Digital Methods for Performing Daily Tasks Among Older Adults: An Initial Report of Frequency of Use and Perceived Utility.

OBJECTIVE: Digital technologies permit new ways of performing instrumental activities of daily living (iADLs) for older adults, but these approaches are not usually considered in existing iADL measures. The current study investigated how a sample of older adults report using digital versus analog approaches for iADLs. METHOD: 248 older adults completed the Digital and Analog Daily Activities Survey, a newly developed measure of how an individual performs financial, navigation, medication, and other iADLs. RESULTS: The majority of participants reported regularly using digital methods for some iADLs, such as paying bills (67.7%) and using GPS (67.7%). Low digital adopters were older than high adopters (F(2, 245) = 12.24, p < .001), but otherwise the groups did not differ in terms of gender, years of education, or history of neurological disorders. Participants who used digital methods relatively more than analog methods reported greater levels of satisfaction with their approach and fewer daily errors. CONCLUSIONS: Many older adults have adopted digital technologies for supporting daily tasks, which suggests limitations to the validity of current iADL assessments. By capitalizing on existing habits and enriching environments with new technologies, there are opportunities to promote technological reserve in older adults in a manner that sustains daily functioning.

National trends in the endovascular and surgical treatment of idiopathic intracranial hypertension.

BACKGROUND: The pattern of surgical treatments for Idiopathic Intracranial Hypertension (IIH) in the United States is not well-studied, specifically the trend of utilizing endovascular venous stenting (EVS) as an emerging technique. METHODS: In this cross-sectional study, we aimed to explore the national trend of utilizing different procedures for the treatment of IIH including EVS, Optic Nerve Sheath Fenestration (ONSF), and CSF Shunting, with a focus on novel endovascular procedures. Moreover, we explored rates of 90-day readmission and length of hospital stay following different procedures, besides the effects of sociodemographic and clinical parameters on procedure choice. RESULTS: 36,437 IIH patients were identified from records between 2010 and 2018. Those in the EVS group were 29 years old on average, and 93.4 % were female. Large academic hospital setting was independently associated with higher EVS utilization, while other factors were not predictive of procedure choice. The proportion of EVS use in IIH hospitalizations increased significantly from 2010 to 2018 (P < 0.001), while there was a relative decline in the frequency of shunting procedures (P = 0.001), with ONSF utilization remaining stable (P = 0.39). The rate of 90-day readmission and length of hospital stay were considerably lower following EVS compared to other procedures (Ps < 0.001). CONCLUSION: This study presents novel population-level data on national trends in the frequency and outcome of EVS for IIH therapy. EVS was associated with shorter length of hospital stays and fewer readmission rates. In addition, a continuous increase in venous stenting compared to other procedures suggests an increasing role for endovascular therapies in IIH.

Designing an interprofessional dementia specialty clinic: Conceptualization and evaluation of a patient-centered model.

The need for blueprints to design specialty care interprofessional collaboration (IPC) models is urgent, given the expanding aging population and current challenges in dementia diagnosis and treatment. We describe key steps creating an interprofessional outpatient dementia specialty clinic, efforts to sustain the model, and evaluation of interprofessional effectiveness and clinician satisfaction. The conception for the Comprehensive Memory Center was informed by qualitative research methodologies including focus groups, interviews, and literature reviews. Quantitative evaluation included satisfaction surveys and team effectiveness measures. The IPC model diverges from typical dementia practices through its interprofessional team, visit structure, approach to decision-making, in-house services, and community collaborations. Team retreats and workshops helped build clinician knowledge of interprofessional values and practices to sustain the IPC model. In the first 3.5 years, we served nearly 750 patients and their caregivers. Team evaluation results revealed that increased access to consultation and sharing the workload and emotional burden were beneficial. The majority of team members preferred the IPC model to traditional models of clinical care.

Prospective Observational Cohort Study of Tenecteplase Versus Alteplase in Routine Clinical Practice.

BACKGROUND: A 10-hospital regional network transitioned to tenecteplase as the standard of care stroke thrombolytic in September 2019 because of potential workflow advantages and reported noninferior clinical outcomes relative to alteplase in meta-analyses of randomized trials. We assessed whether tenecteplase use in routine clinical practice reduced thrombolytic workflow times with noninferior clinical outcomes. METHODS: We designed a prospective registry-based observational, sequential cohort comparison of tenecteplase- (n=234) to alteplase-treated (n=354) stroke patients. We hypothesized: (1) an increase in the proportion of patients meeting target times for target door-to-needle time and transfer door-in-door-out time, and (2) noninferior favorable (discharge to home with independent ambulation) and unfavorable (symptomatic intracranial hemorrhage, in-hospital mortality or discharge to hospice) in the tenecteplase group. Total hospital cost associated with each treatment was also compared. RESULTS: Target door-to-needle time within 45 minutes for all patients was superior for tenecteplase, 41% versus 29%; adjusted odds ratio, 1.85 (95% CI, 1.27-2.71); P=0.001; 58% versus 41% by Get With The Guidelines criteria. Target door-in-door-out time within 90 minutes was superior for tenecteplase 37% (15/43) versus 14% (9/65); adjusted odds ratio, 3.62 (95% CI, 1.30-10.74); P=0.02. Favorable outcome for tenecteplase fell within the 6.5% noninferiority margin; adjusted odds ratio, 1.26 (95% CI, 0.89-1.80). Unfavorable outcome was less for tenecteplase, 7.3% versus 11.9%, adjusted odds ratio, 0.77 (95% CI, 0.42-1.37) but did not fall within the prespecified 1% noninferior boundary. Net benefit (%favorable-%unfavorable) was greater for the tenecteplase sample: 37% versus 27%. P=0.02. Median cost per hospital encounter was less for tenecteplase cases ($13 382 versus $15 841; P<0.001). CONCLUSIONS: Switching to tenecteplase in routine clinical practice in a 10-hospital network was associated with shorter door-to-needle time and door-in-door-out times, noninferior favorable clinical outcomes at discharge, and reduced hospital costs. Evaluation in larger, multicenter cohorts is recommended to determine if these observations generalize.

Optimizing Emergency Stroke Transport Strategies Using Physiological Models.

BACKGROUND AND PURPOSE: The criteria for choosing between drip and ship and mothership transport strategies in emergency stroke care is widely debated. Although existing data-driven probability models can inform transport decision-making at an epidemiological level, we propose a novel mathematical, physiologically derived framework that provides insight into how patient characteristics underlying infarct core growth influence these decisions. METHODS: We represent the physiology of time-dependent infarct core growth within an ischemic penumbra as an exponential function with consideration to rate-determining collateral blood flow. Monte Carlo methods generate distributions of infarct core volumes, which are translated to distributions of 90-day modified Rankin Scale scores. We apply the model to a stroke network that serves rural Bastrop County and urban Travis County by simulating transport strategies from thousands of potential patient pickup locations. In every pickup location, the simulation yields a distribution of outcomes corresponding to each transport strategy. A 2-sample Kolmogorov-Smirnov test and Student t test determine which transport strategy provides a significantly better probability of a good outcome for a given pickup location in each respective county (P<0.01). RESULTS: In Travis County, drip and ship provides significantly better probabilities of a good outcome in 24.0% of the pickup locations, while 59.8% favor mothership. In Bastrop County, 11.3% of the pickup locations favor drip and ship, while only 7.1% favor mothership. The remaining pickup locations in each county are not statistically significant in either direction. We also reveal how differing rates of infarct core growth, the application of bypass policies, and the use of large vessel occlusion field tests impact these results. CONCLUSIONS: Modeling stroke physiology enables the use of clinically relevant metrics for determining comparative significance between drip and ship and mothership in a given geography. This formalism can help understand and inform emergency medical service transport decision-making, as well as regional bypass policies.

Effect of spontaneous movement on respiration in preterm infants.

NEW FINDINGS: What is the central question of this study? The respiratory centres in the brainstem that control respiration receive inputs from various sources, including proprioceptors in muscles and joints and suprapontine centres, which all affect limb movements. What is the effect of spontaneous movement on respiration in preterm infants? What is the main finding and its importance? Apnoeic events tend to be preceded by movements. These activity bursts can cause respiratory instability that leads to an apnoeic event. These findings show promise that infant movements might serve as potential predictors of life-threatening apnoeic episodes, but more research is required. ABSTRACT: A common condition in preterm infants (<37 weeks' gestational age) is apnoea resulting from immaturity and instability of the respiratory system. As apnoeas are implicated in several acute and long-term complications, prediction of apnoeas may preempt their onset and subsequent complications. This study tests the hypothesis that infant movements are a predictive marker for apnoeic episodes and examines the relation between movement and respiration. Movement was detected using a wavelet algorithm applied to the photoplethysmographic signal. Respiratory activity was measured in nine infants using respiratory inductance plethysmography; in an additional eight infants, respiration and partial pressure of airway carbon dioxide ( PCO2 ) were measured by a nasal cannula with side-stream capnometry. In the first cohort, the distribution of movements before and after the onset of 370 apnoeic events was compared. Results showed that apnoeic events were associated with longer movement duration occurring before apnoea onsets compared to after. In the second cohort, respiration was analysed in relation to movement, comparing standard deviation of inter-breath intervals (IBI) before and after apnoeas. Poincaré maps of the respiratory activity quantified variability of airway PCO2 in phase space. Movement significantly increased the variability of IBI and PCO2 . Moreover, destabilization of respiration was dependent on the duration of movement. These findings support that bodily movements of the infants precede respiratory instability. Further research is warranted to explore the predictive value of movement for life-threatening events, useful for clinical management and risk stratification.

Characterizing the performance of emergency medical transport time metrics in a residentially segregated community.

OBJECTIVE: To derive and characterize the performance of various metrics of emergency transport time in assessing for sociodemographic disparities in the setting of residential segregation. Secondarily to characterize racial disparities in emergency transport time of suspected stroke patients in Austin, Texas. DATA SOURCES: We used a novel dataset of 2518 unique entries with detailed spatial and temporal information on all suspected stroke transports conducted by a public emergency medical service in Central Texas between 2010 and 2018. STUDY DESIGN: We conducted one-way ANOVA tests with post-hoc pairwise t-tests to assess how mean hospital transport times varied by patient race. We also developed a spatially-independent metric of emergency transport urgency, the ratio of expected duration of self-transport to a hospital and the measured transport time by an ambulance. DATA COLLECTION/EXTRACTION: We calculated ambulance arrival and destination times using sequential temporospatial coordinates. We excluded any entries in which patient race was not recorded. We also excluded entries in which ambulances' routes did not pass within 100 m of either the patient's location or the documented hospital destination. PRINCIPAL FINDINGS: We found that mean transport time to a hospital was 2.5 min shorter for black patients compared to white patients. However, white patients' transport times to a hospital were found to be, on average, 4.1 min shorter than expected compared to 3.4 min shorter than expected for black patients. One-way ANOVA testing for the spatially-independent index of emergency transport urgency was not statistically significant, indicating that average transport time did not vary significantly across racial groups when accounting for variations in transport distance. CONCLUSIONS: Using a novel transport urgency index, we demonstrate that these findings represent race-based variation in spatial distributions rather than racial bias in emergency medical transport. These results highlight the importance of closely examining spatial distributions when utilizing temporospatial data to investigate geographically-dependent research questions.

Falling off a limit cycle using phase-agnostic stimuli: Applications to clinical oscillopathies.

For over a century, physiological studies have shown that precisely timed pulses can switch off a biological oscillator. This empiric finding has shaped our mechanistic understanding of how perturbations start, stop, and reset biological oscillators and has led to treatments that suppress pathological oscillations using electrical pulses given within specified therapeutic phase windows. Here, we present evidence, using numerical simulations of models of epileptic seizures and reentrant tachycardia, that the phase window can be opened to the entire cycle using novel complex stimulus waveforms. Our results reveal that the trajectories are displaced by such phase-agnostic stimuli off the oscillator's limit cycle and corralled into a region where oscillation is suppressed, irrespective of the phase at which the stimulus was applied. Our findings suggest the need for broadening theoretical understanding of how complex perturbing waveforms interact with biological oscillators to access their arrhythmic states. In clinical practice, oscillopathies may be treated more effectively with non-traditional stimulus waveforms that obviate the need for phase specificity.

Falling off a limit cycle using phase-agnostic stimuli: Definitions and conceptual framework.

Nearly a half-century of biomedical research has revealed methods and mechanisms by which an oscillator with bistable limit cycle kinetics can be stopped using critical stimuli applied at a specific phase. Is it possible to construct a stimulus that stops oscillation regardless of the phase at which the stimulus is applied? Using a radial isochron clock model, we demonstrate the existence of such stimulus waveforms, which can take on highly complex shapes but with a surprisingly simple mechanism of rhythm suppression. The perturbation, initiated at any phase of the limit cycle, first corrals the oscillator to a narrow range of new phases, then drives the oscillator to its phase singularity. We further constructed a library of waveforms having different durations, each achieving phase-agnostic suppression of rhythm but with varying rates of phase corralling prior to amplitude suppression. The optimal stimulus energy to achieve phase-agnostic suppression of rhythm is dependent on the rate of phase corralling and the configuration of the phaseless set. We speculate that these results are generic and suggest the existence of stimulus waveforms that can stop the rhythm of more complex oscillators irrespective of the applied phase.

Optimizing stimulus waveforms for electroceuticals.

There has been a growing interest in the use of electrical stimulation as a therapy across diverse medical conditions. Most electroceutical devices use simple waveforms, for example sinusoidal or rectangular biphasic pulses. Clinicians empirically tune the waveform parameters (e.g. amplitude, frequency) without altering the fundamental shape of the stimulus. In this article, we review computational strategies that have been used to optimize the shape of stimulus waveforms in order to improve clinical outcomes, and we discuss potential directions for future exploration.

Characterizing spiking in noisy type II neurons.

Understanding the dynamics of noisy neurons remains an important challenge in neuroscience. Here, we describe a simple probabilistic model that accurately describes the firing behavior in a large class (type II) of neurons. To demonstrate the usefulness of this model, we show how it accurately predicts the interspike interval (ISI) distributions, bursting patterns and mean firing rates found by: (1) simulations of the classic Hodgkin-Huxley model with channel noise, (2) experimental data from squid giant axon with a noisy input current and (3) experimental data on noisy firing from a neuron within the suprachiasmatic nucleus (SCN). This simple model has 6 parameters, however, in some cases, two of these parameters are coupled and only 5 parameters account for much of the known behavior. From these parameters, many properties of spiking can be found through simple calculation. Thus, we show how the complex effects of noise can be understood through a simple and general probabilistic model.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm.

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Pulmonary effects of intravenous atropine induce ventilation perfusion mismatch.

Atropine is used for a number of medical conditions, predominantly for its cardiovascular effects. Cholinergic nerves that innervate pulmonary smooth muscle, glands, and vasculature may be affected by anticholinergic medications. We hypothesized that atropine causes alterations in pulmonary gas exchange. We conducted a prospective interventional study with detailed physiologic recordings in anesthetized, spontaneously breathing rats (n = 8). Animals breathing a normoxic gas mixture titrated to a partial arterial pressure of oxygen of 110-120 were exposed to an escalating dose of intravenous atropine (0.001, 0.01, 0.1, 5.0, and 20.0 mg/kg body mass). Arterial blood gas measurements were recorded every 2 min (×5) at baseline, and following each of the 5 doses of atropine. In addition, the animals regional pulmonary blood flow was measured using neutron-activated microspheres. Oxygenation decreased immediately following intravenous administration of atropine, despite a small increase in the volume of inspired air with no change in respiratory rate. Arterial blood gas analysis showed an increase in pulmonary dysfunction, characterized by a widening of the alveolar-arteriole gradient (p < 0.003 all groups except for the lowest dose of atropine). The microsphere data demonstrates an abrupt and marked heterogeneity of pulmonary blood flow following atropine treatment. In conclusion, atropine was found to decrease pulmonary gas exchange in a dose-dependent fashion in this rat model.

Ischemic stroke in evolution: predictive value of perfusion computed tomography.

BACKGROUND: Various perfusion computed tomography (PCT) parameters have been used to identify tissue at risk of infarction in the setting of acute stroke. The purpose of this study was to examine predictive value of the PCT parameters commonly used in clinical practice to define ischemic penumbra. The patient selection criterion aimed to exclude the effect of thrombolysis from the imaging data. METHODS: Consecutive acute stroke patients were screened and a total of 18 patients who initially underwent PCT and CT angiogram (CTA) on presentation but did not qualify to receive thrombolytic therapy were selected. The PCT images were postprocessed using a delay-sensitive deconvolution algorithm. All the patients had follow-up noncontrast CT or magnetic resonance imaging to delineate the extent of their infarction. The extent of lesions on PCT maps calculated from mean transit time (MTT), time to peak (TTP), cerebral blood flow, and cerebral blood volume were compared and correlated with the final infarct size. A collateral grading score was used to measure collateral blood supply on the CTA studies. RESULTS: The average size of MTT lesions was larger than infarct lesions (P < .05). The correlation coefficient of TTP/infarct lesions (r = .95) was better than MTT/infarct lesions (r = .66) (P = .004). CONCLUSIONS: A widely accepted threshold to define MTT lesions overestimates the ischemic penumbra. In this setting, TTP with appropriate threshold is a better predictor of infarct in acute stroke patients. The MTT/TTP mismatch correlates with the status of collateral blood supply to the tissue at risk of infarction.

Internet-Enabled Behaviors in Older Adults During the Pandemic: Patterns of Use, Psychosocial Impacts, and Plans for Continued Utilization.

In response to social distancing measures during the COVID-19 pandemic, there was a need to increase the frequency of internet enabled behaviors (IEBs). To date, little is known about how the pandemic impacted IEBs in older adults, a population that has historically been linked to lower digital literacy and utilization. We administered an online survey between April and July 2021 to 298 adults who were over age 50 (mean age = 73 years; 93.5% non-Hispanic white; 94% smart phone owners; 83.5% retired). Older adults self-reported IEBs for social, shopping, medical, and leisure activities during the pandemic, plans for continued use of these behaviors, and completed measures of psychosocial functioning. 66.8% of respondents reported an overall increase in IEBs during the pandemic, most notably for online meeting attendance. More frequent online meeting use was associated with less depression (r = -0.12, p = .04) and less loneliness (r = -0.14, p = .02). With regard to plans for continued use, 82.5% of the sample reported at least one IEB (M = 2.18, SD = 1.65) that they increased during the pandemic and planned to maintain over time (e.g., online shopping for household goods). Plans for continued use were more likely in participants who used IEBs more overall during the pandemic (r = 0.56, p < .001), and who frequently sought technical support on search engines (r = 0.22, p < .001), or online video sites (r = 0.16, p = .006). In summary, IEBs during the pandemic were associated with favorable psychosocial functioning and expectations for continued use in this sample of predominantly white older adults who had some baseline technological familiarity.

In Vivo Deformation of the Human Basilar Artery.

An estimated 6.8 million people in the United States have an unruptured intracranial aneurysms, with approximately 30,000 people suffering from intracranial aneurysms rupture each year. Despite the development of population-based scores to evaluate the risk of rupture, retrospective analyses have suggested the limited usage of these scores in guiding clinical decision-making. With recent advancements in imaging technologies, artery wall motion has emerged as a promising biomarker for the general study of neurovascular mechanics and in assessing the risk of intracranial aneurysms. However, measuring arterial wall deformations in vivo itself poses several challenges, including how to image local wall motion and deriving the anisotropic wall strains over the cardiac cycle. To overcome these difficulties, we first developed a novel in vivo MRI-based imaging method to acquire cardiac gated images of the human basilar artery (BA) over the cardiac cycle. Next, complete BA endoluminal surfaces from each frame were segmented, producing high-resolution point clouds of the endoluminal surfaces. From these point clouds we developed a novel B-spline-based surface representation, then exploited the local support nature of B-splines to determine the local endoluminal surface strains. Results indicated distinct regional and temporal variations in BA wall deformation, highlighting the heterogeneous nature BA function. These included large circumferential strains (up to ∼ 20 % ), and small longitudinal strains, which were often contractile and out of phase with the circumferential strains patterns. Of particular interest was the temporal phase lag in the maximum circumferential perimeter length, which indicated that the BA deforms asynchronously over the cardiac cycle. In summary, the proposed method enabled local deformation analysis, allowing for the successful reproduction of local features of the BA, such as regional principal stretches, areal changes, and pulsatile motion. Integrating the proposed method into existing population-based scores has the potential to improve our understanding of mechanical properties of human BA and enhance clinical decision-making.

Building Digital Twins for Cardiovascular Health: From Principles to Clinical Impact.

The past several decades have seen rapid advances in diagnosis and treatment of cardiovascular diseases and stroke, enabled by technological breakthroughs in imaging, genomics, and physiological monitoring, coupled with therapeutic interventions. We now face the challenge of how to (1) rapidly process large, complex multimodal and multiscale medical measurements; (2) map all available data streams to the trajectories of disease states over the patient's lifetime; and (3) apply this information for optimal clinical interventions and outcomes. Here we review new advances that may address these challenges using digital twin technology to fulfill the promise of personalized cardiovascular medical practice. Rooted in engineering mechanics and manufacturing, the digital twin is a virtual representation engineered to model and simulate its physical counterpart. Recent breakthroughs in scientific computation, artificial intelligence, and sensor technology have enabled rapid bidirectional interactions between the virtual-physical counterparts with measurements of the physical twin that inform and improve its virtual twin, which in turn provide updated virtual projections of disease trajectories and anticipated clinical outcomes. Verification, validation, and uncertainty quantification builds confidence and trust by clinicians and patients in the digital twin and establishes boundaries for the use of simulations in cardiovascular medicine. Mechanistic physiological models form the fundamental building blocks of the personalized digital twin that continuously forecast optimal management of cardiovascular health using individualized data streams. We present exemplars from the existing body of literature pertaining to mechanistic model development for cardiovascular dynamics and summarize existing technical challenges and opportunities pertaining to the foundation of a digital twin.

Technology use and subjective cognitive concerns in older adults.

OBJECTIVES: How technology impacts the day to day cognitive functioning of older adults is a matter of some debate. On the one hand, the use of technologies such as smartphones and social media, may lead to more subjective cognitive concerns (SCC) by promoting distractibility and reliance on devices to perform memory tasks. However, continued digital engagement in older adults may also be related to better cognitive functioning. Given these competing viewpoints, our study evaluated if frequency of digital device use was associated with greater or less subjective cognitive concerns. METHOD: Participants were 219 adults over the age of 65 (mean age =75 years) who had internet access. Measures assessing frequency of digital device use along with SCC were administered. Hierarchical multiple regression was used to gage association between frequency of device use and SCC, controlling for relevant demographic and lifestyle factors. RESULTS: Increased frequency of digital device use was associated with less SCC, over and above the influence of demographic factors, across cognitive (but especially in executive) domains. This effect was observed for general device usage, with no statistically significant associations were observed between texting/video call, social media use and SCC. DISCUSSION: Results were broadly consistent with the technological reserve hypothesis in that digital engagement was associated with better experienced cognitive functioning in older adults. While device use may contribute to distractibility in certain cases, the current results add to a burgeoning literature that digital engagement may be a protective factor for cognitive changes with age.

Optimal stimulus shapes for neuronal excitation.

An important problem in neuronal computation is to discern how features of stimuli control the timing of action potentials. One aspect of this problem is to determine how an action potential, or spike, can be elicited with the least energy cost, e.g., a minimal amount of applied current. Here we show in the Hodgkin & Huxley model of the action potential and in experiments on squid giant axons that: 1) spike generation in a neuron can be highly discriminatory for stimulus shape and 2) the optimal stimulus shape is dependent upon inputs to the neuron. We show how polarity and time course of post-synaptic currents determine which of these optimal stimulus shapes best excites the neuron. These results are obtained mathematically using the calculus of variations and experimentally using a stochastic search methodology. Our findings reveal a surprising complexity of computation at the single cell level that may be relevant for understanding optimization of signaling in neurons and neuronal networks.

Automatic Segmentation and Quantitative Assessment of Stroke Lesions on MR Images.

Lesion studies are crucial in establishing brain-behavior relationships, and accurately segmenting the lesion represents the first step in achieving this. Manual lesion segmentation is the gold standard for chronic strokes. However, it is labor-intensive, subject to bias, and limits sample size. Therefore, our objective is to develop an automatic segmentation algorithm for chronic stroke lesions on T1-weighted MR images. Methods: To train our model, we utilized an open-source dataset: ATLAS v2.0 (Anatomical Tracings of Lesions After Stroke). We partitioned the dataset of 655 T1 images with manual segmentation labels into five subsets and performed a 5-fold cross-validation to avoid overfitting of the model. We used a deep neural network (DNN) architecture for model training. Results: To evaluate the model performance, we used three metrics that pertain to diverse aspects of volumetric segmentation, including shape, location, and size. The Dice similarity coefficient (DSC) compares the spatial overlap between manual and machine segmentation. The average DSC was 0.65 (0.61−0.67; 95% bootstrapped CI). Average symmetric surface distance (ASSD) measures contour distances between the two segmentations. ASSD between manual and automatic segmentation was 12 mm. Finally, we compared the total lesion volumes and the Pearson correlation coefficient (ρ) between the manual and automatically segmented lesion volumes, which was 0.97 (p-value < 0.001). Conclusions: We present the first automated segmentation model trained on a large multicentric dataset. This model will enable automated on-demand processing of MRI scans and quantitative chronic stroke lesion assessment.