Metacognition as a window into subjective affective experience.

When patients seek professional help for mental disorders, they often do so because of troubling subjective affective experiences. While these subjective states are at the center of the patient's symptomatology, scientific tools for studying them and their cognitive antecedents are limited. Here, we explore the use of concepts and analytic tools from the science of consciousness, a field of research that has faced similar challenges in having to develop robust empirical methods for addressing a phenomenon that has been considered difficult to pin down experimentally. One important strand is the operationalization of some relevant processes in terms of metacognition and confidence ratings, which can be rigorously studied in both humans and animals. By assessing subjective experience with similar approaches, we hope to develop new scientific approaches for studying affective processes and promoting psychological resilience in the face of debilitating emotional experiences.

Putting the "mental" back in "mental disorders": a perspective from research on fear and anxiety.

Mental health problems often involve clusters of symptoms that include subjective (conscious) experiences as well as behavioral and/or physiological responses. Because the bodily responses are readily measured objectively, these have come to be emphasized when developing treatments and assessing their effectiveness. On the other hand, the subjective experience of the patient reported during a clinical interview is often viewed as a weak correlate of psychopathology. To the extent that subjective symptoms are related to the underlying problem, it is often assumed that they will be taken care of if the more objective behavioral and physiological symptoms are properly treated. Decades of research on anxiety disorders, however, show that behavioral and physiological symptoms do not correlate as strongly with subjective experiences as is typically assumed. Further, the treatments developed using more objective symptoms as a marker of psychopathology have mostly been disappointing in effectiveness. Given that "mental" disorders are named for, and defined by, their subjective mental qualities, it is perhaps not surprising, in retrospect, that treatments that have sidelined mental qualities have not been especially effective. These negative attitudes about subjective experience took root in psychiatry and allied fields decades ago when there were few avenues for scientifically studying subjective experience. Today, however, cognitive neuroscience research on consciousness is thriving, and offers a viable and novel scientific approach that could help achieve a deeper understanding of mental disorders and their treatment.

Reversing frontal disinhibition rescues behavioural deficits in models of CACNA1A-associated neurodevelopment disorders.

CACNA1A deletions cause epilepsy, ataxia, and a range of neurocognitive deficits, including inattention, impulsivity, intellectual deficiency and autism. To investigate the underlying mechanisms, we generated mice carrying a targeted Cacna1a deletion restricted to parvalbumin-expressing (PV) neurons (PVCre;Cacna1ac/+) or to cortical pyramidal cells (PC) (Emx1Cre;Cacna1ac/+). GABA release from PV-expressing GABAergic interneurons (PV-INs) is reduced in PVCre;Cacna1ac/+ mutants, resulting in impulsivity, cognitive rigidity and inattention. By contrast, the deletion of Cacna1a in PCs does not impact cortical excitability or behaviour in Emx1Cre;Cacna1ac/+ mutants. A targeted Cacna1a deletion in the orbitofrontal cortex (OFC) results in reversal learning deficits while a medial prefrontal cortex (mPFC) deletion impairs selective attention. These deficits can be rescued by the selective chemogenetic activation of cortical PV-INs in the OFC or mPFC of PVCre;Cacna1ac/+ mutants. Thus, Cacna1a haploinsufficiency disrupts perisomatic inhibition in frontal cortical circuits, leading to a range of potentially reversible neurocognitive deficits.

Real-Time Functional MRI in the Treatment of Mental Health Disorders.

Multiple mental disorders have been associated with dysregulation of precise brain processes. However, few therapeutic approaches can correct such specific patterns of brain activity. Since the late 1960s and early 1970s, many researchers have hoped that this feat could be achieved by closed-loop brain imaging approaches, such as neurofeedback, that aim to modulate brain activity directly. However, neurofeedback never gained mainstream acceptance in mental health, in part due to methodological considerations. In this review, we argue that, when contemporary methodological guidelines are followed, neurofeedback is one of the few intervention methods in psychology that can be assessed in double-blind placebo-controlled trials. Furthermore, using new advances in machine learning and statistics, it is now possible to target very precise patterns of brain activity for therapeutic purposes. We review the recent literature in functional magnetic resonance imaging neurofeedback and discuss current and future applications to mental health.

Multivoxel pattern analysis reveals dissociations between subjective fear and its physiological correlates.

In studies of anxiety and other affective disorders, objectively measured physiological responses have commonly been used as a proxy for measuring subjective experiences associated with pathology. However, this commonly adopted "biosignal" approach has recently been called into question on the grounds that subjective experiences and objective physiological responses may dissociate. We performed machine-learning-based analyses on functional magnetic resonance imaging (fMRI) data to assess this issue in the case of fear. Although subjective fear and objective physiological responses were correlated in general, the respective whole-brain multivoxel decoders for the two measures were different. Some key brain regions such as the amygdala and insula appear to be primarily involved in the prediction of physiological reactivity, whereas some regions previously associated with metacognition and conscious perception, including some areas in the prefrontal cortex, appear to be primarily predictive of the subjective experience of fear. The present findings are in support of the recent call for caution in assuming a one-to-one mapping between subjective sufferings and their putative biosignals, despite the clear advantages in the latter's being objectively and continuously measurable in physiological terms.

Towards an unconscious neural reinforcement intervention for common fears.

Can "hardwired" physiological fear responses (e.g., for spiders and snakes) be reprogramed unconsciously in the human brain? Currently, exposure therapy is among the most effective treatments for anxiety disorders, but this intervention is subjectively aversive to patients, causing many to drop out of treatment prematurely. Here we introduce a method to bypass the subjective unpleasantness in conscious exposure, by directly pairing monetary reward with unconscious occurrences of decoded representations of naturally feared animals in the brain. To decode physiological fear representations without triggering excessively aversive reactions, we capitalize on recent advancements in functional magnetic resonance imaging decoding techniques, and use a method called hyperalignment to infer the relevant representations of feared animals for a designated participant based on data from other "surrogate" participants. In this way, the procedure completely bypasses the need for a conscious encounter with feared animals. We demonstrate that our method can lead to reliable reductions in physiological fear responses, as measured by skin conductance as well as amygdala hemodynamic activity. Not only do these results raise the intriguing possibility that naturally occurring fear responses can be "reprogrammed" outside of conscious awareness, importantly, they also create the rare opportunity to rigorously test a psychological intervention of this nature in a double-blind, placebo-controlled fashion. This may pave the way for a new approach combining the appealing rationale and proven efficacy of conventional psychotherapy with the rigor and leverage of clinical neuroscience.

Interaction between the prefrontal and visual cortices supports subjective fear.

It has been reported that threatening and non-threatening visual stimuli can be distinguished based on the multi-voxel patterns of haemodynamic activity in the human ventral visual stream. Do these findings mean that there may be evolutionarily hardwired mechanisms within early perception, for the fast and automatic detection of threat, and maybe even for the generation of the subjective experience of fear? In this human neuroimaging study, we presented participants ('fear' group: N = 30; 'no fear' group: N = 30) with 2700 images of animals that could trigger subjective fear or not as a function of the individual's idiosyncratic 'fear profiles' (i.e. fear ratings of animals reported by a given participant). We provide evidence that the ventral visual stream may represent affectively neutral visual features that are statistically associated with fear ratings of participants, without representing the subjective experience of fear itself. More specifically, we show that patterns of haemodynamic activity predictive of a specific 'fear profile' can be observed in the ventral visual stream whether a participant reports being afraid of the stimuli or not. Further, we found that the multivariate information synchronization between ventral visual areas and prefrontal regions distinguished participants who reported being subjectively afraid of the stimuli from those who did not. Together, these findings support the view that the subjective experience of fear may depend on the relevant visual information triggering implicit metacognitive mechanisms in the prefrontal cortex. This article is part of the theme issue 'Sensing and feeling: an integrative approach to sensory processing and emotional experience'.

The Signature Biobank: A longitudinal biopsychosocial repository of psychiatric emergency patients.

The Signature Biobank is a longitudinal repository of biospecimen, psychological, sociodemographic, and diagnostic data that was created in 2012. The Signature Consortium represents a group of approximately one hundred Quebec-based transdisciplinary clinicians and research scientists with various expertise in the field of psychiatry. The objective of the Signature Biobank is to investigate the multi-faceted underpinnings of psychiatric disorders among patients in crisis. The Signature Consortium is expanding and includes new active members that seek to highlight the contributions made by Signature Biobank since its inception. This article details our research protocol, directions, and summarizes contributions. To date, we have collected biological samples (n = 1,986), and questionnaire data (n = 2,085) from psychiatric emergency patients of the Institut universitaire en santé mentale de Montréal (Quebec, Canada), with a large proportion from whom both data types were collected (n = 1,926). In addition to this, a subsample of patients was followed-up at hospital discharge, and two additional outpatient clinic appointments (n = 958 with at least one follow-up). In addition, a socio-demographically matched comparison group of individuals who were not hospitalized for psychiatric disorders (n = 149) was recruited from the surrounding catchment area. To summarize, a systematic review of the literature shows that the Signature Biobank has contributed to better characterizing psychiatric comorbidities, biological profiles, and psychosocial functioning across some of the most common psychiatric disorders, including psychosis, mood, anxiety, and substance use disorders. The Signature Biobank is now one of the world's largest repositories of data collected from patients receiving care at a psychiatric emergency unit.

Multi-voxel neuro-reinforcement changes resting-state functional connectivity: A pilot study.

Background: Multi-voxel neuro-reinforcement has been shown to selectively reduce amygdala reactivity in response to feared stimuli, but the precise mechanisms supporting these effects are still unknown. The current pilot study seeks to identify potential intermediaries of change using functional brain connectivity at rest. Methods: Individuals (N = 11) diagnosed with at least two animal subtype specific phobias took part in a double-blind multi-voxel neuro-reinforcement clinical trial targeting one of two phobic animals, with the untargeted animal as placebo control. Changes in whole-brain resting state functional connectivity from pre-treatment to post-treatment were measured using group ICA. These changes were tested to see if they predicted the previously observed decreases in amygdala reactivity in response to images of target phobic animals. Results: A common functional connectivity network overlapping with the visual network was identified in resting state data pre-treatment and post-treatment. Significant increases in functional connectivity in this network from pre-treatment to post-treatment were found in higher level visual and cognitive processing regions of the brain. Increases in functional connectivity in these regions also significantly predicted decreases in task-based amygdala reactivity to targeted phobic animals following multi-voxel neuro-reinforcement. Specifically, greater increases of functional connectivity pre-treatment to post-treatment were associated with greater decreases of amygdala reactivity to target phobic stimuli pre-treatment to post-treatment. Conclusions: These findings provide preliminary evidence that multi-voxel neuro-reinforcement can induce persisting functional connectivity changes in the brain. Moreover, these changes in functional connectivity were not limited to the direct area of neuro-reinforcement, suggesting neuro-reinforcement may change how the targeted region interacts with other brain regions. Identification of these brain regions represent a first step towards explaining the underlying mechanisms of change in previous multi-voxel neuro-reinforcement studies. Future research should seek to replicate these effects in a larger sample size to further assess their role in the effects observed from multi-voxel neuro-reinforcement.

A Multivoxel Pattern Analysis of Anhedonia During Fear Extinction: Implications for Safety Learning.

BACKGROUND: Pavlovian learning processes are central to the etiology and treatment of anxiety disorders. Anhedonia and related perturbations in reward processes have been implicated in Pavlovian learning. Associations between anhedonia symptoms and neural indices of Pavlovian learning can inform transdiagnostic associations among depressive and anxiety disorders. METHODS: Participants ages 18 to 19 years (67% female) completed a fear extinction (n = 254) and recall (n = 249) paradigm during functional magnetic resonance imaging. Symptom dimensions of general distress (common to anxiety and depression), fears (more specific to anxiety), and anhedonia-apprehension (more specific to depression) were evaluated. We trained whole-brain multivoxel pattern decoders for anhedonia-apprehension during extinction and extinction recall and tested the decoders' ability to predict anhedonia-apprehension in an external validation sample. Specificity analyses examined effects covarying for general distress and fears. Decoding was repeated within canonical brain networks to highlight candidate neurocircuitry underlying whole-brain effects. RESULTS: Whole-brain decoder training succeeded during both tasks. Prediction of anhedonia-apprehension in the external validation sample was successful for extinction (R2 = 0.047; r = 0.276, p = .002) but not extinction recall (R2 < 0.001, r = -0.063, p = .492). The extinction decoder remained significantly associated with anhedonia-apprehension covarying for fears and general distress (t121 = 3.209, p = .002). Exploratory results highlighted activity in the cognitive control, default mode, limbic, salience, and visual networks related to these effects. CONCLUSIONS: Results suggest that patterns of brain activity during extinction, particularly in the cognitive control, default mode, limbic, salience, and visual networks, can be predictive of anhedonia symptoms. Future research should examine associations between anhedonia and extinction, including studies of exposure therapy or positive affect treatments among anhedonic individuals.

A generative adversarial model of intrusive imagery in the human brain.

The mechanisms underlying the subjective experiences of mental disorders remain poorly understood. This is partly due to long-standing over-emphasis on behavioral and physiological symptoms and a de-emphasis of the patient's subjective experiences when searching for treatments. Here, we provide a new perspective on the subjective experience of mental disorders based on findings in neuroscience and artificial intelligence (AI). Specifically, we propose the subjective experience that occurs in visual imagination depends on mechanisms similar to generative adversarial networks that have recently been developed in AI. The basic idea is that a generator network fabricates a prediction of the world, and a discriminator network determines whether it is likely real or not. Given that similar adversarial interactions occur in the two major visual pathways of perception in people, we explored whether we could leverage this AI-inspired approach to better understand the intrusive imagery experiences of patients suffering from mental illnesses such as post-traumatic stress disorder (PTSD) and acute stress disorder. In our model, a nonconscious visual pathway generates predictions of the environment that influence the parallel but interacting conscious pathway. We propose that in some patients, an imbalance in these adversarial interactions leads to an overrepresentation of disturbing content relative to current reality, and results in debilitating flashbacks. By situating the subjective experience of intrusive visual imagery in the adversarial interaction of these visual pathways, we propose testable hypotheses on novel mechanisms and clinical applications for controlling and possibly preventing symptoms resulting from intrusive imagery.

Conducting decoded neurofeedback studies.

Closed-loop neurofeedback has sparked great interest since its inception in the late 1960s. However, the field has historically faced various methodological challenges. Decoded fMRI neurofeedback may provide solutions to some of these problems. Notably, thanks to the recent advancements of machine learning approaches, it is now possible to target unconscious occurrences of specific multivoxel representations. In this tools of the trade paper, we discuss how to implement these interventions in rigorous double-blind placebo-controlled experiments. We aim to provide a step-by-step guide to address some of the most common methodological and analytical considerations. We also discuss tools that can be used to facilitate the implementation of new experiments. We hope that this will encourage more researchers to try out this powerful new intervention method.

The DecNef collection, fMRI data from closed-loop decoded neurofeedback experiments.

Decoded neurofeedback (DecNef) is a form of closed-loop functional magnetic resonance imaging (fMRI) combined with machine learning approaches, which holds some promises for clinical applications. Yet, currently only a few research groups have had the opportunity to run such experiments; furthermore, there is no existing public dataset for scientists to analyse and investigate some of the factors enabling the manipulation of brain dynamics. We release here the data from published DecNef studies, consisting of 5 separate fMRI datasets, each with multiple sessions recorded per participant. For each participant the data consists of a session that was used in the main experiment to train the machine learning decoder, and several (from 3 to 10) closed-loop fMRI neural reinforcement sessions. The large dataset, currently comprising more than 60 participants, will be useful to the fMRI community at large and to researchers trying to understand the mechanisms underlying non-invasive modulation of brain dynamics. Finally, the data collection size will increase over time as data from newly run DecNef studies will be added.

Could Brain Decoding Machines Change Our Minds?

In a recent experiment, Zhang and colleagues designed a closed-loop brain-machine interface that learned to reduce participants' pain by decoding pain-related brain activity. In doing so, they also highlighted some of the challenges associated with coadaptive processes in brain-machine communication.

Current Status of Neurofeedback for Post-traumatic Stress Disorder: A Systematic Review and the Possibility of Decoded Neurofeedback.

Background: Post-traumatic stress disorder (PTSD) is a neuropsychiatric affective disorder that can develop after traumatic life-events. Exposure-based therapy is currently one of the most effective treatments for PTSD. However, exposure to traumatic stimuli is so aversive that a significant number of patients drop-out of therapy during the course of treatment. Among various attempts to develop novel therapies that bypass such aversiveness, neurofeedback appears promising. With neurofeedback, patients can unconsciously self-regulate brain activity via real-time monitoring and feedback of the EEG or fMRI signals. With conventional neurofeedback methods, however, it is difficult to induce neural representation related to specific trauma because the feedback is based on the neural signals averaged within specific brain areas. To overcome this difficulty, novel neurofeedback approaches such as Decoded Neurofeedback (DecNef) might prove helpful. Instead of the average BOLD signals, DecNef allows patients to implicitly regulate multivariate voxel patterns of the BOLD signals related with feared stimuli. As such, DecNef effects are postulated to derive either from exposure or counter-conditioning, or some combination of both. Although the exact mechanism is not yet fully understood. DecNef has been successfully applied to reduce fear responses induced either by fear-conditioned or phobic stimuli among non-clinical participants. Methods: Follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review was conducted to compare DecNef effect with those of conventional EEG/fMRI-based neurofeedback on PTSD amelioration. To elucidate the possible mechanisms of DecNef on fear reduction, we mathematically modeled the effects of exposure-based and counter conditioning separately and applied it to the data obtained from past DecNef studies. Finally, we conducted DecNef on four PTSD patients. Here, we review recent advances in application of neurofeedback to PTSD treatments, including the DecNef. This review is intended to be informative for neuroscientists in general as well as practitioners planning to use neurofeedback as a therapeutic strategy for PTSD. Results: Our mathematical model suggested that exposure is the key component for DecNef effects in the past studies. Following DecNef a significant reduction of PTSD severity was observed. This effect was comparable to those reported for conventional neurofeedback approach. Conclusions: Although a much larger number of participants will be needed in future, DecNef could be a promising therapy that bypasses the unpleasantness of conscious exposure associated with conventional therapies for fear related disorders, including PTSD.

Unconscious Psychological Treatments for Physiological Survival Circuits.

The idea of targeting unconscious or implicit processes in psychological treatments is not new, but until recently it has not been easy to manipulate these processes without also engaging consciousness. Here we review how this is possible, using various modern cognitive neuroscience methods including a technique known as Decoded Neural-Reinforcement. We discuss the general advantages of this approach, such as how it can facilitate double-blind placebo-controlled studies, and minimize premature patient dropouts in the treatment of fear. We also speculate how this may generalize to other similar physiological survival processes.

Measuring away an attentional confound?

A recent fMRI study by Webb et al. (Cortical networks involved in visual awareness independent of visual attention, Proc Natl Acad Sci U S A 2016;113:13923-28) proposes a new method for finding the neural correlates of awareness by matching attention across awareness conditions. The experimental design, however, seems at odds with known features of attention. We highlight logical and methodological points that are critical when trying to disentangle attention and awareness.

BDNF Val66Met Polymorphism Is Associated with Self-Reported Empathy.

Empathy is an important driver of human social behaviors and presents genetic roots that have been studied in neuroimaging using the intermediate phenotype approach. Notably, the Val66Met polymorphism of the Brain-derived neurotrophic factor (BDNF) gene has been identified as a potential target in neuroimaging studies based on its influence on emotion perception and social cognition, but its impact on self-reported empathy has never been documented. Using a neurogenetic approach, we investigated the association between the BDNF Val66Met polymorphism and self-reported empathy (Davis' Interpersonal Reactivity Index; IRI) in a sample of 110 young adults. Our results indicate that the BDNF genotype is significantly associated with the linear combination of the four facets of the IRI, one of the most widely used self-reported empathy questionnaire. Crucially, the effect of BDNF Val66Met goes beyond the variance explained by two polymorphisms of the oxytocin transporter gene previously associated with empathy and its neural underpinnings (OXTR rs53576 and rs2254298). These results represent the first evidence suggesting a link between the BDNF gene and self-reported empathy and warrant further studies of this polymorphism due to its potential clinical significance.

Behavioral and TMS Markers of Action Observation Might Reflect Distinct Neuronal Processes.

Transcranial magnetic stimulation (TMS) studies have shown that observing an action induces muscle-specific changes in corticospinal excitability. From a signal detection theory standpoint, this pattern can be related to sensitivity, which here would measure the capacity to distinguish between two action observation conditions. In parallel to these TMS studies, action observation has also been linked to behavioral effects such as motor priming and interference. It has been hypothesized that behavioral markers of action observation could be related to TMS markers and thus represent a potentially cost-effective mean of assessing the functioning of the action-perception system. However, very few studies have looked at possible relationships between these two measures. The aim of this study was to investigate if individual differences in sensitivity to action observation could be related to the behavioral motor priming and interference effects produced by action observation. To this end, 14 healthy participants observed index and little finger movements during a TMS task and a stimulus-response compatibility task. Index muscle displayed sensitivity to action observation, and action observation resulted in significant motor priming+interference, while no significant effect was observed for the little finger in both task. Nevertheless, our results indicate that the sensitivity measured in TMS was not related to the behavioral changes measured in the stimulus-response compatibility task. Contrary to a widespread assumption, the current results indicate that individual differences in physiological and behavioral markers of action observation may be unrelated. This could have important impacts on the potential use of behavioral markers in place of more costly physiological markers of action observation in clinical settings.