Planning, conducting, and analyzing a psychophysiological experiment on challenge and threat: A comprehensive tutorial.

The biopsychosocial model of challenge and threat (BPS-CT) is a powerful framework linking psychological processes to reliable patterns of cardiovascular responses during motivated performance situations. Specifically, the BPS-CT poses challenge and threat as two motivational states that can emerge in response to a demanding, self-relevant task, where greater challenge arises when perceived resources are higher than demands, and greater threat arises when perceived resources are lower than demands. By identifying unique patterns of physiological responses associated with challenge and threat, respectively, the BPS-CT affords insight into subjective appraisals of resources and demands, and their determinants, during motivated performance situations. Despite its broad utility, lack of familiarity with physiological concepts and difficulty with identifying clear guidelines in the literature are barriers to wider uptake of this approach by behavioral researchers. Our goal is to remove these barriers by providing a comprehensive, step-by-step tutorial on conducting an experiment using the challenge and threat model, offering concrete recommendations for those who are new to the method, and serving as a centralized collection of resources for those looking to deepen their understanding. The tutorial spans five parts, covering theoretical introduction, lab setup, data collection, data analysis, and appendices offering additional details about data analysis and equipment. With this, we aim to make challenge and threat research, and the insights it offers, more accessible to researchers throughout the behavioral sciences.

Individual Differences in Multisensory Processing Are Related to Broad Differences in the Balance of Local versus Distributed Information.

The brain's ability to extract information from multiple sensory channels is crucial to perception and effective engagement with the environment, but the individual differences observed in multisensory processing lack mechanistic explanation. We hypothesized that, from the perspective of information theory, individuals with more effective multisensory processing will exhibit a higher degree of shared information among distributed neural populations while engaged in a multisensory task, representing more effective coordination of information among regions. To investigate this, healthy young adults completed an audiovisual simultaneity judgment task to measure their temporal binding window (TBW), which quantifies the ability to distinguish fine discrepancies in timing between auditory and visual stimuli. EEG was then recorded during a second run of the simultaneity judgment task, and partial least squares was used to relate individual differences in the TBW width to source-localized EEG measures of local entropy and mutual information, indexing local and distributed processing of information, respectively. The narrowness of the TBW, reflecting more effective multisensory processing, was related to a broad pattern of higher mutual information and lower local entropy at multiple timescales. Furthermore, a small group of temporal and frontal cortical regions, including those previously implicated in multisensory integration and response selection, respectively, played a prominent role in this pattern. Overall, these findings suggest that individual differences in multisensory processing are related to widespread individual differences in the balance of distributed versus local information processing among a large subset of brain regions, with more distributed information being associated with more effective multisensory processing. The balance of distributed versus local information processing may therefore be a useful measure for exploring individual differences in multisensory processing, its relationship to higher cognitive traits, and its disruption in neurodevelopmental disorders and clinical conditions.

Spectral slowing in chronic stroke reflects abnormalities in both periodic and aperiodic neural dynamics.

Decades of electrophysiological work have demonstrated the presence of "spectral slowing" in stroke patients - a prominent shift in the power spectrum towards lower frequencies, most evident in the vicinity of the lesion itself. Despite the reliability of this slowing as a marker of dysfunctional tissue across patient groups as well as animal models, it has yet to be explained in terms of the pathophysiological processes of stroke. To do so requires clear understanding of the neural dynamics that these differences represent, acknowledging the often overlooked fact that spectral power reflects more than just the amplitude of neural oscillations. To accomplish this, we used a combination of frequency domain and time domain measures to disambiguate and quantify periodic (oscillatory) and aperiodic (non-oscillatory) neural dynamics in resting state magnetoencephalography (MEG) recordings from chronic stroke patients. We found that abnormally elevated low frequency power in these patients was best explained by a steepening of the aperiodic component of the power spectrum, rather than an enhancement of low frequency oscillations, as is often assumed. However, genuine oscillatory activity at higher frequencies was also found to be abnormal, with patients showing alpha slowing and diminished oscillatory activity in the beta band. These aperiodic and periodic abnormalities were found to covary, and could be detected even in the un-lesioned hemisphere, however they were most prominent in perilesional tissue, where their magnitude was predictive of cognitive impairment. This work redefines spectral slowing as a pattern of changes involving both aperiodic and periodic neural dynamics and narrows the gap in understanding between non-invasive markers of dysfunctional tissue and disease processes responsible for altered neural dynamics.

Leukopenia in clozapine treated patients may be induced by other drugs: a case series.

The combination of clozapine and other potentially leukopenic drugs may pose a greater risk for neutropenia. However, neutropenia may not always be due to clozapine. When adding potentially leukopenic drugs, clinicians should look for possible alternatives especially as clozapine is often a drug used as the last resort in treatment refractory schizophrenia.