Fear acquisition and extinction in elderly patients with depression

Impairment in acquisition of conditioned fear in people with depressive symptoms

Background

Depression is one of the primary global public health issues, and there has been a dramatic increase in depression levels among young people over the past decade. The neuroplasticity theory of depression postulates that a malfunction in neural plasticity, which is responsible for learning, memory, and adaptive behavior, is the primary source of the disorder's clinical manifestations. Nevertheless, the impact of depression symptoms on associative learning remains underexplored.

Methods

We used the differential fear conditioning paradigm to investigate the effects of depressive symptoms on fear acquisition and extinction learning. Skin conductance response (SCR) is an objective evaluation indicator, and ratings of nervousness, likeability, and unconditioned stimuli (US) expectancy are subjective evaluation indicators. In addition, we used associability generated by a computational reinforcement learning model to characterize the skin conductance response.

Results

The findings indicate that individuals with depressive symptoms exhibited significant impairment in fear acquisition learning compared to those without depressive symptoms based on the results of the skin conductance response. Moreover, in the discrimination fear learning task, the skin conductance response was positively correlated with associability, as estimated by the hybrid model in the group without depressive symptoms. Additionally, the likeability rating scores improved post-extinction learning in the group without depressive symptoms, and no such increase was observed in the group with depressive symptoms.

Conclusion

The study highlights that individuals with pronounced depressive symptoms exhibit impaired fear acquisition and extinction learning, suggesting a possible deficit in associative learning. Employing the hybrid model to analyze the learning process offers a deeper insight into the associative learning processes of humans, thus allowing for improved comprehension and treatment of these mental health problems.

The Basolateral Amygdala: The Core of a Network for Threat Conditioning, Extinction, and Second-Order Threat Conditioning

Threat conditioning, extinction, and second-order threat conditioning studied in animal models provide insight into the brain-based mechanisms of fear- and anxiety-related disorders and their treatment. Much attention has been paid to the role of the basolateral amygdala (BLA) in such processes, an overview of which is presented in this review. More recent evidence suggests that the BLA serves as the core of a greater network of structures in these forms of learning, including associative and sensory cortices. The BLA is importantly regulated by hippocampal and prefrontal inputs, as well as by the catecholaminergic neuromodulators, norepinephrine and dopamine, that may provide important prediction-error or learning signals for these forms of learning. The sensory cortices may be required for the long-term storage of threat memories. As such, future research may further investigate the potential of the sensory cortices for the long-term storage of extinction and second-order conditioning memories.

Predicting Fear Extinction in Posttraumatic Stress Disorder

Fear extinction is the basis of exposure therapies for posttraumatic stress disorder (PTSD), but half of patients do not improve. Predicting fear extinction in individuals with PTSD may inform personalized exposure therapy development. The participants were 125 trauma-exposed adults (96 female) with a range of PTSD symptoms. Electromyography, electrocardiogram, and skin conductance were recorded at baseline, during dark-enhanced startle, and during fear conditioning and extinction. Using a cross-validated, hold-out sample prediction approach, three penalized regressions and conventional ordinary least squares were trained to predict fear-potentiated startle during extinction using 50 predictor variables (5 clinical, 24 self-reported, and 21 physiological). The predictors, selected by penalized regression algorithms, were included in multivariable regression analyses, while univariate regressions assessed individual predictors. All the penalized regressions outperformed OLS in prediction accuracy and generalizability, as indexed by the lower mean squared error in the training and holdout subsamples. During early extinction, the consistent predictors across all the modeling approaches included dark-enhanced startle, the depersonalization and derealization subscale of the dissociative experiences scale, and the PTSD hyperarousal symptom score. These findings offer novel insights into the modeling approaches and patient characteristics that may reliably predict fear extinction in PTSD. Penalized regression shows promise for identifying symptom-related variables to enhance the predictive modeling accuracy in clinical research.

Prevalence of depression in older adults: A systematic review and meta-analysis

Depression is a prevalent mental disorder in older adults, but the prevalence in older adults varies largely across studies due to differences in regional cultures and screening tools. The objective of this review is to systematically evaluate the global prevalence of depression in older adults. PubMed, Embase, Web of Science and Cochran Library databases were searched independently from 2000 to 2021. Subgroups, sensitivity, and meta-regression analyses were performed to address heterogeneity. Publication bias was evaluated using Egger's test. Forty-eight eligible studies were included in this review. The global prevalence of depression in older adults was 28.4%, with high between-study heterogeneity. The meta-analysis showed that the prevalence of depression in older adults is high although it varied with geographic regions, screening tools, sample sizes and representativeness, and study quality. Therefore, it is necessary to carefully consider appropriate screening tools to estimate the prevalence in different regions of a population.