From conflict management to reward-based decision making: Actors and critics in primate medial frontal cortex

Visualizing risky situations induces a stronger neural response in brain areas associated with mental imagery and emotions than visualizing non-risky situations

In an fMRI study, we tested the prediction that visualizing risky situations induces a stronger neural response in brain areas associated with mental imagery and emotions than visualizing non-risky and more positive situations. We assumed that processing mental images that allow for "trying-out" the future has greater adaptive importance for risky than non-risky situations, because the former can generate severe negative outcomes. We identified several brain regions that were activated when participants produced images of risky situations and these regions overlap with brain areas engaged in visual, speech, and movement imagery. We also found that producing images of risky situations, in contrast to non-risky situations, was associated with increased neural activation in the insular cortex and cerebellum-the regions involved, among other functions, in emotional processing. Finally, we observed an increased BOLD signal in the cingulate gyrus associated with reward-based decision making and monitoring of decision outcomes. In summary, risky situations increased neural activation in brain areas involved in mental imagery, emotional processing, and decision making. These findings imply that the evaluation of everyday risky situations may be driven by emotional responses that result from mental imagery.

Dynamic Feedback Between Antidepressant Placebo Expectancies and Mood

Importance

Despite high antidepressant placebo response rates, the mechanisms underlying the persistence of antidepressant placebo effects are still poorly understood.

Objective

To investigate the neurobehavioral mechanisms underlying the evolution of antidepressant placebo effects using a reinforcement learning (RL) framework.

Design, Setting, and Participants

In this acute within-patient cross-sectional study of antidepressant placebos, patients aged 18 to 55 years not receiving medication for major depressive disorder (MDD) were recruited at the University of Pittsburgh between February 21, 2017, to March 1, 2021.

Interventions

The antidepressant placebo functional magnetic resonance imaging task manipulates placebo-associated expectancies using visually cued fast-acting antidepressant infusions and controls their reinforcement with sham visual neurofeedback while assessing expected and experienced mood improvement.

Main Outcomes and Measures

The trial-by-trial evolution of expectancies and mood was examined using multilevel modeling and RL, relating model-predicted signals to spatiotemporal dynamics of blood oxygenation level-dependent (BOLD) response.

Results

A bayesian RL model comparison in 60 individuals (mean [SE] age, 24.5 [0.8] years; 51 females [85%]) with MDD revealed that antidepressant placebo trial-wise expectancies were updated by composite learning signals multiplexing sensory evidence (neurofeedback) and trial-wise mood (bayesian omnibus risk <0.001; exceedance probability = 97%). Placebo expectancy, neurofeedback manipulations, and composite learning signals modulated the visual cortex and dorsal attention network (threshold-free cluster enhancement [TFCE] = 1 - P >.95). As participants anticipated antidepressant infusions, learned placebo expectancies modulated the salience network (SN, TFCE = 1 - P >.95), positively scaling with depression severity.

Conclusions and Relevance

Results of this cross-sectional study suggest that on a timescale of minutes, antidepressant placebo effects were maintained by positive feedback loops between expectancies and mood improvement. During learning, representations of placebos and their perceived effects were enhanced in primary and secondary sensory cortices. Latent learned placebo expectancies were encoded in the SN.

The distinct role of orbitofrontal and medial prefrontal cortex in encoding impulsive choices in an animal model of attention deficit hyperactivity disorder

Attention deficit hyperactivity disorder (ADHD) is a complex neurodevelopmental disorder affecting up to 5% of children worldwide. The lack of understanding of ADHD etiology prevented the development of effective treatment for the disease. Here, using in vivo electrophysiology recordings, we have recorded and analyzed the neuronal encoding of delay discounting behavior in prefrontal and orbitofrontal cortex of spontaneously hypertensive rat (SHR). We found that in the presence of rewards, neurons in the orbitofrontal cortex (OFC) were activated regardless to the value of the rewards and OFC neurons in SHR exhibited significantly higher rates of neuronal discharging towards the presence of rewards. While in the medial prefrontal cortex (mPFC), neurons of SHR responded similarly in the presence of large rewards compared with control rats whereas they displayed higher firing rates towards smaller rewards. In addition, the reward-predicting neurons in the OFC encodes for value of rewards in control animals and they were strongly activated upon receiving a small immediate reinforcer in the SHR whereas the reward-predicting neurons in the mPFC neurons generally did not respond to the value of the rewards. Our study characterized the neuronal discharging patterns of OFC and mPFC neurons in the SHR and the control animals and provided novel insights for further understanding the neuronal basis of ADHD pathology.

Learning whom to cooperate with: neurocomputational mechanisms for choosing cooperative partners

Cooperation is fundamental for survival and a functioning society. With substantial individual variability in cooperativeness, we must learn whom to cooperate with, and often make these decisions on behalf of others. Understanding how people learn about the cooperativeness of others, and the neurocomputational mechanisms supporting this learning, is therefore essential. During functional magnetic resonance imaging scanning, participants completed a novel cooperation-partner-choice task where they learned to choose between cooperative and uncooperative partners through trial-and-error both for themselves and vicariously for another person. Interestingly, when choosing for themselves, participants made faster and more exploitative choices than when choosing for another person. Activity in the ventral striatum preferentially responded to prediction errors (PEs) during self-learning, whereas activity in the perigenual anterior cingulate cortex (ACC) signaled both personal and vicarious PEs. Multivariate pattern analyses showed distinct coding of personal and vicarious choice-making and outcome processing in the temporoparietal junction (TPJ), dorsal ACC, and striatum. Moreover, in right TPJ the activity pattern that differentiated self and other outcomes was associated with individual differences in exploitation tendency. We reveal neurocomputational mechanisms supporting cooperative learning and show that this learning is reflected in trial-by-trial univariate signals and multivariate patterns that can distinguish personal and vicarious choices.

Distinctive types of aversiveness are represented as the same in a portion of the dorsal anterior cingulate cortex: An fMRI study with the cue paradigm

Some studies have argued that the dorsal anterior cingulate cortex (dACC) is generally activated in response to aversive information, including pain, negative affect, and cognitive conflict. Other studies have claimed that the dACC has subdivisions, and each division has a specific function. By manipulating emotionally and cognitively aversive cues, the present study determined whether the dACC is generally responsive to aversiveness or it has subdivisions for specific forms of aversiveness. Conjunction functional magnetic resonance imaging (fMRI) analysis showed that emotionally and cognitively aversive cues activated the same portion of the dACC. When these cues were contiguously presented, the region demonstrated additive activity, further supporting the overlapping representation of the two different forms of aversiveness in the dACC. Additional effective connectivity analysis showed that the dACC was co-activated with different brain regions depending on the cue type, characterizing its behavioral control mechanism. Complementary multivariate analyses showed that the reaction time was negatively correlated with the activity of the dACC and that the activity of the dACC under the emotional cue was predicted by the individual state anxiety score but not under the cognitive cue. We also found that the superior part of the dACC was uniquely activated in response to cognitively aversive cues, partially supporting the functional segregation account. Collectively, our results provide evidence that the specific locus of the dACC is generally responsive to distinctive motivational information, whereas the other loci may have segregated functions. Discussion includes recent neurocomputational theories that seem to satisfactorily account for the present results.

Prefrontal Circuits guiding Social Preference: Implications in Autism Spectrum Disorder

Although Autism Spectrum Disorder (ASD) is increasing in diagnostic prevalence, treatment options are inadequate largely due to limited understanding of ASD's underlying neural mechanisms. Contributing to difficulties in treatment development is the vast heterogeneity of ASD, from physiological causes to clinical presentations. Recent studies suggest that distinct genetic and neurological alterations may converge onto similar underlying neural circuits. Therefore, an improved understanding of neural circuit-level dysfunction in ASD may be a more productive path to developing broader treatments that are effective across a greater spectrum of ASD. Given the social preference behavioral deficits commonly seen in ASD, dysfunction in circuits mediating social preference may contribute to the atypical development of social cognition. We discuss some of the animal models used to study ASD and examine the function and effects of dysregulation of the social preference circuits, notably the medial prefrontal cortex-amygdala and the medial prefrontal cortex-nucleus accumbens circuits, in these animal models. Using the common circuits underlying similar behavioral disruptions of social preference behaviors as an example, we highlight the importance of identifying disruption in convergent circuits to improve the translational success of animal model research for ASD treatment development.

Auricular Transcutaneous Vagus Nerve Stimulation Diminishes Alpha-Band-Related Inhibitory Gating Processes During Conflict Monitoring in Frontal Cortices

BACKGROUND

Pursuing goals is compromised when being confronted with interfering information. In such situations, conflict monitoring is important. Theoretical considerations on the neurobiology of response selection and control suggest that auricular transcutaneous vagus nerve stimulation (atVNS) should modulate conflict monitoring. However, the neurophysiological-functional neuroanatomical underpinnings are still not understood.

METHODS

AtVNS was applied in a randomized crossover study design (n = 45). During atVNS or sham stimulation, conflict monitoring was assessed using a Flanker task. EEG data were recorded and analyzed with focus on theta and alpha band activity. Beamforming was applied to examine functional neuroanatomical correlates of atVNS-induced EEG modulations. Moreover, temporal EEG signal decomposition was applied to examine different coding levels in alpha and theta band activity.

RESULTS

AtVNS compromised conflict monitoring processes when it was applied at the second appointment in the crossover study design. On a neurophysiological level, atVNS exerted specific effects because only alpha-band activity was modulated. Alpha-band activity was lower in middle and superior prefrontal regions during atVNS stimulation and thus lower when there was also a decline in task performance. The same direction of alpha-band modulations was evident in fractions of the alpha-band activity coding stimulus-related processes, stimulus-response translation processes, and motor response-related processes.

CONCLUSIONS

The combination of prior task experience and atVNS compromises conflict monitoring processes. This is likely due to reduction of the alpha-band-associated inhibitory gating process on interfering information in frontal cortices. Future research should pay considerable attention to boundary conditions affecting the direction of atVNS effects.

The role of left angular gyrus in the representation of linguistic composition relations

Language comprehension is compositional: individual words are combined structurally to form larger meaning representations. The neural basis for compositionality is at the center of a growing body of recent research. Previous work has largely used univariate analysis to investigate the question, a technique that could potentially lead to the loss of fined‐grained information due to the procedure of averaging over neural responses. In a functional magnetic resonance imaging experiment, the present study examined different types of composition relations in Chinese phrases, using a 1‐back composition relation probe (CRP) task and a 1‐back word probe (WP) task. We first analyzed the data using the multivariate representation similarity analysis, which better captures the fine‐grained representational differences in the stimuli. The results showed that the left angular gyrus (AG) represents different types of composition relations in the CRP task, but no brain areas were identified in the WP task. We also conducted a traditional univariate analysis and found greater activations in the bilateral inferior frontal gyrus in the CRP task relative to the WP task. We discuss the methodological and theoretical implications of our findings in the context of the larger language neural network identified in previous studies. Our findings highlight the role of left AG in representing and distinguishing fine‐grained linguistic composition relations.

Experiencing Happiness Together Facilitates Dyadic Coordination through the Enhanced Interpersonal Neural Synchronization

Experiencing positive emotions together facilitates interpersonal understanding and promotes subsequent social interaction among individuals. However, the neural underpinnings of such emotional-social effect remain to be discovered. Current study employed the fNIRS-based hyperscanning to investigate the above mentioned relationship. After participants in dyad watching movie clips with happily or neutral emotion, they were asked to perform the interpersonal cooperative task, with their neural activation of prefrontal cortex (PFC) being recorded simultaneously via functional near infrared spectroscopy. Results suggested that compared with the neutral movie watching together, a higher interpersonal neural synchronization (INS) in left inferior frontal gyrus during participant dyads watching happiness movie together. Subsequently, dyads in happiness showed more effective coordination interaction during performed the interpersonal cooperation task compared to those in the neutral condition, and such facilitated effect was associated with increased cooperation-related INS at left middle frontal cortex. A mediation analysis showed that the coordination interaction fully mediated the relationship between the emotion-induced INS during the happiness movie-viewing and the cooperation-related INS in interpersonal cooperation. Taken together, our findings suggest that the faciliatory effect experiencing happiness together has on interpersonal cooperation can be reliably reflected by the INS magnitude at the brain level.

Reward signalling in brainstem nuclei under fluctuating blood glucose

Phasic dopamine release from mid-brain dopaminergic neurons is thought to signal errors of reward prediction (RPE). If reward maximisation is to maintain homeostasis, then the value of primary rewards should be coupled to the homeostatic errors they remediate. This leads to the prediction that RPE signals should be configured as a function of homeostatic state and thus diminish with the attenuation of homeostatic error. To test this hypothesis, we collected a large volume of functional MRI data from five human volunteers on four separate days. After fasting for 12 hours, subjects consumed preloads that differed in glucose concentration. Participants then underwent a Pavlovian cue-conditioning paradigm in which the colour of a fixation-cross was stochastically associated with the delivery of water or glucose via a gustometer. This design afforded computation of RPE separately for better- and worse-than expected outcomes during ascending and descending trajectories of serum glucose fluctuations. In the parabrachial nuclei, regional activity coding positive RPEs scaled positively with serum glucose for both ascending and descending glucose levels. The ventral tegmental area and substantia nigra became more sensitive to negative RPEs when glucose levels were ascending. Together, the results suggest that RPE signals in key brainstem structures are modulated by homeostatic trajectories of naturally occurring glycaemic flux, revealing a tight interplay between homeostatic state and the neural encoding of primary reward in the human brain.

The Best Laid Plans: Computational Principles of Anterior Cingulate Cortex

Despite continual debate for the past 30 years about the function of anterior cingulate cortex (ACC), its key contribution to neurocognition remains unknown. However, recent computational modeling work has provided insight into this question. Here we review computational models that illustrate three core principles of ACC function, related to hierarchy, world models, and cost. We also discuss four constraints on the neural implementation of these principles, related to modularity, binding, encoding, and learning and regulation. These observations suggest a role for ACC in hierarchical model-based hierarchical reinforcement learning (HMB-HRL), which instantiates a mechanism motivating the execution of high-level plans.

The social dilemma: prefrontal control of mammalian sociability

Mammalian social interactions are orchestrated by a wide array of neural circuits. While some aspects of social behaviors are driven by subcortical circuits, and are considered to be highly conserved and hard-wired, others require dynamic and context-dependent modulation that integrates current state, past experience and goal-driven action selection. These cognitive social processes are known to be dependent on the integrity of the prefrontal cortex. However, the circuit mechanisms through which the prefrontal cortex supports complex social functions are still largely unknown, and it is unclear if and how they diverge from prefrontal control of behavior outside of the social domain. Here we review recent studies exploring the role of prefrontal circuits in mammalian social functions, and attempt to synthesize these findings to a holistic view of prefrontal control of sociability.

Recent advances in the application of predictive coding and active inference models within clinical neuroscience

Research in clinical neuroscience is founded on the idea that a better understanding of brain (dys)function will improve our ability to diagnose and treat neurological and psychiatric disorders. In recent years, neuroscience has converged on the notion that the brain is a 'prediction machine,' in that it actively predicts the sensory input that it will receive if one or another course of action is chosen. These predictions are used to select actions that will (most often, and in the long run) maintain the body within the narrow range of physiological states consistent with survival. This insight has given rise to an area of clinical computational neuroscience research that focuses on characterizing neural circuit architectures that can accomplish these predictive functions, and on how the associated processes may break down or become aberrant within clinical conditions. Here, we provide a brief review of examples of recent work on the application of predictive processing models of brain function to study clinical (psychiatric) disorders, with the aim of highlighting current directions and their potential clinical utility. We offer examples of recent conceptual models, formal mathematical models, and applications of such models in empirical research in clinical populations, with a focus on making this material accessible to clinicians without expertise in computational neuroscience. In doing so, we aim to highlight the potential insights and opportunities that understanding the brain as a prediction machine may offer to clinical research and practice.

Integration of conflict resolution and positive emotions: Electrophysiological evidence

Previous studies have shown that conflict monitoring is integrated with negative emotions. However, the idea that conflict resolution facilitates positive stimuli processing has not reached a consistent conclusion. We suggested that conflict resolution was integrated with positive emotions. The present study used ERPs, took the flanker task as primes, set different durations (i.e., 600 ms and 1200 ms) between the resolution of conflicts and the presentation of targets, and chose affective words as targets to investigate the affective effect of cognitive conflict during the resolution stage. Participants' task was to react to the flanker task and then evaluate the valence of the target words. The findings of experiment1 (600 ms) and experiment2 (1200 ms) were consistent. Behavioral results showed that the conflict effect was significant, and the positive signal effect of conflict resolution was found. In ERPs results, the enhanced N2 amplitudes for incongruent primes showed a significant conflict effect. The enhanced conflict SP amplitudes for incongruent primes reflected conflict resolution. As expected, the enhanced N400 amplitudes for positive targets after incongruent primes indicated that conflict resolution facilitated positive stimuli processing. Time-frequency analyses showed that incongruent primes elicited larger theta (4-8 Hz) power than congruent primes over the frontal areas. More importantly, we found that theta (4-8 Hz) power for positive targets after incongruent primes was lower than those after congruent primes over the central areas. These findings suggested that conflict resolution facilitated positive stimulus processing, and this positive effect was a carry-over effect, which indicated that conflict resolution was integrated with positive emotions.

Light-sensitive circuits related to emotional processing underlie the antidepressant neural targets of light therapy

Since Aaron Beck proposed his cognitive model of depression, biased attention, biased processing, and biased rumination (different phases of biased cognition) have been considered as the key elements consistently linked with depression. Increasing evidence suggests that the functional failures in the "emotional processing system (EPS)" underlie the neurological foundation of the biased cognition of depression. Light therapy, a non-intrusive approach, exerts powerful effects on emotion and cognition and affects the activity, functional connectivity, and plasticity of multiple brain structures. Although numerous studies have reported its effectiveness in treating depression, the findings have not been integrated with Beck's cognitive model and EPS, and the neurobiological mechanisms of antidepressant light therapy remain largely unknown. In this review, integrated with the classical theories of Beck's cognitive model of depression and EPS, we identified the key neural circuits and abnormalities involved in the cognitive bias of depression and, accordingly, identified and depicted several light-sensitive circuits (LSCs, neural circuits in the EPS that are responsive to light stimulation) that may underlie the antidepressant neural targets of light therapy, as listed below: In summary, the LSCs above narrow down the research scope of identifying the neural targets of antidepressant light therapy and help elucidate the neuropsychological mechanism of antidepressant light therapy.

Neural Dynamics of Cognitive Control in Various Types of Incongruence

Conflict-control is a core function of cognitive control. Although numerous studies have considered cognitive control to be domain-general, the shared and distinct brain responses to different types of incongruence or conflict remain unclear. Using a hybrid flanker task, the present study explored the temporal dynamics of brain activation to three types of incongruence: flanker interference, rule-based response switch (rule-switch), and action-based response switch (response-alternation). The results showed that: (1) all three types of incongruence evoked larger N2 amplitudes than the congruent condition in the frontal region, with the N2 amplitudes and topographical distribution of the N2 effect differing between the different types of incongruence; and (2) in the P300 time window, the flanker interference condition yielded the most delayed P300 latency, whereas the rule-switch and response-alternation conditions yielded smaller P300 amplitudes with a longer interval from P300 peak to a keypress. These findings suggest that different types of incongruence are first monitored similarly by the cognitive control system and then resolved differently.

The human cingulum: From the limbic tract to the connectionist paradigm

The cingulum is a core component of the limbic lobe and part of the circuit that was described by Papez where environmental experiences become endowed with emotional awareness. Recent techniques for the study of cerebral connectivity have updated this fasciculus' morphology and led to the acknowledgment that its involvement in superior functions goes far beyond emotion processing. Long and robust, the cingulum is a long association fasciculus with terminations in all cerebral lobes. These observations plead for a pivotal rethinking of its role in the human brain and lead to the conclusion that to merely consider it as the main fasciculus of the limbic system was actually a reductionism. This paper summarizes the key facts regarding why the cingulum is now perceived as a primary interconnecting apparatus in the medial aspect of the cerebral hemisphere.

Interplay between midbrain and dorsal anterior cingulate regions arbitrates lingering reward effects on memory encoding

Rewarding events enhance memory encoding via dopaminergic influences on hippocampal plasticity. Phasic dopamine release depends on immediate reward magnitude, but presumably also on tonic dopamine levels, which may vary as a function of the average accumulation of reward over time. Using model-based fMRI in combination with a novel associative memory task, we show that immediate reward magnitude exerts a monotonically increasing influence on the nucleus accumbens, ventral tegmental area (VTA), and hippocampal activity during encoding, and enhances memory. By contrast, average reward levels modulate feedback-related responses in the VTA and hippocampus in a non-linear (inverted U-shape) fashion, with similar effects on memory performance. Additionally, the dorsal anterior cingulate cortex (dACC) monotonically tracks average reward levels, while VTA-dACC functional connectivity is non-linearly modulated (inverted U-shape) by average reward. We propose that the dACC computes the net behavioral impact of average reward and relays this information to memory circuitry via the VTA.

Game theoretical mapping of white matter contributions to visuospatial attention in stroke patients with hemineglect

White matter bundles linking gray matter nodes are key anatomical players to fully characterize associations between brain systems and cognitive functions. Here we used a multivariate lesion inference approach grounded in coalitional game theory (multiperturbation Shapley value analysis, MSA) to infer causal contributions of white matter bundles to visuospatial orienting of attention. Our work is based on the characterization of the lesion patterns of 25 right hemisphere stroke patients and the causal analysis of their impact on three neuropsychological tasks: line bisection, letter cancellation, and bells cancellation. We report that, out of the 11 white matter bundles included in our MSA coalitions, the optic radiations, the inferior fronto-occipital fasciculus and the anterior cingulum were the only tracts to display task-invariant contributions (positive, positive, and negative, respectively) to the tasks. We also report task-dependent influences for the branches of the superior longitudinal fasciculus and the posterior cingulum. By extending prior findings to white matter tracts linking key gray matter nodes, we further characterize from a network perspective the anatomical basis of visual and attentional orienting processes. The knowledge about interactions patterns mediated by white matter tracts linking cortical nodes of attention orienting networks, consolidated by further studies, may help develop and customize brain stimulation approaches for the rehabilitation of visuospatial neglect.

Reward Modulates Affective Priming Effect in Cognitive Conflict Processing: Electrophysiological Evidence

Previous research demonstrated that cognitive conflict could induce an affective priming effect, and the stage (detection/resolution) of conflict processing led to different directions (positive/negative) of the affective priming effect. We suggested that rewards play a critical role in the affective priming effect on conflict resolution. The present study used event-related potentials (ERPs), using the arrow flanker task as primes and choosing specific affective words as targets to investigate the affective priming effect induced by cognitive conflict during the resolution stage. Our question was whether rewards created a modulating effect. Participants were asked to judge the congruency of the prime stimuli and then evaluate the valence of the target words. For behavioral results, the conflict effect was significant, and the reward promoted the behavioral performance of participants. For ERP results, enhanced N2 amplitudes for incongruent primes indicated a significant conflict effect. More importantly, as expected, in the rewarded condition, the enhanced N400 amplitudes for positive targets following incongruent primes were found, indicating a positive priming effect. However, in the unrewarded condition, the reduced N400 amplitudes for positive targets following incongruent primes were found, indicating conflict resolution hindered the processing of positive stimuli. These findings suggested that cognitive conflict-induced the positive priming effect during the resolution stage and that rewards had a moderating effect on the positive priming effect.

A computational perspective on the roles of affect in cognitive control

Previous work has demonstrated that cognitive control can be influenced by affect, both when it is tied to the anticipated outcomes for cognitive performance (integral affect) and when affect is induced independently of performance (incidental affect). However, the mechanisms through which such interactions occur remain debated, in part because they have yet to be formalized in a way that allows experimenters to test quantitative predictions of a putative mechanism. To generate such predictions, we leveraged a recent model that determines cognitive control allocation by weighing potential costs and benefits in order to determine the overall Expected Value of Control (EVC). We simulated potential accounts of how integral and incidental affect might influence this valuation process, including whether incidental positive affect influences how difficult one perceives a task to be, how effortful it feels to exert control, and/or the marginal utility of succeeding at the task. We find that each of these accounts makes dissociable predictions regarding affect's influence on control allocation and measures of task performance (e.g., conflict adaptation, switch costs). We discuss these findings in light of the existing empirical findings and theoretical models. Collectively, this work grounds existing theories regarding affect-control interactions, and provides a method by which specific predictions of such accounts can be confirmed or refuted based on empirical data.

Striatal dopamine D2 binding correlates with locus of control: Preliminary evidence from [11C]raclopride Positron Emission Tomography

The ability to exert control has been widely investigated as a hallmark of adaptive behaviour. Dopamine is recognized as the key neuromodulator mediating various control-related processes. The neural mechanisms underlying the subjective perception of being in control, or Locus of Control (LOC) are however less clear. LOC indicates the subjective tendency to attribute environmental outcomes to one's actions (internal LOC) or instead to external incontrollable factors (external LOC). Here we hypothesized that dopamine levels also relate to LOC. Previous work shows that dopamine signaling mediates learning of action-outcome relationships, outcome predictability, and opportunity cost. Prominent theories propose dopamine dysregulation as the key pathogenetic mechanism in schizophrenia and depression. Critically, external LOC is a risk factor for schizophrenia and depression, and predicts increased vulnerability to stress. However, a direct link between LOC and dopamine levels in healthy control had not been demonstrated. The purpose of our study was to investigate this link. Using [¹¹C]raclopride Positron Emission Tomography we tested the relationship between D2 receptor binding in the striatum and LOC (measured with the Rotter Locus of Control scale) in 15 healthy volunteers. Our results show a large and positive correlation: increased striatal D2 binding was associated with External LOC. This finding opens promising avenues for the study of several psychological impairments that have been associated with both dopamine and LOC, such as addiction, schizophrenia, and depression.

Cost-benefit trade-offs in decision-making and learning

Value-based decision-making involves trading off the cost associated with an action against its expected reward. Research has shown that both physical and mental effort constitute such subjective costs, biasing choices away from effortful actions, and discounting the value of obtained rewards. Facing conflicts between competing action alternatives is considered aversive, as recruiting cognitive control to overcome conflict is effortful. Moreover, engaging control to proactively suppress irrelevant information that could conflict with task-relevant information would presumably also be cognitively costly. Yet, it remains unclear whether the cognitive control demands involved in preventing and resolving conflict also constitute costs in value-based decisions. The present study investigated this question by embedding irrelevant distractors (flanker arrows) within a reversal-learning task, with intermixed free and instructed trials. Results showed that participants learned to adapt their free choices to maximize rewards, but were nevertheless biased to follow the suggestions of irrelevant distractors. Thus, the perceived cost of investing cognitive control to suppress an external suggestion could sometimes trump internal value representations. By adapting computational models of reinforcement learning, we assessed the influence of conflict at both the decision and learning stages. Modelling the decision showed that free choices were more biased when participants were less sure about which action was more rewarding. This supports the hypothesis that the costs linked to conflict management were traded off against expected rewards. During the learning phase, we found that learning rates were reduced in instructed, relative to free, choices. Learning rates were further reduced by conflict between an instruction and subjective action values, whereas learning was not robustly influenced by conflict between one’s actions and external distractors. Our results show that the subjective cognitive control costs linked to conflict factor into value-based decision-making, and highlight that different types of conflict may have different effects on learning about action outcomes.

Value-based decision-making involves trading off the cost associated with an action–such as physical or mental effort–against its expected reward. Although facing conflicts between competing action alternatives is considered aversive and effortful, it remains unclear whether conflict also constitutes a cost in value-based decisions. We tested this hypothesis by combining a classic conflict (flanker) task with a reinforcement-learning task. Results showed that participants learned to maximise their earnings, but were nevertheless biased to follow irrelevant suggestions. Computational model-based analyses showed a greater choice bias with more uncertainty about the best action to make, supporting the hypothesis that the costs linked to conflict management were traded off against expected rewards. We additionally found that learning rates were reduced when following instructions, relative to when choosing freely what to do. Learning was further reduced by conflict between instructions and subjective action values. In short, we found that the subjective cognitive control costs linked to conflict factor into value-based decision-making, and that different types of conflict may have different effects on learning about action outcomes.

Functional Neuroimaging Test of an Emerging Neurobiological Model of Hoarding Disorder

BACKGROUND

Over the past decade, functional neuroimaging studies have found abnormal brain function in several cortical systems when patients with compulsive hoarding behaviors make decisions about personal possessions. The purpose of this study was to use functional magnetic resonance imaging to test a neurobiological model of hoarding disorder (HD) that has begun to emerge from these small studies by confirming HD-related brain dysfunction in previously implicated brain regions in the largest sample of HD patients examined to date.

METHODS

We compared 79 adults diagnosed with DSM-5 HD with 44 non-HD control participants using a functional magnetic resonance imaging task of decision making to acquire or discard material possessions and on a control task involving semantic processing.

RESULTS

HD brain activation profiles prominently featured insular and anterior cingulate cortex overengagement during possession-related choices that were not seen in non-HD brain activation profiles and also correlated with hoarders' clutter and difficulty discarding. Although HD patients overengaged the insula when deciding to discard, relative to when performing the non-decision making task contrast, the HD insula also was generally blunted.

CONCLUSIONS

This study links the defining behavioral symptoms of HD to localized brain dysfunction within cingulo-opercular brain systems and firmly establishes the context-dependent importance of this network dysfunction in HD. The relevance of dysfunction in these brain regions is highlighted by a failure to replicate HD-related abnormalities in other brain regions implicated in prior HD functional magnetic resonance imaging studies. This study also raises the novel possibility that HD may involve abnormality in the inferior frontal cortex engaged for executive control over semantic processing.

Learning to synchronize: How biological agents can couple neural task modules for dealing with the stability-plasticity dilemma

We provide a novel computational framework on how biological and artificial agents can learn to flexibly couple and decouple neural task modules for cognitive processing. In this way, they can address the stability-plasticity dilemma. For this purpose, we combine two prominent computational neuroscience principles, namely Binding by Synchrony and Reinforcement Learning. The model learns to synchronize task-relevant modules, while also learning to desynchronize currently task-irrelevant modules. As a result, old (but currently task-irrelevant) information is protected from overwriting (stability) while new information can be learned quickly in currently task-relevant modules (plasticity). We combine learning to synchronize with task modules that learn via one of several classical learning algorithms (Rescorla-Wagner, backpropagation, Boltzmann machines). The resulting combined model is tested on a reversal learning paradigm where it must learn to switch between three different task rules. We demonstrate that our combined model has significant computational advantages over the original network without synchrony, in terms of both stability and plasticity. Importantly, the resulting models' processing dynamics are also consistent with empirical data and provide empirically testable hypotheses for future MEG/EEG studies.

Parameters as Trait Indicators: Exploring a Complementary Neurocomputational Approach to Conceptualizing and Measuring Trait Differences in Emotional Intelligence

Current assessments of trait emotional intelligence (EI) rely on self-report inventories. While this approach has seen considerable success, a complementary approach allowing objective assessment of EI-relevant traits would provide some potential advantages. Among others, one potential advantage is that it would aid in emerging efforts to assess the brain basis of trait EI, where self-reported competency levels do not always match real-world behavior. In this paper, we review recent experimental paradigms in computational cognitive neuroscience (CCN), which allow behavioral estimates of individual differences in range of parameter values within computational models of neurocognitive processes. Based on this review, we illustrate how several of these parameters appear to correspond well to EI-relevant traits (i.e., differences in mood stability, stress vulnerability, self-control, and flexibility, among others). In contrast, although estimated objectively, these parameters do not correspond well to the optimal performance abilities assessed within competing “ability models” of EI. We suggest that adapting this approach from CCN—by treating parameter value estimates as objective trait EI measures—could (1) provide novel research directions, (2) aid in characterizing the neural basis of trait EI, and (3) offer a promising complementary assessment method.

Revisiting foraging approaches in neuroscience

Many complex real-world decisions, such as deciding which house to buy or whether to switch jobs, involve trying to maximize reward across a sequence of choices. Optimal Foraging Theory is well suited to study these kinds of choices because it provides formal models for reward-maximization in sequential situations. In this article, we review recent insights from foraging neuroscience, behavioral ecology, and computational modelling. We find that a commonly used approach in foraging neuroscience, in which choice items are encountered at random, does not reflect the way animals direct their foraging efforts in certain real-world settings, nor does it reflect efficient reward-maximizing behavior. Based on this, we propose that task designs allowing subjects to encounter choice items strategically will further improve the ecological validity of foraging approaches used in neuroscience, as well as give rise to new behavioral and neural predictions that deepen our understanding of sequential, value-based choice.

Conflict-related dorsomedial frontal cortex activation during healthy food decisions is associated with increased cravings for high-fat foods

Previous studies suggest obesity is associated with altered function within the insula and dorsomedial frontal cortex (including dorsal anterior cingulate cortex; DMFC/dACC), reflecting abnormal reward processing and reduced sensitivity to feelings of satiety. Given the proposed roles of DMFC/dACC in monitoring response conflict and reward-based decision making, the present study examined DMFC/dACC activation, and functional connectivity between the DMFC/dACC and the anterior insula (AI), during food-related decision-making. Twenty participants recruited from the general population (10 Female) performed a decision task while undergoing functional magnetic resonance imaging. They were instructed to "choose the healthier option" when simultaneously shown pairs of images of different foods. Significant DMFC/dACC activation was observed during food-related decision-making, and activation levels also positively correlated with self-reported cravings for high-fat foods (r = 0.57, p = 0.009) and self-reported desire to eat the high-fat foods depicted in the images (r = 0.48, p = 0.032). Negative functional connectivity estimates between the right AI and DMFC/dACC were also associated with self-reported control over eating (r = -0.50, p = 0.025). These results suggest that (1) more intense cravings for unhealthy foods are associated with greater response conflict when deciding between healthy and unhealthy food options, and (2) lack of eating-related control may involve a reduced influence of insula-mediated bodily signals on decision-making. This task may offer a neuroimaging-based probe for identifying individuals vulnerable to eating-related disorders and should be replicated in clinical populations.

Transcranial direct-current stimulation reduces nociceptive behaviour in an orofacial pain model

BACKGROUND

Transcranial direct-current stimulation (tDCS) is a noninvasive method of brain stimulation suggested as a therapeutic tool for pain and is related to the reversal of maladaptive plasticity associated with chronic pain.

OBJECTIVES

This study investigated the effect of tDCS, a non-pharmacological therapy, on local mechanical hyperalgesia, and remote thermal hyperalgesia in rats submitted to orofacial inflammatory pain model, by facial von Frey and hot plate tests, respectively. In addition, we evaluated levels of BDNF, NGF, IL-10 and IL-6 in the brainstem and blood serum of these animals at 24 hours and 7 days after the end of tDCS treatment.

METHODS

Rats were subjected to temporomandibular joint pain and treated with tDCS. The animals were divided into control, pain and pain + treatment groups. Mechanical and thermal hyperalgesia were evaluated at baseline, 7 days after administration of complete Freund's adjuvant, and immediately, 24 hours, and 7 days after the tDCS treatment. Neuroimmunomodulators levels were determined by ELISA. Statistical analyses were performed by (GEE)/Bonferroni (behavioural tests), three-way ANOVA/SNK (neurochemical tests) and Kruskal-Wallis (histological analysis).

RESULTS

Transcranial direct-current stimulation reduced mechanical and thermal hyperalgesia (P < 0.01). We observed interaction between factors (pain and treatment) increasing brainstem BDNF (P < 0.01) and NGF (P < 0.05) levels. Furthermore, we found an increase in IL-6 and IL-10 levels in the brainstem at 24 hours and 7 days after tDCS, respectively.

CONCLUSION

We showed that tDCS reduces thermal and mechanical hyperalgesia induced by orofacial pain until 7 days after treatment. These findings demonstrate that tDCS was effective in the control of orofacial inflammatory pain.

Oscillatory signatures of reward prediction errors in declarative learning

Reward prediction errors (RPEs) are crucial to learning. Whereas these mismatches between reward expectation and reward outcome are known to drive procedural learning, their role in declarative learning remains underexplored. Earlier work from our lab addressed this, and consistently found that signed reward prediction errors (SRPEs; "better-than-expected" signals) boost declarative learning. In the current EEG study, we sought to explore the neural signatures of SRPEs. Participants studied 60 Dutch-Swahili word pairs while RPE magnitudes were parametrically manipulated. Behaviorally, we replicated our previous findings that SRPEs drive declarative learning, with increased recognition for word pairs accompanied by large, positive RPEs. In the EEG data, at the start of reward feedback processing, we found an oscillatory (theta) signature consistent with unsigned reward prediction errors (URPEs; "different-than-expected" signals). Slightly later during reward feedback processing, we observed oscillatory (high-beta and high-alpha) signatures for SRPEs during reward feedback, similar to SRPE signatures during procedural learning. These findings illuminate the time course of neural oscillations in processing reward during declarative learning, providing important constraints for future theoretical work.

The anatomy of apathy: A neurocognitive framework for amotivated behaviour

Apathy is a debilitating syndrome associated with many neurological disorders, including several common neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease, and focal lesion syndromes such as stroke. Here, we review neuroimaging studies to identify anatomical correlates of apathy, across brain disorders. Our analysis reveals that apathy is strongly associated with disruption particularly of dorsal anterior cingulate cortex (dACC), ventral striatum (VS) and connected brain regions. Remarkably, these changes are consistent across clinical disorders and imaging modalities. Review of the neuroimaging findings allows us to develop a neurocognitive framework to consider potential mechanisms underlying apathy. According to this perspective, an interconnected group of brain regions - with dACC and VS at its core - plays a crucial role in normal motivated behaviour. Specifically we argue that motivated behaviour requires a willingness to work, to keep working, and to learn what is worth working for. We propose that deficits in any one or more of these processes can lead to the clinical syndrome of apathy, and outline specific approaches to test this hypothesis. A richer neurobiological understanding of the mechanisms underlying apathy should ultimately facilitate development of effective therapies for this disabling condition.

Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner

Optimal decision-making is based on integrating information from several dimensions of decisional space (e.g., reward expectation, cost estimation, effort exertion). Despite considerable empirical and theoretical efforts, the computational and neural bases of such multidimensional integration have remained largely elusive. Here we propose that the current theoretical stalemate may be broken by considering the computational properties of a cortical-subcortical circuit involving the dorsal anterior cingulate cortex (dACC) and the brainstem neuromodulatory nuclei: ventral tegmental area (VTA) and locus coeruleus (LC). From this perspective, the dACC optimizes decisions about stimuli and actions, and using the same computational machinery, it also modulates cortical functions (meta-learning), via neuromodulatory control (VTA and LC). We implemented this theory in a novel neuro-computational model–the Reinforcement Meta Learner (RML). We outline how the RML captures critical empirical findings from an unprecedented range of theoretical domains, and parsimoniously integrates various previous proposals on dACC functioning.

A major challenge for all organisms is selecting optimal behaviour to obtain resources while minimizing energetic and other expenses. Evolution provided mammals with exceptional decision-making capabilities to face this challenge. Even though neuroscientists have identified a heterogeneous and distributed set of brain structures to be involved, a comprehensive theory about the biological and computational basis of such decision-making is yet to be formulated. We propose that the interaction between the medial prefrontal cortex (a part of the frontal lobes) and the subcortical nuclei releasing catecholaminergic neuromodulators will be key to such a theory. We argue that this interaction allows both the selection of optimal behaviour and, more importantly, the optimal modulation of the very brain circuits that drive such behavioral selection (i.e., meta-learning). We implemented this theory in a novel neuro-computational model, the Reinforcement Meta-Learner (RML). By means of computer simulations we showed that the RML provides a biological and computational account for a set of neuroscientific data with unprecedented scope, thereby suggesting a critical mechanism of decision-making in the mammalian brain.

Effects of transcranial direct current stimulation for treating depression: A modeling study

BACKGROUND

Transcranial direct current stimulation (tDCS) above the left dorsolateral prefrontal cortex (lDLPFC) has been widely used to improve symptoms of major depressive disorder (MDD). However, the effects of different stimulation protocols in the entire frontal lobe have not been investigated in a large sample including patient data.

METHODS

We used 38 head models created from structural magnetic resonance imaging data of 19 healthy adults and 19 MDD patients and applied computational modeling to simulate the spatial distribution of tDCS-induced electric fields (EFs) in 20 frontal regions. We evaluated effects of seven bipolar and two multi-electrode 4 × 1 tDCS protocols.

RESULTS

For bipolar montages, EFs were of comparable strength in the lDLPFC and in the medial prefrontal cortex (MPFC). Depending on stimulation parameters, EF cortical maps varied to a considerable degree, but were found to be similar in controls and patients. 4 × 1 montages produced more localized, albeit weaker effects.

LIMITATIONS

White matter anisotropy was not modeled. The relationship between EF strength and clinical response to tDCS could not be evaluated.

CONCLUSIONS

In addition to lDLPFC stimulation, excitability changes in the MPFC should also be considered as a potential mechanism underlying clinical efficacy of bipolar montages. MDD-associated anatomical variations are not likely to substantially influence current flow. Individual modeling of tDCS protocols can substantially improve cortical targeting. We make recommendations for future research to explicitly test the contribution of lDLPFC vs. MPFC stimulation to therapeutic outcomes of tDCS in this disorder.

Human midcingulate cortex encodes distributed representations of task progress

The function of midcingulate cortex (MCC) remains elusive despite decades of investigation and debate. Complicating matters, individual MCC neurons respond to highly diverse task-related events, and MCC activation is reported in most human neuroimaging studies employing a wide variety of task manipulations. Here we investigate this issue by applying a model-based cognitive neuroscience approach involving neural network simulations, functional magnetic resonance imaging, and representational similarity analysis. We demonstrate that human MCC encodes distributed, dynamically evolving representations of extended, goal-directed action sequences. These representations are uniquely sensitive to the stage and identity of each sequence, indicating that MCC sustains contextual information necessary for discriminating between task states. These results suggest that standard univariate approaches for analyzing MCC function overlook the major portion of task-related information encoded by this brain area and point to promising new avenues for investigation.

Dorsal Anterior Cingulate Cortices Differentially Lateralize Prediction Errors and Outcome Valence in a Decision-Making Task

The dorsal anterior cingulate cortex (dACC) is proposed to facilitate learning by signaling mismatches between the expected outcome of decisions and the actual outcomes in the form of prediction errors. The dACC is also proposed to discriminate outcome valence-whether a result has positive (either expected or desirable) or negative (either unexpected or undesirable) value. However, direct electrophysiological recordings from human dACC to validate these separate, but integrated, dimensions have not been previously performed. We hypothesized that local field potentials (LFPs) would reveal changes in the dACC related to prediction error and valence and used the unique opportunity offered by deep brain stimulation (DBS) surgery in the dACC of three human subjects to test this hypothesis. We used a cognitive task that involved the presentation of object pairs, a motor response, and audiovisual feedback to guide future object selection choices. The dACC displayed distinctly lateralized theta frequency (3-8 Hz) event-related potential responses-the left hemisphere dACC signaled outcome valence and prediction errors while the right hemisphere dACC was involved in prediction formation. Multivariate analyses provided evidence that the human dACC response to decision outcomes reflects two spatiotemporally distinct early and late systems that are consistent with both our lateralized electrophysiological results and the involvement of the theta frequency oscillatory activity in dACC cognitive processing. Further findings suggested that dACC does not respond to other phases of action-outcome-feedback tasks such as the motor response which supports the notion that dACC primarily signals information that is crucial for behavioral monitoring and not for motor control.

Hierarchical Active Inference: A Theory of Motivated Control

Motivated control refers to the coordination of behaviour to achieve affectively valenced outcomes or goals. The study of motivated control traditionally assumes a distinction between control and motivational processes, which map to distinct (dorsolateral versus ventromedial) brain systems. However, the respective roles and interactions between these processes remain controversial. We offer a novel perspective that casts control and motivational processes as complementary aspects - goal propagation and prioritization, respectively - of active inference and hierarchical goal processing under deep generative models. We propose that the control hierarchy propagates prior preferences or goals, but their precision is informed by the motivational context, inferred at different levels of the motivational hierarchy. The ensuing integration of control and motivational processes underwrites action and policy selection and, ultimately, motivated behaviour, by enabling deep inference to prioritize goals in a context-sensitive way.

Probing the role of the vestibular system in motivation and reward-based attention

The vestibular system has widespread connections in the central nervous system. Several activation loci following vestibular stimulations have been notably reported in deep, limbic areas that are otherwise difficult to reach and modulate in healthy subjects. Following preliminary evidence, suggesting that such stimulations might affect mood and affective processing, we wondered whether the vestibular system is also involved in motivation. Evolutionary accounts suggest that visuo-vestibular mismatches might have a role in preventing the search for and exploitation of goods that previously resulted in aversive reactions, as they would be a fine warning signal which follows the contact with or ingestion of noxious neurotoxins. The first question was thus whether vestibular stimulation alters sensitivity to reward. Secondly, we sought to assess whether attention is allocated in space differently when cued by highly motivational stimuli, and if this interplay is further modulated by the vestibular system. In order to evaluate both motivational and attentional assets, we administered a Posner-like cueing task to 30 healthy subjects concurrently receiving sham or galvanic vestibular stimulation (GVS; Left-Anodal and Right-Anodal configurations). The participants had to discriminate targets appearing in either exogenously cued or uncued locations (50% validity); cues predicted the amount of points (0, 2, or 10) and thus money that they could earn for a correct response. The results highlight a robust inhibition of return (IOR) (faster responses for invalidly-cued targets) which was not modulated by different levels of reward or GVS. Across all stimulation sessions, rewards exerted a powerful beneficial effect over performance: reaction times were faster when rewards were at stake. However, this effect was largest in sham, but greatly reduced in GVS conditions, most notably with the Right-Anodal configuration. This is the first evidence for a decreased sensitivity to rewards causally induced by a perturbation of the vestibular system. While future studies will shed light on its neural underpinnings and clinical implications, here we argue that GVS could be a safe and promising way to enrich our understanding of reward processes and eventually tackle the management of patients with aberrant sensitivity to rewards.

Distinct Roles for the Anterior Cingulate and Dorsolateral Prefrontal Cortices During Conflict Between Abstract Rules

Distinct patterns of activity within the anterior cingulate cortex (ACC) and dorsolateral prefrontal cortex (dlPFC) reported in neuroimaging studies during tasks involving conflict between competing responses have often been cited as evidence for their key contributions to conflict-monitoring and behavioral adaptation, respectively. However, supporting evidence from neuropsychological patients has been scarce and contradictory. We administered a well-studied analog of the Wisconsin Card Sorting Test, designed to elicit conflict between 2 abstract rules, to a cohort of 6 patients with damage to ACC or dlPFC. Patients who had sustained more significant damage to the ACC were not impaired either on a measure of "conflict cost" nor on measures of "conflict-induced behavioral adaptation." In contrast, damage to dlPFC did not affect the conflict cost measure but abolished the patients' ability to adapt their behavior following exposure to conflict, compared with controls. This pattern of results complements the findings from nonhuman primates with more circumscribed lesions to ACC or dlPFC on the same task and provides converging evidence that ACC is not necessary for performance when conflict is elicited between 2 abstract rules, whereas dlPFC plays a fundamental role in behavioral adaptation.

The impact of traumatic stress on Pavlovian biases

BACKGROUND

Disturbances in Pavlovian valuation systems are reported to follow traumatic stress exposure. However, motivated decisions are also guided by instrumental mechanisms, but to date the effect of traumatic stress on these instrumental systems remain poorly investigated. Here, we examine whether a single episode of severe traumatic stress influences flexible instrumental decisions through an impact on a Pavlovian system.

METHODS

Twenty-six survivors of the 2011 Norwegian terror attack and 30 matched control subjects performed an instrumental learning task in which Pavlovian and instrumental associations promoted congruent or conflicting responses. We used reinforcement learning models to infer how traumatic stress affected learning and decision-making. Based on the importance of dorsal anterior cingulate cortex (dACC) for cognitive control, we also investigated if individual concentrations of Glx (=glutamate + glutamine) in dACC predicted the Pavlovian bias of choice.

RESULTS

Survivors of traumatic stress expressed a greater Pavlovian interference with instrumental action selection and had significantly lower levels of Glx in the dACC. Across subjects, the degree of Pavlovian interference was negatively associated with dACC Glx concentrations.

CONCLUSIONS

Experiencing traumatic stress appears to render instrumental decisions less flexible by increasing the susceptibility to Pavlovian influences. An observed association between prefrontal glutamatergic levels and this Pavlovian bias provides novel insight into the neurochemical basis of decision-making, and suggests a mechanism by which traumatic stress can impair flexible instrumental behaviours.

Affective-associative two-process theory: a neurocomputational account of partial reinforcement extinction effects

The partial reinforcement extinction effect (PREE) is an experimentally established phenomenon: behavioural response to a given stimulus is more persistent when previously inconsistently rewarded than when consistently rewarded. This phenomenon is, however, controversial in animal/human learning theory. Contradictory findings exist regarding when the PREE occurs. One body of research has found a within-subjects PREE, while another has found a within-subjects reversed PREE (RPREE). These opposing findings constitute what is considered the most important problem of PREE for theoreticians to explain. Here, we provide a neurocomputational account of the PREE, which helps to reconcile these seemingly contradictory findings of within-subjects experimental conditions. The performance of our model demonstrates how omission expectancy, learned according to low probability reward, comes to control response choice following discontinuation of reward presentation (extinction). We find that a PREE will occur when multiple responses become controlled by omission expectation in extinction, but not when only one omission-mediated response is available. Our model exploits the affective states of reward acquisition and reward omission expectancy in order to differentially classify stimuli and differentially mediate response choice. We demonstrate that stimulus-response (retrospective) and stimulus-expectation-response (prospective) routes are required to provide a necessary and sufficient explanation of the PREE versus RPREE data and that Omission representation is key for explaining the nonlinear nature of extinction data.

Why do we fall into sync with others? Interpersonal synchronization and the brain's optimization principle

Spontaneous interpersonal synchronization of rhythmic behavior such as gait or hand clapping is a ubiquitous phenomenon in human interactions, and is potentially important for social relationships and action understanding. Although several authors have suggested a role of the mirror neuron system in interpersonal coupling, the underlying brain mechanisms are not well understood. Here we argue that more general theories of neural computations, namely predictive coding and the Free Energy Principle, could explain interpersonal coordination dynamics. Each brain minimizes coding costs by reducing the mismatch between the representations of observed and own motor behavior. Continuous mutual prediction and alignment result in an overall minimization of free energy, thus forming a stable attractor state.

Interplay of prefrontal cortex and amygdala during extinction of drug seeking

Extinction of Pavlovian conditioning is a complex process that involves brain regions such as the medial prefrontal cortex (mPFC), the amygdala and the locus coeruleus. In particular, noradrenaline (NA) coming from the locus coeruleus has been recently shown to play a different role in two subregions of the mPFC, the prelimbic (PL) and the infralimbic (IL) regions. How these regions interact in conditioning and subsequent extinction is an open issue. We studied these processes using two approaches: computational modelling and NA manipulation in a conditioned place preference paradigm (CPP) in mice. In the computational model, NA in PL and IL causes inputs arriving to these regions to be amplified, thus allowing them to modulate learning processes in amygdala. The model reproduces results from studies involving depletion of NA from PL, IL, or both in CPP. In addition, we simulated new experiments of NA manipulations in mPFC, making predictions on the possible results. We searched the parameters of the model and tested the robustness of the predictions by performing a sensitivity analysis. We also present an empirical experiment where, in accord with the model, a double depletion of NA from both PL and IL in CPP with amphetamine impairs extinction. Overall the proposed model, supported by anatomical, physiological, and behavioural data, explains the differential role of NA in PL and IL and opens up the possibility to understand extinction mechanisms more in depth and hence to aid the development of treatments for disorders such as addiction.

Auditory conflict and congruence in frontotemporal dementia

Impaired analysis of signal conflict and congruence may contribute to diverse socio-emotional symptoms in frontotemporal dementias, however the underlying mechanisms have not been defined. Here we addressed this issue in patients with behavioural variant frontotemporal dementia (bvFTD; n = 19) and semantic dementia (SD; n = 10) relative to healthy older individuals (n = 20). We created auditory scenes in which semantic and emotional congruity of constituent sounds were independently probed; associated tasks controlled for auditory perceptual similarity, scene parsing and semantic competence. Neuroanatomical correlates of auditory congruity processing were assessed using voxel-based morphometry. Relative to healthy controls, both the bvFTD and SD groups had impaired semantic and emotional congruity processing (after taking auditory control task performance into account) and reduced affective integration of sounds into scenes. Grey matter correlates of auditory semantic congruity processing were identified in distributed regions encompassing prefrontal, parieto-temporal and insular areas and correlates of auditory emotional congruity in partly overlapping temporal, insular and striatal regions. Our findings suggest that decoding of auditory signal relatedness may probe a generic cognitive mechanism and neural architecture underpinning frontotemporal dementia syndromes.

The Anterior Cingulate Gyrus and Social Cognition: Tracking the Motivation of Others

The anterior cingulate cortex (ACC) is implicated in a broad range of behaviors and cognitive processes, but it has been unclear what contribution, if any, the ACC makes to social behavior. We argue that anatomical and functional evidence suggests that a specific sub-region of ACC-in the gyrus (ACCg)-plays a crucial role in processing social information. We propose that the computational properties of the ACCg support a contribution to social cognition by estimating how motivated other individuals are and dynamically updating those estimates when further evidence suggests they have been erroneous. Notably this model, based on vicarious motivation and error processing, provides a unified account of neurophysiological and neuroimaging evidence that the ACCg is sensitive to costs, benefits, and errors during social interactions. Furthermore, it makes specific, testable predictions about a key mechanism that may underpin variability in socio-cognitive abilities in health and disease.