Frontostriatal Contribution to the Interplay of Flexibility and Stability in Serial Prediction

Gray matter matters: Cognitive stability and flexibility in schizophrenia spectrum disorder

Cognitive dysfunction constitutes a core characteristic of schizophrenia spectrum disorders (SZ). Specifically, deficits in updating generative models (i.e., cognitive flexibility) and shielding against distractions (i.e., cognitive stability) are considered critical contributors to cognitive impairment in these patients. Here, we examined the structural integrity of frontostriatal networks and their associations with reduced cognitive stability and flexibility in SZ patients. In a sample of 21 patients diagnosed with SZ and 22 healthy controls, we measured gray matter volume (GMV) using structural MRI. Further, cognitive stability and flexibility were assessed using a switch-drift paradigm, quantifying the successful ignoring of distracters and detection of rule switches. Compared to controls, patients showed significantly smaller GMV in the whole brain and three predefined regions of interest: the medial prefrontal cortex (mPFC), inferior frontal gyrus (IFG), and caudate nucleus (CN). Notably, GMV in these areas positively correlated with correct rule-switch detection but not with ignoring rule-compatible drifts. Further, the volumetric differences between SZ patients and controls were statistically explainable by considering the behavioral performance in the switch-drift task. Our results indicate that morphological abnormalities in frontostriatal networks are associated with deficient flexibility in SZ patients and highlight the necessity of minimizing neurodevelopmental and progressive brain atrophy in this population.

Cognitive simulation along with neural adaptation explain effects of suggestions: a novel theoretical framework

Hypnosis is an effective intervention with proven efficacy that is employed in clinical settings and for investigating various cognitive processes. Despite their practical success, no consensus exists regarding the mechanisms underlying well-established hypnotic phenomena. Here, we suggest a new framework called the Simulation-Adaptation Theory of Hypnosis (SATH). SATH expands the predictive coding framework by focusing on (a) redundancy elimination in generative models using intrinsically generated prediction errors, (b) adaptation due to amplified or prolonged neural activity, and (c) using internally generated predictions as a venue for learning new associations. The core of our treatise is that simulating proprioceptive, interoceptive, and exteroceptive signals, along with the top-down attenuation of the precision of sensory prediction errors due to neural adaptation, can explain objective and subjective hypnotic phenomena. Based on these postulations, we offer mechanistic explanations for critical categories of direct verbal suggestions, including (1) direct-ideomotor, (2) challenge-ideomotor, (3) perceptual, and (4) cognitive suggestions. Notably, we argue that besides explaining objective responses, SATH accounts for the subjective effects of suggestions, i.e., the change in the sense of agency and reality. Finally, we discuss individual differences in hypnotizability and how SATH accommodates them. We believe that SATH is exhaustive and parsimonious in its scope, can explain a wide range of hypnotic phenomena without contradiction, and provides a host of testable predictions for future research.

Mismatch novelty exploration training shifts VPAC1 receptor-mediated modulation of hippocampal synaptic plasticity by endogenous VIP in male rats

Novelty influences hippocampal-dependent memory through metaplasticity. Mismatch novelty detection activates the human hippocampal CA1 area and enhances rat hippocampal-dependent learning and exploration. Remarkably, mismatch novelty training (NT) also enhances rodent hippocampal synaptic plasticity while inhibition of VIP interneurons promotes rodent exploration. Since VIP, acting on VPAC1 receptors (Rs), restrains hippocampal LTP and depotentiation by modulating disinhibition, we now investigated the impact of NT on VPAC1 modulation of hippocampal synaptic plasticity in male Wistar rats. NT enhanced both CA1 hippocampal LTP and depotentiation unlike exploring an empty holeboard (HT) or a fixed configuration of objects (FT). Blocking VIP VPAC1Rs with PG 97269 (100 nM) enhanced both LTP and depotentiation in naïve animals, but this effect was less effective in NT rats. Altered endogenous VIP modulation of LTP was absent in animals exposed to the empty environment (HT). HT and FT animals showed mildly enhanced synaptic VPAC1R levels, but neither VIP nor VPAC1R levels were altered in NT animals. Conversely, NT enhanced the GluA1/GluA2 AMPAR ratio and gephyrin synaptic content but not PSD-95 excitatory synaptic marker. In conclusion, NT influences hippocampal synaptic plasticity by reshaping brain circuits modulating disinhibition and its control by VIP-expressing hippocampal interneurons while upregulation of VIP VPAC1Rs is associated with the maintenance of VIP control of LTP in FT and HT animals. This suggests VIP receptor ligands may be relevant to co-adjuvate cognitive recovery therapies in aging or epilepsy, where LTP/LTD imbalance occurs.

Control dilemma: Evidence of the stability-flexibility trade-off

Cognitive control can be applied flexibly when task goals or environments change (i.e., cognitive flexibility), or stably to pursue a goal in the face of distraction (i.e., cognitive stability). Whether these seemingly contradictory characteristics have an inverse relationship has been controversial, as some studies have suggested a trade-off mechanism between cognitive flexibility and cognitive stability, while others have not found such reciprocal associations. This study investigated the possible antagonistic correlation between cognitive flexibility and stability using a novel version of the flexibility-stability paradigm and the classic cued task switching paradigm. In Experiment 1, we showed that cognitive flexibility was inversely correlated with cognitive stability, as increased distractor proportions were associated with decreased cognitive flexibility and greater cognitive stability. Moreover, cognitive flexibility and stability were regulated by a single control system instead of two independent control mechanisms, as the model selection results indicated that the reciprocally regulated model with one integration parameter outperformed all other models, and the model parameter was inversely linked to cognitive flexibility and stability. We found similar results using the classic cued task switching paradigm in Experiment 2. Therefore, a trade-off between cognitive flexibility and stability was observed from the paradigms used in this study.

Gamma-Aminobutyric Acid and Glutamate Concentrations in the Striatum and Anterior Cingulate Cortex Not Found to Be Associated with Cognitive Flexibility

Behavioral flexibility and goal-directed behavior heavily depend on fronto-striatal networks. Within these circuits, gamma-aminobutyric acid (GABA) and glutamate play an important role in (motor) response inhibition, but it has remained largely unclear whether they are also relevant for cognitive inhibition. We hence investigated the functional role of these transmitters for cognitive inhibition during cognitive flexibility. Healthy young adults performed two paradigms assessing different aspects of cognitive flexibility. Magnetic resonance spectroscopy (MRS) was used to quantify GABA+ and total glutamate/glutamine (Glx) levels in the striatum and anterior cingulate cortex (ACC) referenced to N-acetylaspartate (NAA). We observed typical task switching and backward inhibition effects, but striatal and ACC concentrations of GABA+/NAA and Glx/NAA were not associated with cognitive flexibility in a functionally relevant manner. The assumption of null effects was underpinned by Bayesian testing. These findings suggest that behavioral and cognitive inhibition are functionally distinct faculties, that depend on (at least partly) different brain structures and neurotransmitter systems. While previous studies consistently demonstrated that motor response inhibition is modulated by ACC and striatal GABA levels, our results suggest that the functionally distinct cognitive inhibition required for successful switching is not, or at least to a much lesser degree, modulated by these factors.

Social conformity is associated with inter-trial electroencephalogram variability

Human society encompasses diverse social influences, and people experience events differently and may behave differently under such influence, including in forming an impression of others. However, little is known about the underlying neural relevance of individual differences in following others' opinions or social norms. In the present study, we designed a series of tasks centered on social influence to investigate the underlying relevance between an individual's degree of social conformity and their neural variability. We found that individual differences under the social influence are associated with the amount of inter-trial electroencephalogram (EEG) variability over multiple stages in a conformity task (making face judgments and receiving social influence). This association was robust in the alpha band over the frontal and occipital electrodes for negative social influence. We also found that inter-trial EEG variability is a very stable, participant-driven internal state measurement and could be interpreted as mindset instability. Overall, these findings support the hypothesis that higher inter-trial EEG variability may be related to higher mindset instability, which makes participants more vulnerable to exposed external social influence. The present study provides a novel approach that considers the stability of one's endogenous neural signal during tasks and links it to human social behaviors.

Effects of DRD2/ANKK1 and COMT Val158Met polymorphisms on stabilization against and adaptation to unexpected events

Genetic variations affecting dopaminergic neuromodulation such as the DRD2/ANKK1 and the COMT Val158Met polymorphisms contribute to goal-directed behavior that requires a balance between stabilization and updating of current states and behaviors. Dopamine is also thought to be relevant for encoding of surprise signals to sensory input and adaptive learning. A link between goal-directed behavior and learning from surprise is therefore plausible. In the present fMRI study, we investigated whether DRD2 and COMT polymorphisms are related to behavioral responses and neural signals in the caudate nucleus and dlPFC during updating or stabilizing internal models of predictable digit sequences. To-be-detected switches between sequences and to-be-ignored digit omissions within a sequence varied by information-theoretic quantities of surprise and entropy. We found that A1 noncarriers and Val-carriers showed a lower response threshold along with increased caudate and dlPFC activation to surprising switches compared with A1-carriers and Met-homozygotes, whose dlPFC activity increased with decreasing switch surprise. In contrast, there were overall smaller differences in behavioral and neural modulation by drift surprise. Our results suggest that the impact of dopamine-relevant polymorphisms in the flexibility-stability trade-off may result in part from the role of dopamine in encoding the weight afforded to events requiring updating or stabilization.

Ignore the glitch but mind the switch: Positive effects of methylphenidate on cognition in attention deficit hyperactivity disorder are related to prediction gain

Neuropsychological symptoms such as inattention and distractibility constitute a core characteristic of attention deficit hyperactivity disorder (ADHD). Here, we tested the hypothesis that attentional dysfunctions result from a deficit in neural gain modulation, which translates into difficulty in predictively weighting relevant sensory input while ignoring distraction. We compared thirty-seven hitherto untreated adults diagnosed with ADHD and thirty-eight healthy participants with a serial switch-drift task that requires internal models of predictable digit sequences to be either updated or stabilized. Switches between sequences that had to be indicated by key presses and digit omissions within a sequence (drifts) that should be ignored varied by stimulus-bound surprise quantified as Shannon information. To investigate whether catecholaminergic modulation by increasing extracellular norepinephrine and dopamine levels leads to an amelioration in prediction gain, participants were tested twice, with patients receiving a single dose of methylphenidate, a norepinephrine/dopamine reuptake inhibitor, in the second session. Patients and controls differed in both updating and stabilizing, depending on the respective event surprise. Specifically, patients showed difficulty in detecting expectable switches, while having greater difficulty to ignore surprising distractions. Thus, underconfident prior beliefs in ADHD may fail to appropriately weight expected relevant input, whereas the gain of neural responses to unexpected irrelevant distractors is increased. Methylphenidate improved both flexibility and stability of prediction and had a positive effect on selective responding over time. Our results suggest that ADHD is associated with an impairment in the use of prior expectations to optimally weight sensory inputs, which is improved by increasing catecholaminergic neurotransmission.

Cerebral and behavioral signs of impaired cognitive flexibility and stability in schizophrenia spectrum disorders

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Patients are impaired regarding both, cognitive flexibility and stability.

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Deficient prediction error discrimination is related to reduced striatal activation.

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Decreased ACC and hippocampus activation predicts impaired rule switch detection.

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Decreased frontal and insular activation predicts impaired distractor shielding.

Background

Manifold cognitive deficits have been reported in schizophrenia spectrum disorders, including disturbances in flexible updating to altered circumstances as well as stabilization deficits in the face of distractors. In this functional magnetic resonance imaging study, we examined the neural correlates of these deficits as two complementary components of predictive processing.

Methods

In 22 patients with schizophrenia spectrum disorders and 22 healthy matched control participants, we applied a serial predictive switch-drift task to assess flexibility as successful detection of prediction-rule switches, and stability as successfully ignoring distractors (“drifts”).

Results

Patients compared with controls less reliably detected rule switches and also less efficiently inhibited drifts. A reduced striatal response to switches or drifts correlated with weaker switch-drift-discrimination in patients, suggesting impaired gating of prediction errors. The increase in activity in anterior cingulate cortex and hippocampus for detected vs. undetected switches was reduced in patients compared to controls, which may reflect impaired behavioral adaptation following prediction errors. The comparison between shielding against distractions and undetected switches showed increased activity in the inferior frontal cortex and posterior insula in controls but not in patients.

Conclusion

Our results suggest new insights into the specific disruption of predictive flexibility and stability in schizophrenia spectrum disorders, which is characterized by impaired striatal gating and inadequate cortical encoding of predictive errors.

Impaired context-sensitive adjustment of behaviour in Parkinson's disease patients tested on and off medication: An fMRI study

The brain's sensitivity to and accentuation of unpredicted over predicted sensory signals plays a fundamental role in learning. According to recent theoretical models of the predictive coding framework, dopamine is responsible for balancing the interplay between bottom-up input and top-down predictions by controlling the precision of surprise signals that guide learning. Using functional MRI, we investigated whether patients with Parkinson's disease (PD) show impaired learning from prediction errors requiring either adaptation or stabilisation of current predictions. Moreover, we were interested in whether deficits in learning over a specific time scale would be accompanied by altered surprise responses in dopamine-related brain structures. To this end, twenty-one PD patients tested on and off dopaminergic medication and twenty-one healthy controls performed a digit prediction paradigm. During the task, violations of sequence-based predictions either signalled the need to update or to stabilise the current prediction and, thus, to react to them or ignore them, respectively. To investigate contextual adaptation to prediction errors, the probability (or its inverse, surprise) of the violations fluctuated across the experiment. When the probability of prediction errors over a specific time scale increased, healthy controls but not PD patients off medication became more flexible, i.e., error rates at violations requiring a motor response decreased in controls but increased in patients. On the neural level, this learning deficit in patients was accompanied by reduced signalling in the substantia nigra and the caudate nucleus. In contrast, differences between the groups regarding the probabilistic modulation of behaviour and neural responses were much less pronounced at prediction errors requiring only stabilisation but no adaptation. Interestingly, dopaminergic medication could neither improve learning from prediction errors nor restore the physiological, neurotypical pattern. Our findings point to a pivotal role of dysfunctions of the substantia nigra and caudate nucleus in deficits in learning from flexibility-demanding prediction errors in PD. Moreover, the data witness poor effects of dopaminergic medication on learning in PD.

Exploitation of local and global information in predictive processing

While prediction errors have been established to instigate learning through model adaptation, recent studies have stressed the role of model-compliant events in predictive processing. Specifically, probabilistic information at critical points in time (so-called checkpoints) has been suggested to be sampled in order to evaluate the internal model, particularly in uncertain contexts. This way, initial model-based expectations are iteratively reaffirmed under uncertainty, even in the absence of prediction errors. Using electroencephalography (EEG), the present study aimed to investigate the interplay of such global uncertainty information and local adjustment cues prompting on-line adjustments of expectations. Within a stream of single digits, participants were to detect ordered sequences (i.e., 3-4-5-6-7) that had a regular length of five digits and were occasionally extended to seven digits. Over time, these extensions were either rare (low irreducible uncertainty) or frequent (high uncertainty) and could be unexpected or indicated by incidental colour cues. Accounting for cue information, an N400 component was revealed as the correlate of locally unexpected (vs expected) outcomes, reflecting effortful integration of incongruous information. As for model-compliant information, multivariate pattern decoding within the P3b time frame demonstrated effective exploitation of local (adjustment cues vs non-informative analogues) and global information (high vs low uncertainty regular endings) sampled from probabilistic events. Finally, superior fit of a global model (disregarding local adjustments) compared to a local model (including local adjustments) in a representational similarity analysis underscored the precedence of global reference frames in hierarchical predictive processing. Overall, results suggest that just like error-induced model adaptation, model evaluation is not limited to either local or global information. Following the hierarchical organisation of predictive processing, model evaluation too can occur at several levels of the processing hierarchy.

Neurocognitive Mechanism of Human Resilience: A Conceptual Framework and Empirical Review

Resilience is an innate human capacity that holds the key to uncovering why some people rebound after trauma and others never recover. Various theories have debated the mechanisms underlying resilience at the psychological level but have not yet incorporated neurocognitive concepts/findings. In this paper, we put forward the idea that cognitive flexibility moderates how well people adapt to adverse experiences, by shifting attention resources between cognition–emotion regulation and pain perception. We begin with a consensus on definitions and highlight the role of cognitive appraisals in mediating this process. Shared concepts among appraisal theories suggest that cognition–emotion, as well as pain perception, are cognitive mechanisms that underlie how people respond to adversity. Frontal brain circuitry sub-serves control of cognition and emotion, connecting the experience of physical pain. This suggests a substantial overlap between these phenomena. Empirical studies from brain imaging support this notion. We end with a discussion of how the role of the frontal brain network in regulating human resilience, including how the frontal brain network interacts with cognition–emotion–pain perception, can account for cognitive theories and why cognitive flexibilities’ role in these processes can create practical applications, analogous to the resilience process, for the recovery of neural plasticity.

Being right matters: Model-compliant events in predictive processing

While prediction errors (PE) have been established to drive learning through adaptation of internal models, the role of model-compliant events in predictive processing is less clear. Checkpoints (CP) were recently introduced as points in time where expected sensory input resolved ambiguity regarding the validity of the internal model. Conceivably, these events serve as on-line reference points for model evaluation, particularly in uncertain contexts. Evidence from fMRI has shown functional similarities of CP and PE to be independent of event-related surprise, raising the important question of how these event classes relate to one another. Consequently, the aim of the present study was to characterise the functional relationship of checkpoints and prediction errors in a serial pattern detection task using electroencephalography (EEG). Specifically, we first hypothesised a joint P3b component of both event classes to index recourse to the internal model (compared to non-informative standards, STD). Second, we assumed the mismatch signal of PE to be reflected in an N400 component when compared to CP. Event-related findings supported these hypotheses. We suggest that while model adaptation is instigated by prediction errors, checkpoints are similarly used for model evaluation. Intriguingly, behavioural subgroup analyses showed that the exploitation of potentially informative reference points may depend on initial cue learning: Strict reliance on cue-based predictions may result in less attentive processing of these reference points, thus impeding upregulation of response gain that would prompt flexible model adaptation. Overall, present results highlight the role of checkpoints as model-compliant, informative reference points and stimulate important research questions about their processing as function of learning und uncertainty.

Association of grey matter changes with stability and flexibility of prediction in akinetic-rigid Parkinson's disease

Parkinson's disease (PD), which is caused by degeneration of dopaminergic neurons in the midbrain, results in a heterogeneous clinical picture including cognitive decline. Since the phasic signal of dopamine neurons is proposed to guide learning by signifying mismatches between subjects' expectations and external events, we here investigated whether akinetic-rigid PD patients without mild cognitive impairment exhibit difficulties in dealing with either relevant (requiring flexibility) or irrelevant (requiring stability) prediction errors. Following our previous study on flexibility and stability in prediction (Trempler et al. J Cogn Neurosci 29(2):298-309, 2017), we then assessed whether deficits would correspond with specific structural alterations in dopaminergic regions as well as in inferior frontal cortex, medial prefrontal cortex, and the hippocampus. Twenty-one healthy controls and twenty-one akinetic-rigid PD patients on and off medication performed a task which required to serially predict upcoming items. Switches between predictable sequences had to be indicated via button press, whereas sequence omissions had to be ignored. Independent of the disease, midbrain volume was related to a general response bias to unexpected events, whereas right putamen volume correlated with the ability to discriminate between relevant and irrelevant prediction errors. However, patients compared with healthy participants showed deficits in stabilisation against irrelevant prediction errors, associated with thickness of right inferior frontal gyrus and left medial prefrontal cortex. Flexible updating due to relevant prediction errors was also affected in patients compared with controls and associated with right hippocampus volume. Dopaminergic medication influenced behavioural performance across, but not within the patients. Our exploratory study warrants further research on deficient prediction error processing and its structural correlates as a core of cognitive symptoms occurring already in early stages of the disease.