Abnormal prediction error processing in schizophrenia and depression

Do people know how suicidal they will be? Understanding suicidal prospection

INTRODUCTION

Little research has been done on how people mentally simulate future suicidal thoughts and urges, a process we term suicidal prospection.

METHODS

Participants were 94 adults with recent suicidal thoughts. Participants completed a 42-day real-time monitoring study and then a follow-up survey 28 days later. Each night, participants provided predictions for the severity of their suicidal thoughts the next day and ratings of the severity of suicidal thoughts over the past day. We measured three aspects of suicidal prospection: predicted levels of desire to kill self, urge to kill self, and intent to kill self. We generated prediction errors by subtracting participants' predictions of the severity of their suicidal thoughts from their experienced severity.

RESULTS

Participants tended to overestimate (although the average magnitude was small and the modal error was zero) the severity of their future suicidal thoughts. The best fitting models suggested that participants used both their current suicidal thinking and previous predictions of their suicidal thinking to generate predictions of their future suicidal thinking. Finally, the average severity of predicted future suicidal thoughts predicted the number of days participants thought about suicide during the follow-up period.

CONCLUSIONS

This study highlights prospection as a psychological process to better understand suicidal thoughts and behaviors.

Common neural deficits across reward functions in major depression: a meta-analysis of fMRI studies

Major depressive disorder (MDD) is characterized by deficient reward functions in the brain. However, existing findings on functional alterations during reward anticipation, reward processing, and learning among MDD patients are inconsistent, and it was unclear whether a common reward system implicated in multiple reward functions is altered in MDD. Here we meta-analyzed 18 past studies that compared brain reward functions between adult MDD patients (N = 477, mean age = 26.50 years, female = 59.40%) and healthy controls (N = 506, mean age = 28.11 years, females = 55.58%), and particularly examined group differences across multiple reward functions. Jack-knife sensitivity and subgroup meta-analyses were conducted to test robustness of findings across patient comorbidity, task paradigm, and reward nature. Meta-regression analyses assessed the moderating effect of patient symptom severity and anhedonia scores. We found during reward anticipation, MDD patients showed lower activities in the lateral prefrontal-thalamus circuitry. During reward processing, patients displayed reduced activities in the right striatum and prefrontal cortex, but increased activities in the left temporal cortex. During reward learning, patients showed reduced activity in the lateral prefrontal-thalamic-striatal circuitry and the right parahippocampal-occipital circuitry but higher activities in bilateral cerebellum and the left visual cortex. MDD patients showed decreased activity in the right thalamus during both reward anticipation and learning, and in the right caudate during both reward processing and learning. Larger functional changes in MDD were observed among patients with more severe symptoms and higher anhedonia levels. The thalamic-striatal circuitry functional alterations could be the key neural mechanism underlying MDD patients overarching reward function deficiencies.

Is P3 amplitude associated with greater gaze distraction effect in schizotypy?

A recently proposed "Hyperfocusing hypothesis" suggests that schizotypy is associated with a more narrow but more intense way of allocating attention. The current study aims to test a vital prediction of this hypothesis in a social context, that schizotypy may be related to greater difficulty overcoming the distracting effects of gaze. This could cause a longer time to respond to targets that are invalidly cued by gaze. The current study tested this prediction in a modified Posner cueing paradigm by using P3 as an indicator for attentional resources. Seventy-four young healthy individuals with different levels of schizotypy were included, they were asked to detect the location of a target that was cued validly or invalidly by the gaze and head orientation. The results revealed that (a) schizotypy is associated with hyperfocusing on gaze direction, leading to greater difficulty overcoming the distracting effect of gaze. The higher the trait-schizotypy score, the more time needed to respond to targets that were invalidly cued by gaze (b) schizotypy is associated with reduced P3 which is directed by social communicative stimuli. The higher the trait-schizotypy score, the smaller the amplitude of P3 (c) the relationship between schizotypal traits and response times of the gaze-invalid condition is fully intermediated by P3. The findings of the current study suggest the P3 component may be a crucial neural mechanism underlying joint attention deficits in schizophrenia.

Neural correlates of prediction error in patients with schizophrenia: evidence from an fMRI meta-analysis

Abnormal processes of learning from prediction errors, i.e. the discrepancies between expectations and outcomes, are thought to underlie motivational impairments in schizophrenia. Although dopaminergic abnormalities in the mesocorticolimbic reward circuit have been found in patients with schizophrenia, the pathway through which prediction error signals are processed in schizophrenia has yet to be elucidated. To determine the neural correlates of prediction error processing in schizophrenia, we conducted a meta-analysis of whole-brain neuroimaging studies that investigated prediction error signal processing in schizophrenia patients and healthy controls. A total of 14 studies (324 schizophrenia patients and 348 healthy controls) using the reinforcement learning paradigm were included. Our meta-analysis showed that, relative to healthy controls, schizophrenia patients showed increased activity in the precentral gyrus and middle frontal gyrus and reduced activity in the mesolimbic circuit, including the striatum, thalamus, amygdala, hippocampus, anterior cingulate cortex, insula, superior temporal gyrus, and cerebellum, when processing prediction errors. We also found hyperactivity in frontal areas and hypoactivity in mesolimbic areas when encoding prediction error signals in schizophrenia patients, potentially indicating abnormal dopamine signaling of reward prediction error and suggesting failure to represent the value of alternative responses during prediction error learning and decision making.

Do the negative symptoms of schizophrenia reflect reduced responsiveness to reward? Examination using a reward prediction error (RPE) task

BACKGROUND

A leading theory of the negative symptoms of schizophrenia is that they reflect reduced responsiveness to rewarding stimuli. This proposal has been linked to abnormal (reduced) dopamine function in the disorder, because phasic release of dopamine is known to code for reward prediction error (RPE). Nevertheless, few functional imaging studies have examined if patients with negative symptoms show reduced RPE-associated activations.

METHODS

Matched groups of DSM-5 schizophrenia patients with high negative symptom scores (HNS, N = 27) or absent negative symptoms (ANS, N = 27) and healthy controls (HC, N = 30) underwent fMRI scanning while they performed a probabilistic monetary reward task designed to generate a measure of RPE.

RESULTS

In the HC, whole-brain analysis revealed that RPE was positively associated with activation in the ventral striatum, the putamen, and areas of the lateral prefrontal cortex and orbitofrontal cortex, among other regions. Group comparison revealed no activation differences between the healthy controls and the ANS patients. However, compared to the ANS patients, the HNS patients showed regions of significantly reduced activation in the left ventrolateral and dorsolateral prefrontal cortex, and in the right lingual and fusiform gyrus. HNS and ANS patients showed no activation differences in ventral striatal or midbrain regions-of-interest (ROIs), but the HNS patients showed reduced activation in a left orbitofrontal cortex ROI.

CONCLUSIONS

The findings do not suggest that a generalized reduction of RPE signalling underlies negative symptoms. Instead, they point to a more circumscribed dysfunction in the lateral frontal and possibly the orbitofrontal cortex.

Reinforcement learning deficits exhibited by postnatal PCP-treated rats enable deep neural network classification

The ability to appropriately update the value of a given action is a critical component of flexible decision making. Several psychiatric disorders, including schizophrenia, are associated with impairments in flexible decision making that can be evaluated using the probabilistic reversal learning (PRL) task. The PRL task has been reverse-translated for use in rodents. Disrupting glutamate neurotransmission during early postnatal neurodevelopment in rodents has induced behavioral, cognitive, and neuropathophysiological abnormalities relevant to schizophrenia. Here, we tested the hypothesis that using the NMDA receptor antagonist phencyclidine (PCP) to disrupt postnatal glutamatergic transmission in rats would lead to impaired decision making in the PRL. Consistent with this hypothesis, compared to controls the postnatal PCP-treated rats completed fewer reversals and exhibited disruptions in reward and punishment sensitivity (i.e., win-stay and lose-shift responding, respectively). Moreover, computational analysis of behavior revealed that postnatal PCP-treatment resulted in a pronounced impairment in the learning rate throughout PRL testing. Finally, a deep neural network (DNN) trained on the rodent behavior could accurately predict the treatment group of subjects. These data demonstrate that disrupting early postnatal glutamatergic neurotransmission impairs flexible decision making and provides evidence that DNNs can be trained on behavioral datasets to accurately predict the treatment group of new subjects, highlighting the potential for DNNs to aid in the diagnosis of schizophrenia.

Insular and Striatal Correlates of Uncertain Risky Reward Pursuit in Schizophrenia

BACKGROUND AND HYPOTHESIS

Risk-taking in specific contexts can be beneficial, leading to rewarding outcomes. Schizophrenia is associated with disadvantageous decision-making, as subjects pursue uncertain risky rewards less than controls. However, it is unclear whether this behavior is associated with more risk sensitivity or less reward incentivization. Matching on demographics and intelligence quotient (IQ), we determined whether risk-taking was more associated with brain activation in regions affiliated with risk evaluation or reward processing.

STUDY DESIGN

Subjects (30 schizophrenia/schizoaffective disorder, 30 controls) completed a modified, fMRI Balloon Analogue Risk Task. Brain activation was modeled during decisions to pursue risky rewards and parametrically modeled according to risk level.

STUDY RESULTS

The schizophrenia group exhibited less risky-reward pursuit despite previous adverse outcomes (Average Explosions; F(1,59) = 4.06, P = .048) but the comparable point at which risk-taking was volitionally discontinued (Adjusted Pumps; F(1,59) = 2.65, P = .11). Less activation was found in schizophrenia via whole brain and region of interest (ROI) analyses in the right (F(1,59) = 14.91, P < 0.001) and left (F(1,59) = 16.34, P < 0.001) nucleus accumbens (NAcc) during decisions to pursue rewards relative to riskiness. Risk-taking correlated with IQ in schizophrenia, but not controls. Path analyses of average ROI activation revealed less statistically determined influence of anterior insula upon dorsal anterior cingulate bilaterally (left: χ2 = 12.73, P < .001; right: χ2 = 9.54, P = .002) during risky reward pursuit in schizophrenia.

CONCLUSIONS

NAcc activation in schizophrenia varied less according to the relative riskiness of uncertain rewards compared to controls, suggesting aberrations in reward processing. The lack of activation differences in other regions suggests similar risk evaluation. Less insular influence on the anterior cingulate may relate to attenuated salience attribution or inability for risk-related brain region collaboration to sufficiently perceive situational risk.

A meta-analysis of the neural substrates of monetary reward anticipation and outcome in alcohol use disorder

The capacity to anticipate and detect rewarding outcomes is fundamental for the development of adaptive decision-making and goal-oriented behavior. Delineating the neural correlates of different stages of reward processing is imperative for understanding the neurobiological mechanism underlying alcohol use disorder (AUD). To examine the neural correlates of monetary anticipation and outcome in AUD patients, we performed two separate voxel-wise meta-analyses of functional neuroimaging studies, including 12 studies investigating reward anticipation and 7 studies investigating reward outcome using the monetary incentive delay task. During the anticipation stage, AUD patients displayed decreased activation in response to monetary cues in mesocortical-limbic circuits and sensory areas, including the ventral striatum (VS), insula, hippocampus, inferior occipital gyrus, supramarginal gyrus, lingual gyrus and fusiform gyrus. During the outcome stage, AUD patients exhibited reduced activation in the dorsal striatum, VS and insula, and increased activation in the orbital frontal cortex and medial temporal area. Our findings suggest that different activation patterns are associated with nondrug rewards during different reward processing stages, potentially reflecting a changed sensitivity to monetary reward in AUD.

A neural mechanism underlying predictive visual motion processing in patients with schizophrenia

Psychotic symptoms may be traced back to sensory sensitivity. Thereby, visual motion (VM) processing particularly has been suggested to be impaired in schizophrenia (SCZ). In healthy brains, VM underlies predictive processing within hierarchically structured systems. However, less is known about predictive VM processing in SCZ. Therefore, we performed fMRI during a VM paradigm with three conditions of varying predictability, i.e., Predictable-, Random-, and Arbitrary motion. The study sample comprised 17 SCZ patients and 23 healthy controls. We calculated general linear model (GLM) analysis to assess group differences in VM processing across motion conditions. Here, we identified significantly lower activity in right temporoparietal junction (TPJ) for SCZ patients. Therefore, right TPJ was set as seed for connectivity analyses. For patients, across conditions we identified increased connections to higher regions, namely medial prefrontal cortex, or paracingulate gyrus. Healthy subjects activated sensory regions as area V5, or superior parietal lobule. Reduced TPJ activity may reflect both a failure in the bottom-up flow of visual information and a decrease of signal processing as consequence of increased top-down input from frontal areas. In sum, these altered neural patterns provide a framework for future studies focusing on predictive VM processing to identify potential biomarkers of psychosis.

Tactile suppression stems from specific sensorimotor predictions

Tactile sensations on a moving hand are perceived weaker than when presented on the same but stationary hand. There is an ongoing debate about whether this weaker perception is based on sensorimotor predictions or is due to a blanket reduction in sensitivity. Here, we show greater suppression of sensations matching predicted sensory feedback. This reinforces the idea of precise estimations of future body sensory states suppressing the predicted sensory feedback. Our results shine light on the mechanisms of human sensorimotor control and are relevant for understanding clinical phenomena related to predictive processes.

The ability to sample sensory information with our hands is crucial for smooth and efficient interactions with the world. Despite this important role of touch, tactile sensations on a moving hand are perceived weaker than when presented on the same but stationary hand. This phenomenon of tactile suppression has been explained by predictive mechanisms, such as internal forward models, that estimate future sensory states of the body on the basis of the motor command and suppress the associated predicted sensory feedback. The origins of tactile suppression have sparked a lot of debate, with contemporary accounts claiming that suppression is independent of sensorimotor predictions and is instead due to an unspecific mechanism. Here, we target this debate and provide evidence for specific tactile suppression due to precise sensorimotor predictions. Participants stroked with their finger over textured objects that caused predictable vibrotactile feedback signals on that finger. Shortly before touching the texture, we probed tactile suppression by applying external vibrotactile probes on the moving finger that either matched or mismatched the frequency generated by the stroking movement along the texture. We found stronger suppression of the probes that matched the predicted sensory feedback. These results show that tactile suppression is specifically tuned to the predicted sensory states of a movement.

Spatial and chronic differences in neural activity in medicated and unmedicated schizophrenia patients

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The medicated schizophrenia group yielded concordant activity among three right lateralized frontal clusters and a left lateralized parietal cluster.

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The unmedicated schizophrenia group yielded concordant activity among right lateralized frontal-parietal regions.

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A neural compensatory mechanism in schizophrenia.

A major caveat with investigations on schizophrenic patients is the difficulty to control for medication usage across samples as disease-related neural differences may be confounded by medication usage. Following a thorough literature search (632 records identified), we included 37 studies with a total of 740 medicated schizophrenia patients and 367 unmedicated schizophrenia patients. Here, we perform several meta-analyses to assess the neurofunctional differences between medicated and unmedicated schizophrenic patients across fMRI studies to determine systematic regions associated with medication usage. Several clusters identified by the meta-analysis on the medicated group include three right lateralized frontal clusters and a left lateralized parietal cluster, whereas the unmedicated group yielded concordant activity among right lateralized frontal-parietal regions. We further explored the prevalence of activity within these regions across illness duration and task type. These findings suggest a neural compensatory mechanism across these regions both spatially and chronically, offering new insight into the spatial and temporal dynamic neural differences among medicated and unmedicated schizophrenia patients.

A Predictive Coding Framework for Understanding Major Depression

Predictive coding models of brain processing propose that top-down cortical signals promote efficient neural signaling by carrying predictions about incoming sensory information. These "priors" serve to constrain bottom-up signal propagation where prediction errors are carried via feedforward mechanisms. Depression, traditionally viewed as a disorder characterized by negative cognitive biases, is associated with disrupted reward prediction error encoding and signaling. Accumulating evidence also suggests that depression is characterized by impaired local and long-range prediction signaling across multiple sensory domains. This review highlights the electrophysiological and neuroimaging evidence for disrupted predictive processing in depression. The discussion is framed around the manner in which disrupted generative predictions about the sensorium could lead to depressive symptomatology, including anhedonia and negative bias. In particular, the review focuses on studies of sensory deviance detection and reward processing, highlighting research evidence for both disrupted generative predictions and prediction error signaling in depression. The role of the monoaminergic and glutamatergic systems in predictive coding processes is also discussed. This review provides a novel framework for understanding depression using predictive coding principles and establishes a foundational roadmap for potential future research.

Neural Circuitry of Salience and Reward Processing in Psychosis

The processing of salient and rewarding stimuli is integral to engaging our attention, stimulating anticipation for future events, and driving goal-directed behaviors. Widespread impairments in these processes are observed in psychosis, which may be associated with worse functional outcomes or mechanistically linked to the development of symptoms. Here, we summarize the current knowledge of behavioral and functional neuroimaging in salience, prediction error, and reward. Although each is a specific process, they are situated in multiple feedback and feedforward systems integral to decision making and cognition more generally. We argue that the origin of salience and reward processing dysfunctions may be centered in the subcortex during the earliest stages of psychosis, with cortical abnormalities being initially more spared but becoming more prominent in established psychotic illness/schizophrenia. The neural circuits underpinning salience and reward processing may provide targets for delaying or preventing progressive behavioral and neurobiological decline.

Abnormal prediction error processing in schizophrenia and depression

To make adaptive decisions under uncertainty, individuals need to actively monitor the discrepancy between expected outcomes and actual outcomes, known as prediction errors. Reward‐based learning deficits have been shown in both depression and schizophrenia patients. For this study, we compiled studies that investigated prediction error processing in depression and schizophrenia patients and performed a series of meta‐analyses. In both groups, positive t‐maps of prediction error tend to yield striatum activity across studies. The analysis of negative t‐maps of prediction error revealed two large clusters within the right superior and inferior frontal lobes in schizophrenia and the medial prefrontal cortex and bilateral insula in depression. The concordant posterior cingulate activity was observed in both patient groups, more prominent in the depression group and absent in the healthy control group. These findings suggest a possible role in dopamine‐rich areas associated with the encoding of prediction errors in depression and schizophrenia.