Matthias Staib

Optimising a model-based approach to inferring fear learning from skin conductance responses.

Highlights • We validate a Psychophysiological model (PsPM) to infer anticipatory sympathetic arousal from changes in skin conductance.• We optimise the inversion of this PsPM in terms of a constrained non-linear dynamic causal model.• This method allows a quantification of fear memory in humans.

A pupil size response model to assess fear learning.

Abstract During fear conditioning, pupil size responses dissociate between conditioned stimuli that are contingently paired (CS+) with an aversive unconditioned stimulus, and those that are unpaired (CS‐). Current approaches to assess fear learning from pupil responses rely on ad hoc specifications. Here, we sought to develop a psychophysiological model (PsPM) in which pupil responses are characterized by response functions within the framework of a linear time‐invariant system. This PsPM can be written as a general linear model, which is inverted to yield amplitude estimates of the eliciting process in the central nervous system. We first characterized fear‐conditioned pupil size responses based on an experiment with auditory CS. PsPM‐based parameter estimates distinguished CS+/CS‐ better than, or on par with, two commonly used methods (peak scoring, area under the curve). We validated this PsPM in four independent experiments with auditory, visual, and somatosensory CS, as well as short (3.5 s) and medium (6 s) CS/US intervals. Overall, the new PsPM provided equal or decisively better differentiation of CS+/CS‐ than the two alternative methods and was never decisively worse. We further compared pupil responses with concurrently measured skin conductance and heart period responses. Finally, we used our previously developed luminance‐related pupil responses to infer the timing of the likely neural input into the pupillary system. Overall, we establish a new PsPM to assess fear conditioning based on pupil responses. The model has a potential to provide higher statistical sensitivity, can be applied to other conditioning paradigms in humans, and may be easily extended to nonhuman mammals.

Modeling fear-conditioned bradycardia in humans

Abstract Across species, cued fear conditioning is a common experimental paradigm to investigate aversive Pavlovian learning. While fear‐conditioned stimuli (CS+) elicit overt behavior in many mammals, this is not the case in humans. Typically, autonomic nervous system activity is used to quantify fear memory in humans, measured by skin conductance responses (SCR). Here, we investigate whether heart period responses (HPR) evoked by the CS, often observed in humans and small mammals, are suitable to complement SCR as an index of fear memory in humans. We analyze four datasets involving delay and trace conditioning, in which heart beats are identified via electrocardiogram or pulse oximetry, to show that fear‐conditioned heart rate deceleration (bradycardia) is elicited and robustly distinguishes CS+ from CS−. We then develop a psychophysiological model (PsPM) of fear‐conditioned HPR. This PsPM is inverted to yield estimates of autonomic input into the heart. We show that the sensitivity to distinguish CS+ and CS− (predictive validity) is higher for model‐based estimates than peak‐scoring analysis, and compare this with SCR. Our work provides a novel tool to investigate fear memory in humans that allows direct comparison between species.

A matching pursuit algorithm for inferring tonic sympathetic arousal from spontaneous skin conductance fluctuations

Abstract Tonic sympathetic arousal is often inferred from spontaneous fluctuations in skin conductance, and this relies on assumptions about the shape of these fluctuations and how they are generated. We have previously furnished a psychophysiological model for this relation, and an efficient and reliable inversion method to estimate tonic arousal from given data in the framework of dynamic causal modeling (DCM). Here, we provide a fast alternative inversion method in the form of a matching pursuit (MP) algorithm. Analyzing simulated data, this algorithm approximates the true underlying arousal up to about 10 spontaneous fluctuations per minute of data. For empirical data, we assess predictive validity as the ability to differentiate two known psychological arousal states. Predictive validity is comparable between the methods for three datasets, and also comparable to visual peak scoring. Computation time of the MP algorithm is 2–3 orders of magnitude faster for the MP than the DCM algorithm. In summary, the new MP algorithm provides a fast and reliable alternative to DCM inversion for SF data, in particular when the expected number of fluctuations is lower than 10 per minute, as in typical experimental situations.

Assessing fear learning via conditioned respiratory amplitude responses

Abstract Respiratory physiology is influenced by cognitive processes. It has been suggested that some cognitive states may be inferred from respiration amplitude responses (RAR) after external events. Here, we investigate whether RAR allow assessment of fear memory in cued fear conditioning, an experimental model of aversive learning. To this end, we built on a previously developed psychophysiological model (PsPM) of RAR, which regards interpolated RAR time series as the output of a linear time invariant system. We first establish that average RAR after CS+ and CS− are different. We then develop the response function of fear‐conditioned RAR, to be used in our PsPM. This PsPM is inverted to yield estimates of cognitive input into the respiratory system. We analyze five validation experiments involving fear acquisition and retention, delay and trace conditioning, short and medium CS‐US intervals, and data acquired with bellows and MRI‐compatible pressure chest belts. In all experiments, CS+ and CS− are distinguished by their estimated cognitive inputs, and the sensitivity of this distinction is higher for model‐based estimates than for peak scoring of RAR. Comparing these data with skin conductance responses (SCR) and heart period responses (HPR), we find that, on average, RAR performs similar to SCR in distinguishing CS+ and CS−, but is less sensitive than HPR. Overall, our work provides a novel and robust tool to investigate fear memory in humans that may allow wide and straightforward application to diverse experimental contexts.

Non-medical prescription opioid users exhibit dysfunctional physiological stress responses to social rejection

Non-medical prescription opioid use (NMPOU) recently increased dramatically, especially in the U.S. Although chronic opioid use is commonly accompanied by deficits in social functioning and dysregulation of the hypothalamic-pituitary adrenergic (HPA) stress axis, little is known about the impact of NMPOU on psychosocial stress responses. Therefore, we measured physiological responses of the autonomic nervous system and the HPA axis to social rejection using the Cyberball paradigm. We compared 23 individuals with NMPOU, objectively confirmed by hair and urine analyses, with 29 opioid-naïve, healthy controls. As expected, heart rate variability (HRV), an index of parasympathetic activity, increased significantly during exclusion within controls, while in the NMPOU group only a trend in the same direction was found. However, increased HRV was robustly moderated by opioid craving indicating worse emotion regulation to social exclusion specifically in individuals with high opioid craving. Greater levels of the adrenocorticotropic hormone and cortisol responses to social rejection were found in the NMPOU group indicating hyperreactivity of the HPA axis to social exclusion. Self-ratings suggest that opioid users were aware of rejection, but less emotionally affected by exclusion. Furthermore, controls showed greater negative mood after the Cyberball confirming the tasks validity. Moreover, NMPOU individuals reported a smaller social network size compared to controls. Present findings suggest that chronic NMPOU is associated with dysfunctional physiological responses to psychosocial stressors such as social rejection. In sum, NMPOU was associated with poorer regulation of the parasympathetic nervous system, especially under opioid craving highlighting its potential importance in relapse prevention.

Stimulus-invariant auditory cortex threat encoding during fear conditioning with simple and complex sounds

&NA; Learning to predict threat depends on amygdala plasticity and does not require auditory cortex (ACX) when threat predictors (conditioned stimuli, CS) are simple sine tones. However, ACX is required in rodents to learn from some naturally occurring CS. Yet, the precise function of ACX, and whether it differs for different CS types, is unknown. Here, we address how ACX encodes threat predictions during human fear conditioning using functional magnetic resonance imaging (fMRI) with multivariate pattern analysis. As in previous rodent work, CS+ and CS‐ were defined either by direction of frequency modulation (complex) or by frequency of pure tones (simple). In an instructed non‐reinforcement context, different sets of simple and complex sounds were always presented without reinforcement (neutral sounds, NS). Threat encoding was measured by separation of fMRI response patterns induced by CS+/CS‐, or similar NS1/NS2 pairs. We found that fMRI patterns in Heschls gyrus encoded threat prediction over and above encoding the physical stimulus features also present in NS, i.e. CS+/CS‐ could be separated better than NS1/NS2. This was the case both for simple and complex CS. Furthermore, cross‐prediction demonstrated that threat representations were similar for simple and complex CS, and thus unlikely to emerge from stimulus‐specific top‐down, or learning‐induced, receptive field plasticity. Searchlight analysis across the entire ACX demonstrated further threat representations in a region including BA22 and BA42. However, in this region, patterns were distinct for simple and complex sounds, and could thus potentially arise from receptive field plasticity. Strikingly, across participants, individual size of Heschls gyrus predicted strength of fear learning for complex sounds. Overall, our findings suggest that ACX represents threat predictions, and that Heschls gyrus contains a threat representation that is invariant across physical stimulus categories.

Neurocircuitry of impaired affective sound processing: A clinical disorders perspective

Decoding affective meaning from sensory information is central to accurate and adaptive behavior in many natural and social contexts. Human vocalizations (speech and non-speech), environmental sounds (e.g. thunder, noise, or animal sounds) and human-produced sounds (e.g. technical sounds or music) can carry a wealth of important aversive, threatening, appealing, or pleasurable affective information that sometimes implicitly influences and guides our behavior. A deficit in processing such affective information is detrimental to adaptive environmental behavior, psychological well-being, and social interactive abilities. These deficits can originate from a diversity of psychiatric and neurological disorders, and are associated with neural dysfunctions across largely distributed brain networks. Recent neuroimaging studies in psychiatric and neurological patients outline the cortical and subcortical neurocircuitry of the complimentary and differential functional roles for affective sound processing. This points to and confirms a recently proposed distributed network rather than a single brain region underlying affective sound processing, and highlights the notion of a multi-functional process that can be differentially impaired in clinical disorders.