A double-blind trial of decoded neurofeedback intervention for specific phobias.

AIM: A new closed-loop functional magnetic resonance imaging method called multivoxel neuroreinforcement has the potential to alleviate the subjective aversiveness of exposure-based interventions by directly inducing phobic representations in the brain, outside of conscious awareness. The current study seeks to test this method as an intervention for specific phobia. METHODS: In a randomized, double-blind, controlled single-university trial, individuals diagnosed with at least two (one target, one control) animal subtype-specific phobias were randomly assigned (1:1:1) to receive one, three, or five sessions of multivoxel neuroreinforcement in which they were rewarded for implicit activation of a target animal representation. Amygdala response to phobic stimuli was assessed by study staff blind to target and control animal assignments. Pretreatment to posttreatment differences were analyzed with a two-way repeated-measures anova. RESULTS: A total of 23 participants (69.6% female) were randomized to receive one (n = 8), three (n = 7), or five (n = 7) sessions of multivoxel neuroreinforcement. Eighteen (n = 6 each group) participants were analyzed for our primary outcome. After neuroreinforcement, we observed an interaction indicating a significant decrease in amygdala response for the target phobia but not the control phobia. No adverse events or dropouts were reported as a result of the intervention. CONCLUSION: Results suggest that multivoxel neuroreinforcement can specifically reduce threat signatures in specific phobia. Consequently, this intervention may complement conventional psychotherapy approaches with a nondistressing experience for patients seeking treatment. This trial sets the stage for a larger randomized clinical trial to replicate these results and examine the effects on real-life exposure. CLINICAL TRIAL REGISTRATION: The now-closed trial was prospectively registered at ClinicalTrials.gov with ID NCT03655262.

A double-blind trial of decoded neurofeedback intervention for specific phobias.

Aim: A new closed-loop fMRI method called multi-voxel neuro-reinforcement has the potential to alleviate the subjective aversiveness of exposure-based interventions by directly inducing phobic representations in the brain, outside of conscious awareness. The current study seeks to test this method as an intervention for specific phobia. Methods: In a randomized, double-blind, controlled single-university trial, individuals diagnosed with at least two (1 target, 1 control) animal subtype specific phobias were randomly assigned (1:1:1) to receive 1, 3, or 5 sessions of multi-voxel neuro-reinforcement in which they were rewarded for implicit activation of a target animal representation. Amygdala response to phobic stimuli was assessed by study staff blind to target and control animal assignments. Pre-treatment to post-treatment differences were analyzed with a 2-way repeated-measures ANOVA. Results: A total of 23 participants (69.6% female) were randomized to receive 1 (n=8), 3 (n=7), or 5 (n=7) sessions of multi-voxel neuro-reinforcement. Eighteen (n=6 each group) participants were analyzed for our primary outcome. After neuro-reinforcement, we observed an interaction indicating a significant decrease in amygdala response for the target phobia but not the control phobia. No adverse events or dropouts were reported as a result of the intervention. Conclusion: Results suggest multi-voxel neuro-reinforcement can specifically reduce threat signatures in specific phobia. Consequently, this intervention may complement conventional psychotherapy approaches with a non-distressing experience for patients seeking treatment. This trial sets the stage for a larger randomized clinical trial to replicate these results and examine the effects on real-life exposure. Clinical Trial Registration: The now-closed trial was prospectively registered at ClinicalTrials.gov with ID NCT03655262.

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'.

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.

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.

Consciousness beyond the human case.

There is growing interest in the relationship been AI and consciousness. Joseph LeDoux and Jonathan Birch thought it would be a good moment to put some of the big questions in this area to some leading experts. The challenge of addressing the questions they raised was taken up by Kristin Andrews, Nicky Clayton, Nathaniel Daw, Chris Frith, Hakwan Lau, Megan Peters, Susan Schneider, Anil Seth, Thomas Suddendorf, and Marie Vanderkerckhoeve.

Natural statistics support a rational account of confidence biases.

Previous work has sought to understand decision confidence as a prediction of the probability that a decision will be correct, leading to debate over whether these predictions are optimal, and whether they rely on the same decision variable as decisions themselves. This work has generally relied on idealized, low-dimensional models, necessitating strong assumptions about the representations over which confidence is computed. To address this, we used deep neural networks to develop a model of decision confidence that operates directly over high-dimensional, naturalistic stimuli. The model accounts for a number of puzzling dissociations between decisions and confidence, reveals a rational explanation of these dissociations in terms of optimization for the statistics of sensory inputs, and makes the surprising prediction that, despite these dissociations, decisions and confidence depend on a common decision variable.

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.

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.

Do we understand the prefrontal cortex?

Many suggestions have been made as to the functions of the prefrontal (PF) cortex. However, they involve labelling areas using psychological terminology. But what we need to know is how the PF cortex operates. We argue that understanding this must start with describing the flow of information. We illustrate this argument by considering three PF areas. Each has a unique pattern of inputs and outputs, and we suggest that the implication is that each performs a unique transformation from the inputs to the outputs. The caudal PF cortex transforms input that is maintained by attention or short-term memory into the target of the appropriate eye movement. The mid-dorsal PF cortex transforms input concerning the order of objects or actions into the target of the appropriate eye and hand movements, thus supporting sequences of action. The ventral PF cortex transforms input concerning an object or sound into prospective activity that encodes the associated object or sound. However, it is important to appreciate that the mid-dorsal and ventral PF cortex are specialized for encoding abstract transformations, irrespective of the specific actions or objects. The advantage is that this enables generalization to novel problems that have the same underlying logic. We account for the difference between fast learning and slow learning in this way. The human brain has co-opted these mechanisms so as to support intelligence. Non-verbal tests of IQ typically use sequences of letters, numbers or designs. These test the ability to understand the abstract rules that apply. Here the activations lie in the mid-dorsal PF cortex. Verbal tests typically assess the ability to understand semantic associations. These can be presented either in pictorial or verbal form. Here the activations lie in the ventral PF cortex.

Subjective experiences as nodes within mental disorder networks.

What are the functional roles of subjective experiences? Answering this question amounts to charting a course for the cognitive science of consciousness, where mental processes can be described in terms of their functions. If we strategically focus on mental disorders, preliminary answers may be in sight within 25 years.

Consensus Goals in the Field of Visual Metacognition.

Despite the tangible progress in psychological and cognitive sciences over the last several years, these disciplines still trail other more mature sciences in identifying the most important questions that need to be solved. Reaching such consensus could lead to greater synergy across different laboratories, faster progress, and increased focus on solving important problems rather than pursuing isolated, niche efforts. Here, 26 researchers from the field of visual metacognition reached consensus on four long-term and two medium-term common goals. We describe the process that we followed, the goals themselves, and our plans for accomplishing these goals. If this effort proves successful within the next few years, such consensus building around common goals could be adopted more widely in psychological science.

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.

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.

Evidence for Transcranial Magnetic Stimulation Induced Functional Connectivity Oscillations in the Brain.

Transcranial magnetic stimulation (TMS) is an effective research tool to elucidate mechanisms of function in the brain. Despite its widespread use, very few studies have looked at dynamic functional connectivity responses to TMS. This work performs an exploratory analysis of dynamic functional network connectivity (dynFNC) to evaluate evidence of brain response to TMS. Results show clear functional dynamic patterns categorized by frequency. Some patterns appear to be more directly linked to TMS, but there is one pattern that might be a TMS-independent response to the excitation. This first look presents an analysis methodology and important results to consider in future research.

Is blindsight possible under signal detection theory? Comment on Phillips (2021).

Phillips argues that blindsight is due to response criterion artifacts under degraded conscious vision. His view provides alternative explanations for some studies, but may not work well when one considers several key findings in conjunction. Empirically, not all criterion effects are decidedly nonperceptual. Awareness is not completely abolished for some stimuli, in some patients. But in other cases, it is clearly impaired relative to the corresponding visual sensitivity. This relative dissociation is what makes blindsight so important and interesting. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Transcranial magnetic stimulation alters multivoxel patterns in the absence of overall activity changes.

Transcranial magnetic stimulation (TMS) has become one of the major tools for establishing the causal role of specific brain regions in perceptual, motor, and cognitive processes. Nevertheless, a persistent limitation of the technique is the lack of clarity regarding its precise effects on neural activity. Here, we examined the effects of TMS intensity and frequency on concurrently recorded blood-oxygen-level-dependent (BOLD) signals at the site of stimulation. In two experiments, we delivered TMS to the dorsolateral prefrontal cortex in human subjects of both sexes. In Experiment 1, we delivered a series of pulses at high (100% of motor threshold) or low (50% of motor threshold) intensity, whereas, in Experiment 2, we always used high intensity but delivered stimulation at four different frequencies (5, 8.33, 12.5, and 25 Hz). We found that the TMS intensity and frequency could be reliably decoded using multivariate analysis techniques even though TMS had no effect on the overall BOLD activity at the site of stimulation in either experiment. These results provide important insight into the mechanisms through which TMS influences neural activity.

Attention Drifting In and Out: The Boredom Feedback Model.

We synthesize established and emerging research to propose a feedback process model that explicates key antecedents, experiences, and consequences of the emotion boredom. The proposed Boredom Feedback Model posits that the dynamic process of boredom resembles a feedback loop that centers on attention shifts instigated by inadequate attentional engagement. Inadequate attentional engagement is a discrepancy between desired and actual levels of attentional engagement and is a product of external and internal influences, reflected in objective resources and cognitive appraisals. The model sheds light on several essential yet unresolved puzzles in the literature, including how people learn to cope with boredom, how to understand the relation between self-control and boredom, how the roles of attention and meaning in boredom can be integrated, why boredom is associated with both high- and low-arousal negative emotions, and what contributes to chronic boredom. The model offers testable hypotheses for future research.