Relevant bibliographies by topics / Neural stress processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Neural stress processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Neural stress processing"

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Weymar, Mathias, Lars Schwabe, Andreas Löw, and Alfons O. Hamm. "Stress Sensitizes the Brain: Increased Processing of Unpleasant Pictures after Exposure to Acute Stress." Journal of Cognitive Neuroscience 24, no. 7 (July 2012): 1511–18. http://dx.doi.org/10.1162/jocn_a_00174.

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A key component of acute stress is a surge in vigilance that enables a prioritized processing of highly salient information to promote the organism's survival. In this study, we investigated the neural effects of acute stress on emotional picture processing. ERPs were measured during a deep encoding task, in which 40 male participants categorized 50 unpleasant and 50 neutral pictures according to arousal and valence. Before picture encoding, participants were subjected either to the Socially Evaluated Cold Pressor Test (SECPT) or to a warm water control procedure. The exposure to the SECPT resulted in increased subjective and autonomic (heart rate and blood pressure) stress responses relative to the control condition. Viewing of unpleasant relative to neutral pictures evoked enhanced late positive potentials (LPPs) over centro-parietal scalp sites around 400 msec after picture onset. Prior exposure to acute stress selectively increased the LPPs for unpleasant pictures. Moreover, the LPP magnitude for unpleasant pictures following the SECPT was positively associated with incidental free recall performance 24 hr later. The present results suggest that acute stress sensitizes the brain for increased processing of cues in the environment, particularly priming the processing of unpleasant cues. This increased processing is related to later long-term memory performance.
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Sadeh, Naomi, Jeffrey M. Spielberg, Stacie L. Warren, Gregory A. Miller, and Wendy Heller. "Aberrant Neural Connectivity During Emotional Processing Associated With Posttraumatic Stress." Clinical Psychological Science 2, no. 6 (May 14, 2014): 748–55. http://dx.doi.org/10.1177/2167702614530113.

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Sinha, Rajita, Cheryl M. Lacadie, R. Todd Constable, and Dongju Seo. "Dynamic neural activity during stress signals resilient coping." Proceedings of the National Academy of Sciences 113, no. 31 (July 18, 2016): 8837–42. http://dx.doi.org/10.1073/pnas.1600965113.

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Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping.
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Meier, Jacqueline Katharina, Mathias Weymar, and Lars Schwabe. "Stress Alters the Neural Context for Building New Memories." Journal of Cognitive Neuroscience 32, no. 12 (December 2020): 2226–40. http://dx.doi.org/10.1162/jocn_a_01613.

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Stressful events affect mnemonic processing, in particular for emotionally arousing events. Previous research on the mechanisms underlying stress effects on human memory focused on stress-induced changes in the neural activity elicited by a stimulus. We tested an alternative mechanism and hypothesized that stress may already alter the neural context for successful memory formation, reflected in the neural activity preceding a stimulus. Therefore, 69 participants underwent a stress or control procedure before encoding neutral and negative pictures. During encoding, we recorded high-density EEG and analyzed—based on multivariate searchlight analyses—oscillatory activity and cross-frequency coupling patterns before stimulus onset that were predictive of memory tested 24 hr later. Prestimulus theta predicted subsequent memory in controls but not in stressed participants. Instead, prestimulus gamma predicted successful memory formation after stress, specifically for emotional material. Likewise, stress altered the patterns of prestimulus theta–beta and theta–gamma phase–amplitude coupling predictive of subsequent memory, again depending on the emotionality of the presented material. Our data suggest that stress changes the neural context for building new memories, tuning this neural context specifically to the encoding of emotionally salient events. These findings point to a yet unknown mechanism through which stressful events may change (emotional) memory formation.
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Liddell, Belinda J., Jessica Cheung, Tim Outhred, Pritha Das, Gin S. Malhi, Kim L. Felmingham, Angela Nickerson, et al. "Neural Correlates of Posttraumatic Stress Disorder Symptoms, Trauma Exposure, and Postmigration Stress in Response to Fear Faces in Resettled Refugees." Clinical Psychological Science 7, no. 4 (April 5, 2019): 811–25. http://dx.doi.org/10.1177/2167702619841047.

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Refugees are exposed to multiple traumatic events and postmigration stressors, elevating risk for posttraumatic stress disorder (PTSD), but there is limited research into how these factors affect emotional neural systems. Here, resettled refugees in Australia ( N = 85) completed a functional magnetic resonance imaging scan while viewing fear and neutral faces. We examined the influence of PTSD symptoms, cumulative trauma, and recent postmigration stress on neural reactivity and regional coupling within the refugee sample. Cumulative trauma and postmigration stress but not PTSD symptoms correlated with fear-related brain activity and connectivity. Trauma exposure correlated with stronger activity but overall decreased connectivity in the bilateral posterior insula/rolandic operculum, postcentral gyrus, ventral anterior cingulate cortex, and posterior cingulate gyrus. Postmigration stress correlated with fusiform gyrus hyperactivity and increased connectivity in face-processing networks. Findings highlight the impact of past trauma and recent postmigration stress on fear-related neural responses within refugees over and above PTSD symptoms.
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Hatou, K., A. P. Pamungkas, and T. Morimoto. "Image Processing by Artificial Neural Networks for Stress Diagnosis of Tomato." IFAC Proceedings Volumes 44, no. 1 (January 2011): 1768–72. http://dx.doi.org/10.3182/20110828-6-it-1002.02875.

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Matthews, Gerald, Jinchao Lin, and Ryan Wohleber. "Personality, Stress and Resilience." Psihologijske teme 26, no. 1 (2017): 139–62. http://dx.doi.org/10.31820/pt.26.1.6.

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Personality traits are consistently correlated with various indices of acute psychological stress response, including negative emotions and performance impairment. However, resilience is a complex personal characteristic with multiple neural and psychological roots. This article advocates a multifactorial approach to understanding resilience that recognizes the complexity of the topic both empirically and theoretically. The Trait-Stressor-Outcome (TSO) framework for organizing empirical data recognizes the multiplicity of traits, stressors and outcome metrics that may moderate stress response. Research requires a fine-grained data collection approach that discriminates multiple stress factors. Also, multiple layers of theory are necessary to explain individual differences in stress response, including biases in neural functioning, attentional processing, as well as styles of coping and emotion-regulation. Cognitive science differentiates multiple levels of explanation and allows for the integration of mechanisms at multiple levels of abstraction from the neural substrate. We illustrate the application of the multifactorial approach to collecting interpreting data on operator stress resulting from interaction with technology.
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Henckens, Marloes J. A. G., Floris Klumpers, Daphne Everaerd, Sabine C. Kooijman, Guido A. van Wingen, and Guillén Fernández. "Interindividual differences in stress sensitivity: basal and stress-induced cortisol levels differentially predict neural vigilance processing under stress." Social Cognitive and Affective Neuroscience 11, no. 4 (December 14, 2015): 663–73. http://dx.doi.org/10.1093/scan/nsv149.

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Neumeister, P., K. Feldker, C. Y. Heitmann, C. Buff, L. Brinkmann, M. Bruchmann, and T. Straube. "Specific amygdala response to masked fearful faces in post-traumatic stress relative to other anxiety disorders." Psychological Medicine 48, no. 7 (September 27, 2017): 1209–17. http://dx.doi.org/10.1017/s0033291717002513.

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AbstractBackgroundAltered amygdala activation to fear-related stimuli has been proposed to be a potential neural correlate of heightened threat sensitivity in anxiety- and stress-related disorders. However, the role of stimulus awareness and disorder specificity remains widely unclear. Here we investigated amygdala responses to conscious and unconscious fearful faces in patients suffering from panic disorder (PD), generalized anxiety disorder (GAD), or post-traumatic stress disorder (PTSD) and in a large sample of healthy controls (HC).MethodsDuring event-related functional magnetic resonance imaging participants (n = 120; 20 PD, 20 GAD, 20 PTSD, 60 HC) were confronted with briefly presented fearful faces, neutral faces, and non-faces in a backward masking paradigm. The design allowed for the analysis of trial-by-trial face detection performance and amygdala responses to fearful v. neutral faces.ResultsAll participants exhibited increased amygdala activation to fearful v. neutral faces during conscious trials. Specifically during unconscious face processing, the PTSD, compared with all other groups, showed higher right basolateral (BLA) amygdala activity to fearful v. neutral faces.ConclusionsThe present study shows that BLA amygdala hyperactivity during unconscious, but not conscious, processing of fearful faces differentiates PTSD from the investigated disorders. This finding suggests an automatic and specific neural hyper-responsivity to general fear cues in PTSD and supports the idea of categorical differences between PTSD and other anxiety-related disorders.
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Sanjuan, Pilar M., Chloe Andrews, and Eric D. Claus. "Abnormal target detection and novelty processing neural response in posttraumatic stress disorder." Progress in Neuro-Psychopharmacology and Biological Psychiatry 85 (July 2018): 54–61. http://dx.doi.org/10.1016/j.pnpbp.2018.04.003.

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Dissertations / Theses on the topic "Neural stress processing"

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Rietmolen, Noemie te. "Neural signature of metrical stress processing in French." Thesis, Toulouse 2, 2019. http://www.theses.fr/2019TOU20006.

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La thèse actuelle présente une étude ERP du traitement du stress métrique en français. En effet, l'accentuation métrique joue un rôle important dans la compréhension des langues comme l'anglais et le néérlandais, mais son rôle dans le traitement du français n'est pas bien connu. Le français est une langue traditionnellement décrite sans accent. Cette thèse remet en question cette vision traditionnelle et s'aligne sur deux modèles métriques d'accentuation français, proposant que l'accent est encodé dans des patrons cognitifs sous-jacents. Dans notre étude interdisciplinaire en français sur le traitement des contraintes métriques, nous adoptons une approche fonctionnelle. Nous utilisons la méthode des potentiels évoqués (ERP), qui nous fournit une mesure extrêmement sensible et précise nous permettant de déterminer s’il existe un accent métrique en français et dans quelle mesure l'accent métrique aide l’auditeur à comprendre la parole. Nous montrerons que l'accent métrique facilite le traitement de la parole en français
The current dissertation presents an ERP-investigation of metrical stress processing in French. Indeed, while metrical stress is well known to play an invaluable role in speech comprehension, its functions in French speech processing are unclear. French is a language traditionally described as having no accent. This dissertation questions the traditional view and aligns to two metrical models on French accentuation, which propose stress to be encoded in cognitive templates underlying the abstract representation of the word. In our interdisciplinary investigation of metrical stress processing in French, we take a functional, yet metrically rooted, approach. We use the method of Event-Related Potentials (ERP), which provides us with a highly sensitive and temporally precise measure allowing us to determine whether there is metrical stress in French, and to what extent metrical stress aids the listener in speech comprehension. We will show that metrical stress facilitates processing throughout French comprehension and argue for metrical stress, as well as the domain of the word, to be given a more prominent place in the descriptions of French prosody
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Kirkham, Elizabeth. "The effects of early life stress on affective processing : behavioural and neural correlates." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/20413/.

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Schmidt, Kristin. "Manipulating the hypothalamic-pituitary-adrenal axis : effects on cognitive and emotional information processing and neural connectivity." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:c0475a98-e070-4446-9179-eb87047cb854.

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Despite extensive evidence documenting abnormal hypothalamic-pituitary-adrenal (HPA) axis functioning as a risk factor for the development of depression and other psychiatric disorders, and experimental evidence from acute stress manipulations, the effects of sustained cortisol alterations on clinically relevant cognitive-behavioural and neural processing remain poorly understood. The aim of this thesis was to characterise how non-acute changes in cortisol levels modify behavioural and neural biases implicated in stress-related disorders by following two complementary lines of evidence: firstly, by increasing cortisol via a direct pharmacological intervention; and secondly, by testing the ability of gut microbiota manipulations to alter cortisol reactivity. The first study found that sustained increases in cortisol following 10-day administration of hydrocortisone were associated with altered memory and emotional processing in healthy volunteers. Specifically, participants receiving hydrocortisone showed enhanced recognition of emotional words, while their neutral memory performance was unaffected despite lower parahippocampal and occipital activation during viewing and encoding of neutral pictures. Furthermore, we found that resting-state functional connectivity between limbic-temporal regions of interest (amygdala and hippocampus) and the striatum (head of the caudate), as well as frontal and prelimbic cortices was decreased. In contrast, hippocampal and visual processing during negative facial expressions, and functional connectivity between the amygdala and the brainstem at rest, were increased in the hydrocortisone versus placebo groups. Overall, these findings suggest that non-acute increases in glucocorticoids enhance processing of emotionally salient information in limbic-temporal regions, which may modulate further neural mechanisms of sensory and homeostatic relevance. Enhancements in declarative emotional memory following hydrocortisone also implicate the modulation of amygdalar-hippocampal interactions by cortisol. Conversely, neutral stimulus processing was found to be either reduced or unaffected across a number of cognitive and memory domains. A specific increase for negative processing was further supported by poorer self-reported well-being at the mid-point of the study in participants receiving hydrocortisone. In a separate study exploring the ability of prebiotic supplements to affect cortisol reactivity and emotional processing, a Bimuno-galactooligosaccharide prebiotic was found to reduce the waking cortisol response and increase positive versus negative attentional processing in healthy volunteers. While these effects were not found to be associated, they provide initial promising evidence of the ability to target the HPA axis and emotional processing via the gut microbiota in humans. Overall, this thesis supports the idea that stress-induced physiological changes after prolonged or repeated cortisol exposure are associated with neural and behavioural alterations, which in turn have been crucial in understanding neuropsychological mechanisms underlying psychiatric disease. A better stratification of the effects of sustained HPA axis alterations on psychiatrically relevant cognitive-emotional domains and neural mechanisms thus remains of high priority.
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Graham, Alice. "Interparental Conflict and Neural Functioning in Infancy: An fMRI Study." Thesis, University of Oregon, 2014. http://hdl.handle.net/1794/18485.

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Early life stress (ELS) affects the developing brain and impacts capacity for self-regulation and risk for psychopathology. The high spatial resolution of functional magnetic resonance imaging (fMRI) confers an advantage for studying specific neural regions posited to link ELS with subsequent functioning. The first chapter in this dissertation reviews the literature establishing the feasibility and utility of fMRI research with infants and young children. This chapter examines methodological issues and outlines the potential for this technique to make unique contributions to understanding how ELS influences brain development. The next two chapters present results from a study that employed a functional activation paradigm and resting state functional connectivity MRI (rs-fcMRI) to examine associations between a common source of ELS, non-physical interparental conflict, and neural functioning during infancy. The functional activation paradigm focused on emotional tone of voice as a stimulus relevant to interparental conflict, which is likely salient to infants. Higher levels of interparental conflict (as reported by mothers) were associated with infants (6 to 12 months of age) showing greater reactivity to very angry versus neutral tone of voice in neural regions associated with processing and regulation of stress and emotion (hypothalamus and rostral anterior cingulate cortex). The rs-fcMRI analysis examined coordinated neural functioning in the absence of stimuli, focusing on the amygdala as a key region for understanding the impact of ELS and the posterior cingulate cortex as part of a group of regions that show higher levels of activity in the absence of stimuli (the default network). The results replicate previous work characterizing the default network in infants and provide novel evidence for the functional connectivity of the amydgala and amygdala subregions during infancy. Interparental conflict was associated with variation in the connectivity of both regions. Thus levels of interparental conflict were associated with neural reactivity to a stressor-relevant stimulus and with patterns of coordinated neural functioning in the absence of such stimuli. These results provide support for the utility of using fMRI with infants to examine early emerging associations between common forms of ELS and brain functioning. This dissertation includes previously published and co-authored material.
2016-10-17
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Staněk, Miroslav. "Určování stresu z řečového signálu." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255289.

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Předložená disertační práce se zabývá vývojem algoritmů pro detekci stresu z řečového signálu. Inovativnost této práce se vyznačuje dvěma typy analýzy řečového signálu, a to za použití samohláskových polygonů a analýzy hlasivkových pulsů. Obě tyto základní analýzy mohou sloužit k detekci stresu v řečovém signálu, což bylo dokázáno sérií provedených experimentů. Nejlepších výsledků bylo dosaženo pomocí tzv. Closing-To-Opening phase ratio příznaku v Top-To-Bottom kritériu v kombinaci s vhodným klasifikátorem. Detekce stresu založená na této analýze může být definována jako jazykově i fonémově nezávislá, což bylo rovněž dokázáno získanými výsledky, které dosahují v některých případech až 95% úspěšnosti. Všechny experimenty byly provedeny na vytvořené české databázi obsahující reálný stres, a některé experimenty byly také provedeny pro anglickou stresovou databázi SUSAS.
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Rising, Barry John Paul. "Hardware architectures for stochastic bit-stream neural networks : design and implementation." Thesis, Royal Holloway, University of London, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326219.

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Kellmeyer, David. "Detection of highway warning signs in natural video images using color image processing and neural network techniques on a PC." Ohio : Ohio University, 1992. http://www.ohiolink.edu/etd/view.cgi?ohiou1172782930.

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Harding, Joanne Marie. "Evaluation of the neutral red assay as a stress response indicator in mussels (Mytilus spp.) in relation to seasonal, environmental, handling, harvesting, processing, and post-harvest storage conditions /." Internet access available to MUN users only, 2003. http://collections.mun.ca/u?/theses,162431.

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Karlsson, Simon, and Per Welander. "Generative Adversarial Networks for Image-to-Image Translation on Street View and MR Images." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148475.

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Generative Adversarial Networks (GANs) is a deep learning method that has been developed for synthesizing data. One application for which it can be used for is image-to-image translations. This could prove to be valuable when training deep neural networks for image classification tasks. Two areas where deep learning methods are used are automotive vision systems and medical imaging. Automotive vision systems are expected to handle a broad range of scenarios which demand training data with a high diversity. The scenarios in the medical field are fewer but the problem is instead that it is difficult, time consuming and expensive to collect training data. This thesis evaluates different GAN models by comparing synthetic MR images produced by the models against ground truth images. A perceptual study is also performed by an expert in the field. It is shown by the study that the implemented GAN models can synthesize visually realistic MR images. It is also shown that models producing more visually realistic synthetic images not necessarily have better results in quantitative error measurements, when compared to ground truth data. Along with the investigations on medical images, the thesis explores the possibilities of generating synthetic street view images of different resolution, light and weather conditions. Different GAN models have been compared, implemented with our own adjustments, and evaluated. The results show that it is possible to create visually realistic images for different translations and image resolutions.
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Al-Bayati, Mohammad. "Der Einfluss von Urbanicity auf Stressverarbeitungsmechanismen." Doctoral thesis, 2017. http://hdl.handle.net/11858/00-1735-0000-0023-3E1D-2.

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Books on the topic "Neural stress processing"

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Krivoyekov, Syergyey, and Roman Ayzman. Psychophysiology. ru: INFRA-M Academic Publishing LLC., 2015. http://dx.doi.org/10.12737/10884.

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Psychophysiology — the science studying interrelation of mentality of the person and physiological processes. Fundamental knowledge of work of a brain, first of all, of nervous regulation of functions of an organism, the general and specific features of the highest falls within the scope of its interests nervous activity, the defining character and behavior of the person, psychophysiological mechanisms of regulation of functional states. In the book neurophysiological bases of coding and information processing in nervous system, neural mechanisms of feelings, perceptions, memories, training, motivations and emotions, thinking and the speech, attention, consciousness, behavior, mental activity are stated. Separate the section is devoted to physiological bases of mental changes at various functional, extreme and pathophysiological states (a stress, post-stressful frustration, addiktivny states, depressions, etc.) and to ways of their correction. Authors tried to pay special attention to disclosure of specifics of psychophysiology of the person, to difference of physiological mechanisms of regulation of mental functions of the person in comparison with model researches on animals. For simplification of work on discipline and the best digestion of material the textbook is supplied with the glossary. For students, undergraduates, graduate students and teachers of psychological and medical faculties of higher education institutions.
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Maren, Stephen. Neural Circuits for Context Processing in Aversive Learning and Memory. Edited by Israel Liberzon and Kerry J. Ressler. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190215422.003.0005.

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The nature and properties of emotional expression depend importantly on not only the stimuli that elicit emotional responses, but also the context in which those stimuli are experienced. Deficits in context processing have been associated with a variety of cognitive-emotional disorders, including post-traumatic stress disorder (PTSD). These deficits can be localized to specific neural circuits underlying context processing in the mammalian brain. In particular, the hippocampus has been implicated through numerous animal and human studies to be involved both in normal contextual memory formation, but also in discrimination of trauma-related cues. Decreased hippocampal functioning, as is observed in PTSD, is associated with increased generalization of fear and threat responses as well as deficits in extinction of fear. Understanding context processing offers the opportunity to further understand the biology of PTSD and to target new approaches to therapeutics.
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Bauer, Elizabeth P., and Denis Paré. Behavioral Neuroscience of Circuits Involved in Fear Processing. Edited by Israel Liberzon and Kerry J. Ressler. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190215422.003.0002.

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Normal fear regulation includes the ability to learn by experience that some circumstances predict danger. This process, which can be modeled in the laboratory using Pavlovian fear conditioning, appears to be disrupted in individuals with post-traumatic stress disorder (PTSD). Understanding of the mechanisms underlying fear learning has progressed tremendously in the last 25 years, and constitutes a promising paradigm to study the neural bases of PTSD. This chapter first reviews current knowledge of the brain structures involved in fear learning, expression and extinction, including the contributions of the amygdala and prefrontal cortex. It then addresses how these circuits are affected by PTSD and how fear processing is altered in PTSD. Understanding PTSD within a fear-conditioning and extinction framework provides insight into why certain individuals are susceptible to developing PTSD and suggests potential therapies.
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Goodkind, Madeleine S., and Amit Etkin. Functional Neurocircuitry and Neuroimaging Studies of Anxiety Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0034.

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Anxiety and fear serve adaptive functions and include wide-ranging subjective, physiological, behavioral, and cognitive responses. When these reactions are present chronically, and to a heightened degree that generalizes to signals beyond those that are objectively dangerous, one sees emergence of clinical anxiety disorders. Historically, anxiety disorders have been conceptualized as disruptions in fear processing, though more recent accounts also highlight changes in emotional reactivity beyond fear and deficits in emotion regulation. In this chapter, we review the neural circuitry relevant for fear processing and for emotional reactivity and regulation more broadly. We then review neuroimaging studies of social anxiety disorder, specific phobia, generalized anxiety disorder, panic disorder, and posttraumatic stress disorder. We highlight areas of overlap between disorders as well as disorder-specific perturbations.
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Karpova, Nina N. Pharmacological Adjuncts and Evidence-Supported Treatments for Trauma. Edited by Sara Maltzman. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199739134.013.32.

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A large proportion of humans experienced a traumatic event in their lifetime, with more than 10% developing posttraumatic stress disorder (PTSD), panic disorder, phobias, and other fear/anxiety disorders. The neural circuitry of fear responses is highly conserved in humans as well as rodents, and this allows for translational research using animal models of fear. Fear/anxiety disorders in humans are most efficiently treated by exposure-based psychotherapy (i.e., cognitive behavioral therapy; CBT), the main aspects of which are closely modeled by extinction training in Pavlovian fear conditioning and extinction paradigms in rodents. To improve the efficacy of psychotherapy, pharmacological agents potent for enhancing learning and memory consolidation processing should be developed to combine with exposure-based therapy. The purpose of these adjunctive pharmacological agents is to promote fear memory erasure and the consolidation of extinction memories, thus providing a combined treatment of increased effectiveness. This review discusses established pharmacological adjuncts to behavioral therapeutic interventions for fear/anxiety disorders. The mechanisms of action of these adjuncts, as well as the evidence for and against the pharmacological treatment strategies and their limitations are discussed.
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Grossberg, Stephen. The Visual World as Illusion. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780199794607.003.0007.

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This chapter shows how visual illusions arise from neural processes that play an adaptive role in achieving the remarkable perceptual capabilities of advanced brains. It clarifies that many visual percepts are visual illusions, in the sense that they arise from active processes that reorganize and complete perceptual representations from the noisy data received by retinas. Some of these representations look illusory, whereas others look real. The chapter heuristically summarizes explanations of illusions that arise due to completion of perceptual groupings, filling-in of surface lightnesses and colors, transformation of ambiguous motion signals into coherent percepts of object motion direction and speed, and interactions between the form and motion cortical processing streams. A central theme is that the brain is organized into parallel processing streams with computationally complementary properties, that interstream interactions overcome these complementary deficiencies to compute effective representations of the world, and how these representations generate visual illusions.
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Mason, Peggy. Seeing the World. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190237493.003.0015.

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Modern life is highly dependent on high-acuity vision, and this chapter emphasizes the mechanisms and pathways that support high-acuity or form vision. Because the most common visual impairment is refractive error, the refractive power of the cornea and lens is described at some length. The processes of emmetropization, accommodation, and far viewing are considered. The participation of the outer retina in phototransduction and the visual cycle are detailed, and relevant diseases, including retinitis pigmentosa and age-related macular degeneration, are introduced. The neural processes that transform different wavelengths of light into color perception and common forms of color blindness are explained. Visual processing within cortex, including processing through the dorsal and visual streams, are presented. The process through which babies learn to interpret the firing in their brains as representing visual objects and the importance of the initial years of life to this process are described.
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Merabet, Lotfi, and Alvaro Pascual-Leone. Studies of Crossmodal Functions with TMS. Edited by Charles M. Epstein, Eric M. Wassermann, and Ulf Ziemann. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780198568926.013.0029.

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In the brain, information from all the senses interacts and is integrated in order to create a unified sensory percept. Some percepts appear unimodal, and some, cross modal. Unimodal percepts can be modified by crossmodal interactions given that our brains process multiple streams of sensory information in parallel and promote extensive interactions. TMS can provide valuable insights on the neural substrates associated with multisensory processing in humans. TMS is commonly described as a ‘relatively painless’ method of stimulating the brain noninvasively. However, TMS itself is strong multisensory and this should be considered while interpreting the results. With regard to the crossmodal sensory changes that follow sensory deprivation, these changes can be revealed using a variety of methods including the combination of TMS with neuroimaging.
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Book chapters on the topic "Neural stress processing"

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Sharma, Nandita, and Tom Gedeon. "Stress Classification for Gender Bias in Reading." In Neural Information Processing, 348–55. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24965-5_39.

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Sharma, Nandita, and Tom Gedeon. "Artificial Neural Network Classification Models for Stress in Reading." In Neural Information Processing, 388–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34478-7_48.

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Baghdadi, Asma, Yassine Aribi, and Adel M. Alimi. "Efficient Human Stress Detection System Based on Frontal Alpha Asymmetry." In Neural Information Processing, 858–67. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70093-9_91.

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Bosse, Tibor, Charlotte Gerritsen, Jeroen de Man, and Jan Treur. "Measuring Stress-Reducing Effects of Virtual Training Based on Subjective Response." In Neural Information Processing, 322–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34475-6_39.

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Santhanagopalan, Meena, Madhu Chetty, Cameron Foale, Sunil Aryal, and Britt Klein. "Relevance of Frequency of Heart-Rate Peaks as Indicator of ‘Biological’ Stress Level." In Neural Information Processing, 598–609. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04239-4_54.

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Naze, Sebastien, and Jan Treur. "A Computational Model for Development of Post-Traumatic Stress Disorders by Hebbian Learning." In Neural Information Processing, 141–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34481-7_18.

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Li, Na, Bin Hu, Jing Chen, Hong Peng, Qinglin Zhao, and Mingqi Zhao. "Investigation of Chronic Stress Differences between Groups Exposed to Three Stressors and Normal Controls by Analyzing EEG Recordings." In Neural Information Processing, 512–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-42042-9_64.

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Lombardi, Livia, and Federica Marcolin. "Psychological Stress Detection by 2D and 3D Facial Image Processing." In Progresses in Artificial Intelligence and Neural Systems, 163–73. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5093-5_16.

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Ghesmoune, Mohammed, Hanene Azzag, and Mustapha Lebbah. "G-Stream: Growing Neural Gas over Data Stream." In Neural Information Processing, 207–14. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12637-1_26.

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Arandjelović, Ognjen, Ducson Pham, and Svetha Venkatesh. "Stream Quantiles via Maximal Entropy Histograms." In Neural Information Processing, 327–34. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12640-1_40.

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Conference papers on the topic "Neural stress processing"

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Carvalho, Micael, Matthieu Cord, Sandra Avila, Nicolas Thome, and Eduardo Valle. "Deep Neural Networks Under Stress." In 2016 IEEE International Conference on Image Processing (ICIP). IEEE, 2016. http://dx.doi.org/10.1109/icip.2016.7533200.

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Xia, Tian, Xianfeng Rui, Chien-Lin Huang, Iek Heng Chu, Shaojun Wang, and Mei Han. "An Attention Based Deep Neural Network for Automatic Lexical Stress Detection." In 2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2019. http://dx.doi.org/10.1109/globalsip45357.2019.8969232.

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Avila, Anderson R., Shruti R. Kshirsagar, Abhishek Tiwari, Daniel Lafond, Douglas O'Shaughnessy, and Tiago H. Falk. "Speech-Based Stress Classification based on Modulation Spectral Features and Convolutional Neural Networks." In 2019 27th European Signal Processing Conference (EUSIPCO). IEEE, 2019. http://dx.doi.org/10.23919/eusipco.2019.8903014.

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Briñez de León, Juan C., Mateo Rico, John W. Branch, and Alejandro Restrepo-Martínez. "StressNet: A deep convolutional neural network for recovering the stress field from isochromatic images." In Applications of Digital Image Processing XLIII, edited by Andrew G. Tescher and Touradj Ebrahimi. SPIE, 2020. http://dx.doi.org/10.1117/12.2568609.

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Yang, Liu, Junyu Zhang, Tingxuan Chen, Wuji Lei, and Xiaolong Liu. "Predicting Residual Stress by Finding Peak Shape Using Artificial Neural Networks." In 2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). IEEE, 2020. http://dx.doi.org/10.1109/ispa-bdcloud-socialcom-sustaincom51426.2020.00105.

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Markovic, Dusan, Dejan Vujicic, Dijana Stojic, Zeljko Jovanovic, Uros Pesovic, and Sinisa Randic. "Monitoring System Based on IoT Sensor Data with Complex Event Processing and Artificial Neural Networks for Patients Stress Detection." In 2019 18th International Symposium INFOTEH-JAHORINA (INFOTEH). IEEE, 2019. http://dx.doi.org/10.1109/infoteh.2019.8717748.

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Weatheritt, Jack, Richard D. Sandberg, Julia Ling, Gonzalo Saez, and Julien Bodart. "A Comparative Study of Contrasting Machine Learning Frameworks Applied to RANS Modeling of Jets in Crossflow." In ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-63403.

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Classical RANS turbulence models have known deficiencies when applied to jets in crossflow. Identifying the linear Boussinesq stress-strain hypothesis as a major contribution to erroneous prediction, we consider and contrast two machine learning frameworks for turbulence model development. Gene Expression Programming, an evolutionary algorithm that employs a survival of the fittest analogy, and a Deep Neural Network, based on neurological processing, add non-linear terms to the stress-strain relationship. The results are Explicit Algebraic Stress Model-like closures. High fidelity data from an inline jet in crossflow study is used to regress new closures. These models are then tested on a skewed jet to ascertain their predictive efficacy. For both methodologies, a vast improvement over the linear relationship is observed.
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Henrickson, James V., Kenton Kirkpatrick, and John Valasek. "Rapid Characterization of Shape Memory Alloy Material Parameters Using Computational Intelligence Methods." In ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/smasis2013-3016.

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Shape memory alloys are capable of delivering advantageous solutions to a wide range of engineering-based problems. Implementation of these solutions, however, is often complicated by the hysteretic, non-linear, thermo-mechanical behavior of the material. Although existing shape memory alloy constitutive models are largely accurate in describing this unique behavior, they require prior characterization of the material parameters. Consequently, before thorough modeling and simulation can occur for a shape memory alloy-based project, one must first go through the process of identifying several material parameters unique to shape memory alloys. Current characterization procedures necessitate extensive experimentation, data collection, and data processing. As a result, these methods simultaneously create a high barrier of entry for engineers new to active materials and impede the advanced study of shape memory alloy material parameter evolution. This paper develops a novel method in which computational intelligence methods are used to rapidly identify shape memory alloy material parameters. Specifically, an artificial neural network is trained to identify transformation temperatures and stress influence coefficients of given shape memory alloy specimens using strain-temperature coordinates as inputs. After generating training data through the use of a constitutive model, the resulting trained artificial neural network was used to identify parameters for a number of randomly generated theoretical shape memory alloys. Results presented in the paper show that the artificial neural network was able to rapidly identify both transformation temperatures and stress influence coefficients with satisfactory accuracy. The generation of training data was then repeated using Taguchi methods. Further results presented in the paper show that the artificial neural network trained with the Taguchi-based training data yielded improved characterization accuracy while using less training data.
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Gers, F. A., and J. Schmidhuber. "Neural processing of complex continual input streams." In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium. IEEE, 2000. http://dx.doi.org/10.1109/ijcnn.2000.860830.

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Chen, G. (Sheng), L. Huang, J. Y. Chang, and L. B. Chen. "Intelligent Diagnosis of Bolting System Under Dynamic Impact." In ASME 2013 Conference on Information Storage and Processing Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/isps2013-2931.

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The properties of fasteners as significant parts in varied engineering systems have been widely investigated [1–3], from hard disk drive devices to construction ground control. These problems are complex in nature because every bolting involves different sources of nonlinear and uncertainty characteristics. The interfaces forces such as contact forces, friction forces and bonding are not known in reality. The base forces and deformation could be redistributed non-uniformly in the presence of complex loadings such as shock and impact. Most of the reported studies focused on the design issues, characterization of the linear dynamic properties and energy dissipation of bolting system as well as using bolts with integrated detecting systems or dynamometers. The capability to assess the interface properties of bolting system is important for mechatronics, mechanical, civil and mining engineering [1–4]. Even though some conventional approaches have been used to infer bolting integrity, the diagnosis technology has been lacking. This study is conducted to explore the possibility of the diagnosis bolting interface integrity under impact by using accelerometer signal. The statistical pattern identification such as artificial neural network and support vector machine is used to diagnose the bolting integrity. By integrating the analysis and experimental data, an ANN is established as a nonparametric model to predict the system properties. Numerous numerical and experimental researches have been conducted to characterize the typical bolting system, which enables extraction of varied dynamic features from different mechanisms associated with the failures. This kind of database could be used as feature to characterizing the effect of complex loads on bolting for ANN training. To further illustrate the feature extraction, we investigated system models. Due to its adaptive and nonlinear input–output transformation capabilities, artificial neural network (ANN) has been widely applied in the field of pattern and system recognition. The proposed approach is capable of monitoring the stress/strain history and integrity of bolting interface with the goal of detecting structural damage and defects. The results from simulation, testing and ANN identification demonstrated the high performance of the proposed approach compared with conventional ones. In the following, an approach is proposed to reliably estimate the dynamic properties of a bolt-surrounding solid mass specimen using its impact response signal. The developed approach can be readily extended to the bolting connection in other systems such as mechanical and mechatronics systems.
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