Complement Biosensors Identify a Classical Pathway Stimulus in Complement-Mediated Hemolytic Uremic Syndrome.

Complement-mediated hemolytic uremic syndrome (CM-HUS) is a thrombotic microangiopathy characterized by germline variants or acquired antibodies to complement proteins and regulators. Building upon our prior experience with the modified Ham (mHam) assay for ex vivo diagnosis of complementopathies, we have developed an array of cell-based complement "biosensors'' by selective removal of complement regulatory proteins (CD55 and CD59, CD46, or a combination thereof) in an autonomously bioluminescent HEK293 cell line. These biosensors can be used as a sensitive method for diagnosing CM-HUS and monitoring therapeutic complement blockade. Using specific complement pathway inhibitors, this model identifies IgM-driven classical pathway stimulus during both acute disease and in many patients during clinical remission. This provides a potential explanation for ~50% of CM-HUS patients who lack an alternative pathway "driving" variant and suggests at least a subset of CM-HUS is characterized by a breakdown of IgM immunologic tolerance. Key Points: CM-HUS has a CP stimulus driven by polyreactive IgM, addressing the mystery of why 40% of CM-HUS lack complement specific variantsComplement biosensors and the bioluminescent mHam can be used to aid in diagnosis of CM-HUS and monitor complement inhibitor therapy.

Graves-PCD: protocol for a randomised, dose-finding, adaptive trial of the plasma cell-depleting agent daratumumab in severe Graves' disease.

INTRODUCTION: Severe Graves' disease is a life-changing condition with poor outcomes from currently available treatments. It is caused by directly pathogenic thyroid-stimulating hormone receptor-stimulating antibodies (TRAb), which are secreted from plasma cells. The human anti-CD38 monoclonal antibody daratumumab was developed to target plasma cells which express high levels of CD38, and is currently licensed for treatment of the plasma cell malignancy, myeloma. However, it can also deplete benign plasma cells with the potential to reduce TRAb and alter the natural history of severe Graves' disease. This study aims to establish proof of concept that daratumumab has efficacy in patients with severe Graves' disease and will provide important data to inform a choice of dosing regimen for subsequent trials. METHODS AND ANALYSIS: The Graves-PCD trial aims to determine if daratumumab modulates the humoral immune response in patients with severe Graves' disease, and if so, over what time period, and to find an optimal dose. It is a single-blinded, randomised, dose-finding, adaptive trial using four different doses of daratumumab or placebo in 30 adult patients. Part 1 of the trial is dose-finding and, following an interim analysis, in part 2, the remaining patients will be randomised between the chosen dose(s) from the interim analysis or placebo. The primary outcome is the percentage change in serum TRAb from baseline to 12 weeks. ETHICS AND DISSEMINATION: The trial received a favourable ethical opinion from London-Hampstead Research Ethics Committee (reference 21/LO/0449). The results of this trial will be disseminated at international meetings, in the peer-reviewed literature and through partner patient group newsletters and presentations at patient education events. TRIAL REGISTRATION NUMBER: ISRCTN81162400.

Individualization of petrol sources by high field nuclear magnetic resonance spectroscopy.

In the forensic science context petrol is considered the most common fire accelerant. However, the identification and classification of petrol sources through the years has been proven to be a challenge in the investigation of fire related incidents. This research explored the possibility of identification and classification of petrol sources using high field NMR spectroscopy. In this study, 1H NMR profiling, using specific pulse sequences to analyse neat aliquot petrol samples of different brands collected at different times across the UK and Ireland is shown, for the first time, to provide a diagnostic 'fingerprint' with specific chemical compounds that can be used for identification and classification of petrol samples. This enables linkage of unknown petrol samples to a source and in addition provides a tool which allows exclusion of potential petrol sources. A new, innovative method using 1H selTOCSY is described for the individualization and classification of petrol samples through the identification of olefinic markers in the samples. Those markers were identified as (i) 3-methyl-1-butene, (ii) a mixture of 1-pentene and 3-methyl-1-butene, (iii) 2-methyl-2-butene and (iv) a mixture of cis and trans-2-pentene.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities.

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which, in turn, modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (n = 149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Acute psychosocial stress modulates neural and behavioral substrates of cognitive control.

Acute psychosocial stress affects learning, memory, and attention, but the evidence for the influence of stress on the neural processes supporting cognitive control remains mixed. We investigated how acute psychosocial stress influences performance and neural processing during the Go/NoGo task-an established cognitive control task. The experimental group underwent the Trier Social Stress Test (TSST) acute stress induction, whereas the control group completed personality questionnaires. Then, participants completed a functional magnetic resonance imaging (fMRI) Go/NoGo task, with self-report, blood pressure and salivary cortisol measurements of induced stress taken intermittently throughout the experimental session. The TSST was successful in eliciting a stress response, as indicated by significant Stress > Control between-group differences in subjective stress ratings and systolic blood pressure. We did not identify significant differences in cortisol levels, however. The stress induction also impacted subsequent Go/NoGo task performance, with participants who underwent the TSST making fewer commission errors on trials requiring the most inhibitory control (NoGo Green) relative to the control group, suggesting increased vigilance. Univariate analysis of fMRI task-evoked brain activity revealed no differences between stress and control groups for any region. However, using multivariate pattern analysis, stress and control groups were reliably differentiated by activation patterns contrasting the most demanding NoGo trials (i.e., NoGo Green trials) versus baseline in the medial intraparietal area (mIPA, affiliated with the dorsal attention network) and subregions of the cerebellum (affiliated with the default mode network). These results align with prior reports linking the mIPA and the cerebellum to visuomotor coordination, a function central to cognitive control processes underlying goal-directed behavior. This suggests that stressor-induced hypervigilance may produce a facilitative effect on response inhibition which is represented neurally by the activation patterns of cognitive control regions.

Functionality of arousal-regulating brain circuitry at rest predicts human cognitive abilities.

Arousal state is regulated by subcortical neuromodulatory nuclei, such as locus coeruleus, which send wide-reaching projections to cortex. Whether higher-order cortical regions have the capacity to recruit neuromodulatory systems to aid cognition is unclear. Here, we hypothesized that select cortical regions activate the arousal system, which in turn modulates large-scale brain activity, creating a functional circuit predicting cognitive ability. We utilized the Human Connectome Project 7T functional magnetic resonance imaging dataset (N=149), acquired at rest with simultaneous eye tracking, along with extensive cognitive assessment for each subject. First, we discovered select frontoparietal cortical regions that drive large-scale spontaneous brain activity specifically via engaging the arousal system. Second, we show that the functionality of the arousal circuit driven by bilateral posterior cingulate cortex (associated with the default mode network) predicts subjects' cognitive abilities. This suggests that a cortical region that is typically associated with self-referential processing supports cognition by regulating the arousal system.

Locomotor-cognitive dual-tasking in children with developmental coordination disorder.

Introduction: Children with Developmental Coordination Disorder (DCD) demonstrate deficits in predictive motor control and aspects of cognitive control compared with their typically developing (TD) peers. Adjustment to dynamic environments depends on both aspects of control and the deficits for children with DCD may constrain their ability to perform daily actions that involve dual-tasking. Under the assumption that motor-cognitive integration is compromised in children with DCD, we examined proportional dual-task costs using a novel locomotor-cognitive dual-task paradigm that enlisted augmented reality. We expect proportional dual-task performance costs to be greater for children with DCD compared to their TD peers. Methods: Participants were 34 children aged 6-12 years (16 TD, 18 DCD) who walked along a straight 12 m path under single- and dual-task conditions, the cognitive task being visual discrimination under simple or complex stimulus conditions presented via augmented reality. Dual-task performance was measured in two ways: first, proportional dual-task costs (pDTC) were computed for cognitive and gait outcomes and, second, within-trial costs (p-WTC) were measured as the difference on gait outcomes between pre- and post-stimulus presentation. Results: On measures of pDTC, TD children increased their double-limb support time when walking in response to a dual-task, while the children with DCD increased their locomotor velocity. On p-WTC, both groups increased their gait variability (step length and step width) when walking in response to a dual-task, of which the TD group had a larger proportional change than the DCD group. Greater pDTCs on motor rather than cognitive outcomes were consistent across groups and method of dual-task performance measurement. Discussion: Contrary to predictions, our results failed to support dramatic differences in locomotor-cognitive dual-task performance between children with DCD and TD, with both groups tending to priorities the cognitive over the motor task. Inclusion of a within-trial calculation of dual-task interference revealed an expectancy effect for both groups in relation to an impending visual stimulus. It is recommended that dual-task paradigms in the future continue to use augmented reality to present the cognitive task and consider motor tasks of sufficient complexity to probe the limits of performance in children with DCD.

The validity of raw custom-processed global navigation satellite systems data during straight-line sprinting across multiple days.

OBJECTIVES: (1) Determine the validity of instantaneous speed and acceleration and (2) the variation in validity over time (multiple sessions) for global navigation satellite systems (GNSS) devices. DESIGN: Repeated measures. METHODS: 10-Hz GNSS devices from Statsports (n = 2, Apex Pro) and Catapult (n = 2, Vector S7) were examined, whilst a speed laser manufactured by MuscleLab (n = 1, LaserSpeed) was the criterion measure, sampling at 2.56 kHz, with data exported at 1000 Hz. Ten participants completed 40 m sprinting and changes of pace on three separate days. Root mean square error (RMSE) was used to assess the magnitude and direction of the difference between GNSS and criterion measures (instantaneous speed, instantaneous acceleration). Linear mixed models were built to assess the difference in validity across days. RESULTS: RMSE ranged from 0.14 to 0.21 m·s-1 and 0.22 to 0.47 m·s-2 for speed and acceleration, respectively showing strong agreement. There were small variations in the agreement to criterion between days for both devices for speed (Catapult RMSE = 0.12 to 21 m·s-1; Statsports RMSE = 0.14 to 0.17 m·s-1) and for acceleration (Catapult RMSE = 0.26 to 0.47 m·s-2; Statsports RMSE = 0.22 to 0.43 m·s-2) across all movements. There was a negative linear relationship between speed and acceleration error as speed increased. CONCLUSIONS: Wearable microtechnology devices from Catapult (Vector S7) and Statsports (Apex Pro) have suitable validity when measuring instantaneous speed and acceleration across multiple days. There may be small variations during different sessions and over the speed spectrum.

Validity and Reliability of Thoracic-Mounted Inertial Measurement Units to Derive Gait Characteristics During Running.

ABSTRACT: Horsley, BJ, Tofari, PJ, Halson, SL, Kemp, JG, Chalkley, D, Cole, MH, Johnston, RD, and Cormack, SJ. Validity and reliability of thoracic-mounted inertial measurement units to derive gait characteristics during running. J Strength Cond Res 38(2): 274-282, 2024-Inertial measurement units (IMUs) attached to the tibia or lumbar spine can be used to analyze running gait but, with team-sports, are often contained in global navigation satellite system (GNSS) units worn on the thoracic spine. We assessed the validity and reliability of thoracic-mounted IMUs to derive gait characteristics, including peak vertical ground reaction force (vGRF peak ) and vertical stiffness (K vert ). Sixteen recreationally active subjects performed 40 m run throughs at 3-4, 5-6, and 7-8 m·s -1 . Inertial measurement units were attached to the tibia, lumbar, and thoracic spine, whereas 2 GNSS units were also worn on the thoracic spine. Initial contact (IC) from a validated algorithm was evaluated with F1 score and agreement (mean difference ± SD ) of gait data with the tibia and lumbar spine using nonparametric limits of agreement (LoA). Test-retest error {coefficient of variation, CV (95% confidence interval [CI])} established reliability. Thoracic IMUs detected a nearly perfect proportion (F1 ≥ 0.95) of IC events compared with tibia and lumbar sites. Step length had the strongest agreement (0 ± 0.04 m) at 3-4 m·s -1 , whereas contact time improved from 3 to 4 (-0.028 ± 0.018 second) to 7-8 m·s -1 (-0.004 ± 0.013 second). All values for K vert fell within the LoA at 7-8 m·s -1 . Test-retest error was ≤12.8% for all gait characteristics obtained from GNSS units, where K vert was most reliable at 3-4 m·s -1 (6.8% [5.2, 9.6]) and vGRF peak at 7-8 m·s -1 (3.7% [2.5, 5.2]). The thoracic-spine site is suitable to derive gait characteristics, including K vert , from IMUs within GNSS units, eliminating the need for additional sensors to analyze running gait.

The efficacy of dance interventions for the activity and participation of individuals with cerebral palsy - a systematic review and meta-analysis.

PURPOSE: The aim of this review was to examine the efficacy of dance interventions for individuals with cerebral palsy (CP), measured at any level of the International Classification of Functioning, Disability and Health (ICF). METHODS: A systematic review and meta-analysis was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A comprehensive search of peer-reviewed articles was performed using six electronic databases. RESULTS: Fourteen studies were included in this review, nine of which were also included in the meta-analysis. The meta-analyses yielded a large overall effect for cognitive, motor, and social-emotional function outcomes, with a high degree of heterogeneity between outcome effects, attributable to differences in study design. CONCLUSION: Although recent studies provide support for the acceptance and efficacy of dance interventions for people with CP, the systematic review revealed significant limitations in study design (only 2 randomised control trials). High-quality research that measures outcomes across all dimensions of the ICF, and particularly at the level of participation, are needed to improve the level of empirical support for dance-based interventions.

Movement- and step-based dance practice for cerebral palsy have a positive impact on walking/gait, balance/postural control, and range of motion.Dance programs should move beyond a traditional focus on body structure and function, placing participation at the forefront of the program.Rehabilitation professionals should consider forming partnerships with stakeholders, addressing their goals, experiences, and challenges, with dance as a feasible and important option for participation-based practice.

Gastrointestinal and genitourinary symptoms in facioscapulohumeral muscular dystrophy: Prevalence and impact.

INTRODUCTION/AIMS: Anecdotally, patients with facioscapulohumeral muscular dystrophy (FSHD) describe gastrointestinal (GI) and genitourinary (GU) symptoms. We explored the prevalence of GI and GU symptoms and their impact on quality of life (QOL) in people with FSHD compared to healthy household controls. METHODS: In this descriptive, cross-sectional study, we emailed a survey exploring GI and GU symptoms to all FSHD Society patient contacts (n = 3507). We invited those with FSHD and unaffected household controls to respond. Non-parametric statistics were used to compare symptom frequency and impact of symptoms between respondents with FSHD and household controls. Within the FSHD group, symptom frequency was assessed relative to measures of disease progression (need for ambulatory or respiratory support). RESULTS: Surveys from 701 respondents (652 with FSHD) ≥18 years old were included in analysis. Those with FSHD had symptoms affecting both GI and GU systems more frequently than controls using ordinal rating of symptom frequency. Within the FSHD group, more advanced disease was associated with increased symptom frequency. QOL was negatively impacted by the GI and GU symptoms. There was no difference between groups in use of medications to treat these symptoms. DISCUSSION: Recognition and treatment of GI and GU symptoms in people with FSHD, particularly those with more advanced disease, could improve QOL. Additional investigation is required to confirm these findings and understand the physiology.

Precision data-driven modeling of cortical dynamics reveals idiosyncratic mechanisms underlying canonical oscillations.

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and is a strong marker of individual differences. In this work, we present an algorithmic optimization framework that makes it possible to directly invert and parameterize brain-wide dynamical-systems models involving hundreds of interacting brain areas, from single-subject time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG markers. Lastly, we demonstrate the power of our technique in resolving individual differences in the generation of alpha and beta-frequency oscillations. We characterize subjects based upon model attractor topology and a dynamical-systems mechanism by which these topologies generate individual variation in the expression of alpha vs. beta rhythms. We trace these phenomena back to global variation in excitation-inhibition balance, highlighting the explanatory power of our framework in generating mechanistic insights.

Complement biomarkers in the antiphospholipid syndrome - Approaches to quantification and implications for clinical management.

Complement is a major driver of antiphospholipid syndrome (APS) and a promising therapeutic target in refractory and catastrophic APS. Complement testing in APS is largely limited to research settings, and reliable, rapid-turnaround biomarkers are needed to predict those at risk for adverse clinical outcomes and most likely to benefit from complement inhibition. We review complement biomarkers and their association with thrombosis and obstetric outcomes, including: (i) complement proteins and activation fragments in the fluid phase; (ii) assays that evaluate complement on cell membranes (e.g. in vivo cell-bound complement fragments, hemolytic assays, and ex vivo 'functional' cell-based assays, and (iii) sequencing of complement genes. Current studies highlight the inconsistencies in testing both between studies and various aPL/APS subgroups, suggesting that either cell-based testing or multiplex panels employing a combination of biomarkers simultaneously may be most clinically relevant. Standardization of complement assays is needed to ensure reproducibility and establish clinically relevant applications.

Competing numerical magnitude codes in decimal comparison: Whole number and rational number distance both impact performance.

A critical difference between decimal and whole numbers is that among whole numbers the number of digits provides reliable information about the size of the number, e.g., double-digit numbers are larger than single-digit numbers. However, for decimals, fewer digits can sometimes denote a larger number (i.e., 0.8 > 0.27). Accordingly, children and adults perform worse when comparing such Inconsistent decimal pairs relative to Consistent pairs, where the larger number also has more digits (i.e., 0.87 > 0.2). Two explanations have been posited for this effect. The string length congruity account proposes that participants compare each position in the place value system, and they additionally compare the number of digits. The semantic interference account suggests that participants additionally activate the whole number referents of numbers - the numbers unadorned with decimal points (e.g., 8 < 27) - and compare these. The semantic interference account uniquely predicts that for Inconsistent problems with the same actual rational distance, those with larger whole number distances should be harder, e.g., 0.9 vs. 0.81 should be harder than 0.3 vs. 0.21 because 9 < < 81 whereas 3 < 21. Here we test this prediction in two experiments with college students (Study 1: n = 58 participants, Study 2: n = 78). Across both, we find a main effect of consistency, demonstrating string length effects, and also that whole number distance interferes with processing conflicting decimals, demonstrating semantic interference effects. Evidence for both effects supports the semantic interference account, highlighting that decimal comparison difficulties arise from multiple competing numerical codes. Finally, for accuracy we found no relationship between whole number distance sensitivity and math achievement, indicating that whole number magnitude interference affects participants similarly across the spectrum of math achievement.

Validity and Reliability of Methods to Assess Movement Deficiencies Following Concussion: A COSMIN Systematic Review.

BACKGROUND: There is an increased risk of subsequent concussion and musculoskeletal injury upon return to play following a sports-related concussion. Whilst there are numerous assessments available for clinicians for diagnosis and during return to play following concussion, many may lack the ability to detect these subclinical changes in function. Currently, there is no consensus or collated sources on the reliability, validity and feasibility of these assessments, which makes it difficult for clinicians and practitioners to select the most appropriate assessment for their needs. OBJECTIVES: This systematic review aims to (1) consolidate the reliability and validity of motor function assessments across the time course of concussion management and (2) summarise their feasibility for clinicians and other end-users. METHODS: A systematic search of five databases was conducted. Eligible studies were: (1) original research; (2) full-text English language; (3) peer-reviewed with level III evidence or higher; (4) assessed the validity of lower-limb motor assessments used to diagnose or determine readiness for athletes or military personnel who had sustained a concussion or; (5) assessed the test-retest reliability of lower-limb motor assessments used for concussion management amongst healthy athletes. Acceptable lower-limb motor assessments were dichotomised into instrumented and non-instrumented and then classified into static (stable around a fixed point), dynamic (movement around a fixed point), gait, and other categories. Each study was assessed using the COSMIN checklist to establish methodological and measurement quality. RESULTS: A total of 1270 records were identified, with 637 duplicates removed. Titles and abstracts of 633 records were analysed, with 158 being retained for full-text review. A total of 67 records were included in this review; 37 records assessed reliability, and 35 records assessed the validity of lower-limb motor assessments. There were 42 different assessments included in the review, with 43% being non-instrumented, subjective assessments. Consistent evidence supported the use of instrumented assessments over non-instrumented, with gait-based assessments demonstrating sufficient reliability and validity compared to static or dynamic assessments. CONCLUSION: These findings suggest that instrumented, gait-based assessments should be prioritised over static or dynamic balance assessments. The use of laboratory equipment (i.e. 3D motion capture, pressure sensitive walkways) on average exhibited sufficient reliability and validity, yet demonstrate poor feasibility. Further high-quality studies evaluating the reliability and validity of more readily available devices (i.e. inertial measurement units) are needed to fill the gap in current concussion management protocols. Practitioners can use this resource to understand the accuracy and precision of the assessments they have at their disposal to make informed decisions regarding the management of concussion. TRAIL REGISTRATION: This systematic review was registered on PROSPERO (reg no. CRD42021256298).

Neural representation dynamics reveal computational principles of cognitive task learning.

During cognitive task learning, neural representations must be rapidly constructed for novel task performance, then optimized for robust practiced task performance. How the geometry of neural representations changes to enable this transition from novel to practiced performance remains unknown. We hypothesized that practice involves a shift from compositional representations (task-general activity patterns that can be flexibly reused across tasks) to conjunctive representations (task-specific activity patterns specialized for the current task). Functional MRI during learning of multiple complex tasks substantiated this dynamic shift from compositional to conjunctive representations, which was associated with reduced cross-task interference (via pattern separation) and behavioral improvement. Further, we found that conjunctions originated in subcortex (hippocampus and cerebellum) and slowly spread to cortex, extending multiple memory systems theories to encompass task representation learning. The formation of conjunctive representations hence serves as a computational signature of learning, reflecting cortical-subcortical dynamics that optimize task representations in the human brain.

Terrain Characterization via Machine vs. Deep Learning Using Remote Sensing.

Terrain traversability is critical for developing Go/No-Go maps for ground vehicles, which significantly impact a mission's success. To predict the mobility of terrain, one must understand the soil characteristics. In-situ measurements performed in the field are the current method of collecting this information, which is time-consuming, costly, and can be lethal for military operations. This paper investigates an alternative approach using thermal, multispectral, and hyperspectral remote sensing from an unmanned aerial vehicle (UAV) platform. Remotely sensed data combined with machine learning (linear, ridge, lasso, partial least squares (PLS), support vector machines (SVM), and k nearest neighbors (KNN)) and deep learning (multi-layer perceptron (MLP) and convolutional neural network (CNN)) are used to perform a comparative study to estimate the soil properties, such as the soil moisture and terrain strength, used to generate prediction maps of these terrain characteristics. This study found that deep learning outperformed machine learning. Specifically, a multi-layer perceptron performed the best for predicting the percent moisture content (R2/RMSE = 0.97/1.55) and the soil strength (in PSI), as measured by a cone penetrometer for the averaged 0-6" (CP06) (R2/RMSE = 0.95/67) and 0-12" depth (CP12) (R2/RMSE = 0.92/94). A Polaris MRZR vehicle was used to test the application of these prediction maps for mobility purposes, and correlations were observed between the CP06 and the rear wheel slip and the CP12 and the vehicle speed. Thus, this study demonstrates the potential of a more rapid, cost-efficient, and safer approach to predict terrain properties for mobility mapping using remote sensing data with machine and deep learning algorithms.

Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations.

Brain activity flow models estimate the movement of task-evoked activity over brain connections to help explain network-generated task functionality. Activity flow models have been shown to accurately generate task-evoked brain activations across a wide variety of brain regions and task conditions. However, these models have had limited explanatory power, given known issues with causal interpretations of the standard functional connectivity measures used to parameterize activity flow models. We show here that functional/effective connectivity (FC) measures grounded in causal principles facilitate mechanistic interpretation of activity flow models. We progress from simple to complex FC measures, with each adding algorithmic details reflecting causal principles. This reflects many neuroscientists' preference for reduced FC measure complexity (to minimize assumptions, minimize compute time, and fully comprehend and easily communicate methodological details), which potentially trades off with causal validity. We start with Pearson correlation (the current field standard) to remain maximally relevant to the field, estimating causal validity across a range of FC measures using simulations and empirical fMRI data. Finally, we apply causal-FC-based activity flow modeling to a dorsolateral prefrontal cortex region (DLPFC), demonstrating distributed causal network mechanisms contributing to its strong activation during a working memory task. Notably, this fully distributed model is able to account for DLPFC working memory effects traditionally thought to rely primarily on within-region (i.e., not distributed) recurrent processes. Together, these results reveal the promise of parameterizing activity flow models using causal FC methods to identify network mechanisms underlying cognitive computations in the human brain.