Dimensionality and optimal combination of autonomic fear-conditioning measures in humans.

Fear conditioning, also termed threat conditioning, is a commonly used learning model with clinical relevance. Quantification of threat conditioning in humans often relies on conditioned autonomic responses such as skin conductance responses (SCR), pupil size responses (PSR), heart period responses (HPR), or respiration amplitude responses (RAR), which are usually analyzed separately. Here, we investigate whether inter-individual variability in differential conditioned responses, averaged across acquisition, exhibits a multi-dimensional structure, and the extent to which their linear combination could enhance the precision of inference on whether threat conditioning has occurred. In a mega-analytic approach, we re-analyze nine data sets including 256 individuals, acquired by the group of the last author, using standard routines in the framework of psychophysiological modeling (PsPM). Our analysis revealed systematic differences in effect size between measures across datasets, but no evidence for a multidimensional structure across various combinations of measures. We derive the statistically optimal weights for combining the four measures and subsets thereof, and we provide out-of-sample performance metrics for these weights, accompanied by bias-corrected confidence intervals. We show that to achieve the same statistical power, combining measures allows for a relevant reduction in sample size, which in a common scenario amounts to roughly 24%. To summarize, we demonstrate a one-dimensional structure of threat conditioning measures, systematic differences in effect size between measures, and provide weights for their optimal linear combination in terms of maximal retrodictive validity.

Functional sophistication in human escape.

Animals including humans must cope with immediate threat and make rapid decisions to survive. Without much leeway for cognitive or motor errors, this poses a formidable computational problem. Utilizing fully immersive virtual reality with 13 natural threats, we examined escape decisions in N = 59 humans. We show that escape goals are dynamically updated according to environmental changes. The decision whether and when to escape depends on time-to-impact, threat identity and predicted trajectory, and stable personal characteristics. Its implementation appears to integrate secondary goals such as behavioral affordances. Perturbance experiments show that the underlying decision algorithm exhibits planning properties and can integrate novel actions. In contrast, rapid information-seeking and foraging-suppression are only partly devaluation-sensitive. Instead of being instinctive or hardwired stimulus-response patterns, human escape decisions integrate multiple variables in a flexible computational architecture. Taken together, we provide steps toward a computational model of how the human brain rapidly solves survival challenges.

Converting sounds to meaning with ventral semantic language networks: integration of interdisciplinary data on brain connectivity, direct electrical stimulation and clinical disconnection syndromes.

Numerous traditional linguistic theories propose that semantic language pathways convert sounds to meaningful concepts, generating interpretations ranging from simple object descriptions to communicating complex, analytical thinking. Although the dual-stream model of Hickok and Poeppel is widely employed, proposing a dorsal stream, mapping speech sounds to articulatory/phonological networks, and a ventral stream, mapping speech sounds to semantic representations, other language models have been proposed. Indeed, despite seemingly congruent models of semantic language pathways, research outputs from varied specialisms contain only partially congruent data, secondary to the diversity of applied disciplines, ranging from fibre dissection, tract tracing, and functional neuroimaging to neuropsychiatry, stroke neurology, and intraoperative direct electrical stimulation. The current review presents a comprehensive, interdisciplinary synthesis of the ventral, semantic connectivity pathways consisting of the uncinate, middle longitudinal, inferior longitudinal, and inferior fronto-occipital fasciculi, with special reference to areas of controversies or consensus. This is achieved by describing, for each tract, historical concept evolution, terminations, lateralisation, and segmentation models. Clinical implications are presented in three forms: (a) functional considerations derived from normal subject investigations, (b) outputs of direct electrical stimulation during awake brain surgery, and (c) results of disconnection syndromes following disease-related lesioning. The current review unifies interpretation of related specialisms and serves as a framework/thinking model for additional research on language data acquisition and integration.

High Interrater Variability in Intraoperative Language Testing and Interpretation in Awake Brain Mapping Among Neurosurgeons or Neuropsychologists: An Emerging Need for Standardization.

OBJECTIVE: Brain mapping with direct electric stimulation is considered the gold standard for maximum safe resection of tumors affecting eloquent regions. However, no consensus exists in selection and interpretation of intraoperative testing for language and other cognitive domains. Our aim was to capture and statistically analyze variability in practices in intraoperative language testing among neurosurgeons and neuropsychologists in the United States, Europe, and the rest of the world. METHODS: An electronic questionnaire was developed by a multidisciplinary team at Queen Square, London, and distributed internationally through selected organized societies. The survey included 2 domains: terminology and common understanding of clinical deficits; and selection of intraoperative tests used per specific brain region. Participants were stratified by specialty, years of experience, and monthly caseload. Data were analyzed using Krippendorff α, Wilcoxon rank sum test, and Kruskal-Wallis analysis of variance. RESULTS: A total of 137 specialists participated. A low agreement was recorded for each of the 20 questions (Krippendorff α = -0.023 to 0.312). Further subgroup analysis revealed low interrater reliability independent of specialism (neurosurgeons, α = 0.013-0.318 compared with nonneurosurgeons, α = -0.021 to 0.398; P = 0.808) and years of experience (<1 years, α = -0.003 to 0.282; 2-5 years, α = 0.009-0.327; 6-10 years, α = 0.003-0.234; and >10 years, α = -0.003 to 0.372; P = 0.200). CONCLUSIONS: The current study documents high interrater variability, regardless of specialism and years of experience in the cohort of neurosurgeons and language specialists surveyed and may be applicable to a wider group of specialists, indicating the need to reduce interobserver, interinstitutional and interspecialty variability, reach consensus, and increase the validity, interpretation, and predictive power of intraoperative mapping.