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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., (© 2024 The Author(s). Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.)

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., (© 2024 The Author(s). Psychiatry and Clinical Neurosciences published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.)

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of National Academy of Sciences.)

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 Author(s) 2020. Published by Oxford University Press.)

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.

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., Competing Interests: Conflict of interest statement: M.K. is the inventor of patents related to the DecNef method used in this study, and the original assignee of the patents is Advanced Telecommunications Research Institute International, with which the authors are affiliated., (Copyright © 2018 the Author(s). Published by PNAS.)

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.

Motor representations in the human mirror neuron system are tuned to respond to specific observed actions. This ability is widely believed to be influenced by genetic factors, but no study has reported a genetic variant affecting this system so far. One possibility is that genetic variants might interact with visuomotor associative learning to configure the system to respond to novel observed actions. In this perspective, we conducted a candidate gene study on the Brain-derived neurotrophic factor (BDNF) Val66Met polymorphism, a genetic variant linked to motor learning in regions of the mirror neuron system, and tested the effect of this polymorphism on motor facilitation and visuomotor associative learning. In a single-pulse TMS study carried on 16 Met (Val/Met and Met/Met) and 16 Val/Val participants selected from a large pool of healthy volunteers, Met participants showed significantly less muscle-specific corticospinal sensitivity during action observation, as well as reduced visuomotor associative learning, compared to Val homozygotes. These results are the first evidence of a genetic variant tuning sensitivity to action observation and bring to light the importance of considering the intricate relation between genetics and associative learning in order to further understand the origin and function of the human mirror neuron system.

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.

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.

Unlabelled: Vicarious pain has been shown to enhance observers' nociceptive reactivity and pain perception. We exposed healthy participants to specific parts of facial pain expressions in order to investigate which components are required to induce this modulation. We created 2 classes of stimuli: one containing the most useful information for identification of pain expressions (diagnostic) and one containing the least useful information (antidiagnostic). Twenty-eight normal volunteers received electrical stimulation of the sural nerve immediately after they viewed these stimuli. Subjective ratings (intensity and unpleasantness) as well as the nociceptive flexion reflex (NFR) evoked by the shock were recorded. Results show that diagnostic stimuli lead to higher subjective ratings of shock pain than the antidiagnostic stimuli, but the stimuli classes had no significant impact on the NFR. A control experiment showed that our facial stimuli were given very low valence and arousal ratings compared to stimuli previously used to demonstrate the effect of emotional pictures on pain. Thus, the results are unlikely to be explained by emotions felt by the observer and suggest a vicarious facilitation of supraspinal pain processing induced by key features underlying pain expressions recognition. Results provide further support to the perception-action model of empathy., Perspective: This study demonstrates that visual features that are efficiently used for the recognition of pain expressions are sufficient to induce a vicarious facilitation of self-pain. Supraspinal pain responses were modulated by the informativeness of the areas of the pain expressions that participants viewed prior to the painful stimulations., (Copyright © 2013 American Pain Society. Published by Elsevier Inc. All rights reserved.)

According to an influential view, based on studies of development and of the face inversion effect, human face recognition relies mainly on the treatment of the distances among internal facial features. However, there is surprisingly little evidence supporting this claim. Here, we first use a sample of 515 face photographs to estimate the face recognition information available in interattribute distances. We demonstrate that previous studies of interattribute distances generated faces that exaggerated by 376% this information compared to real-world faces. When human observers are required to recognize faces solely on the basis of real-world interattribute distances, they perform poorly across a broad range of viewing distances (equivalent to 2 to more than 16 m in the real-world). In contrast, recognition is almost perfect when observers recognize faces on the basis of real-world information other than interattribute distances such as attribute shapes and skin properties. We conclude that facial cues other than interattribute distances such as attribute shapes and skin properties are the dominant information of face recognition mechanisms.