Measuring human context fear conditioning and retention after consolidation.

Fear conditioning is a laboratory paradigm commonly used to investigate aversive learning and memory. In context fear conditioning, a configuration of elemental cues (conditioned stimulus [CTX]) predicts an aversive event (unconditioned stimulus [US]). To quantify context fear acquisition in humans, previous work has used startle eyeblink responses (SEBRs), skin conductance responses (SCRs), and verbal reports, but different quantification methods have rarely been compared. Moreover, preclinical intervention studies mandate recall tests several days after acquisition, and it is unclear how to induce and measure context fear memory retention over such a time interval. First, we used a semi-immersive virtual reality paradigm. In two experiments (N = 23 and N = 28), we found successful declarative learning and memory retention over 7 d but no evidence of other conditioned responses. Next, we used a configural fear conditioning paradigm with five static room images as CTXs in two experiments (N = 29 and N = 24). Besides successful declarative learning and memory retention after 7 d, SCR and pupil dilation in response to CTX onset differentiated CTX+/CTX- during acquisition training, and SEBR and pupil dilation differentiated CTX+/CTX- during the recall test, with medium to large effect sizes for the most sensitive indices (SEBR: Hedge's g = 0.56 and g = 0.69; pupil dilation: Hedge's g = 0.99 and g = 0.88). Our results demonstrate that with a configural learning paradigm, context fear memory retention can be demonstrated over 7 d, and we provide robust and replicable measurement methods to this end.

Dimensionality and optimal combination of autonomic fear-conditioning measures in humans.

Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.

Cross-species anxiety tests in psychiatry: pitfalls and promises.

Behavioural anxiety tests in non-human animals are used for anxiolytic drug discovery, and to investigate the neurobiology of threat avoidance. Over the past decade, several of them were translated to humans with three clinically relevant goals: to assess potential efficacy of candidate treatments in healthy humans; to develop diagnostic tests or biomarkers; and to elucidate the pathophysiology of anxiety disorders. In this review, we scrutinise these promises and compare seven anxiety tests that are validated across species: five approach-avoidance conflict tests, unpredictable shock anticipation, and the social intrusion test in children. Regarding the first goal, three tests appear suitable for anxiolytic drug screening in humans. However, they have not become part of the drug development pipeline and achieving this may require independent confirmation of predictive validity and cost-effectiveness. Secondly, two tests have shown potential to measure clinically relevant individual differences, but their psychometric properties, predictive value, and clinical applicability need to be clarified. Finally, cross-species research has not yet revealed new evidence that the physiology of healthy human behaviour in anxiety tests relates to the physiology of anxiety symptoms in patients. To summarise, cross-species anxiety tests could be rendered useful for drug screening and for development of diagnostic instruments. Using these tests for aetiology research in healthy humans or animals needs to be queried and may turn out to be unrealistic.

Immersive VR for investigating threat avoidance: The VRthreat toolkit for Unity.

All animals have to respond to immediate threats in order to survive. In non-human animals, a diversity of sophisticated behaviours has been observed, but research in humans is hampered by ethical considerations. Here, we present a novel immersive VR toolkit for the Unity engine that allows assessing threat-related behaviour in single, semi-interactive, and semi-realistic threat encounters. The toolkit contains a suite of fully modelled naturalistic environments, interactive objects, animated threats, and scripted systems. These are arranged together by the researcher as a means of creating an experimental manipulation, to form a series of independent "episodes" in immersive VR. Several specifically designed tools aid the design of these episodes, including a system to allow for pre-sequencing the movement plans of animal threats. Episodes can be built with the assets included in the toolkit, but also easily extended with custom scripts, threats, and environments if required. During the experiments, the software stores behavioural, movement, and eye tracking data. With this software, we aim to facilitate the use of immersive VR in human threat avoidance research and thus to close a gap in the understanding of human behaviour under threat.

Asymmetric representation of aversive prediction errors in Pavlovian threat conditioning.

Survival in biological environments requires learning associations between predictive sensory cues and threatening outcomes. Such aversive learning may be implemented through reinforcement learning algorithms that are driven by the signed difference between expected and encountered outcomes, termed prediction errors (PEs). While PE-based learning is well established for reward learning, the role of putative PE signals in aversive learning is less clear. Here, we used functional magnetic resonance imaging in humans (21 healthy men and women) to investigate the neural representation of PEs during maintenance of learned aversive associations. Four visual cues, each with a different probability (0, 33, 66, 100%) of being followed by an aversive outcome (electric shock), were repeatedly presented to participants. We found that neural activity at omission (US-) but not occurrence of the aversive outcome (US+) encoded PEs in the medial prefrontal cortex. More expected omission of aversive outcome was associated with lower neural activity. No neural signals fulfilled axiomatic criteria, which specify necessary and sufficient components of PE signals, for signed PE representation in a whole-brain search or in a-priori regions of interest. Our results might suggest that, different from reward learning, aversive learning does not involve signed PE signals that are represented within the same brain region for all conditions.

Algorithms for survival: a comparative perspective on emotions.

The nature and neural implementation of emotions is the subject of vigorous debate. Here, we use Bayesian decision theory to address key complexities in this field and conceptualize emotions in terms of their relationship to survival-relevant behavioural choices. Decision theory indicates which behaviours are optimal in a given situation; however, the calculations required are radically intractable. We therefore conjecture that the brain uses a range of pre-programmed algorithms that provide approximate solutions. These solutions seem to produce specific behavioural manifestations of emotions and can also be associated with core affective dimensions. We identify principles according to which these algorithms are implemented in the brain and illustrate our approach by considering decision making in the face of proximal threat.

Evidence for a minimal role of stimulus awareness in reversal of threat learning.

In an ever-changing environment, survival depends on learning which stimuli represent threat, and also on updating such associations when circumstances shift. It has been claimed that humans can acquire physiological responses to threat-associated stimuli even when they are unaware of them, but the role of awareness in updating threat contingencies remains unknown. This complex process-generating novel responses while suppressing learned ones-relies on distinct neural mechanisms from initial learning, and has only been shown with awareness. Can it occur unconsciously? Here, we present evidence that threat reversal may not require awareness. Participants underwent classical threat conditioning to visual stimuli that were suppressed from awareness. One of two images was paired with an electric shock; halfway through the experiment, contingencies were reversed and the shock was paired with the other image. Despite variations in suppression across participants, we found that physiological responses reflected changes in stimulus-threat pairings independently of stimulus awareness. These findings suggest that unconscious affective processing may be sufficiently flexible to adapt to changing circumstances.

Hippocampal Representation of Threat Features and Behavior in a Human Approach-Avoidance Conflict Anxiety Task.

Decisions under threat are crucial to survival and require integration of distinct situational features, such as threat probability and magnitude. Recent evidence from human lesion and neuroimaging studies implicated anterior hippocampus (aHC) and amygdala in approach-avoidance decisions under threat, and linked their integrity to cautious behavior. Here we sought to elucidate how threat dimensions and behavior are represented in these structures. Twenty human participants (11 female) completed an approach-avoidance conflict task during high-resolution fMRI. Participants could gather tokens under threat of capture by a virtual predator, which would lead to token loss. Threat probability (predator wake-up rate) and magnitude (amount of token loss) varied on each trial. To disentangle effects of threat features, and ensuing behavior, we performed a multifold parametric analysis. We found that high threat probability and magnitude related to BOLD signal in left aHC/entorhinal cortex. However, BOLD signal in this region was better explained by avoidance behavior than by these threat features. A priori ROI analysis confirmed the relation of aHC BOLD response with avoidance. Exploratory subfield analysis revealed that this relation was specific to anterior CA2/3 but not CA1. Left lateral amygdala responded to low and high, but not intermediate, threat probability. Our results suggest that aHC BOLD signal is better explained by avoidance behavior than by threat features in approach-avoidance conflict. Rather than representing threat features in a monotonic manner, it appears that aHC may compute approach-avoidance decisions based on integration of situational threat features represented in other neural structures.SIGNIFICANCE STATEMENT An effective threat anticipation system is crucial to survival across species. Natural threats, however, are diverse and have distinct features. To be able to adapt to different modes of danger, the brain needs to recognize these features, integrate them, and use them to modify behavior. Our results disclose the human anterior hippocampus as a likely arbiter of approach-avoidance decisions harnessing compound environmental information while partially replicating previous findings and blending into recent efforts to illuminate the neural basis of approach-avoidance conflict in humans.

Model of theta frequency perturbations and contextual fear memory.

Theta oscillations in the hippocampal local field potential (LFP) appear during translational movement and arousal, modulate the activity of principal cells, and are associated with spatial cognition and episodic memory function. All known anxiolytics slightly but consistently reduce hippocampal theta frequency. However, whether this electrophysiological effect is mechanistically related to the decreased behavioral expression of anxiety is currently unclear. Here, we propose that a reduction in theta frequency affects synaptic plasticity and mnemonic function and that this can explain the reduction in anxiety behavior. We test this hypothesis in a biophysical model of contextual fear conditioning. First, we confirm that our model reproduces previous empirical results regarding the dependence of synaptic plasticity on presynaptic firing rate. Next, we investigate how theta frequency during contextual conditioning impacts learning. These simulations demonstrate that learned associations between threat and context are attenuated when learning takes place under reduced theta frequency. Additionally, our simulations demonstrate that learned associations result in increased theta activity in the amygdala, consistent with empirical data. In summary, we propose a mechanism that can account for the behavioral effect of anxiolytics by impairing the integration of threat attributes of an environment into the cognitive map due to reduced synaptic potentiation.

Computational optimization of associative learning experiments.

With computational biology striving to provide more accurate theoretical accounts of biological systems, use of increasingly complex computational models seems inevitable. However, this trend engenders a challenge of optimal experimental design: due to the flexibility of complex models, it is difficult to intuitively design experiments that will efficiently expose differences between candidate models or allow accurate estimation of their parameters. This challenge is well exemplified in associative learning research. Associative learning theory has a rich tradition of computational modeling, resulting in a growing space of increasingly complex models, which in turn renders manual design of informative experiments difficult. Here we propose a novel method for computational optimization of associative learning experiments. We first formalize associative learning experiments using a low number of tunable design variables, to make optimization tractable. Next, we combine simulation-based Bayesian experimental design with Bayesian optimization to arrive at a flexible method of tuning design variables. Finally, we validate the proposed method through extensive simulations covering both the objectives of accurate parameter estimation and model selection. The validation results show that computationally optimized experimental designs have the potential to substantially improve upon manual designs drawn from the literature, even when prior information guiding the optimization is scarce. Computational optimization of experiments may help address recent concerns over reproducibility by increasing the expected utility of studies, and it may even incentivize practices such as study pre-registration, since optimization requires a pre-specified analysis plan. Moreover, design optimization has the potential not only to improve basic research in domains such as associative learning, but also to play an important role in translational research. For example, design of behavioral and physiological diagnostic tests in the nascent field of computational psychiatry could benefit from an optimization-based approach, similar to the one presented here.

Impact of a reminder/extinction procedure on threat-conditioned pupil size and skin conductance responses.

A reminder can render consolidated memory labile and susceptible to amnesic agents during a reconsolidation window. For the case of threat memory (also termed fear memory), it has been suggested that extinction training during this reconsolidation window has the same disruptive impact. This procedure could provide a powerful therapeutic principle for treatment of unwanted aversive memories. However, human research yielded contradictory results. Notably, all published positive replications quantified threat memory by conditioned skin conductance responses (SCR). Yet, other studies measuring SCR and/or fear-potentiated startle failed to observe an effect of a reminder/extinction procedure on the return of fear. Here we sought to shed light on this discrepancy by using a different autonomic response, namely, conditioned pupil dilation, in addition to SCR, in a replication of the original human study. N = 71 humans underwent a 3-d threat conditioning, reminder/extinction, and reinstatement, procedure with 2 CS+, of which one was reminded. Participants successfully learned the threat association on day 1, extinguished conditioned responding on day 2, and showed reinstatement on day 3. However, there was no difference in conditioned responding between the reminded and the nonreminded CS, neither in pupil size nor SCR. Thus, we found no evidence that a reminder trial before extinction prevents the return of threat-conditioned responding.

Saccadic scanpath length: an index for human threat conditioning.

Threat-conditioned cues are thought to capture overt attention in a bottom-up process. Quantification of this phenomenon typically relies on cue competition paradigms. Here, we sought to exploit gaze patterns during exclusive presentation of a visual conditioned stimulus, in order to quantify human threat conditioning. To this end, we capitalized on a summary statistic of visual search during CS presentation, scanpath length. During a simple delayed threat conditioning paradigm with full-screen monochrome conditioned stimuli (CS), we observed shorter scanpath length during CS+ compared to CS- presentation. Retrodictive validity, i.e., effect size to distinguish CS+ and CS-, was maximized by considering a 2-s time window before US onset. Taking into account the shape of the scan speed response resulted in similar retrodictive validity. The mechanism underlying shorter scanpath length appeared to be longer fixation duration and more fixation on the screen center during CS+ relative to CS- presentation. These findings were replicated in a second experiment with similar setup, and further confirmed in a third experiment using full-screen patterns as CS. This experiment included an extinction session during which scanpath differences appeared to extinguish. In a fourth experiment with auditory CS and instruction to fixate screen center, no scanpath length differences were observed. In conclusion, our study suggests scanpath length as a visual search summary statistic, which may be used as complementary measure to quantify threat conditioning with retrodictive validity similar to that of skin conductance responses.

Disentangling Hippocampal and Amygdala Contribution to Human Anxiety-Like Behavior.

Anxiety comprises a suite of behaviors to deal with potential threat and is often modeled in approach-avoidance conflict tasks. Collectively, these tests constitute a predominant preclinical model of anxiety disorder. A body of evidence suggests that both ventral hippocampus and amygdala lesions impair anxiety-like behavior, but the relative contribution of these two structures is unclear. A possible reason is that approach-avoidance conflict tasks involve a series of decisions and actions, which may be controlled by distinct neural mechanisms that are difficult to disentangle from behavioral readouts. Here, we capitalize on a human approach-avoidance conflict test, implemented as computer game, that separately measures several action components. We investigate three patients of both sexes with unspecific unilateral medial temporal lobe (MTL) damage, one male with selective bilateral hippocampal (HC), and one female with selective bilateral amygdala lesions, and compare them to matched controls. MTL and selective HC lesions, but not selective amygdala lesions, increased approach decision when possible loss was high. In contrast, MTL and selective amygdala lesions, but not selective HC lesions, increased return latency. Additionally, selective HC and selective amygdala lesions reduced approach latency. In a task targeted at revealing subjective assumptions about the structure of the computer game, MTL and selective HC lesions impacted on reaction time generation but not on the subjective task structure. We conclude that deciding to approach reward under threat relies on hippocampus but not amygdala, whereas vigor of returning to safety depends on amygdala but not on hippocampus.SIGNIFICANCE STATEMENT Approach-avoidance conflict tests are widely investigated in rodents, and increasingly in humans, to understand the neural basis of anxiety-like behavior. However, the contribution of the most relevant brain regions, ventral hippocampus and amygdala, is incompletely understood. We use a human computerized test that separates different action components and find that hippocampus, but not amygdala, lesions impair approach decisions, whereas amygdala, but not hippocampus, lesions impair the vigor of return to safety.

Threat Memory Reminder Under Matrix Metalloproteinase 9 Inhibitor Doxycycline Globally Reduces Subsequent Memory Plasticity.

Associative memory can be rendered malleable by a reminder. Blocking the ensuing reconsolidation process is suggested as a therapeutic target for unwanted aversive memories. Matrix metalloproteinase-9 (MMP-9) is required for structural synapse remodeling involved in memory consolidation. Inhibiting MMP-9 with doxycycline is suggested to attenuate human threat conditioning. Here, we investigated whether MMP-9 inhibition also interferes with threat memory reconsolidation. Male and female human participants (N = 78) learned the association between two visual conditioned stimuli (CS+) and a 50% chance of an unconditioned nociceptive stimulus (US), and between CS- and the absence of US. On day 7, one CS+ was reminded without reinforcement 3.5 h after ingesting either 200 mg of doxycycline or placebo. On day 14, retention of CS memory was assessed under extinction by fear-potentiated startle. Contrary to our expectations, we observed a greater CS+/CS- difference in participants who were reminded under doxycycline compared with placebo. Participants who were reminded under placebo showed extinction learning during the retention test, which was not observed in the doxycycline group. There was no difference between the reminded and the nonreminded CS+ in either group. In contrast, during relearning after the retention test, the CS+/CS- difference was more pronounced in the placebo group than in the doxycycline group. To summarize, a single dose of doxycycline before threat memory reminder appeared to have no specific impact on reconsolidation, but to globally impair extinction learning, and threat relearning, beyond drug clearance.SIGNIFICANCE STATEMENT Matrix metalloproteinase-9 inhibition appears to attenuate memory consolidation. It could also be a target for blocking reconsolidation. Here, we test this hypothesis in human threat conditioning. We find that doxycycline has no specific impact on a reminded cue, but confers a global reduction in extinction learning and threat learning beyond the clearance of the drug. This may point toward a more long-lasting impact of doxycycline treatment on memory plasticity.

Primary auditory cortex representation of fear-conditioned musical sounds.

Auditory cortex is required for discriminative fear conditioning beyond the classical amygdala microcircuit, but its precise role is unknown. It has previously been suggested that Heschl's gyrus, which includes primary auditory cortex (A1), but also other auditory areas, encodes threat predictions during presentation of conditioned stimuli (CS) consisting of monophones, or frequency sweeps. The latter resemble natural prosody and contain discriminative spectro-temporal information. Here, we use functional magnetic resonance imaging (fMRI) in humans to address CS encoding in A1 for stimuli that contain only spectral but no temporal discriminative information. Two musical chords (complex) or two monophone tones (simple) were presented in a signaled reinforcement context (reinforced CS+ and nonreinforced CS-), or in a different context without reinforcement (neutral sounds, NS1 and NS2), with an incidental sound detection task. CS/US association encoding was quantified by the increased discriminability of BOLD patterns evoked by CS+/CS-, compared to NS pairs with similar physical stimulus differences and task demands. A1 was defined on a single-participant level and based on individual anatomy. We find that in A1, discriminability of CS+/CS- was higher than for NS1/NS2. This representation of unconditioned stimulus (US) prediction was of comparable magnitude for both types of sounds. We did not observe such encoding outside A1. Different from frequency sweeps investigated previously, musical chords did not share representations of US prediction with monophone sounds. To summarize, our findings suggest decodable representation of US predictions in A1, for various types of CS, including musical chords that contain no temporal discriminative information.

No substantial change in the balance between model-free and model-based control via training on the two-step task.

Human decisions can be habitual or goal-directed, also known as model-free (MF) or model-based (MB) control. Previous work suggests that the balance between the two decision systems is impaired in psychiatric disorders such as compulsion and addiction, via overreliance on MF control. However, little is known whether the balance can be altered through task training. Here, 20 healthy participants performed a well-established two-step task that differentiates MB from MF control, across five training sessions. We used computational modelling and functional near-infrared spectroscopy to assess changes in decision-making and brain hemodynamic over time. Mixed-effects modelling revealed overall no substantial changes in MF and MB behavior across training. Although our behavioral and brain findings show task-induced changes in learning rates, these parameters have no direct relation to either MF or MB control or the balance between the two systems, and thus do not support the assumption of training effects on MF or MB strategies. Our findings indicate that training on the two-step paradigm in its current form does not support a shift in the balance between MF and MB control. We discuss these results with respect to implications for restoring the balance between MF and MB control in psychiatric conditions.

Pavlovian-to-instrumental transfer after human threat conditioning.

Threat conditioning is a common associative learning model with translational relevance. How threat-conditioned cues impact on formally unrelated instrumental behavior in humans is not well known. Such an effect is known as Pavlovian-to-instrumental transfer (PIT). While PIT with aversive primary Pavlovian reinforcers is established in nonhuman animals, this is less clear in humans, where secondary reinforcers or instructed instrumental responses are most often investigated. We modified an existing human PIT procedure to include primary reinforcers. Participants first learned to obtain (or avoid losing) appetitive instrumental reinforcement (chocolate) by appropriate approach or avoidance actions. They either had to act (Go) or to withhold an action (NoGo), and in the Go condition either to approach a reward target to collect it or to withdraw from the reward target to avoid losing it. Then they learned to associate screen color (CS) with aversive Pavlovian reinforcement (electric shock US). In the transfer phase, we conducted the instrumental task during the presence of Pavlovian CS. In a first experiment, we show that the aversive Pavlovian CS+, compared to CS-, increased response rate in Go-Withdraw trials, i.e., induce conditioned facilitation of avoidance responses. This finding was confirmed in a second and independent experiment with an increased number of Go-Withdraw trials. Notably, we observed no appreciable conditioned suppression of approach responses. Effect size to distinguish CS+/CS- in Go-Withdraw trials was d = 0.42 in the confirmation sample. This would require n = 37 participants to demonstrate threat learning with 80% power. Thus, the effect size is on a practically useful scale although smaller than for model-based analysis of autonomic measures. In summary, our results indicate conditioned facilitation of formally unrelated instrumental avoidance behavior in humans and provide a novel behavioral threat learning measure that requires only key presses.

High-precision magnetoencephalography for reconstructing amygdalar and hippocampal oscillations during prediction of safety and threat.

Learning to associate neutral with aversive events in rodents is thought to depend on hippocampal and amygdala oscillations. In humans, oscillations underlying aversive learning are not well characterised, largely due to the technical difficulty of recording from these two structures. Here, we used high-precision magnetoencephalography (MEG) during human discriminant delay threat conditioning. We constructed generative anatomical models relating neural activity with recorded magnetic fields at the single-participant level, including the neocortex with or without the possibility of sources originating in the hippocampal and amygdalar structures. Models including neural activity in amygdala and hippocampus explained MEG data during threat conditioning better than exclusively neocortical models. We found that in both amygdala and hippocampus, theta oscillations during anticipation of an aversive event had lower power compared to safety, both during retrieval and extinction of aversive memories. At the same time, theta synchronisation between hippocampus and amygdala increased over repeated retrieval of aversive predictions, but not during safety. Our results suggest that high-precision MEG is sensitive to neural activity of the human amygdala and hippocampus during threat conditioning and shed light on the oscillation-mediated mechanisms underpinning retrieval and extinction of fear memories in humans.

Human Pavlovian fear conditioning conforms to probabilistic learning.

Learning to predict threat from environmental cues is a fundamental skill in changing environments. This aversive learning process is exemplified by Pavlovian threat conditioning. Despite a plethora of studies on the neural mechanisms supporting the formation of associations between neutral and aversive events, our computational understanding of this process is fragmented. Importantly, different computational models give rise to different and partly opposing predictions for the trial-by-trial dynamics of learning, for example expressed in the activity of the autonomic nervous system (ANS). Here, we investigate human ANS responses to conditioned stimuli during Pavlovian fear conditioning. To obtain precise, trial-by-trial, single-subject estimates of ANS responses, we build on a statistical framework for psychophysiological modelling. We then consider previously proposed non-probabilistic models, a simple probabilistic model, and non-learning models, as well as different observation functions to link learning models with ANS activity. Across three experiments, and both for skin conductance (SCR) and pupil size responses (PSR), a probabilistic learning model best explains ANS responses. Notably, SCR and PSR reflect different quantities of the same model: SCR track a mixture of expected outcome and uncertainty, while PSR track expected outcome alone. In summary, by combining psychophysiological modelling with computational learning theory, we provide systematic evidence that the formation and maintenance of Pavlovian threat predictions in humans may rely on probabilistic inference and includes estimation of uncertainty. This could inform theories of neural implementation of aversive learning.