (long-term potentiation, LTP). Acute platform stress almost abolished H-PFC LTP in both wild-type and Df(h22q11)/+ mice. H-PFC LTP was restored to prestress levels by clozapine (3 mg/kg i.p.) in stressed Df(h22q11)/+ mice, but the restoration of stress-induced LTP, while significant, was similar between wild-type and Df(h22q11)/+ mice. A medial PFC dysfunction may underlie the negative and cognitive symptoms in human 22q11 deletion carriers, and these results are relevant to the current debate on the utility of clozapine in such subjects.

Absence of Excess Intra-Individual Variability in Retinal Function in People With Schizophrenia

People with schizophrenia exhibit increased intra-individual variability in both behavioral and neural signatures of cognition. Examination of intra-individual variability may uncover a unique functionally relevant aspect of impairment that is not captured by typical between-group comparisons of mean or median values. We and others have observed that retinal activity measured using electroretinography (ERG) is significantly reduced in people with schizophrenia; however, it is currently unclear whether greater intra-individual variability in the retinal response can also be observed. To investigate this, we examined intra-individual variability from 25 individuals with schizophrenia and 24 healthy controls under two fERG conditions: (1) a light-adapted condition in which schizophrenia patients demonstrated reduced amplitudes; and (2) a dark-adapted condition in which the groups did not differ in amplitudes. Intraclass correlation coefficients (ICC) were generated to measure intra-individual variability for each subject, reflecting the consistency of activation values (in μv) across all sampling points (at a 2 kHz sampling rate) within all trials within a condition. Contrary to our predictions, results indicated that the schizophrenia and healthy control groups did not differ in intra-individual variability in fERG responses in either the light- or dark-adapted conditions. This finding remained consistent when variability was calculated as the standard deviation (SD) and coefficient of variation (CV) of maximum positive and negative microvolt values within the a- and b-wave time windows. This suggests that although elevated variability in schizophrenia may be observed at perceptual and cognitive levels of processing, it is not present in the earliest stages of sensory processing in vision.

Latent-Profile Analysis Reveals Behavioral and Brain Correlates of Dopamine-Cognition Associations

Evidence suggests that associations between the neurotransmitter dopamine and cognition are nonmonotonic and open to modulation by various other factors. The functional implications of a given level of dopamine may therefore differ from person to person. By applying latent-profile analysis to a large (n = 181) sample of adults aged 64-68 years, we probabilistically identified 3 subgroups that explain the multivariate associations between dopamine D2/3R availability (probed with 11C-raclopride-PET, in cortical, striatal, and hippocampal regions) and cognitive performance (episodic memory, working memory, and perceptual speed). Generally, greater receptor availability was associated with better cognitive performance. However, we discovered a subgroup of individuals for which high availability, particularly in striatum, was associated with poor performance, especially for working memory. Relative to the rest of the sample, this subgroup also had lower education, higher body-mass index, and lower resting-state connectivity between caudate nucleus and dorsolateral prefrontal cortex. We conclude that a smaller subset of individuals induces a multivariate non-linear association between dopamine D2/3R availability and cognitive performance in this group of older adults, and discuss potential reasons for these differences that await further empirical scrutiny.

Intrinsic neural activity differences in psychosis biotypes: Findings from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium

Intro

The Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) proposed "Biotypes," subgroups of psychosis cases with neuro-cognitive homology. Neural activity unbound to stimulus processing (nonspecific or intrinsic activity) was important for differentiating Biotypes, with Biotype-2 characterized by high nonspecific neural activity. A precise estimate of intrinsic activity (IA) was not included in the initial Biotypes characterization. This report hypothesizes intrinsic activity is a critical differentiating feature for psychosis Biotypes.

Method

Participants were recruited at B-SNIP sites and included probands with psychosis (schizophrenia, schizoaffective disorder, bipolar I disorder), their first-degree biological relatives, and healthy persons (N = 1338). Probands were also sub-grouped by psychosis Biotype. 10-sec inter-stimulus intervals during an auditory paired-stimuli task were used to quantify intrinsic activity from 64 EEG sensors. Single-trial power and connectivity measures at empirically derived frequency bands were quantified. Multivariate discriminant and correlational analyses were used to summarize variables that efficiently and maximally differentiated groups by conventional diagnoses and Biotypes and to determine their relationship to clinical and social functioning.

Results

Biotype-1 consistently exhibited low IA, and Biotype 2 exhibited high IA relative to healthy persons across power frequency bands (delta/theta, alpha, beta, gamma) and alpha band connectivity estimates. DSM groups did not differ from healthy persons on any IA measure.

Discussion

Psychosis Biotypes, but not DSM syndromes, were differentiated by intrinsic activity; Biotype-2 was uniquely characterized by an accentuation of this measure. Neurobiologically defined psychosis subgroups may facilitate the use of intrinsic activity in translation models aimed at developing effective treatments for psychosisrelevant deviations in neural modulation.

The Eminence of Co-Expressed Ties in Schizophrenia Network Communities

Exploring gene networks is crucial for identifying significant biological interactions occurring in a disease condition. These interactions can be acknowledged by modeling the tie structure of networks. Such tie orientations are often detected within embedded community structures. However, most of the prevailing community detection modules are intended to capture information from nodes and its attributes, usually ignoring the ties. In this study, a modularity maximization algorithm is proposed based on nonlinear representation of local tangent space alignment (LTSA). Initially, the tangent coordinates are computed locally to identify k-nearest neighbors across the genes. These local neighbors are further optimized by generating a nonlinear network embedding function for detecting gene communities based on eigenvector decomposition. Experimental results suggest that this algorithm detects gene modules with a better modularity index of 0.9256, compared to other traditional community detection algorithms. Furthermore, co-expressed genes across these communities are identified by discovering the characteristic tie structures. These detected ties are known to have substantial biological influence in the progression of schizophrenia, thereby signifying the influence of tie patterns in biological networks. This technique can be extended logically on other diseases networks for detecting substantial gene “hotspots”.

Embodied gestalts: Unstable visual phenomena become stable when they are stimuli for competitive action selection

An animal's environment is rich with affordances. Different possible actions are specified by visual information while competing for dominance over neural dynamics. Affordance competition models account for this in terms of winner-takes-all cross-inhibition dynamics. Multistable phenomena also reveal how the visual system deals with ambiguity. Their key property is spontaneous instability, in forms such as alternating dominance in binocular rivalry. Theoretical models of self-inhibition or self-organized instability posit that the instability is tied to some kind of neural adaptation and that its functional significance is to enable flexible perceptual transitions. We hypothesized that the two perspectives are interlinked. Spontaneous instability is an intrinsic property of perceptual systems, but it is revealed when they are stripped from the constraints of possibilities for action. To test this, we compared a multistable gestalt phenomenon against its embodied version and estimated the neural adaptation and competition parameters of an affordance transition dynamic model. Wertheimer's (Zeitschrift fur Psychologie 61, 161-265, 1912) optimal (β) and pure (φ) forms of apparent motion from a stroboscopic point-light display were endowed with action relevance by embedding the display in a visual object-tracking task. Thus, each mode was complemented by its action, because each perceptual mode uniquely enabled different ways of tracking the target. Perceptual judgment of the traditional apparent motion exhibited spontaneous instabilities, in the form of earlier switching when the frame rate was changed stepwise. In contrast, the embodied version exhibited hysteresis, consistent with affordance transition studies. Consistent with our predictions, the parameter for competition between modes in the affordance transition model increased, and the parameter for self-inhibition vanished.

The Hyperfocusing Hypothesis: A New Account of Cognitive Dysfunction in Schizophrenia

Impairments in basic cognitive processes such as attention and working memory are commonly observed in people with schizophrenia and are predictive of long-term outcome. In this review, we describe a new theory-the hyperfocusing hypothesis-which provides a unified account of many aspects of impaired cognition in schizophrenia. This hypothesis proposes that schizophrenia involves an abnormally narrow but intense focusing of processing resources. This hyperfocusing impairs the ability of people with schizophrenia to distribute attention among multiple locations, decreases the number of representations that can simultaneously be maintained in working memory, and causes attention to be abnormally captured by irrelevant inputs that share features with active representations. Evidence supporting the hyperfocusing hypothesis comes from a variety of laboratory tasks and from both behavioral and electrophysiological measures of processing. In many of these tasks, people with schizophrenia exhibit supranormal effects of task manipulations, which cannot be explained by a generalized cognitive deficit or by nonspecific factors such as reduced motivation or poor task comprehension. In addition, the degree of hyperfocusing in these tasks is often correlated with the degree of impairment in measures of broad cognitive function, which are known to be related to long-term outcome. Thus, the mechanisms underlying hyperfocusing may be a good target for new treatments targeting cognitive deficits in schizophrenia.

Altered spatial profile of distraction in people with schizophrenia

Attention is critical for effective processing of incoming information and has long been identified as a potential area of dysfunction in people with schizophrenia (PSZ). In the realm of visual processing, both spatial attention and feature-based attention are involved in biasing selection toward task-relevant stimuli and avoiding distraction. Evidence from multiple paradigms has suggested that PSZ may hyperfocus and have a narrower "spotlight" of spatial attention. In contrast, feature-based attention seems largely preserved, with some suggestion of increased processing of stimuli sharing the target-defining feature. In the current study, we examined the spatial profile of feature-based distraction using a task in which participants searched for a particular color target and attempted to ignore distractors that varied in distance from the target location and either matched or mismatched the target color. PSZ differed from healthy controls in terms of interference from peripheral distractors that shared the target-color presented 200 ms before a central target. Specifically, PSZ showed an amplified gradient of spatial attention, with increased distraction to near distractors and less interference to far distractors. Moreover, consistent with hyperfocusing, individual differences in this spatial profile were correlated with positive symptoms, such that those with greater positive symptoms showed less distraction by target-colored distractors near the task-relevant location. (PsycINFO Database Record

Hallucinations both in and out of context: An active inference account

Hallucinations, including auditory verbal hallucinations (AVH), occur in both the healthy population and in psychotic conditions such as schizophrenia (often developing after a prodromal period). In addition, hallucinations can be in-context (they can be consistent with the environment, such as when one hallucinates the end of a sentence that has been repeated many times), or out-of-context (such as the bizarre hallucinations associated with schizophrenia). In previous work, we introduced a model of hallucinations as false (positive) inferences based on a (Markov decision process) formulation of active inference. In this work, we extend this model to include content–to disclose the computational mechanisms behind in- and out-of-context hallucinations. In active inference, sensory information is used to disambiguate alternative hypotheses about the causes of sensations. Sensory information is balanced against prior beliefs, and when this balance is tipped in the favor of prior beliefs, hallucinations can occur. We show that in-context hallucinations arise when (simulated) subjects cannot use sensory information to correct prior beliefs about hearing a voice, but beliefs about content (i.e. the sequential order of a sentence) remain accurate. When hallucinating subjects also have inaccurate beliefs about state transitions, out-of-context hallucinations occur; i.e. their hallucinated speech content is disordered. Note that out-of-context hallucinations in this setting does not refer to inference about context, but rather to false perceptual inference that emerges when the confidence in–or precision of–sensory evidence is reduced. Furthermore, subjects with inaccurate beliefs about state transitions but an intact ability to use sensory information do not hallucinate and are reminiscent of prodromal patients. This work demonstrates the different computational mechanisms that may underlie the spectrum of hallucinatory experience–from the healthy population to psychotic states.

Long-Range Temporal Correlations in Resting State Beta Oscillations are Reduced in Schizophrenia

Symptoms of schizophrenia (SCZ) are likely to be generated by genetically mediated synaptic dysfunction, which contribute to large-scale functional neural dysconnectivity. Recent electrophysiological studies suggest that this dysconnectivity is present not only at a spatial level but also at a temporal level, operationalized as long-range temporal correlations (LRTCs). Previous research suggests that alpha and beta frequency bands have weaker temporal stability in people with SCZ. This study sought to replicate these findings with high-density electroencephalography (EEG), enabling a spatially more accurate analysis of LRTC differences, and to test associations with characteristic SCZ symptoms and cognitive deficits. A 128-channel EEG was used to record eyes-open resting state brain activity of 23 people with SCZ and 24 matched healthy controls (HCs). LRTCs were derived for alpha (8-12 Hz) and beta (13-25 Hz) frequency bands. As an exploratory analysis, LRTC was source projected using sLoreta. People with SCZ showed an area of significantly reduced beta-band LRTC compared with HCs over bilateral posterior regions. There were no between-group differences in alpha-band activity. Individual symptoms of SCZ were not related to LRTC values nor were cognitive deficits. The study confirms that people with SCZ have reduced temporal stability in the beta frequency band. The absence of group differences in the alpha band may be attributed to the fact that people had, in contrast to previous studies, their eyes open in the current study. Taken together, our study confirms the utility of LRTC as a marker of network instability in people with SCZ and provides a novel empirical perspective for future examinations of network dysfunction salience in SCZ research.

Auditory steady-state EEG response across the schizo-bipolar spectrum

Deviant auditory steady-state responses (aSSRs) in the gamma range (30-90 Hz) may be translational biomarkers for schizophrenia (SZ). This study tests whether aSSR deviations are (i) specific to SZ across the psychosis dimension, (ii) specific to particular frequency bands, and (iii) present in bipolar I disorder without psychosis (BDNP).

METHODS

Beta (20-), low- (40-), and high-gamma (80-Hz) aSSRs were measured with EEG and compared across 113 SZ, 105 schizoaffective disorder (SAD), 99 bipolar disorder with psychosis (BDP), 68 BDNP, and 137 healthy comparison subjects (HC). Standard aSSR measures (single-trial power [STP] and inter-trial phase coherence [ITC]), as well as evoked responses to stimulus onsets/offsets and pre-stimulus power, were quantified. Multivariate canonical discriminant analysis was used to summarize variables that efficiently and maximally differentiated groups.

RESULTS

(i) Psychosis groups showed reduced responses on ITC 20 Hz, STP/ITC 40 Hz, STP/ITC 80 Hz, indicating dimensional reductions in aSSR across the psychosis spectrum not specific to aSSR frequency. For the 40- and 80-Hz ITCs there was greater reduction in SZ compared to SAD, possibly indexing cortical disruptions linked to psychosis without mood symptoms. (ii) All probands had elevated pre-stimulus power, possibly compromising neural entrainment to the steady-state stimuli. (iii) Onset/Offset and 80 Hz ITC responses were most important for group discrimination and showed dimensional reduction across the schizo-bipolar spectrum.

CONCLUSIONS

Deviant aSSRs were found across the schizo-bipolar spectrum at multiple frequencies with psychosis status and severity linked to greatest reductions at low and high gamma.

Intrinsic mesocorticolimbic connectivity is negatively associated with social amotivation in people with schizophrenia

BACKGROUND

Social amotivation is a core element of the negative symptoms of schizophrenia. However, it is still largely unknown which neural substrates underpin social amotivation in people with schizophrenia, though deficiencies in the mesocorticolimbic dopamine system have been proposed.

METHODS

We examined the association between social amotivation and substantia nigra/ventral tegmental area-seeded intrinsic connectivity in 84 people with schizophrenia using resting state functional magnetic resonance imaging.

RESULTS

Spontaneous fluctuations of midbrain dopaminergic regions were positively associated with striatal and prefrontal fluctuations in people with schizophrenia. Most importantly, social amotivation was negatively associated with functional connectivity between the midbrain's substantia nigra/ventral tegmental area and medial- and lateral prefrontal cortex, the temporoparietal junction, and dorsal and ventral striatum. These associations were observed independently of depressive and positive symptoms.

CONCLUSIONS

Our findings suggest that social amotivation in people with schizophrenia is associated with altered intrinsic connectivity of mesocorticolimbic pathways linked to cognitive control and reward processing. Dysconnectivity of dopaminergic neuronal ensembles that are fundamental to approach behavior and motivation may help explain the lack of initiative social behavior in people with social amotivation.

Dysregulation of auditory neuroplasticity in schizophrenia

Schizophrenia is a complex brain syndrome characterized by an array of positive symptoms (delusions, hallucinations, disorganized speech), negative symptoms (alogia, apathy, avolition) and cognitive impairments (memory, executive functions). Although investigations of the cognitive deficits in schizophrenia have primarily concentrated on disturbances affecting higher-order cognitive processes, there is an increasing realization that schizophrenia also affects early sensory processing, which might, in fact, play a significant role in the development of higher-order cognitive impairments. Recent evidence suggests that many of these early sensory processing impairments possibly arise from a dysregulation of plasticity regulators in schizophrenia, resulting in either reduced plasticity or excessive unregulated plasticity. The purpose of the present manuscript is to provide a concise overview of how the dysregulation of cortical plasticity mechanisms contributes to schizophrenia symptoms with an emphasis on auditory dysplasticity and to discuss its relevance for treatment outcomes. The idea that plasticity mechanisms are not constrained only within sensitive periods suggests that many functional properties of sensory neurons can be altered throughout the lifetime.

Phosphodiesterase 1b (PDE1B) Regulates Spatial and Contextual Memory in Hippocampus

Augmentation of cyclic nucleotide signaling through inhibition of phosphodiesterase (PDE) activity has long been understood to enhance memory. Efforts in this domain have focused predominantly on PDE4, a cAMP-specific phosphodiesterase implicated in consolidation. But less is known about the function of other PDEs expressed in neuroanatomical regions critical to memory. The PDE1 isoforms are the only PDEs to regulate neuronal cAMP and cGMP levels in a Ca²⁺/Calmodulin (CaM) dependent manner. Here, we show that knock-down of PDE1B in hippocampus of adult mice enhances contextual and spatial memory without effect on non-cognitive behaviors. Pharmacological augmentation of memory in rats was observed with a selective inhibitor of PDE1 dosed before and immediately after training, but not with drug dosed either 1 h after training or before recall. Our data clearly demonstrate a role for the PDE1B isoforms as negative regulators of memory, and they implicate PDE1 in an early phase of consolidation, but not retrieval. Inhibition of PDE1B is a promising therapeutic mechanism for treating memory impairment.

From Computation to the First-Person: Auditory-Verbal Hallucinations and Delusions of Thought Interference in Schizophrenia-Spectrum Psychoses

Schizophrenia-spectrum psychoses are highly complex and heterogeneous disorders that necessitate multiple lines of scientific inquiry and levels of explanation. In recent years, both computational and phenomenological approaches to the understanding of mental illness have received much interest, and significant progress has been made in both fields. However, there has been relatively little progress bridging investigations in these seemingly disparate fields. In this conceptual review and collaborative project from the 4th Meeting of the International Consortium on Hallucination Research, we aim to facilitate the beginning of such dialogue between fields and put forward the argument that computational psychiatry and phenomenology can in fact inform each other, rather than being viewed as isolated or even incompatible approaches. We begin with an overview of phenomenological observations on the interrelationships between auditory-verbal hallucinations (AVH) and delusional thoughts in general, before moving on to review several theoretical frameworks and empirical findings in the computational modeling of AVH. We then relate the computational models to the phenomenological accounts, with a special focus on AVH and delusions that involve the senses of agency and ownership of thought (delusions of thought interference). Finally, we offer some tentative directions for future research, emphasizing the importance of a mutual understanding between separate lines of inquiry.

Dopamine and Cognitive Control in Prefrontal Cortex

Cognitive control, the ability to orchestrate behavior in accord with our goals, depends on the prefrontal cortex. These cognitive functions are heavily influenced by the neuromodulator dopamine. We review here recent insights exploring the influence of dopamine on neuronal response properties in prefrontal cortex (PFC) during ongoing behaviors in primates. This review suggests three major computational roles of dopamine in cognitive control: (i) gating sensory input, (ii) maintaining and manipulating working memory contents, and (iii) relaying motor commands. For each of these roles, we propose a neuronal microcircuit based on known mechanisms of action of dopamine in PFC, which are corroborated by computational network models. This conceptual approach accounts for the various roles of dopamine in prefrontal executive functioning.

Decreased brain connectivity in smoking contrasts with increased connectivity in drinking

In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors.

Dopaminergic Modulation of Synaptic Plasticity, Its Role in Neuropsychiatric Disorders, and Its Computational Modeling

Neuromodulators modify intrinsic characteristics of the nervous system in order to reconfigure the functional properties of neural circuits. This reconfiguration is crucial for the flexibility of the nervous system to respond on an input-modulated basis. Such a functional rearrangement is realized by modification of intrinsic properties of the neural circuits including synaptic interactions. Dopamine is an important neuromodulator involved in motivation and stimulus-reward learning process, and adjusts synaptic dynamics in multiple time scales through different pathways. The modification of synaptic plasticity by dopamine underlies the change in synaptic transmission and integration mechanisms, which affects intrinsic properties of the neural system including membrane excitability, probability of neurotransmitters release, receptors’ response to neurotransmitters, protein trafficking, and gene transcription. Dopamine also plays a central role in behavioral control, whereas its malfunction can cause cognitive disorders. Impaired dopamine signaling is implicated in several neuropsychiatric disorders such as Parkinson’s disease, drug addiction, schizophrenia, attention-deficit/hyperactivity disorder, obsessive-compulsive disorder and Tourette’s syndrome. Therefore, dopamine plays a crucial role in the nervous system, where its proper modulation of neural circuits may enhance plasticity-related procedures, but disturbances in dopamine signaling might be involved in numerous neuropsychiatric disorders. In recent years, several computational models are proposed to formulate the involvement of dopamine in synaptic plasticity or neuropsychiatric disorders and address their connection based on the experimental findings.

Effect of GAD1 genotype status on auditory attention and acute nicotine administration in healthy volunteers

OBJECTIVE

The effects of GABA modulating drugs and nicotine, the prototypical nicotinic cholinergic agonist, on attention have been investigated using subcomponents of the P300 event-related potentials (ERP), which index involuntary (P3a) and voluntary attention (P3b). However, investigations into how such pharmacologic effects interact with genetic features in the GABA system remain unclear. This study examined the moderating effects of a single nucleotide polymorphism (rs7557793) in the glutamic acid decarboxylase 67 (GAD1) gene, which is implicated in the conversion of glutamate to GABA, on P300-indices of auditory attentional processing; the influence of nicotine administration was also assessed.

METHODS

The effects of GAD1 genotype (TT/CC/CT) were examined on the P3a/b in response to an auditory selective attention task in healthy, nonsmoking male volunteers (N = 126; 18-40 years). Participants responded to rare target stimuli (P3b-eliciting) and ignored frequent nontarget stimuli as well as rare distractor stimuli (P3a-eliciting). In a subsample (N = 59), P3a/b profiles to acute nicotine (vs. placebo) administration were examined as a function of GAD1 genotype. As a secondary aim, earlier sensory processes were assessed with N200 ERP subcomponents elicited by novel (N2a) and target (N2b) auditory stimuli.

RESULTS

GAD1 allelic variation moderated early sensory processes, enhancing N2a amplitudes in CT versus TT carriers. Further, TT homozygotes exhibited larger P3b amplitudes than CC homozygotes in the placebo versus nicotine condition. Regardless of genotype, nicotine versus placebo moderated the N200 ERP.

CONCLUSION

These findings expand our knowledge regarding the attentional effects of GAD1 genetic variants in relation to nicotine.

Dopamine guides competition for cognitive control: Common effects of haloperidol on working memory and response conflict

Several lines of evidence suggest that dopamine modulates working memory (the ability to faithfully maintain and efficiently manipulate information over time) but its specific role has not been fully defined. Nor is it clear whether any effects of dopamine are specific to memory processes or whether they reflect more general cognitive mechanisms that extend beyond the working memory domain. Here, we examine the effect of haloperidol, principally a dopamine D₂ receptor antagonist, on the ability of humans to ignore distracting information or update working memory contents. We compare these effects to performance on an independent measure of cognitive control (response conflict) which has minimal memory requirements. Haloperidol did not selectively affect the ability to ignore or update, but instead reduced the overall quality of recall. In addition, it impaired the ability to overcome response conflict. The deleterious effect of haloperidol on response conflict was selectively associated with the negative effect of the drug on ignoring - but not updating - suggesting that dopamine affects protection of working memory contents and inhibition in response conflict through a common mechanism. These findings provide new insights into the role of dopamine D₂ receptors on human cognition. They suggest that D₂ receptor effects on protecting the memory contents from distraction might be related to a more general process that supports inhibitory control in contexts that do not require working memory.

Analysis of influencing factors of visual working memory in young adult patients with schizophrenia

BACKGROUND

Patients with schizophrenia have general cognitive impairments, and the impairment of working memory is considered to be the basis of cognitive impairments. The research on visual working memory, one of the subcomponents, is getting more and more attention. However, the influencing factors which cause the deficits of visual working memory in patients with schizophrenia have not been clearly explained. To provide evidence for cognitive impairment interventions, the present study explored the factors influencing the deficits of patients' visual working memory.

AIM

The present study discussed the relevant factors influencing the visual working memory of patients with schizophrenia by measuring the accuracy of the visual working memory of patients with schizophrenia and healthy controls.

METHODS

Colour-recall paradigm was employed to measure the accuracy of the visual working memory of 61 healthy controls and 61 patients who met the International Classification of Diseases, Tenth Revision diagnostic criteria for schizophrenia. The age range of subjects was 18-50. Scale for the Assessment of Positive Symptoms (SAPS) and Scale for the Assessment of Negative Symptoms (SANS) were used to evaluate the patients' clinical symptoms.

RESULTS

Compared with the healthy control group, the accuracy of visual working memory of patients with schizophrenia was significantly impaired (t=3.062, p=0.003). The accuracy of visual working memory of patients with schizophrenia was not related to age (r=0.023, p=0.860), the age of onset (r=-0.003, p=0.979), the duration of illness (r=-0.038, p=0.769), education level (r=-0.181, p=0.162), continuous working time before illness (r=-0.107, p=0.413) or the daily dose of antipsychotic drugs (r=0.062, p=0.635); however, it was positively related to the number of hospitalisations (r=0.471, p<0.001). The total score of Scale for the Assessment of Positive Symptoms (SAPS) was negatively related to the accuracy of visual working memory (r=-0.388, p=0.005), while the total score of Scale for the Assessment of Negative Symptoms (SANS) (r=0.416, p=0.001), the total score of diminished emotional expressiveness (r=0.352, p=0.005) and the total score of attention disorder (r=0.310, p=0.015) were positively related to the accuracy of visual working memory. Patients using a single drug and those using multiple drugs were compared with each other. They were not significantly different in age (t=0.010, p=0.992), the number of hospitalisations (t=0.656, p=0.514), the duration of illness (t=0.701, p=0.486), the total score of SANS (t=0.078, p=0.938), the total score of SAPS (t=1.815, p=0.079) and the daily dose of antipsychotic drugs (t=1.794, p=0.078). However, in order to explore whether single or combined drug use would affect the accuracy of visual working memory of patients with schizophrenia, the present study also compared these two groups' different S0 values of the accuracy of visual working memory. The results showed that the accuracy of visual working memory of patients with schizophrenia with combined drug use was significantly better than that of patients with single drug use (t=2.515, p=0.015, independent sample t-test).

CONCLUSION

The present study indicates that the visual working memory of young adult patients with schizophrenia is impaired compared with the healthy people within the same age range. The impairment is more obvious in patients who have multiple hospitalisations and suffer from severe negative symptoms. The impairment in patients with more severe positive symptoms is not very obvious. Combined drug use is likely to alleviate the impairment.

Dopamine tunes prefrontal outputs to orchestrate aversive processing

Decades of research suggest that the mesocortical dopamine system exerts powerful control over mPFC physiology and function. Indeed, dopamine signaling in the medial prefrontal cortex (mPFC) is implicated in a vast array of processes, including working memory, stimulus discrimination, stress responses, and emotional and behavioral control. Consequently, even slight perturbations within this delicate system result in profound disruptions of mPFC-mediated processes. Many neuropsychiatric disorders are associated with dysregulation of mesocortical dopamine, including schizophrenia, depression, attention deficit hyperactivity disorder, post-traumatic stress disorder, among others. Here, we review the anatomy and functions of the mesocortical dopamine system. In contrast to the canonical role of striatal dopamine in reward-related functions, recent work has revealed that mesocortical dopamine fine-tunes distinct efferent projection populations in a manner that biases subsequent behavior towards responding to stimuli associated with potentially aversive outcomes. We propose a framework wherein dopamine can serve as a signal for switching mPFC states by orchestrating how information is routed to the rest of the brain.

Dopamine enhances signal-to-noise ratio in cortical-brainstem encoding of aversive stimuli

Despite abundant evidence that dopamine (DA) modulates medial prefrontal cortex (mPFC) activity to mediate diverse behavioral functions^1,2, the precise circuit computations remain elusive. One potentially unifying model by which DA can underlie a diversity of functions is to modulate the signal-to-noise ratio (SNR) in subpopulations of mPFC neurons^3–6, where neural activity conveying sensory information (signal) is amplified relative to spontaneous firing (noise). Here, we demonstrate that DA increases the SNR of responses to aversive stimuli in mPFC neurons projecting to the dorsal periaqueductal gray (dPAG). Using electrochemical approaches, we reveal the precise time course of pinch-evoked DA release in the mPFC, and show that mPFC DA biases behavioral responses to aversive stimuli. Activation of mPFC-dPAG neurons is sufficient to drive place avoidance and defensive behaviors. mPFC-dPAG neurons displayed robust shock-induced excitations, as visualized by single-cell, projection-defined microendoscopic calcium imaging. Finally, photostimulation of DA terminals in the mPFC revealed an increase in SNR in mPFC-dPAG responses to aversive stimuli. Together, these data highlight how mPFC DA can route sensory information in a valence-specific manner to different downstream circuits.

Attractor-like Dynamics in Belief Updating in Schizophrenia

Subjects with a diagnosis of schizophrenia (Scz) overweight unexpected evidence in probabilistic inference: such evidence becomes "aberrantly salient." A neurobiological explanation for this effect is that diminished synaptic gain (e.g., hypofunction of cortical NMDARs) in Scz destabilizes quasi-stable neuronal network states (or "attractors"). This attractor instability account predicts that (1) Scz would overweight unexpected evidence but underweight consistent evidence, (2) belief updating would be more vulnerable to stochastic fluctuations in neural activity, and (3) these effects would correlate. Hierarchical Bayesian belief updating models were tested in two independent datasets (n = 80 male and n = 167 female) comprising human subjects with Scz, and both clinical and nonclinical controls (some tested when unwell and on recovery) performing the "probability estimates" version of the beads task (a probabilistic inference task). Models with a standard learning rate, or including a parameter increasing updating to "disconfirmatory evidence," or a parameter encoding belief instability were formally compared. The "belief instability" model (based on the principles of attractor dynamics) had most evidence in all groups in both datasets. Two of four parameters differed between Scz and nonclinical controls in each dataset: belief instability and response stochasticity. These parameters correlated in both datasets. Furthermore, the clinical controls showed similar parameter distributions to Scz when unwell, but were no different from controls once recovered. These findings are consistent with the hypothesis that attractor network instability contributes to belief updating abnormalities in Scz, and suggest that similar changes may exist during acute illness in other psychiatric conditions.SIGNIFICANCE STATEMENT Subjects with a diagnosis of schizophrenia (Scz) make large adjustments to their beliefs following unexpected evidence, but also smaller adjustments than controls following consistent evidence. This has previously been construed as a bias toward "disconfirmatory" information, but a more mechanistic explanation may be that in Scz, neural firing patterns ("attractor states") are less stable and hence easily altered in response to both new evidence and stochastic neural firing. We model belief updating in Scz and controls in two independent datasets using a hierarchical Bayesian model, and show that all subjects are best fit by a model containing a belief instability parameter. Both this and a response stochasticity parameter are consistently altered in Scz, as the unstable attractor hypothesis predicts.

Biophysical Modeling of Large-Scale Brain Dynamics and Applications for Computational Psychiatry

Noninvasive neuroimaging has revolutionized the study of the organization of the human brain and how its structure and function are altered in psychiatric disorders. A critical explanatory gap lies in our mechanistic understanding of how systems-level neuroimaging biomarkers emerge from underlying synaptic-level perturbations associated with a disease state. We describe an emerging computational psychiatry approach leveraging biophysically based computational models of large-scale brain dynamics and their potential integration with clinical and pharmacological neuroimaging. In particular, we focus on neural circuit models, which describe how patterns of functional connectivity observed in resting-state functional magnetic resonance imaging emerge from neural dynamics shaped by inter-areal interactions through underlying structural connectivity defining long-range projections. We highlight the importance of local circuit physiological dynamics, in combination with structural connectivity, in shaping the emergent functional connectivity. Furthermore, heterogeneity of local circuit properties across brain areas, which impacts large-scale dynamics, may be critical for modeling whole-brain phenomena and alterations in psychiatric disorders and pharmacological manipulation. Finally, we discuss important directions for future model development and biophysical extensions, which will expand their utility to link clinical neuroimaging to neurobiological mechanisms.

The storage and recall of memories in the hippocampo-cortical system

A quantitative computational theory of the operation of the hippocampus as an episodic memory system is described. The CA3 system operates as a single attractor or autoassociation network (1) to enable rapid one-trial associations between any spatial location (place in rodents or spatial view in primates) and an object or reward and (2) 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, which is also important in episodic memory. The dentate gyrus performs pattern separation by competitive learning to create sparse representations producing, for example, neurons with place-like fields from entorhinal cortex grid cells. The dentate granule cells generate, by the very small number of mossy fibre connections to CA3, a randomizing pattern separation effect that is important during learning but not recall and that separates out the patterns represented by CA3 firing as being very different from each other. This is optimal for an unstructured episodic memory system in which each memory must be kept distinct from other memories. The direct perforant path input to CA3 is quantitatively appropriate for providing the cue for recall in CA3 but not for learning. The CA1 recodes information from CA3 to set up associatively learned backprojections to the neocortex to allow the subsequent retrieval of information to the neocortex, giving a quantitative account of the large number of hippocampo-neocortical and neocortical-neocortical backprojections. Tests of the theory including hippocampal subregion analyses and hippocampal NMDA receptor knockouts are described and support the theory.

Motivation dynamically increases noise resistance by internal feedback during movement

Motivation improves performance, pushing us beyond our normal limits. One general explanation for this is that the effects of neural noise can be reduced, at a cost. If this were possible, reward would promote investment in resisting noise. But how could the effects of noise be attenuated, and why should this be costly? Negative feedback may be employed to compensate for disturbances in a neural representation. Such feedback would increase the robustness of neural representations to internal signal fluctuations, producing a stable attractor. We propose that encoding this negative feedback in neural signals would incur additional costs proportional to the strength of the feedback signal. We use eye movements to test the hypothesis that motivation by reward improves precision by increasing the strength of internal negative feedback. We find that reward simultaneously increases the amplitude, velocity and endpoint precision of saccades, indicating true improvement in oculomotor performance. Analysis of trajectories demonstrates that variation in the eye position during the course of saccades is predictive of the variation of endpoints, but this relation is reduced by reward. This indicates that motivation permits more aggressive correction of errors during the saccade, so that they no longer affect the endpoint. We suggest that such increases in internal negative feedback allow attractor stability, albeit at a cost, and therefore may explain how motivation improves cognitive as well as motor precision.

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Motivation can increase speed and reduce behavioural variability.

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This requires stabilising neural representations so they are robust to noise.

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Stable representations or attractors in neural systems may come at the cost of stronger negative feedback.

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Examination of trajectory correlations demonstrates that reward increases negative feedback.

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We propose that the cost of stabilising signals explain why effort is expensive.

Dopamine D2 Receptors Enhance Population Dynamics in Primate Prefrontal Working Memory Circuits

Working memory is associated with persistent activity in the prefrontal cortex (PFC). The neuromodulator dopamine, which is released by midbrain neurons projecting into the frontal lobe, influences PFC neurons and networks via the dopamine D1 (D1R) and the D2 receptor (D2R) families. Although behavioral, clinical and computational evidence suggest an involvement of D2Rs in working memory, a neuronal explanation is missing. We report an enhancement of persistent working memory responses of PFC neurons after iontophoretically stimulating D2Rs in monkeys memorizing the number of items in a display. D2R activation improved working memory representation at the population level and increased population dynamics during the transition from visual to mnemonic representations. Computational modeling suggests that D2Rs act by modulating interneuron-to-pyramidal signaling. By increasing the population's response dynamics, D2Rs might put PFC networks in a more flexible state and enhance the neurons' working memory coding, thereby controlling dynamic cognitive control.