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Taschereau-Dumouchel, V.

Publications and source records attributed to Taschereau-Dumouchel, V..

8 recordsLinked to original sources

Bidirectional modulation of pain by neurofeedback: Preliminary findings with fMRI at 7T

Previous brain decoding studies indicate that an individuals pain experience can be robustly predicted from distributed patterns of brain activity. Two brain decoders have notably been associated respectively with the nociceptive and cognitive aspects of pain experience, the Neurologic Pain Signature (NPS) and the Stimulus-Intensity Independent Pain Signature (SIIPS). Yet, we still do not know if these brain patterns are also causally related to pain experience. To evaluate this possibility, we used high-field (7-Tesla) fMRI to test whether humans can alter their pain experience by bidirectionally modulating their pain-related brain activity in decoded neurofeedback paradigm. In a double-blind design, participants were trained to up- and down-regulate the NPS or the SIIPS. Our results indicate that participants can achieve bidirectional control of both signatures. NPS expression reliably increased during pain stimulation and covaried with both stimulus intensity and subjective ratings. In contrast, SIIPS expression did not show consistent stimulus-locked effects in the primary analyses. Importantly, reduction in pain rating was specific for SIIPS-training, whereas NPS has failed to show any consistent behavioral effect. Based on these preliminary findings, we hereby preregister a follow-up study, with specified rationale, hypotheses, experimental design, and analysis protocols.

neuroscience↗

Representation of visual uniformity in the lateral prefrontal cortex

Visual illusions tend to have early visual cortical correlates. However, this general trend may not apply to our subjective impression of a detailed and uniform visual world, which may be considered illusory given the paucity of peripheral processing. Using a psychophysically calibrated visual illusion, we assessed the patterns of hemodynamic activity in the human brain that distinguished between the illusory percept of uniformity in the periphery (i.e., Gabor patches having identical orientations) from the accurate perception of incoherence. We identified voxel patterns in the lateral prefrontal cortex that predicted perceived uniformity, which could also generalize to scene uniformity in naturalistic movies. Because similar representations of visual uniformity can also be found in the intermediate and late layers of a feedforward convolutional neural network, the perception of uniformity may involve high-level coding of abstract properties of the entire scene as a whole, that is distinct from the filling-in of specific details in early visual areas.

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Modulating Subjective Pain Perception with Decoded MNI-space Neurofeedback

Pain is a complex emotional experience that still remains challenging to manage. Previous functional magnetic resonance imaging (fMRI) studies have associated pain with distributed patterns of brain activity (i.e., brain decoders), but it is still unclear whether these observations reflect causal mechanisms. To address this question, we devised a new neurofeedback approach leveraging real-time decoding of fMRI data to test if modulating pain-related multivoxel fMRI patterns could lead to changes in subjective pain experience. We first showed that subjective pain ratings can indeed be accurately predicted using a real-time decoding approach based on the stimulus intensity independent pain signature (SIIPS) and the neurologic pain signature (NPS). Next, we trained participants in a double-blinded decoded fMRI neurofeedback experiment to up- or down-regulate the SIIPS. Our results indicate that participants can learn to down-regulate the expression of SIIPS independently from NPS expression. Importantly, the success of this neurofeedback training was associated with the perceived intensity of painful stimulation following the intervention. Taken together, these results indicate that closed-loop brain imaging can be efficiently conducted using a priori fMRI decoders of pain, potentially opening up a new range of applications for decoded neurofeedback, both for clinical and basic science purposes.

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 hemodynamic 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 individuals 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 hemodynamic 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.

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Multivoxel Neural Reinforcement Changes Resting-State Functional Connectivity Within the Threat Regulation Network

Using neural reinforcement, participants can be trained to pair a reward with the activation of specific multivoxel patterns in their brains. In a double-blind placebo-controlled experiment, we previously showed that this intervention can decrease the physiological reactivity associated with naturally feared animals. However, the mechanisms behind the effect remain incompletely understood and its usefulness for treatment remains unclear. If the intervention fundamentally changed the brain responses, we might expect to observe relatively stable changes in the functional connectivity within the threat regulation network. To evaluate this possibility, we conducted functional magnetic resonance imaging (fMRI) sessions while subjects were at rest, before and after neural reinforcement, and quantified the changes in resting-state functional connectivity accordingly. Our results indicate that neural reinforcement increased the connectivity of prefrontal regulatory regions with the amygdala and the ventral temporal cortex (where the visual representations of phobic targets are). Surprisingly, we found no evidence of Hebbian-like learning during neural reinforcement, contrary to what one may expect based on previous neurofeedback studies. These results suggest that multivoxel neural reinforcement, also known as decoded neurofeedback (DecNef), may operate via unique mechanisms, distinct from those involved in conventional neurofeedback.

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Multivoxel patterns for perceptual confidence are associated with false color detection

While it has been proposed that metacognition and conscious perception are related, the mechanistic relationship between the two is unclear. To address this question, we combined decoded neurofeedback (DecNef) in functional magnetic resonance imaging (fMRI) with concurrent psychophysics. Participants were rewarded for activating multivoxel patterns for color discrimination confidence while they detected color in mostly achromatic stimuli. We found that occurences of voxel patterns for high color discrimination confidence were associated with false alarms in the concurrent color detection task, suggesting a link between discrimination confidence and consciousness.

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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 analysis on functional magnetic resonance imaging (fMRI) data to assess this issue in the case of fear. Participants were presented with pictures of commonly feared animals in an fMRI experiment. Multivoxel brain activity decoders were trained to predict participants subjective fear ratings and their skin conductance reactivity, respectively. While subjective fear and objective physiological responses were correlated in general, the respective whole-brain multivoxel decoders for the two measures were not identical. Some key brain regions such as the amygdala and insula appear to be primarily involved in the prediction of physiological reactivity, while 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 latters being objectively and continuously measurable in physiological terms.

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Towards an Unconscious Neurotherapy for Common Fears

Can evolutionarily hardwired fear responses, e.g. for spiders and snakes, be reprogramed unconsciously in the human brain? Currently, exposure therapy is amongst the most effective treatments for anxiety disorders1, but this intervention is subjectively aversive to patients, and rates of premature attrition from treatment have been reported to be as high as 70%2. Here we introduce a novel method to bypass the subjective unpleasantness in conscious exposure, by directly pairing monetary reward with unconscious occurrences of decoded representations of naturally feared objects in the brain. The typical way to identify multivoxel functional magnetic resonance imaging (fMRI) representations for feared objects involves repeated presentations of the relevant images explicitly to subjects. However, for our potential treatment method to be effective in actual clinical settings, we need to decode fear representations without triggering excessively aversive reactions which may cause patients to dropout from treatments prematurely. Here we overcome this challenge by capitalizing on recent advancements in fMRI decoding techniques: We employed a method called hyperalignment3,4 to infer the relevant representations of feared objects for a designated participant based on data from other surrogate participants. This way the procedure completely bypasses the need for the conscious encountering of feared objects. We demonstrate that our method can lead to reliable reductions in physiological fear responses measured by skin conductance as well as amygdala hemodynamic activity. Not only do these results raise the intriguing possibility that naturally occurring fear can be re-programmed outside of conscious awareness, importantly they also created the rare opportunity for a psychological intervention of this nature to be tested rigorously in a double-blind placebo-controlled fashion. This may pave the way for a novel treatment method, combining the appealing rationale and proven efficacy of conventional psychotherapy with the rigor and leverage of clinical neuroscience.

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