We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure coreplatform@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition methods have been applied recently to predict many psychiatric disorders, these techniques have not been utilized to predict subtypes of posttraumatic stress disorder (PTSD), including the dissociative subtype of PTSD (PTSD + DS).
Methods
Using Multiclass Gaussian Process Classification within PRoNTo, we examined the classification accuracy of: (i) the mean amplitude of low-frequency fluctuations (mALFF; reflecting spontaneous neural activity during rest); and (ii) seed-based amygdala complex functional connectivity within 181 participants [PTSD (n = 81); PTSD + DS (n = 49); and age-matched healthy trauma-unexposed controls (n = 51)]. We also computed mass-univariate analyses in order to observe regional group differences [false-discovery-rate (FDR)-cluster corrected p < 0.05, k = 20].
Results
We found that extracted features could predict accurately the classification of PTSD, PTSD + DS, and healthy controls, using both resting-state mALFF (91.63% balanced accuracy, p < 0.001) and amygdala complex connectivity maps (85.00% balanced accuracy, p < 0.001). These results were replicated using independent machine learning algorithms/cross-validation procedures. Moreover, areas weighted as being most important for group classification also displayed significant group differences at the univariate level. Here, whereas the PTSD + DS group displayed increased activation within emotion regulation regions, the PTSD group showed increased activation within the amygdala, globus pallidus, and motor/somatosensory regions.
Conclusion
The current study has significant implications for advancing machine learning applications within the field of psychiatry, as well as for developing objective biomarkers indicative of diagnostic heterogeneity.
Dissociation may involve the protective activation of altered states of consciousness related to acute changes in a variety of brain systems in response to immediate danger. Dissociation can produce a variety of somatoform conditions such as pseudoneurological conversion symptoms, pain disorders and somatization disorder. Individuals with repeated early life trauma such as dissociative identity disorder (DID) or borderline personality disorder (BPD) may show all of these symptoms, leading to a particularly complex and variable clinical picture. Critical anatomical structures for the post-encounter defensive behavior described include the amygdala, the ventral periaqueductal gray and the hypothalamus. Failure of corticolimbic inhibition or excessive corticolimbic inhibition may be one underlying mechanism that leads to altered temporal lobe and limbic system functioning. Typically, dissociative symptoms in neurological disorders have been reported to result from lesions in the limbic system, specifically the temporal lobe or the temporoparietal junction.
This chapter focuses on the sequelae in adulthood of traumatic victimization experienced in early childhood (that is, infancy, toddlerhood, and early school years). Adult survivors of early childhood traumatic victimization are at risk for post-traumatic stress disorder (PTSD), and for heightened anxiety, depression and suicidality, addiction, personality disorders, antisocial or violent behavior, serious mental illness and sexual disorders. Several methodological limitations suggest caution in interpreting the findings from studies on the effects of childhood traumatic victimization on adult functioning and health. The impact of psychological trauma and the etiology and course of post-traumatic disorders differ for males and females in several respects, such that gender may moderate the adverse effects of early life psychological trauma. Minority ethno-racial background is consistently associated with increased risk of childhood psychological trauma, including loss, domestic violence and sexual abuse.
This chapter summarizes available findings on the neuroendocrine effects of exposure to trauma during early development, with a focus on a role for such alterations in the increased risk of mood and anxiety disorders in adulthood. The principal components of the stress system are the hypothalamic-pituitary-adrenal (HPA) axis, the locus ceruleus-norepinephrine (LC-NE) system and the extrahypothalamic corticotropin-releasing factor (CRF) systems. In addition, increased rates of major depression, post-traumatic stress disorder (PTSD) and attention-deficit hyperactivity disorder (ADHD) have been reported in maltreated children. The relationship between early adverse experiences and the development of adult psychopathology is likely mediated by alterations in neurobiological systems involved in the regulation of stress. Findings from the research would have important implications for the development of optimized treatment strategies that directly target different neurobiological pathways involved in depression and anxiety disorders in victims of early child maltreatment.
This chapter examines the relationship between traumatic stress in childhood and the leading causes of morbidity, mortality and disability in the USA: cardiovascular disease, chronic lung disease, chronic liver disease, depression and other forms of mental illness, obesity, smoking and alcohol and drug abuse. The essence of the Adverse Childhood Experiences (ACE) Study has been to match retrospectively, approximately a half century after the fact, an individual's current state of health and well-being against adverse events in childhood. The chapter illustrates with a sampling from the findings in the ACE Study, the long-lasting, strongly proportionate and often profound relationship between adverse childhood experiences and important categories of emotional state, health risks, disease burden, sexual behavior, disability, and healthcare costs. Biomedical disease in adults had a significant relationship to adverse life experiences in childhood in the ACE Study.
There is now ample evidence from the preclinical and clinical fields that early life trauma has both dramatic and long-lasting effects on neurobiological systems and functions that are involved in different forms of psychopathology as well as on health in general. To date, a comprehensive review of the recent research on the effects of early and later life trauma is lacking. This book fills an obvious gap in academic and clinical literature by providing reviews which summarize and synthesize these findings. Topics considered and discussed include the possible biological and neuropsychological effects of trauma at different epochs and their effect on health. This book will be essential reading for psychiatrists, clinical psychologists, mental health professionals, social workers, pediatricians and specialists in child development.