Striatal and Behavioral Responses to Reward Vary by Socioeconomic Status in Adolescents.

Disparities in socioeconomic status (SES) lead to unequal access to financial and social support. These disparities are believed to influence reward sensitivity, which in turn are hypothesized to shape how individuals respond to and pursue rewarding experiences. However, surprisingly little is known about how SES shapes reward sensitivity in adolescence. Here, we investigated how SES influenced adolescent responses to reward, both in behavior and the striatum-a brain region that is highly sensitive to reward. We examined responses to both immediate reward (tracked by phasic dopamine) and average reward rate fluctuations (tracked by tonic dopamine) as these distinct signals independently shape learning and motivation. Adolescents (n = 114; 12-14 years; 58 female) performed a gambling task during functional magnetic resonance imaging. We manipulated trial-by-trial reward and loss outcomes, leading to fluctuations between periods of reward scarcity and abundance. We found that a higher reward rate hastened behavioral responses, and increased guess switching, consistent with the idea that reward abundance increases response vigor and exploration. Moreover, immediate reward reinforced previously rewarding decisions (win-stay, lose-switch) and slowed responses (postreward pausing), particularly when rewards were scarce. Notably, lower-SES adolescents slowed down less after rare rewards than higher-SES adolescents. In the brain, striatal activations covaried with the average reward rate across time and showed greater activations during rewarding blocks. However, these striatal effects were diminished in lower-SES adolescents. These findings show that the striatum tracks reward rate fluctuations, which shape decisions and motivation. Moreover, lower SES appears to attenuate reward-driven behavioral and brain responses.

Fast response times signal social connection in conversation.

Clicking is one of the most robust metaphors for social connection. But how do we know when two people "click"? We asked pairs of friends and strangers to talk with each other and rate their felt connection. For both friends and strangers, speed in response was a robust predictor of feeling connected. Conversations with faster response times felt more connected than conversations with slower response times, and within conversations, connected moments had faster response times than less-connected moments. This effect was determined primarily by partner responsivity: People felt more connected to the degree that their partner responded quickly to them rather than by how quickly they responded to their partner. The temporal scale of these effects (<250 ms) precludes conscious control, thus providing an honest signal of connection. Using a round-robin design in each of six closed networks, we show that faster responders evoked greater feelings of connection across partners. Finally, we demonstrate that this signal is used by third-party listeners as a heuristic of how well people are connected: Conversations with faster response times were perceived as more connected than the same conversations with slower response times. Together, these findings suggest that response times comprise a robust and sufficient signal of whether two minds "click."

High-value decisions are fast and accurate, inconsistent with diminishing value sensitivity.

It is a widely held belief that people's choices are less sensitive to changes in value as value increases. For example, the subjective difference between $11 and $12 is believed to be smaller than between $1 and $2. This idea is consistent with applications of the Weber-Fechner Law and divisive normalization to value-based choice and with psychological interpretations of diminishing marginal utility. According to random utility theory in economics, smaller subjective differences predict less accurate choices. Meanwhile, in the context of sequential sampling models in psychology, smaller subjective differences also predict longer response times. Based on these models, we would predict decisions between high-value options to be slower and less accurate. In contrast, some have argued on normative grounds that choices between high-value options should be made with less caution, leading to faster and less accurate choices. Here, we model the dynamics of the choice process across three different choice domains, accounting for both discriminability and response caution. Contrary to predictions, we mostly observe faster and more accurate decisions (i.e., higher drift rates) between high-value options. We also observe that when participants are alerted about incoming high-value decisions, they exert more caution and not less. We rule out several explanations for these results, using tasks with both subjective and objective values. These results cast doubt on the notion that increasing value reduces discriminability.

Task functional networks predict individual differences in the speed of emotional facial discrimination.

Every individual experiences negative emotions, such as fear and anger, significantly influencing how external information is perceived and processed. With the gradual rise in brain-behavior relationship studies, analyses investigating individual differences in negative emotion processing and a more objective measure such as the response time (RT) remain unexplored. This study aims to address this gap by establishing that the individual differences in the speed of negative facial emotion discrimination can be predicted from whole-brain functional connectivity when participants were performing a face discrimination task. Employing the connectome predictive modeling (CPM) framework, we demonstrated this in the young healthy adult group from the Human Connectome Project-Young Adults (HCP-YA) dataset and the healthy group of the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) dataset. We identified distinct network contributions in the adult and adolescent predictive models. The highest represented brain networks involved in the adult model predictions included representations from the motor, visual association, salience, and medial frontal networks. Conversely, the adolescent predictive models showed substantial contributions from the cerebellum-frontoparietal network interactions. Finally, we observed that despite the successful within-dataset prediction in healthy adults and adolescents, the predictive models failed in the cross-dataset generalization. In conclusion, our study shows that individual differences in the speed of emotional facial discrimination can be predicted in healthy adults and adolescent samples using their functional connectivity during negative facial emotion processing. Future research is needed in the derivation of more generalizable models.

Heavy-intensity priming exercise extends the V̇o2max plateau and increases peak-power output during ramp-incremental exercise.

This study investigated whether a heavy-intensity priming exercise precisely prescribed within the heavy-intensity domain would lead to a greater peak-power output (POpeak) and a longer maximal oxygen uptake (V̇o2max) plateau. Twelve recreationally active adults participated in this study. Two visits were required: 1) a step-ramp-step test [ramp-incremental (RI) control], and 2) an RI test preceded by a priming exercise within the heavy-intensity domain (RI primed). A piecewise equation was used to quantify the V̇o2 plateau duration (V̇o2plateau-time). The mean response time (MRT) was computed during the RI control condition. The delta (Δ) V̇o2 slope (S; mL·min-1·W-1) and V̇o2-Y intercept (Y; mL·min-1) within the moderate-intensity domain between conditions (RI primed minus RI control) were also assessed using a novel graphical analysis. V̇o2plateau-time (P = 0.001; d = 1.27) and POpeak (P = 0.003; d = 1.08) were all greater in the RI primed. MRT (P < 0.001; d = 2.45) was shorter in the RI primed compared with the RI control. A larger ΔV̇o2plateau-time was correlated with a larger ΔMRT between conditions (r = -0.79; P = 0.002). This study demonstrated that heavy-intensity priming exercise lengthened the V̇o2plateau-time and increased POpeak. The overall faster RI-V̇o2 responses seem to be responsible for the longer V̇o2plateau-time. Specifically, a shorter MRT, but not changes in RI-V̇o2-slopes, was associated with a longer V̇o2plateau-time following priming exercise.NEW & NOTEWORTHY It remains unclear whether priming exercise extends the maximal oxygen uptake (V̇o2max) plateau and increases peak-power output (POpeak) during ramp-incremental (RI) tests. This study demonstrates that a priming exercise, precisely prescribed within the heavy-intensity domain, extends the plateau at V̇o2max and leads to a greater POpeak. Specifically, the extended V̇o2max plateau was associated with accelerated RI-V̇o2 responses.

Do we intervene less and slower in the epilepsy monitoring unit for psychogenic seizures?

PURPOSE: Individuals with psychogenic non-epileptic seizures (PNES) can be stigmatized in healthcare settings. We aimed to compare intervention rate (IR), intervention time (IT), and adverse event (AE) rate between PNES and epileptic seizures (ES) in the epilepsy monitoring unit (EMU). METHODS: We used a prospective database of consecutive admissions to our centre's EMU between August 2021 and September 2022. We excluded purely electric seizures and vague, minor spells with no EEG correlate. We therefore only included electroclinical seizures and PNES. We compared the IR, IT, and AE rate between PNES and ES, as diagnosed by an epileptologist during EEG monitoring. We performed the same comparisons between spells occurring in people admitted with a high vs low suspicion of PNES (HSP vs LSP). We also verified if ITs became longer with repeated PNES. RESULTS: We analyzed 586 spells: 43 PNES vs 543 ES, or 133 HSP vs 453 LSP. Our univariate analyses showed that IR was higher for PNES than for ES (93 % vs 61 %, p <.001) but that IT and AE rate were similar across groups. This higher IR was only apparent outside weekday daytime hours, when EEG technologists were not present. HSP did not differ from LSP in terms of IR, IT, and AE rate. As PNES accumulated in individual patients, IT tended to be longer (Spearman's correlation = 0.42; p =.012). SIGNIFICANCE: Our EMU staff did not intervene less or slower for PNES. Rather, IR was higher for PNES than for ES, but IT tended to be longer with repeat PNES.

On-scene time delays for epileptic seizures in developed community-based integrated care system regions.

BACKGROUND: Delayed on-scene time by emergency medical services (EMS) can have detrimental effects on critical cases for people with epilepsy (PWE). In preparation for a super-aged society, a Community-based Integrated Care System is crucial to manage healthcare costs. However, sufficient coordination irrespective of sociomedical changes among medical providers is challenging. AIM: This study aimed to evaluate on-scene time delays in the treatment of PWE, identify factors associated with such delays, and clarify regional differences. The focus was on the volume of acute care beds in regions with a developed Community-based Integrated Care System. METHODS: This population-based observational study evaluated on-scene time delays in the treatment of PWE across six major cities in western Japan between 2017 and 2021. In addition, we also evaluated the association between regional differences focusing on volume of acute care beds ("Reduced region" and "Preserved region", as cities with numbers of acute care beds per 1,000 people below and above the national average, respectively) along with sociomedical factors associated with on-scene time delays. RESULTS: This study included 8,737 PWE transported by EMS, with a mean on-scene time for EMS ranging from 12.9 ± 6.8 min to 21.7 ± 10.6 min. On-scene time delays were evident in Reduced regions, with an increase of 1.45 min (95 % confidence interval 0.86-2.03 min, p < 0.001). A high total EMS call volume independently influenced on-scene time delays during the middle period of the pandemic in Reduced regions. CONCLUSION: Optimal coordination must be facilitated to ensure the effective functioning of the Community-based Integrated Care System, particularly during unusual circumstances.

How important are delays in treatment for health outcomes? The case of ambulance response time and cardiovascular events.

The cost effectiveness of medical treatments is not precisely known due to the compounding effect of multiple determining factors. Ambulance response time (RT) to emergency calls is exploited to learn more about the effect of the timing of treatment on health outcomes. This causal relation is identified by exploiting rainfall at the time of the ambulance run as a shock to RT. The analysis focuses on patients who have undergone a cardiac event and shows that a one-minute increase in average RT leads to 105 more deaths each year in one Italian region. Finally, the economic value of the lives that would be saved by reducing RT is quantified to facilitate policymaking.

Patient adherence and response time in electronic patient-reported outcomes: insights from three longitudinal clinical trials.

PURPOSE: Patient-reported outcome measures (PROMs) are used to collect data on disease symptoms in support of clinical trial endpoints. Clinical studies can last a year or more, and the patients' adherence and response time to daily at-home questionnaires may vary significantly over time. The aim of this study was to understand patterns and changes in patients' completion of daily PROMs during longitudinal clinical studies. METHODS: Data were collected from 1342 patients randomized into three respiratory clinical trials (NCT03401229, NCT03347279, and NCT03406078). PROMs were completed by patients using electronic handheld devices that collected the starting and completion times. A Bayesian generalized linear mixed-effects model was used to identify unbiased coefficients associated with PROM adherence and response time using patient, site, and calendar features as covariates. RESULTS: Adherence decreased over time after randomization, and the rate of decrease was higher in younger patients. The 14-day pre-randomization adherence was correlated with adherence throughout the study. Patients were also more adherent during working days compared to non-working days. Oldest patients took twice as long to complete PROMs throughout the study; however, the response time for all patients decreased during the first month of the study regardless of age. Response time increased 7 days before and after the date of a scheduled clinic visit and when a patient-reported higher symptom burden. CONCLUSION: Detailed analyses of adherence and response time for daily PROMs in clinical trials can provide significant insights about trends of patient behavior in longitudinal clinical studies with high baseline adherence.

Ambulance and helicopter response time. Association with patient outcome and illness severity: Protocol of a systematic literature review and meta-analysis.

BACKGROUND: Response time for emergency medical service units is a key performance indicator. Studies have shown reduced response time association with improved outcome for specific critical conditions. To achieve short response time, emergency vehicles utilize lights and sirens, and crews are allowed to be non-compliant with traffic rules, posing a risk for accident. The purpose of the systematic review and meta-analysis is to provide an overview of the current body of evidence regarding the association, if any, between ambulance and helicopter response time and major complications and mortality in patients conveyed by ambulance and/or helicopter. Our secondary aim will be to enhance knowledge in the field of criteria-based dispatch to provide decision makers with evidence to optimize dispatch of limited resources. RESEARCH QUESTIONS: What is the association between overall emergency medical services unit response time and patient outcomes, major complications, and time-critical conditions? What is the internal and external validity of the included literature? METHODS: We plan the systematic review and meta-analysis to be in accordance with the Cochrane Handbook and Joanna Briggs Institute Manual for Systematic Reviews. The methodology will include formulating the review questions using a Population, Exposure, and Outcome framework. Every study design is eligible, including qualitative, quantitative, and mixed-methods designs. We will include all articles in English, Scandinavian, German, French and Portuguese in this systematic review. RESULTS: We will publish results from the systematic review and meta-analysis in a peer-reviewed journal and we will present the results at scientific conferences and meetings. Results will also be available at www.ahrtemis.dk. CONCLUSION: We will base our conclusions on the findings of the review and meta-analysis.