The cerebellum contributes to context-effects during fear extinction learning: a 7T fMRI study

An externally validated resting-state brain connectivity signature of pain-related learning

Pain can be conceptualized as a precision signal for reinforcement learning in the brain and alterations in these processes are a hallmark of chronic pain conditions. Investigating individual differences in pain-related learning therefore holds important clinical and translational relevance. Here, we developed and externally validated a novel resting-state brain connectivity-based predictive model of pain-related learning. The pre-registered external validation indicates that the proposed model explains 8-12% of the inter-individual variance in pain-related learning. Model predictions are driven by connections of the amygdala, posterior insula, sensorimotor, frontoparietal, and cerebellar regions, outlining a network commonly described in aversive learning and pain. We propose the resulting model as a robust and highly accessible biomarker candidate for clinical and translational pain research, with promising implications for personalized treatment approaches and with a high potential to advance our understanding of the neural mechanisms of pain-related learning.

The impact of the left inferior frontal gyrus on fear extinction: A transcranial direct current stimulation study

INTRODUCTION

Fear extinction is a fundamental component of exposure-based therapies for anxiety-related disorders. The renewal of fear in a different context after extinction highlights the importance of contextual factors. In this study, we aimed to investigate the causal role of the left inferior frontal gyrus (LiFG) in the context-dependency of fear extinction learning via administration of transcranial direct current stimulation (tDCS) over this area.

METHODS

180 healthy subjects were assigned to 9 groups: 3 tDCS conditions (anodal, cathodal, and sham) × 3 context combinations (AAA, ABA, and ABB). The fear conditioning/extinction task was conducted over three consecutive days: acquisition, extinction learning, and extinction recall. tDCS (2 mA, 10min) was administered during the extinction learning phase over the LiFG via a 4-electrode montage. Skin conductance response (SCR) data and self-report assessments were collected.

RESULTS

During the extinction learning phase, groups with excitability-enhancing anodal tDCS showed a significantly higher fear response to the threat cues compared to cathodal and sham stimulation conditions, irrespective of contextual factors. This effect was stable until the extinction recall phase. Additionally, excitability-reducing cathodal tDCS caused a significant decrease of the response difference between the threat and safety cues during the extinction recall phase. The self-report assessments showed no significant differences between the conditions throughout the experiment.

CONCLUSION

Independent of the context, excitability enhancement of the LiFG did impair fear extinction, and led to preservation of fear memory. In contrast, excitability reduction of this area enhanced fear extinction retention. These findings imply that the LiFG plays a role in the fear extinction network, which seems to be however context-independent.

Renewal in human fear conditioning: A systematic review and meta-analysis

Renewal is a 'return of fear' manipulation in human fear conditioning to investigate learning processes underlying anxiety and trauma. Even though renewal paradigms are widely used, no study has compared the strength of different renewal paradigms. We conduct a systematic review (N = 80) and meta-analysis (N = 23) of human fear conditioning studies assessing renewal. Our analysis shows that the classic ABA design is the most effective paradigm, compared to ABC and ABBA designs. We present evidence that conducting extinction in multiple contexts and increasing the similarity between acquisition and extinction contexts reduce renewal. Furthermore, we show that additional cues can be used as safety and 'protection from extinction' cues. The review shows that alcohol weakens the extinction process and that older adults appear less sensitive to context changes and thus show less renewal. The large variability in approaches to study renewal in humans suggests that standardisation of fear conditioning procedures across laboratories would be of great benefit to the field.

Extinction of negative conditioned stimulus valence in human fear conditioning

Fear conditioning is a common experimental paradigm for modelling the development, and exposure-based treatment, of anxiety disorders. Measures of fear such as threat-expectancy, physiological arousal, and fear ratings typically extinguish, however feared stimuli may still be evaluated negatively (i.e. retain negative valence). This systematic review provides the first investigation of the relationship between fear conditioning methodology and extinction of negative stimulus valence. Principal findings were that type of CS (conditioned stimulus) and the CS-US pairing (i.e. specific combination of CS and unconditioned stimulus) predicted extinction outcome. Extinction of absolute negative CS valence was always achieved with shape CSs; often achieved with low fear-relevant animals as CSs, and less frequently achieved with faces as CSs - particularly neutral faces paired with a shock US. Modified extinction procedures typically achieved the same outcome as standard extinction procedures, except for partially-reinforced extinction, which was less effective than standard extinction, and positive imagery training, which was more effective than standard extinction. Further studies are warranted to evaluate the influence of fear conditioning methodology on extinction of absolute negative CS valence.

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Mild Deficits in Fear Learning: Evidence from Humans and Mice with Cerebellar Cortical Degeneration

Functional brain imaging studies in humans suggest involvement of the cerebellum in fear conditioning but do not allow conclusions about the functional significance. The main aim of the present study was to examine whether patients with cerebellar degeneration show impaired fear conditioning and whether this is accompanied by alterations in cerebellar cortical activations. To this end, a 2 d differential fear conditioning study was conducted in 20 cerebellar patients and 21 control subjects using a 7 tesla (7 T) MRI system. Fear acquisition and extinction training were performed on day 1, followed by recall on day 2. Cerebellar patients learned to differentiate between the CS+ and CS-. Acquisition and consolidation of learned fear, however, was slowed. Additionally, extinction learning appeared to be delayed. The fMRI signal was reduced in relation to the prediction of the aversive stimulus and altered in relation to its unexpected omission. Similarly, mice with cerebellar cortical degeneration (spinocerebellar ataxia type 6, SCA6) were able to learn the fear association, but retrieval of fear memory was reduced. In sum, cerebellar cortical degeneration led to mild abnormalities in the acquisition of learned fear responses in both humans and mice, particularly manifesting postacquisition training. Future research is warranted to investigate the basis of altered fMRI signals related to fear learning.

Absence of modulatory effects of 6Hz cerebellar transcranial alternating current stimulation on fear learning in men

Fear is a vital defense mechanism to potential threats, which is influenced by the cerebellum. While the cerebellum's role in acquiring fear responses is well understood, limited knowledge exists about its involvement in fear extinction. In this study, we investigated the effects of cerebellar theta band transcranial alternating current stimulation (ctACS) administered during fear extinction training, based on previous evidence from animal studies suggesting a role of cerebellar theta oscillations in associative memory formation. To this end, thirty-seven healthy right-handed male participants were recruited for a two-day differential fear renewal paradigm. On day 1, they underwent acquisition training in context A followed by extinction training in context B. On day 2, recall was tested in contexts A and B. One group of participants received ctACS in the theta band (6 Hz) during extinction training. The other group received sham ctACS. Although both groups demonstrated the ability to recall previously learned fear and distinguish between low and high threat stimuli, no significant differences were observed between the ctACS and sham groups, indicating that ctACS at this theta frequency range did not impact extinction and recall of previously acquired fear in this study. Nevertheless, using ctACS could still be useful in future research, including brain imaging studies, to better understand how the cerebellum is involved in fear and extinction processes.

Frontopolar multifocal transcranial direct current stimulation reduces conditioned fear reactivity during extinction training: A pilot randomized controlled trial

Exposure-based therapies for anxiety and related disorders are believed to depend on fear extinction learning and corresponding changes in extinction circuitry. Frontopolar multifocal transcranial direct current stimulation (tDCS) has been shown to improve therapeutic safety learning during in vivo exposure and may modulate functional connectivity of networks implicated in fear processing and inhibition. A pilot randomized controlled trial was completed to determine the effects of frontopolar tDCS on extinction learning and memory. Community volunteers (n = 35) completed a 3-day fear extinction paradigm with measurement of electrodermal activity. Participants were randomized (single-blind) to 20-min of sham (n = 17, 30 s. ramp in/out) or active (n = 18) frontopolar (anode over Fpz, 10-10 EEG) multifocal tDCS (20-min, 1.5 mA) prior to extinction training. Mixed ANOVAs revealed a significant group*trial effect on skin conductance response (SCR) to the conditioned stimulus (CS + ) during extinction training (p = 0.007, Cohen's d = 0.55). The effects of frontopolar tDCS were greatest during the first two extinction trials, suggesting that tDCS may have promoted fear inhibition prior to safety learning. Return of fear to the CS + during tests were comparable across conditions (ps > 0.50). These findings suggest that frontopolar tDCS may modulate the processing of threat cues and associated circuitry or promote the inhibition of fear. This has clear implications for the treatment of anxiety and related disorders with therapeutic exposure.

Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach

The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with -90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either -90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability.

Fear conditioning is preserved in very preterm-born young adults despite increased anxiety levels

Very preterm birth is associated with an increased risk for anxiety disorders. Abnormal brain development may result in disordered fear learning processes, which may be exacerbated by environmental risk factors and persist in adulthood. We tested the hypotheses that very preterm-born young adults displayed higher levels of fear conditioning, less differentiation between threat (CS+) and safety (CS-) signals, and stronger resistance to extinction relative to term-born controls. A group of 37 very preterm-born young adults and 31 age- and sex-matched term-born controls performed a differential fear conditioning paradigm on two consecutive days. Acquisition and extinction training were performed on day 1. Recall and reinstatement were tested on day 2. Preterm-born participants showed significantly higher levels of anxiety in the Depression-Anxiety-Stress-Scale-21 questionnaire. The fear conditioning outcome measures, skin conductance response amplitudes and anxiety ratings, were overall higher in the preterm-born group compared to controls. Awareness of CS-US contingencies was mildly reduced in preterms. Acquisition, extinction, recall and reinstatement of differential conditioned fear responses (CS+  > CS-), however, were not significantly different between the groups. There were no significant group by stimulus type interactions. The finding of largely preserved associative fear learning in very preterm-born young adults was unexpected and needs to be confirmed in future studies.

The Computational and Neural Bases of Context-Dependent Learning

Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these processes have been intensively studied, recent advances in computational modeling revealed a key challenge in context-dependent learning that had been largely ignored previously: Under naturalistic conditions, context is typically uncertain, necessitating contextual inference. We review a theoretical approach to formalizing context-dependent learning in the face of contextual uncertainty and the core computations it requires. We show how this approach begins to organize a large body of disparate experimental observations, from multiple levels of brain organization (including circuits, systems, and behavior) and multiple brain regions (most prominently the prefrontal cortex, the hippocampus, and motor cortices), into a coherent framework. We argue that contextual inference may also be key to understanding continual learning in the brain. This theory-driven perspective places contextual inference as a core component of learning.

A neuro-computational social learning framework to facilitate transdiagnostic classification and treatment across psychiatric disorders

Social deficits are among the core and most striking psychiatric symptoms, present in most psychiatric disorders. Here, we introduce a novel social learning framework, which consists of neuro-computational models that combine reinforcement learning with various types of social knowledge structures. We outline how this social learning framework can help specify and quantify social psychopathology across disorders and provide an overview of the brain regions that may be involved in this type of social learning. We highlight how this framework can specify commonalities and differences in the social psychopathology of individuals with autism spectrum disorder (ASD), personality disorders (PD), and major depressive disorder (MDD) and improve treatments on an individual basis. We conjecture that individuals with psychiatric disorders rely on rigid social knowledge representations when learning about others, albeit the nature of their rigidity and the behavioral consequences can greatly differ. While non-clinical cohorts tend to efficiently adapt social knowledge representations to relevant environmental constraints, psychiatric cohorts may rigidly stick to their preconceived notions or overly coarse knowledge representations during learning.

The cerebellum and fear extinction: evidence from rodent and human studies

The role of the cerebellum in emotional control has gained increasing interest, with studies showing it is involved in fear learning and memory in both humans and rodents. This review will focus on the contributions of the cerebellum to the extinction of learned fear responses. Extinction of fearful memories is critical for adaptive behaviour, and is clinically relevant to anxiety disorders such as post-traumatic stress disorder, in which deficits in extinction processes are thought to occur. We present evidence that supports cerebellar involvement in fear extinction, from rodent studies that investigate molecular mechanisms and functional connectivity with other brain regions of the known fear extinction network, to fMRI studies in humans. This evidence is considered in relation to the theoretical framework that the cerebellum is involved in the formation and updating of internal models of the inner and outer world by detecting errors between predicted and actual outcomes. In the case of fear conditioning, these internal models are thought to predict the occurrence of an aversive unconditioned stimulus (US), and when the aversive US is unexpectedly omitted during extinction learning the cerebellum uses prediction errors to update the internal model. Differences between human and rodent studies are highlighted to help inform future work.

The cerebellum regulates fear extinction through thalamo-prefrontal cortex interactions in male mice

Fear extinction is a form of inhibitory learning that suppresses the expression of aversive memories and plays a key role in the recovery of anxiety and trauma-related disorders. Here, using male mice, we identify a cerebello-thalamo-cortical pathway regulating fear extinction. The cerebellar fastigial nucleus (FN) projects to the lateral subregion of the mediodorsal thalamic nucleus (MD), which is reciprocally connected with the dorsomedial prefrontal cortex (dmPFC). The inhibition of FN inputs to MD in male mice impairs fear extinction in animals with high fear responses and increases the bursting of MD neurons, a firing pattern known to prevent extinction learning. Indeed, this MD bursting is followed by high levels of the dmPFC 4 Hz oscillations causally associated with fear responses during fear extinction, and the inhibition of FN-MD neurons increases the coherence of MD bursts and oscillations with dmPFC 4 Hz oscillations. Overall, these findings reveal a regulation of fear-related thalamo-cortical dynamics by the cerebellum and its contribution to fear extinction.

CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning

Reinforcement learning (RL) has become a popular paradigm for modeling animal behavior, analyzing neuronal representations, and studying their emergence during learning. This development has been fueled by advances in understanding the role of RL in both the brain and artificial intelligence. However, while in machine learning a set of tools and standardized benchmarks facilitate the development of new methods and their comparison to existing ones, in neuroscience, the software infrastructure is much more fragmented. Even if sharing theoretical principles, computational studies rarely share software frameworks, thereby impeding the integration or comparison of different results. Machine learning tools are also difficult to port to computational neuroscience since the experimental requirements are usually not well aligned. To address these challenges we introduce CoBeL-RL, a closed-loop simulator of complex behavior and learning based on RL and deep neural networks. It provides a neuroscience-oriented framework for efficiently setting up and running simulations. CoBeL-RL offers a set of virtual environments, e.g., T-maze and Morris water maze, which can be simulated at different levels of abstraction, e.g., a simple gridworld or a 3D environment with complex visual stimuli, and set up using intuitive GUI tools. A range of RL algorithms, e.g., Dyna-Q and deep Q-network algorithms, is provided and can be easily extended. CoBeL-RL provides tools for monitoring and analyzing behavior and unit activity, and allows for fine-grained control of the simulation via interfaces to relevant points in its closed-loop. In summary, CoBeL-RL fills an important gap in the software toolbox of computational neuroscience.

Model-based experimental manipulation of probabilistic behavior in interpretable behavioral latent variable models

Introduction

Interpretable latent variable models that probabilistically link behavioral observations to an underlying latent process have increasingly been used to draw inferences on cognition from observed behavior. The latent process usually connects experimental variables to cognitive computation. While such models provide important insights into the latent processes generating behavior, one important aspect has often been overlooked. They may also be used to generate precise and falsifiable behavioral predictions as a function of the modeled experimental variables. In doing so, they pinpoint how experimental conditions must be designed to elicit desired behavior and generate adaptive experiments.

Methods

These ideas are exemplified on the process of delay discounting (DD). After inferring DD models from behavior on a typical DD task, the models are leveraged to generate a second adaptive DD task. Experimental trials in this task are designed to elicit 9 graded behavioral discounting probabilities across participants. Models are then validated and contrasted to competing models in the field by assessing the ouf-of-sample prediction error.

Results

The proposed framework induces discounting probabilities on nine levels. In contrast to several alternative models, the applied model exhibits high validity as indicated by a comparably low prediction error. We also report evidence for inter-individual differences with respect to the most suitable models underlying behavior. Finally, we outline how to adapt the proposed method to the investigation of other cognitive processes including reinforcement learning.

Discussion

Inducing graded behavioral frequencies with the proposed framework may help to highly resolve the underlying cognitive construct and associated neuronal substrates.

Neuroimaging of Fear Extinction

Extinguishing fear and defensive responses to environmental threats when they are no longer warranted is a critical learning ability that can promote healthy self-regulation and, ultimately, reduce susceptibility to or maintenance of affective-, trauma-, stressor-,and anxiety-related disorders. Neuroimaging tools provide an important means to uncover the neural mechanisms of effective extinction learning that, in turn, can abate the return of fear. Here I review the promises and pitfalls of functional neuroimaging as a method to investigate fear extinction circuitry in the healthy human brain. I discuss the extent to which neuroimaging has validated the core circuits implicated in rodent models and has expanded the scope of the brain regions implicated in extinction processes. Finally, I present new advances made possible by multivariate data analysis tools that yield more refined insights into the brain-behavior relationships involved.

A Model Guided Approach to Evoke Homogeneous Behavior During Temporal Reward and Loss Discounting

Background

The tendency to devaluate future options as a function of time, known as delay discounting, is associated with various factors such as psychiatric illness and personality. Under identical experimental conditions, individuals may therefore strongly differ in the degree to which they discount future options. In delay discounting tasks, this inter-individual variability inevitably results in an unequal number of discounted trials per subject, generating difficulties in linking delay discounting to psychophysiological and neural correlates. Many studies have therefore focused on assessing delay discounting adaptively. Here, we extend these approaches by developing an adaptive paradigm which aims at inducing more comparable and homogeneous discounting frequencies across participants on a dimensional scale.

Method

The proposed approach probabilistically links a (common) discounting function to behavior to obtain a probabilistic model, and then exploits the model to obtain a formal condition which defines how to construe experimental trials so as to induce any desired discounting probability. We first infer subject-level models on behavior on a non-adaptive delay discounting task and then use these models to generate adaptive trials designed to evoke graded relative discounting frequencies of 0.3, 0.5, and 0.7 in each participant. We further compare and evaluate common models in the field through out-of-sample prediction error estimates, to iteratively improve the trial-generating model and paradigm.

Results

The developed paradigm successfully increases discounting behavior during both reward and loss discounting. Moreover, it evokes graded relative choice frequencies in line with model-based expectations (i.e., 0.3, 0.5, and 0.7) suggesting that we can successfully homogenize behavior. Our model comparison analyses indicate that hyperboloid models are superior in predicting unseen discounting behavior to more conventional hyperbolic and exponential models. We report out-of-sample error estimates as well as commonalities and differences between reward and loss discounting, demonstrating for instance lower discounting rates, as well as differences in delay perception in loss discounting.

Conclusion

The present work proposes a model-based framework to evoke graded responses linked to cognitive function at a single subject level. Such a framework may be used in the future to measure cognitive functions on a dimensional rather than dichotomous scale.