2 results
Latent cause inference during extinction learning in trauma-exposed individuals with and without PTSD
- Agnes Norbury, Hannah Brinkman, Mary Kowalchyk, Elisa Monti, Robert H. Pietrzak, Daniela Schiller, Adriana Feder
-
- Journal:
- Psychological Medicine / Volume 52 / Issue 16 / December 2022
- Published online by Cambridge University Press:
- 08 March 2021, pp. 3834-3845
-
- Article
- Export citation
-
Background
Problems in learning that sights, sounds, or situations that were once associated with danger have become safe (extinction learning) may explain why some individuals suffer prolonged psychological distress following traumatic experiences. Although simple learning models have been unable to provide a convincing account of why this learning fails, it has recently been proposed that this may be explained by individual differences in beliefs about the causal structure of the environment.
MethodsHere, we tested two competing hypotheses as to how differences in causal inference might be related to trauma-related psychopathology, using extinction learning data collected from clinically well-characterised individuals with varying degrees of post-traumatic stress (N = 56). Model parameters describing individual differences in causal inference were related to multiple post-traumatic stress disorder (PTSD) and depression symptom dimensions via network analysis.
ResultsIndividuals with more severe PTSD were more likely to assign observations from conditioning and extinction stages to a single underlying cause. Specifically, greater re-experiencing symptom severity was associated with a lower likelihood of inferring that multiple causes were active in the environment.
ConclusionsWe interpret these results as providing evidence of a primary deficit in discriminative learning in participants with more severe PTSD. Specifically, a tendency to attribute a greater diversity of stimulus configurations to the same underlying cause resulted in greater uncertainty about stimulus-outcome associations, impeding learning both that certain stimuli were safe, and that certain stimuli were no longer dangerous. In the future, better understanding of the role of causal inference in trauma-related psychopathology may help refine cognitive therapies for these disorders.
EEG Power spectra and subcortical pathology in chronic disorders of consciousness
- Evan S. Lutkenhoff, Anna Nigri, Davide Rossi Sebastiano, Davide Sattin, Elisa Visani, Cristina Rosazza, Ludovico D'Incerti, Maria Grazia Bruzzone, Silvana Franceschetti, Matilde Leonardi, Stefania Ferraro, Martin M. Monti
-
- Journal:
- Psychological Medicine / Volume 52 / Issue 8 / June 2022
- Published online by Cambridge University Press:
- 23 September 2020, pp. 1491-1500
-
- Article
- Export citation
-
Background
Despite a growing understanding of disorders of consciousness following severe brain injury, the association between long-term impairment of consciousness, spontaneous brain oscillations, and underlying subcortical damage, and the ability of such information to aid patient diagnosis, remains incomplete.
MethodsCross-sectional observational sample of 116 patients with a disorder of consciousness secondary to brain injury, collected prospectively at a tertiary center between 2011 and 2013. Multimodal analyses relating clinical measures of impairment, electroencephalographic measures of spontaneous brain activity, and magnetic resonance imaging data of subcortical atrophy were conducted in 2018.
ResultsIn the final analyzed sample of 61 patients, systematic associations were found between electroencephalographic power spectra and subcortical damage. Specifically, the ratio of beta-to-delta relative power was negatively associated with greater atrophy in regions of the bilateral thalamus and globus pallidus (both left > right) previously shown to be preferentially atrophied in chronic disorders of consciousness. Power spectrum total density was also negatively associated with widespread atrophy in regions of the left globus pallidus, right caudate, and in the brainstem. Furthermore, we showed that the combination of demographics, encephalographic, and imaging data in an analytic framework can be employed to aid behavioral diagnosis.
ConclusionsThese results ground, for the first time, electroencephalographic presentation detected with routine clinical techniques in the underlying brain pathology of disorders of consciousness and demonstrate how multimodal combination of clinical, electroencephalographic, and imaging data can be employed in potentially mitigating the high rates of misdiagnosis typical of this patient cohort.