An examination of intolerance of uncertainty effects on subjective, psychophysiological, and neural markers during uninstructed and instructed threat acquisition and extinction training

Extinction Training ◽

Fmri Data ◽

Future Research ◽

Resonance Imaging ◽

Tentative Evidence

Individuals who score high in self-reported Intolerance of Uncertainty (IU) tend to find uncertainty aversive. Prior research has demonstrated that under uncertainty individuals with high IU display difficulties in updating learned threat associations to safety associations. Importantly, recent research has shown that providing contingency instructions about threat and safety contingencies (i.e. reducing uncertainty) to individuals with high IU promotes the updating of learned threat associations to safety associations. Here we aimed to conceptually replicate IU and contingency instruction-based effects by conducting a secondary analysis of self-reported IU, ratings, skin conductance, and functional magnetic resonance imaging (fMRI) data recorded during uninstructed/instructed blocks of threat acquisition and threat extinction training (n = 48). Self-reported IU was not associated with differential responding to learned threat and safety cues for any measure during uninstructed/instructed blocks of threat acquisition and threat extinction training. There was some tentative evidence that higher IU was associated with greater ratings of unpleasantness and arousal to the safety cue after the experiment and greater skin conductance response to the safety cue during extinction generally. Potential explanations for these null effects and directions for future research are discussed.

Consumer Neuroscience and its Application in Marketing

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c4248.118419 ◽

2019 ◽

Vol 8 (4) ◽

pp. 1607-1611

Keyword(s):

Magnetic Resonance ◽

Skin Conductance ◽

Market Research ◽

Future Research ◽

Resonance Imaging ◽

Consumer Neuroscience ◽

Basic Ideas

There is a very important difference between “Consumer neuroscience” and “Neuromarketing”. While the first field deals in research on subjects like neuroscience, psychology and marketing; the latter is linked to the functionality of neurophysiological tools, namely eye tracking, skin conductance, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). Neuromarketing is interested in carrying out market research which is specific to a particular company. This article covers topics like recent methods in neuroscience used by consumer researchers, basic ideas in consumer neuroscience derived on the basis of initial findings. The article also suggests ideas for future research in the field of consumer neuroscience.

I doubt it is safe: A meta-analysis of self-reported intolerance of uncertainty and threat extinction training

10.31234/osf.io/nrqv6 ◽

2021 ◽

Author(s):

Jayne Morriss ◽

Shannon Jade Wake ◽

Charlotte Elizabeth ◽

Carien M. van Reekum

Keyword(s):

Trait Anxiety ◽

Skin Conductance ◽

Skin Conductance Response ◽

Meta Analysis ◽

Mental Health Disorders ◽

Extinction Training ◽

The Self ◽

Target Uncertainty ◽

Health Disorders

Intolerance of uncertainty (IU), the tendency to find uncertainty distressing, is an important transdiagnostic dimension in mental health disorders. Higher self-reported IU has been linked to poorer threat extinction training (i.e., the updating of threat to safe associations), a key process that is targeted in exposure-based therapies. However, it remains to be seen whether IU-related effects during threat extinction training are reliably and specifically driven by the IU construct or a particular subcomponent of the IU construct over other self-reported measures of anxiety. A meta-analysis of studies from different laboratories (experiment n = 18; sample n = 1006) was conducted on associations between different variants of self-reported IU (i.e., 27-item, 12-item, inhibitory and prospective subscales), trait anxiety and threat extinction training via skin conductance response. The specificity of IU and threat extinction training was assessed against measures of trait anxiety. All of the self-reported variants of IU, but not trait anxiety, were associated with threat extinction training via skin conductance response (i.e., continued responding to the old threat cue). Specificity was observed for the majority of self-reported variants of IU over of trait anxiety. The findings suggest that the IU construct broadly accounts for difficulties in threat extinction training and is specific over other measures of self-reported anxiety. These findings demonstrate the robustness and specificity of IU-related effects during threat extinction training and highlight potential opportunities for translational work to target uncertainty in therapies that rely on threat extinction principles such as exposure therapy.

Informative Biomarkers for Autism Spectrum Disorder Diagnosis in Functional Magnetic Resonance Imaging Data on the Default Mode Network

Applied Sciences ◽

10.3390/app11136216 ◽

2021 ◽

Vol 11 (13) ◽

pp. 6216

Author(s):

Aikaterini S. Karampasi ◽

Antonis D. Savva ◽

Vasileios Ch. Korfiatis ◽

Ioannis Kakkos ◽

George K. Matsopoulos

Keyword(s):

Autism Spectrum Disorder ◽

Magnetic Resonance ◽

Default Mode Network ◽

Autism Spectrum ◽

Fmri Data ◽

Resonance Imaging ◽

Dynamic Connectivity

Effective detection of autism spectrum disorder (ASD) is a complicated procedure, due to the hundreds of parameters suggested to be implicated in its etiology. As such, machine learning methods have been consistently applied to facilitate diagnosis, although the scarcity of potent autism-related biomarkers is a bottleneck. More importantly, the variability of the imported attributes among different sites (e.g., acquisition parameters) and different individuals (e.g., demographics, movement, etc.) pose additional challenges, eluding adequate generalization and universal modeling. The present study focuses on a data-driven approach for the identification of efficacious biomarkers for the classification between typically developed (TD) and ASD individuals utilizing functional magnetic resonance imaging (fMRI) data on the default mode network (DMN) and non-physiological parameters. From the fMRI data, static and dynamic connectivity were calculated and fed to a feature selection and classification framework along with the demographic, acquisition and motion information to obtain the most prominent features in regard to autism discrimination. The acquired results provided high classification accuracy of 76.63%, while revealing static and dynamic connectivity as the most prominent indicators. Subsequent analysis illustrated the bilateral parahippocampal gyrus, right precuneus, midline frontal, and paracingulate as the most significant brain regions, in addition to an overall connectivity increment.

Intolerance of uncertainty is associated with heightened responding in the prefrontal cortex during instructed threat of shock

10.1101/2020.05.23.112268 ◽

2020 ◽

Author(s):

Jayne Morriss ◽

Tiffany Bell ◽

Nicolò Biagi ◽

Tom Johnstone ◽

Carien M. van Reekum

Keyword(s):

Prefrontal Cortex ◽

Anxiety Disorder ◽

Neural Circuitry ◽

Resonance Imaging ◽

Prefrontal Cortical ◽

Cortical Regions ◽

Rostral Prefrontal Cortex ◽

Threat Of Shock

AbstractHeightened responding to uncertain threat is associated with anxiety disorder pathology. Here, we sought to determine if individual differences in self-reported intolerance of uncertainty (IU) underlie differential recruitment of neural circuitry during instructed threat of shock (n = 42). During the task, cues signalled uncertain threat of shock (50%) or certain safety from shock. Ratings, skin conductance and functional magnetic resonance imaging was acquired. Overall, participants displayed greater amygdala activation to uncertain threat vs. safe cues, in the absence of an effect of IU. However, we found that high was associated with greater activity in the medial prefrontal cortex and dorsomedial rostral prefrontal cortex to uncertain threat vs safe cues. These findings suggest that, during instructed threat of shock, IU is specifically related, over trait anxiety, to activation in prefrontal cortical regions. Taken together, these findings highlight the potential of self-reported IU in identifying mechanisms that may be related to conscious threat appraisal and anxiety disorder pathology.

The role of intolerance of uncertainty in the acquisition and extinction of reward

10.1101/2020.05.18.101212 ◽

2020 ◽

Author(s):

Jayne Morriss ◽

Nicolo Biagi ◽

Tina B. Lonsdorf ◽

Marta Andreatta

Keyword(s):

Associative Learning ◽

Conceptual Understanding ◽

Skin Conductance Response ◽

Acquisition Training ◽

Learning Task ◽

Partial Reward ◽

Extinction Training ◽

Corrugator Supercilii

AbstractIndividuals, who score high in self-reported intolerance of uncertainty (IU), tend to find uncertainty anxiety-provoking. IU has been reliably associated with disrupted threat extinction. However, it remains unclear whether IU would be related to disrupted extinction to other arousing stimuli that are not threatening (i.e., rewarding). We addressed this question by conducting a reward associative learning task with acquisition and extinction training phases (n = 58). Throughout the associative learning task, we recorded valence ratings (i.e. liking), skin conductance response (SCR) (i.e. sweating), and corrugator supercilii activity (i.e. brow muscle indicative or negative and positive affect) to learned reward and neutral cues. During acquisition training with partial reward reinforcement, higher IU was associated with greater corrugator supercilii activity to neutral compared to reward cues. IU was not related to valence ratings or SCR’s during the acquisition or extinction training phases. These preliminary results suggest that IU-related deficits during extinction may be limited to situations with threat. The findings further our conceptual understanding of IU’s role in the associative learning and extinction of reward, and in relation to the processing of threat and reward more generally.

Effects of intolerance of uncertainty on subjective and psychophysiological measures during fear acquisition and delayed extinction

10.31234/osf.io/hj5gt ◽

2021 ◽

Author(s):

Maren Klingelhöfer-Jens ◽

Jayne Morriss ◽

Tina B Lonsdorf

Keyword(s):

Fear Conditioning ◽

Skin Conductance ◽

Acquisition Training ◽

Extinction Training ◽

Future Directions ◽

Psychophysiological Measures ◽

Learned Fear ◽

Startle Blink

Individuals who score high in self-reported Intolerance of Uncertainty (IU) tend to find uncertainty unacceptable and aversive. In recent years, research has shed light on the role of IU in modulating subjective (i.e. expectancy ratings) and psychophysiological responses (i.e. skin conductance) across different classical fear conditioning procedures, particularly that of immediate extinction. However, there remain gaps in understanding how IU, in comparison to other negative emotionality traits (STAI-T), impact different types of subjective and psychophysiological measures during different classical fear conditioning procedures. Here, we analyzed IU, STAI-T, subjective (i.e. fear ratings) and psychophysiological (i.e. skin conductance, auditory startle blink) data recorded during fear acquisition training and 24h-delayed extinction training (n = 66). Higher IU, over STAI-T, was: (1) significantly associated with greater fear ratings to the learned fear cue during fear acquisition training, and (2) at trend associated with greater fear ratings to the learned fear versus safe cue during delayed extinction training. Both IU and STAI-T were not related to skin conductance or auditory startle blink during fear acquisition training and delayed extinction training. These results add to and extend our current understanding of the role of IU on subjective and physiological measures during different fear conditioning procedures, particularly that of delayed extinction training. Implications of these findings and future directions are discussed.

Handbook of Research on Applied Cybernetics and Systems Science - Advances in Computational Intelligence and Robotics ◽

Statistical Analysis of Functional Magnetic Resonance Imaging Data

10.4018/978-1-5225-2498-4.ch005 ◽

2017 ◽

pp. 103-114

Author(s):

Nicole A. Lazar

Keyword(s):

Data Analysis ◽

Statistical Analysis ◽

Magnetic Resonance ◽

Temporal Correlation ◽

Fmri Data ◽

Imaging Data ◽

Resonance Imaging

The analysis of functional magnetic resonance imaging (fMRI) data poses many statistical challenges. The data are massive, noisy, and have a complicated spatial and temporal correlation structure. This chapter introduces the basics of fMRI data collection and surveys common approaches for data analysis.

Progressively analogous evidence of covert face recognition from functional magnetic resonance imaging and skin conductance responses studies involving a patient with dissociative amnesia

European Journal of Neuroscience ◽

10.1111/ejn.14087 ◽

2018 ◽

Vol 48 (3) ◽

pp. 1964-1975 ◽

Cited By ~ 2

Author(s):

Natalya Chechko ◽

Susanne Stickel ◽

Thilo Kellermann ◽

Andre Kirner ◽

Ute Habel ◽

...

Keyword(s):

Face Recognition ◽

Magnetic Resonance ◽

Skin Conductance ◽

Resonance Imaging ◽

Dissociative Amnesia ◽

Skin Conductance Responses

Language Functional Magnetic Resonance Imaging in Preoperative Assessment of Language Areas: Correlation with Direct Cortical Stimulation

Neurosurgery ◽

10.1227/01.neu.0000064803.05077.40 ◽

2003 ◽

Vol 52 (6) ◽

pp. 1335-1347 ◽

Cited By ~ 287

Author(s):

Franck-Emmanuel Roux ◽

Kader Boulanouar ◽

Jean-Albert Lotterie ◽

Mehdi Mejdoubi ◽

James P. LeSage ◽

...

Keyword(s):

Magnetic Resonance ◽

Left Hemisphere ◽

Brain Mapping ◽

Fmri Data ◽

Resonance Imaging ◽

Verb Generation ◽

Language Areas

Abstract OBJECTIVE The aim of this study was to analyze the usefulness of preoperative language functional magnetic resonance imaging (fMRI), by correlating fMRI data with intraoperative cortical stimulation results for patients with brain tumors. METHODS Naming and verb generation tasks were used, separately or in combination, for 14 right-handed patients with tumors in the left hemisphere. fMRI data obtained were analyzed with SPM software, with two standard analysis thresholds (P < 0.005 and then P < 0.05). The fMRI data were then registered in a frameless stereotactic neuronavigational device and correlated with direct brain mapping results. We used a statistical model with the fMRI information as a predictor, spatially correlating each intraoperatively mapped cortical site with fMRI data integrated in the neuronavigational system (site-by-site correlation). Eight patients were also studied with language fMRI postoperatively, with the same acquisition protocol. RESULTS We observed high variability in signal extents and locations among patients with both tasks. The activated areas were located mainly in the left hemisphere in the middle and inferior frontal gyri (F2 and F3), the superior and middle temporal gyri (T1 and T2), and the supramarginal and angular gyri. A total of 426 cortical sites were tested for each task among the 14 patients. In frontal and temporoparietal areas, poor sensitivity of the fMRI technique was observed for the naming and verb generation tasks (22 and 36%, respectively) with P < 0.005 as the analysis threshold. Although not perfect, the specificity of the fMRI technique was good in all conditions (97% for the naming task and 98% for the verb generation task). Better correlation (sensitivity, 59%; specificity, 97%) was achieved by combining the two fMRI tasks. Variation of the analysis threshold to P < 0.05 increased the sensitivity to 66% while decreasing the specificity to 91%. Postoperative fMRI data (for the cortical brain areas studied intraoperatively) were in accordance with brain mapping results for six of eight patients. Complete agreement between pre- and postoperative fMRI studies and direct brain mapping results was observed for only three of eight patients. CONCLUSION With the paradigms and analysis thresholds used in this study, language fMRI data obtained with naming or verb generation tasks, before and after surgery, were imperfectly correlated with intraoperative brain mapping results. A better correlation could be obtained by combining the fMRI tasks. The overall results of this study demonstrated that language fMRI could not be used to make critical surgical decisions in the absence of direct brain mapping. Other acquisition protocols are required for evaluation of the potential role of language fMRI in the accurate detection of essential cortical language areas.

Methods of Predicting the Brain Activity Based on Noun

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.2516 ◽

2013 ◽

Vol 347-350 ◽

pp. 2516-2520

Author(s):

Jian Hua Jiang ◽

Xu Yu ◽

Zhi Xing Huang

Keyword(s):

Brain Activity ◽

Past Research ◽

Neural Representation ◽

Fmri Data ◽

Semantic Features ◽

Resonance Imaging ◽

The Past ◽

Machine Learning Methods ◽

The Brain

Over the last decade, functional magnetic resonance imaging (fMRI) has become a primary tool to predict the brain activity.During the past research, researchers transfer the focus from the picture to the word.The results of these researches are relatively successful. In this paper, several typical methods which are machine learning methods are introduced. And most of the methods are by using fMRI data associated with words features. The semantic features (properties or factors) support words neural representation, and have a certain commonality in the people.The purpose of the application of these methods is used for prediction or classification.