Data-driven biomarkers outperform theory-based biomarkers in predicting stroke motor outcomes.

Chronic motor impairments are a leading cause of disability after stroke. Previous studies have predicted motor outcomes based on the degree of damage to predefined structures in the motor system, such as the corticospinal tract. However, such theory-based approaches may not take full advantage of the information contained in clinical imaging data. The present study uses data-driven approaches to predict chronic motor outcomes after stroke and compares the accuracy of these predictions to previously-identified theory-based biomarkers. Using a cross-validation framework, regression models were trained using lesion masks and motor outcomes data from 789 stroke patients (293 female/496 male) from the ENIGMA Stroke Recovery Working Group (age 64.9±18.0 years; time since stroke 12.2±0.2 months; normalised motor score 0.7±0.5 (range [0,1]). The out-of-sample prediction accuracy of two theory-based biomarkers was assessed: lesion load of the corticospinal tract, and lesion load of multiple descending motor tracts. These theory-based prediction accuracies were compared to the prediction accuracy from three data-driven biomarkers: lesion load of lesion-behaviour maps, lesion load of structural networks associated with lesion-behaviour maps, and measures of regional structural disconnection. In general, data-driven biomarkers had better prediction accuracy - as measured by higher explained variance in chronic motor outcomes - than theory-based biomarkers. Data-driven models of regional structural disconnection performed the best of all models tested (R2 = 0.210, p < 0.001), performing significantly better than predictions using the theory-based biomarkers of lesion load of the corticospinal tract (R2 = 0.132, p< 0.001) and of multiple descending motor tracts (R2 = 0.180, p < 0.001). They also performed slightly, but significantly, better than other data-driven biomarkers including lesion load of lesion-behaviour maps (R2 =0.200, p < 0.001) and lesion load of structural networks associated with lesion-behaviour maps (R2 =0.167, p < 0.001). Ensemble models - combining basic demographic variables like age, sex, and time since stroke - improved prediction accuracy for theory-based and data-driven biomarkers. Finally, combining both theory-based and data-driven biomarkers with demographic variables improved predictions, and the best ensemble model achieved R2 = 0.241, p < 0.001. Overall, these results demonstrate that models that predict chronic motor outcomes using data-driven features, particularly when lesion data is represented in terms of structural disconnection, perform better than models that predict chronic motor outcomes using theory-based features from the motor system. However, combining both theory-based and data-driven models provides the best predictions.

Right inferior frontal gyrus damage is associated with impaired initiation of inhibitory control, but not its implementation.

Inhibitory control is one of the most important control functions in the human brain. Much of our understanding of its neural basis comes from seminal work showing that lesions to the right inferior frontal gyrus (rIFG) increase stop-signal reaction time (SSRT), a latent variable that expresses the speed of inhibitory control. However, recent work has identified substantial limitations of the SSRT method. Notably, SSRT is confounded by trigger failures: stop-signal trials in which inhibitory control was never initiated. Such trials inflate SSRT, but are typically indicative of attentional, rather than inhibitory deficits. Here, we used hierarchical Bayesian modeling to identify stop-signal trigger failures in human rIFG lesion patients, non-rIFG lesion patients, and healthy comparisons. Furthermore, we measured scalp-EEG to detect ß-bursts, a neurophysiological index of inhibitory control. rIFG lesion patients showed a more than fivefold increase in trigger failure trials and did not exhibit the typical increase of stop-related frontal ß-bursts. However, on trials in which such ß-bursts did occur, rIFG patients showed the typical subsequent upregulation of ß over sensorimotor areas, indicating that their ability to implement inhibitory control, once triggered, remains intact. These findings suggest that the role of rIFG in inhibitory control has to be fundamentally reinterpreted.

Academic skills after brain injury: A lifespan perspective.

OBJECTIVES: This study investigated academic skills outcomes after brain injury and identified the influence of age and injury factors across the lifespan. METHOD: Our sample included 651 participants with focal brain lesions. Math, reading, and spelling data from the Wide Range Achievement Test (WRAT) were used as the academic skills outcomes. Age of lesion onset ranged from 0 to 85 years old. Linear regressions were conducted to identify the relation between age and injury factors and academic skills outcomes. Lesion-symptom mapping was conducted to identify the brain areas that, when lesioned, were associated with deficits in academic skills. RESULTS: A quadratic model of age of lesion onset significantly predicted math (R² = .28, p < .001), reading (R² = .29, p < .001), and spelling outcomes (R² = .32, p < .001), while accounting for various covariates. Education, sex, lesion size and laterality, etiology, and seizure history were additional reliable predictors of academic skills outcomes across the lifespan. Academic skill deficits were associated with damage to various brain areas across the left-hemisphere frontal, temporal, and parietal lobes, the insular area, and left- and right-hemisphere white matter. CONCLUSIONS: This study supports age of lesion onset as a relevant predictor of academic skills after brain injury in a lifespan sample. Several other variables (e.g., education, sex, lesion characteristics, and seizure history) are notable in the prediction of outcomes across the lifespan. Future work could investigate more diverse samples and emphasize recruitment of early onset injuries to examine generalizability and potential critical periods for academic skills. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Thalamic strokes that severely impair arousal extend into the brainstem.

In this study, we evaluate the role of the thalamus in the neural circuitry of arousal. Level of consciousness within the first 12 hours of a thalamic stroke is assessed with lesion symptom mapping. Impaired arousal correlates with lesions in the paramedian posterior thalamus near the centromedian and parafascicular nuclei, posterior hypothalamus, and midbrain tegmentum. All patients with severely impaired arousal (coma, stupor) had lesion extension into the midbrain and/or pontine tegmentum, whereas purely thalamic lesions did not severely impair arousal. These results are consistent with growing evidence that pathways most critical for human arousal lie outside the thalamus. Ann Neurol 2018;84:926-930.

Choosing spouses and houses: Impaired congruence between preference and choice following damage to the ventromedial prefrontal cortex.

OBJECTIVE: A well-documented effect of focal ventromedial prefrontal cortex (vmPFC) damage is a deficit in real-world decision making. An important aspect of this deficit may be a deficiency in "internal consistency" during social decision making-that is, impaired congruence between expressed preferences versus actual behavioral choices. An example of low internal consistency would be if one expressed the desire to marry someone with impeccable moral character, yet proceeded to marry someone convicted of multiple felonies. Here, we used a neuropsychological approach to investigate neural correlates of internal consistency in complex decision making. METHOD: Sixteen individuals with focal vmPFC lesions, 16 brain damage comparison individuals, and 16 normal comparison individuals completed a 3-option forced-choice preference task in which choices were made using attribute sets. Participants also completed visual-analogue preference ratings to indicate how much they liked each option, and rated the influence of each attribute on their decision making. Options were either social (potential spouses) or nonsocial (potential houses). Internal consistency for a trial was defined as agreement between the choice and the most positively rated option. RESULTS: A mixed design analysis of variance revealed that internal consistency between choices and preferences derived from summed attribute ratings was significantly lower for the vmPFC group relative to comparison participants, but only in the social condition (pη2 = .09), 95% CI [.002, .163]. CONCLUSIONS: Internal consistency during social decisions may be deficient in patients with vmPFC damage, leading to a discrepancy between preferences and choices. The vmPFC may provide an important neural mechanism for aligning behavioral choices with expressed preferences. (PsycINFO Database Record