Exploring the predictive value of different affect dynamics for psychological treatment outcome

In psychotherapy research, many studies have focussed on generating expected treatment response (ETR, Howard et al., 1996) curves at the onset of treatment to identify patients at risk of treatment failure (e.g., Delgadillo et al., 2016; Lutz et al., 2006; Lutz et al., 2019). This line of research resulted in establishing predictive models for ETR based on cross-sectional data, including patient characteristics like problem chronicity, previous treatment, treatment expectations, and global assessment of functioning (Lutz et al., 1999). Notably, initial impairment has consistently emerged as a robust and reliable predictor of treatment outcomes (Beutler et al., 2018; Lutz et al., 2018; Zimmerman et al., 2017). In recent years, the field has sought to advance the accuracy of data assessment and analysis to refine prediction models. To improve data quality, researchers have explored the implementation of Ecological Momentary Assessment (EMA; Stone & Shiffman, 1994). This method aims to mitigate retrospective bias, enhance ecological validity, and capture dynamic aspects of patient experiences (e.g., Hamaker & Wichers, 2017; Shiffman et al., 2008; Trull & Ebner-Priemer, 2013). Affect dynamics and their interplay, in particular, have been suggested as valuable predictors for treatment outcomes, with recent pilot studies demonstrating an incremental explanation of variance (Hehlmann et al., 2024; Lutz et al., 2018). However, the methodological approaches employed to capture affect dynamics demonstrate heterogeneity across studies, with each emphasizing distinct dynamic aspects. A prior study, Dejonckheere and colleagues (2019) investigated multiple approaches for the analysis of affect dynamics,and concluded that most of the indicators derived from these approaches had limited added value over the mean level of affect for predicting psychological well-being. Nonetheless, it remains uncertain whether any of these analytic indicators, including the mean level, have the potential to enhance predictive value beyond the initial impairment. To this end, our study aims to contribute to the existing literature by adopting an approach similar to that of Dejonckheere's study. We plan to apply a broad spectrum of analytic approaches on intensive longitudinal affect data, to examine the additional value the derived indicators may offer in predicting treatment outcomes. Through this examination, we aim to refine and advance our understanding of predictive indicators for psychotherapeutic outcomes

Evidence for a role of a cortico-subcortical network for automatic and unconscious motor inhibition of manual responses

It is now clear that non-consciously perceived stimuli can bias our decisions. Although previous researches highlighted the importance of automatic and unconscious processes involved in voluntary action, the neural correlates of such processes remain unclear. Basal ganglia dysfunctions have long been associated with impairment in automatic motor control. In addition, a key role of the medial frontal cortex has been suggested by administrating a subliminal masked prime task to a patient with a small lesion restricted to the supplementary motor area (SMA). In this task, invisible masked arrows stimuli were followed by visible arrow targets for a left or right hand response at different interstimuli intervals (ISI), producing a traditional facilitation effect for compatible trials at short ISI and a reversal inhibitory effect at longer ISI. Here, by using fast event-related fMRI and a weighted parametric analysis, we showed BOLD related activity changes in a cortico-subcortical network, especially in the SMA and the striatum, directly linked to the individual behavioral pattern. This new imaging result corroborates previous works on subliminal priming using lesional approaches. This finding implies that one of the roles of these regions was to suppress a partially activated movement below the threshold of awareness

Metabolic Levels in the Corpus Callosum and Their Structural and Behavioral Correlates after Moderate to Severe Pediatric TBI

Diffuse axonal injury (DAI) secondary to traumatic brain injury (TBI) contributes to long-term functional morbidity. The corpus callosum (CC) is particularly vulnerable to this type of injury. Magnetic resonance spectroscopy (MRS) was used to characterize the metabolic status of two CC regions of interest (ROIs) (anterior and posterior), and their structural (diffusion tensor imaging; DTI) and neurobehavioral (neurocognitive functioning, bimanual coordination, and interhemispheric transfer time [IHTT]) correlates. Two groups of moderate/severe TBI patients (ages 12–18 years) were studied: post-acute (5 months post-injury; n = 10), and chronic (14.7 months post-injury; n = 8), in addition to 10 age-matched healthy controls. Creatine (energy metabolism) did not differ between groups across both ROIs and time points. In the TBI group, choline (membrane degeneration/inflammation) was elevated for both ROIs at the post-acute but not chronic period. N-acetyl aspartate (NAA) (neuronal/axonal integrity) was reduced initially for both ROIs, with partial normalization at the chronic time point. Posterior, not anterior, NAA was positively correlated with DTI fractional anisotropy (FA) (r = 0.88), and most domains of neurocognition (r range 0.22–0.65), and negatively correlated with IHTT (r = −0.89). Inverse corerlations were noted between creatine and posterior FA (r = −0.76), neurocognition (r range −0.22 to −0.71), and IHTT (r = 0.76). Multimodal studies at distinct time points in specific brain structures are necessary to delineate the course of the degenerative and reparative processes following TBI, which allows for preliminary hypotheses about the nature and course of the neural mechanisms of subsequent functional morbidity. This will help guide the future development of targeted therapeutic agents