Numerous functional neuroimaging studies suggest that widespread bilateral parietal, temporal, and frontal regions are involved in tool-related and pantomimed gesture performance, but the role of these regions in specific aspects of gestural tasks remains unclear. In the largest prospective study of apraxia-related lesions to date, we performed voxel-based lesion-symptom mapping with data from 71 left hemisphere stroke participants to assess the critical neural substrates of three types of actions: gestures produced in response to viewed tools, imitation of tool-specific gestures demonstrated by the examiner, and imitation of meaningless gestures. Thus, two of the three gesture types were tool-related, and two of the three were imitative, enabling pairwise comparisons designed to highlight commonalities and differences. Gestures were scored separately for postural (hand/arm positioning) and kinematic (amplitude/timing) accuracy. Lesioned voxels in the left posterior temporal gyrus were significantly associated with lower scores on the posture component for both of the tool-related gesture tasks. Poor performance on the kinematic component of all three gesture tasks was significantly associated with lesions in left inferior parietal and frontal regions. These data enable us to propose a componential neuroanatomic model of action that delineates the specific components required for different gestural action tasks. Thus, visual posture information and kinematic capacities are differentially critical to the three types of actions studied here: the kinematic aspect is particularly critical for imitation of meaningless movement, capacity for tool-action posture representations are particularly necessary for pantomimed gestures to the sight of tools, and both capacities inform imitation of tool-related movements. These distinctions enable us to advance traditional accounts of apraxia.

Characterizing COVID-19 and Influenza Illnesses in the Real World via Person-Generated Health Data Highlights d We use data from smartphones and wearables from~7,000 people to compare flu and COVID-19 d While symptoms have some overlap, patients report longer COVID-19 illnesses than flu d Elevated resting heart rate measures are more frequent around illness symptoms onset d It is important to consider flu as a confounder in COVID-19 real-world studies

Two fundamental goals of decision making are to select actions that maximize rewards while minimizing costs and to have strong confidence in the accuracy of a judgment. Neural signatures of these two forms of value: the subjective value (SV) of choice alternatives and the value of the judgment (confidence), have both been observed in ventromedial prefrontal cortex (vmPFC). However, the relationship between these dual value signals and their relative time courses are unknown. Twenty-eight men and women underwent fMRI while performing a two-phase approach-avoidance (Ap-Av) task with mixed-outcomes of monetary rewards paired with painful shock stimuli. Neural responses were measured during offer valuation (offer phase) and choice valuation (commit phase) and analyzed with respect to observed decision outcomes, model-estimated SV and confidence. During the offer phase, vmPFC tracked SV and the decision but not confidence. During the commit phase, vmPFC tracked confidence, computed as the quadratic extension of SV, but not the offer valuation nor the decision. In fact, vmPFC responses from the commit phase were selective for confidence even for reject decisions wherein confidence and SV are inversely related. Conversely, activation of the cognitive control network, including within lateral prefrontal cortex (lPFC) and dorsal anterior cingulate cortex (dACC) was associated with ambivalence, during both the offer and commit phases. Taken together, our results reveal complementary representations in vmPFC during value-based decision making that temporally dissociate such that offer valuation (SV) emerges before decision valuation (confidence).

Substantial evidence suggests that conceptual processing of manipulable objects is associated with potentiation of action. Such data have been viewed as evidence that objects are recognized via access to action features. Many objects, however, are associated with multiple actions. For example, a kitchen timer may be clenched with a power grip to move it, but pinched with a precision grip to use it. The present study tested the hypothesis that action evocation during conceptual object processing is responsive to the visual scene in which objects are presented. Twenty-five healthy adults were asked to categorize object pictures presented in different naturalistic visual contexts that evoke either move- or use-related actions. Categorization judgments (natural vs. artifact) were performed by executing a move- or use-related action (clench vs. pinch) on a response device, and response times were assessed as a function of contextual congruence. Although the actions performed were irrelevant to the categorization judgment, responses were significantly faster when actions were compatible with the visual context. This compatibility effect was largely driven by faster pinch responses when objects were presented in use- compared to move-compatible contexts. The present study is the first to highlight the influence of visual scene on stimulus-response compatibility effects during semantic object processing. These data support the hypothesis that action evocation during conceptual object processing is biased toward context-relevant actions.

Commercial wearable devices are surfacing as an appealing mechanism to detect COVID-19 and potentially other public health threats, due to their widespread use. To assess the validity of wearable devices as population health screening tools, it is essential to evaluate predictive methodologies based on wearable devices by mimicking their real-world deployment. Several points must be addressed to transition from statistically significant differences between infected and uninfected cohorts to COVID-19 inferences on individuals. We demonstrate the strengths and shortcomings of existing approaches on a cohort of 32,198 individuals who experience influenza like illness (ILI), 204 of which report testing positive for COVID-19. We show that, despite commonly made design mistakes resulting in overestimation of performance, when properly designed wearables can be effectively used as a part of the detection pipeline. For example, knowing the week of year, combined with naive randomised test set generation leads to substantial overestimation of COVID-19 classification performance at 0.73 AUROC. However, an average AUROC of only 0.55 ± 0.02 would be attainable in a simulation of real-world deployment, due to the shifting prevalence of COVID-19 and non-COVID-19 ILI to trigger further testing. In this work we show how to train a machine learning model to differentiate ILI days from healthy days, followed by a survey to differentiate COVID-19 from influenza and unspecified ILI based on symptoms. In a forthcoming week, models can expect a sensitivity of 0.50 (0-0.74, 95% CI), while utilising the wearable device to reduce the burden of surveys by 35%. The corresponding false positive rate is 0.22 (0.02-0.47, 95% CI). In the future, serious consideration must be given to the design, evaluation, and reporting of wearable device interventions if they are to be relied upon as part of frequent COVID-19 or other public health threat testing infrastructures.

Previous evidence suggests that distinct fronto-parietal regions may be involved in representing action kinematics (means) and action results (outcome) during action observation. However, the evidence is contradictory with respect to the precise regions that are critical for each type of representation. Additionally unknown is the degree to which ability to detect action means and outcome during observation is related to action production performance. We used a behavioral task to evaluate the ability of healthy and left-hemisphere stroke participants to detect differences between pairs of videos that dissociated object-related action means (e.g., wiping with circular or straight movement) and/or outcome (e.g., applying or removing detergent). We expected that deficits in detecting action means would be associated with spatiomotor gesture production deficits, whereas deficits in detecting action outcome would predict impairments in complex naturalistic action. We also hypothesized a posterior to anterior gradient in the regions critical for each type of representation, disproportionately affecting means and outcome encoding, respectively. Results indicated that outcome – but not means – detection predicted naturalistic action performance in stroke participants. Regression and voxel lesion-symptom mapping analyses of lesion data revealed that means – but not outcome – coding relies on the integrity of the left inferior parietal lobe, whereas no selective critical brain region could be identified for outcome detection. Thus, means and outcome representations are dissociable at both the behavioral and neuroanatomical levels. Furthermore, the data are consistent with a degree of parallelism between action perception and production tasks. Finally, they reinforce the evidence for a critical role of the left inferior parietal lobule in the representation of action means, whereas action outcome may rely on a more distributed neural circuit.

Anxiety is characterized by low confidence in daily decisions, coupled with high levels of phenomenological stress. Ventromedial prefrontal cortex (vmPFC) plays an integral role in maladaptive anxious behaviors via decreased sensitivity to threatening vs. non-threatening stimuli (fear generalization). vmPFC is also a key node in approach-avoidance decision making requiring two-dimensional integration of rewards and costs. More recently, vmPFC has been implicated as a key cortical input to the sympathetic branch of the autonomic nervous system. However, little is known about the role of this brain region in mediating rapid stress responses elicited by changes in confidence during decision making. We used an approach-avoidance task to examine the relationship between sympathetically mediated cardiac stress responses, vmPFC activity and choice behavior over long and short time-scales. To do this, we collected concurrent fMRI, EKG and impedance cardiography recordings of sympathetic drive while participants made approach-avoidance decisions about monetary rewards paired with painful electric shock stimuli. We observe first that increased sympathetic drive (shorter pre-ejection period) in states lasting minutes are associated with choices involving reduced decision ambivalence. Thus, on this slow time scale, sympathetic drive serves as a proxy for “mobilization” whereby participants are more likely to show consistent value-action mapping. In parallel, imaging analyses reveal that on shorter time scales (estimated with a trial-to-trial GLM), increased vmPFC activity, particularly during low-ambivalence decisions, is associated with decreased sympathetic state. Our findings support a role of sympathetic drive in resolving decision ambivalence across long time horizons and suggest a potential role of vmPFC in modulating this response on a moment-to-moment basis.

Understanding day-to-day variations in symptoms and medication management can be important in describing patient centered outcomes for people with constipation. Patient Generated Health Data (PGHD) from digital devices is a potential solution, but its utility as a tool for describing experiences of people with frequent constipation is unknown. We conducted a virtual, 16-week prospective study of individuals with frequent constipation from an online wellness platform that connects mobile consumer digital devices including wearable monitors capable of passively collecting steps, sleep, and heart rate data. Participants wore a Fitbit monitoring device for the study duration and were administered daily and monthly surveys assessing constipation symptom severity and medication usage. A set of 38 predetermined day-level behavioral activity metrics were computed from minute-level data streams for steps, sleep and heart rate. Mixed effects regression models were used to compare activity metrics between constipation status (irregular or constipated vs. regular day), medication use (medication day vs. non-medication day) and the interaction of medication day with irregular or constipation days, as well as to model likelihood to treat with constipation medications based on daily self-reported symptom severity. Correction for multiple comparisons was performed with the Benjamini–Hochberg procedure for false discovery rate. This study analyzed 1540 enrolled participants with completed daily surveys (mean age 36.6 sd 10.0, 72.8% female, 88.8% Caucasian). Of those, 1293 completed all monthly surveys and 756 had sufficient Fitbit data density for analysis of activity metrics. At a daily-level, 22 of the 38 activity metrics were significantly associated with bowel movement or medication treatment patterns for constipation. Participants were measured to have fewer steps on irregular days compared to regular days (−200 steps, 95% CI [−280, −120]), longer periods of inactivity on constipated days (9.1 min, 95% CI [5.2, 12.9]), reduced total sleep time on irregular and constipated days (−2.4 min, 95% CI [−4.3, −0.4] and −4.0 min, 95% CI [−6.5, −1.4], respectively). Participants reported greater severity of symptoms for bloating, hard stool, difficulty passing, and painful bowel movements on irregular, constipation and medication days compared to regular days with no medication. Interaction analysis of medication days with irregular or constipation days observed small increases in severity compared to non-medication days. Participants were 4.3% (95% CI 3.2, 5.3) more likely to treat with medication on constipated days versus regular. No significant increase in likelihood was observed for irregular days. Daily likelihood to treat increased for each 1-point change in symptom severity of bloating (2.4%, 95% CI [2.0, 2.7]), inability to pass (2.2%, 95% CI [1.4, 3.0]) and incomplete bowel movements (1.3%, 95% CI [0.9, 1.7]). This is the first large scale virtual prospective study describing the association between passively collected PGHD and constipation symptoms and severity at a day-to-day granularity level. Constipation status, irregular or constipated, was associated with a number of activity metrics in steps and sleep, and likelihood to treat with medication increased with increasing severity for a number of constipation symptoms. Given the small magnitude of effect, further research is needed to understand the clinical relevance of these results. PGHD may be useful as a tool for describing real world patient centered experiences for people with constipation.