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      Exploring the Use of Thermal Infrared Imaging in Human Stress Research

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          Abstract

          High resolution thermal infrared imaging is a pioneering method giving indices of sympathetic activity via the contact-free recording of facial tissues (thermal imprints). Compared to established stress markers, the great advantage of this method is its non-invasiveness. The goal of our study was to pilot the use of thermal infrared imaging in the classical setting of human stress research. Thermal imprints were compared to established stress markers (heart rate, heart rate variability, finger temperature, alpha-amylase and cortisol) in 15 participants undergoing anticipation, stress and recovery phases of two laboratory stress tests, the Cold Pressor Test and the Trier Social Stress Test. The majority of the thermal imprints proved to be change-sensitive in both tests. While correlations between the thermal imprints and established stress markers were mostly non-significant, the thermal imprints (but not the established stress makers) did correlate with stress-induced mood changes. Multivariate pattern analysis revealed that in contrast to the established stress markers the thermal imprints could not disambiguate anticipation, stress and recovery phases of both tests. Overall, these results suggest that thermal infrared imaging is a valuable method for the estimation of sympathetic activity in the stress laboratory setting. The use of this non-invasive method may be particularly beneficial for covert recordings, in the study of special populations showing difficulties in complying with the standard instruments of data collection and in the domain of psychophysiological covariance research. Meanwhile, the established stress markers seem to be superior when it comes to the characterization of complex physiological states during the different phases of the stress cycle.

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          Most cited references30

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          Salivary cortisol as a biomarker in stress research.

          Salivary cortisol is frequently used as a biomarker of psychological stress. However, psychobiological mechanisms, which trigger the hypothalamus-pituitary-adrenal axis (HPAA) can only indirectly be assessed by salivary cortisol measures. The different instances that control HPAA reactivity (hippocampus, hypothalamus, pituitary, adrenals) and their respective modulators, receptors, or binding proteins, may all affect salivary cortisol measures. Thus, a linear relationship with measures of plasma ACTH and cortisol in blood or urine does not necessarily exist. This is particularly true under response conditions. The present paper addresses several psychological and biological variables, which may account for such dissociations, and aims to help researchers to rate the validity and psychobiological significance of salivary cortisol as an HPAA biomarker of stress in their experiments.
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            The neurobiology of stress: from serendipity to clinical relevance.

            B S McEwen (2000)
            The hormones and other physiological agents that mediate the effects of stress on the body have protective and adaptive effects in the short run and yet can accelerate pathophysiology when they are over-produced or mismanaged. Here we consider the protective and damaging effects of these mediators as they relate to the immune system and brain. 'Stress' is a principle focus, but this term is rather imprecise. Therefore, the article begins by noting two new terms, allostasis and allostatic load that are intended to supplement and clarify the meanings of 'stress' and 'homeostasis'. For the immune system, acute stress enhances immune function whereas chronic stress suppresses it. These effects can be beneficial for some types of immune responses and deleterious for others. A key mechanism involves the stress-hormone dependent translocation of immune cells in the blood to tissues and organs where an immune defense is needed. For the brain, acute stress enhances the memory of events that are potentially threatening to the organism. Chronic stress, on the other hand, causes adaptive plasticity in the brain, in which local neurotransmitters as well as systemic hormones interact to produce structural as well as functional changes, involving the suppression of ongoing neurogenesis in the dentate gyrus and remodelling of dendrites in the Ammon's horn. Under extreme conditions only does permanent damage ensue. Adrenal steroids tell only part of the story as far as how the brain adapts, or shows damage, and local tissue modulators - cytokines for the immune response and excitatory amino acid neurotransmitters for the hippocampus. Moreover, comparison of the effects of experimenter-applied stressors and psychosocial stressors show that what animals do to each other is often more potent than what experimenters do to them. And yet, even then, the brain is resilient and capable of adaptive plasticity. Stress-induced structural changes in brain regions such as the hippocampus have clinical ramifications for disorders such as depression, post-traumatic stress disorder and individual differences in the aging process.
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              Comparison of multivariate classifiers and response normalizations for pattern-information fMRI.

              A popular method for investigating whether stimulus information is present in fMRI response patterns is to attempt to "decode" the stimuli from the response patterns with a multivariate classifier. The sensitivity for detecting the information depends on the particular classifier used. However, little is known about the relative performance of different classifiers on fMRI data. Here we compared six multivariate classifiers and investigated how the response-amplitude estimate used (beta- or t-value) and different pattern normalizations affect classification performance. The compared classifiers were a pattern-correlation classifier, a k-nearest-neighbors classifier, Fisher's linear discriminant, Gaussian naïve Bayes, and linear and nonlinear (radial-basis-function kernel) support vector machines. We compared these classifiers' accuracy at decoding the category of visual objects from response patterns in human early visual and inferior temporal cortex acquired in an event-related design with BOLD fMRI at 3T using SENSE and isotropic voxels of about 2-mm width. Overall, Fisher's linear discriminant (with an optimal-shrinkage covariance estimator) and the linear support vector machine performed best. The pattern-correlation classifier often performed similarly as those two classifiers. The nonlinear classifiers never performed better and sometimes significantly worse than the linear classifiers, suggesting overfitting. Defining response patterns by t-values (or in error-standard-deviation units) rather than by beta estimates (in % signal change) to define the patterns appeared advantageous. Cross-validation by a leave-one-stimulus-pair-out method gave higher accuracies than a leave-one-run-out method, suggesting that generalization to independent runs (which more safely ensures independence of the test set) is more challenging than generalization to novel stimuli within the same category. Independent selection of fewer more visually responsive voxels tended to yield better decoding performance for all classifiers. Normalizing mean and standard deviation of the response patterns either across stimuli or across voxels had no significant effect on decoding performance. Overall our results suggest that linear decoders based on t-value patterns may perform best in the present scenario of visual object representations measured for about 60min per subject with 3T fMRI. Published by Elsevier Inc.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                27 March 2014
                : 9
                : 3
                : e90782
                Affiliations
                [1 ]Max Planck Institute for Human Cognitive and Brain Sciences, Department of Social Neuroscience, Leipzig, Germany
                [2 ]Institute of Advanced Biomedical Technologies (ITAB), G. d'Annunzio Foundation, Chieti, Italy
                [3 ]Department of Neuroscience and Imaging, G. d'Annunzio University, Chieti-Pescara, Italy
                University of Texas School of Public Health, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: VE TS. Performed the experiments: VE AM JAG DC. Analyzed the data: VE AM DC AT. Contributed reagents/materials/analysis tools: AM TS. Wrote the paper: VE AM JAG AT TS.

                Article
                PONE-D-13-32802
                10.1371/journal.pone.0090782
                3968009
                24675709
                371ab05e-f2ea-4237-9df3-3e63dea682a1
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 August 2013
                : 5 February 2014
                Page count
                Pages: 11
                Funding
                This work was supported by Max Planck Gesellschaft. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Psychophysics
                Physiology
                Physiological Processes
                Psychology
                Behavior
                Experimental Psychology
                Psychological Stress
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Social Sciences

                Uncategorized
                Uncategorized

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