Separate and overlapping brain areas encode subjective value during delay and effort discounting

AbstractMaking decisions about rewards that involve delay or effort requires the integration of value and cost information. The brain areas recruited in this integration have been well characterized for delay discounting. However only a few studies have investigated how effort costs are integrated into value signals to eventually determine choice. In contrast to previous studies that have evaluated fMRI signals related to physical effort, we used a task that focused on cognitive effort. Participants discounted the value of delayed and effortful rewards. The value of cognitively effortful rewards was represented in the anterior portion of the inferior frontal gyrus and dorsolateral prefrontal cortex. Additionally, the value of the chosen option was encoded in the anterior cingulate cortex, caudate, and cerebellum. While most brain regions showed no significant dissociation between effort discounting and delay discounting, the ACC was significantly more activated in effort compared to delay discounting tasks. Finally, overlapping regions within the right orbitofrontal cortex and lateral temporal and parietal cortices encoded the value of the chosen option during both delay and effort discounting tasks. These results indicate that encoding of rewards discounted by cognitive effort and delay involves partially dissociable brain areas, but a common representation of chosen value is present in the orbitofrontal, temporal and parietal cortices

Normative modeling of brain morphometry in clinical high risk for psychosis

Importance The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals. Objective To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. Design, Setting, and Participants This case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)–derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022. Main Outcomes and Measures For each regional morphometric measure, deviation scores were computed as z scores indexing the degree of deviation from their normative means from a healthy reference population. Average deviation scores (ADS) were also calculated for regional CT, SA, and SV measures and globally across all measures. Regression analyses quantified the association of deviation scores with clinical severity and cognition, and 2-proportion z tests identified case-control differences in the proportion of individuals with infranormal (z < −1.96) or supranormal (z > 1.96) scores. Results Among 1340 individuals with CHR-P, 709 (52.91%) were male, and the mean (SD) age was 20.75 (4.74) years. Among 1237 healthy individuals, 684 (55.30%) were male, and the mean (SD) age was 22.32 (4.95) years. Individuals with CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z scores, and all ADS values. For any given region, the proportion of individuals with CHR-P who had infranormal or supranormal values was low (up to 153 individuals [<11.42%]) and similar to that of healthy individuals (<115 individuals [<9.30%]). Individuals with CHR-P who converted to a psychotic disorder had a higher percentage of infranormal values in temporal regions compared with those who did not convert (7.01% vs 1.38%) and healthy individuals (5.10% vs 0.89%). In the CHR-P group, only the ADS SA was associated with positive symptoms (β = −0.08; 95% CI, −0.13 to −0.02; P = .02 for false discovery rate) and IQ (β = 0.09; 95% CI, 0.02-0.15; P = .02 for false discovery rate). Conclusions and Relevance In this case-control study, findings suggest that macroscale neuromorphometric measures may not provide an adequate explanation of psychosis risk

Loss aversion in effort-based decision making and performance

Data & code for: Losses motivate cognitive effort more than gains in effort-based decision making and performance Abstract Based on studies on risky and impulsive decision making, it has been found that behavior is more strongly driven by the motivation to avoid losses than to pursue gains (loss aversion). However, there is little research on how losses influence the motivation to exert effort. In this study, we compared the effects of loss and gain incentives on cognitive task performance and effort-based decision making. In three experiments, participants performed a cognitively effortful task under gain and loss conditions and made choices about effort expenditure in a decision making task. Results consistently showed significant loss aversion effects in effort-based decision making. Participants were willing to invest more effort (i.e. performance of a longer duration task: Experiments 1 & 2; higher task load: Experiment 3) in the loss compared to the gain condition. On the other hand, losses did not lead to improved performance (sustained attention), or higher physiological effort (pupil diameter) in Experiments 1 and 2. In Experiment 3, losses did enhance working memory performance, but only at the highest load level. Taken together, these results suggest that loss aversion motivates higher effort investment in effort-based decision making, while the effects of loss aversion during performance may depend on the task type or effort level. Based on studies on risky and impulsive decision making, it has been found that behavior is more strongly driven by the motivation to avoid losses than to pursue gains (loss aversion). However, there is little research on how losses influence the motivation to exert effort. In this study, we compared the effects of loss and gain incentives on cognitive task performance and effort-based decision making. In three experiments, participants performed a cognitively effortful task under gain and loss conditions and made choices about effort expenditure in a decision making task. Results consistently showed significant loss aversion effects in effort-based decision making. Participants were willing to invest more effort (i.e. performance of a longer duration task: Experiments 1 & 2; higher task load: Experiment 3) in the loss compared to the gain condition. On the other hand, losses did not lead to improved performance (sustained attention), or higher physiological effort (pupil diameter) in Experiments 1 and 2. In Experiment 3, losses did enhance working memory performance, but only at the highest load level. Taken together, these results suggest that loss aversion motivates higher effort investment in effort-based decision making, while the effects of loss aversion during performance may depend on the task type or effort level

Dissociable influences of implicit temporal expectation on attentional performance and mind wandering

Mind wandering at critical moments during a cognitive task degrades performance. At other moments, mind wandering could serve to conserve task-relevant resources, allowing a brief mental respite. Recent research has shown that, if target timing is predictable, mind wandering episodes coincide with moments of low target likelihood. Conversely, mind wandering can be avoided at moments when targets are expected. In the current study, we tested whether mind wandering can be guided by implicit temporal expectations when target timing is less predictable. In two experiments (Experiment 1: N = 37, Experiment 2: N = 61), participants performed a sustained attention task in which target events were preceded by a variable pre-target interval (foreperiod). As time passes over the foreperiod duration, implicit target expectation increases, given that it has not yet appeared. In Experiment 1, all foreperiod durations were equally probable (uniform distribution: 2-10 seconds). This resulted in faster responses when targets were preceded by long compared to short foreperiods (foreperiod-effect). In contrast, mind wandering, assessed by thought probes inserted following short or long foreperiods, did not follow this pattern. In Experiment 2, alterations in the foreperiod distribution (left or right-skewed) resulted in changes in the behavioral foreperiod-effect, but mind wandering was unaffected. Our findings indicate that implicit timing strongly affects behavioral response to target events, but has no bearing on the mind wandering. Contrastingly, mind wandering did correlate with performance deterioration due to fatigue (time-on-task), suggesting that the thought probe method was sufficiently sensitive to behaviorally relevant changes in mental state

Reward supports flexible orienting of attention to category information and influences subsequent memory

Preparatory control of attention facilitates the efficient processing and encoding of an expected stimulus. However, this can occur at the expense of increasing the processing cost of unexpected stimuli. Preparatory control can be influenced by motivational factors, such as the expectation of a reward. Interestingly, expectation of a high reward can increase target processing, as well as reduce the cost associated with reorienting. Using a semantic cueing paradigm, we examined the interaction of reward expectation and cue-validity on semantic judgment performance and subsequent memory. Preparatory attention was assessed with pupillometry. Valid category cueing, was associated with better semantic judgment performance and better subsequent memory compared to invalidly cued items. Higher reward also resulted in larger pre-target pupil diameter, which could be indicative of increased preparatory task engagement or arousal. Critically, higher reward also reduced reorienting cost in both semantic judgment and subsequent memory performance. Our findings suggest that reward expectation can facilitate the effective control of preparatory attention for semantic information, and can support optimal goal-directed behavior based on changing task demands

Assessing ‘Readiness’ by Tracking Fluctuations in Daily Sleep Duration and their Effects on Daily Mood, Motivation, and Sleepiness

Study Objectives: Consumer sleep trackers issue daily guidance on ‘readiness’ without clear empirical basis. We investigated how self-rated mood, motivation, and sleepiness (MMS) levels are affected by daily fluctuations in sleep duration, timing, and efficiency and overall sleep regularity. We also determined how temporally specific these associations are. Methods: 119 healthy university students (64 female, mean age=22.54±1.74 years) wore a wearable sleep tracker and undertook twice-daily smartphone-delivered ecological momentary assessment of mood, motivation, and sleepiness at post-wake and pre-bedtime timings for 2-6 weeks. Naps and their duration were reported daily. Nocturnal sleep on 2471 nights were examined using multilevel models to uncover within-subject and between-subject associations between sleep duration, timing, efficiency, and nap duration on following day MMS ratings. Time-lagged analyses examined the temporal specificity of these associations. Linear regression models investigated associations between MMS ratings and sleep variability, controlling for sleep duration. Results: Nocturnal sleep durations were short (6.03±0.71h), and bedtimes were late (1:42AM±1:05). Within-subjects, nocturnal sleep longer than a person’s average was associated with better mood, higher motivation, and lower sleepiness after waking. Effects of such longer sleep duration lingered for mood and sleepiness till the pre bedtime window (all ps<.005) but did not extend to the next day. Between-subjects, higher intraindividual sleep variability, but not sleep duration, was associated with poorer mood and lower motivation after waking. Longer average sleep duration was associated with less sleepiness after waking and lower motivation pre-bedtime (all ps<.05). Longer naps reduced post-nap sleepiness and improved mood. Controlling for nocturnal sleep duration, longer naps also associated with lower post-waking sleepiness on the following day. Conclusions: Positive connections between nocturnal sleep and nap duration with MMS are temporally circumscribed, lending credence to the construction of sleep-based, daily ‘readiness’ scores. Higher sleep duration variability lowers an individual’s post waking mood and motivation

Country Differences in Nocturnal Sleep Variability: Observations from a Large-scale, Long-term Sleep Wearable Study

Sleep duration, timing and consistency are all important for maintaining good physical health and psychological functioning. While differences in sleep duration across countries are well-known, fewer large-scale studies characterising differences in sleep variability and differences between weekday and weekend sleep have been conducted. The goal of this study was, therefore, to capitalize on the increased use of wearable technology to characterise nocturnal sleep, weekday sleep variability and changes in sleep patterns at the weekend in a large, globally diverse sample. Using data from over 50 million night’s sleep, sleep measures for ~220,000 wearable device users from 35 countries were calculated. Multiple regression was used to assess the impact country of residence had on a number of sleep measures including sleep duration, sleep variability, weekend sleep extension and social jet lag. Our results support prior findings that nocturnal sleep duration and sleep efficiency are lower in Asia than other regions. Furthermore, weekend sleep extension is longer in Europe and the USA than in Asia, and is only partially related to shorter weekday sleep duration. There are also cross-country differences in social jetlag although the regional differences are less distinct than for weekend sleep extension. Variability in weekday sleep duration also tends to be greater in Asia than other regions. Our results suggest that culture affects not only sleep duration and timing, but also how sleep is modulated over the course of the week. While sleep is influenced by many factors, we hypothesize that differing work cultures may be one contributory factor in explaining why sleep patterns differ in different countries

Procedural performance following sleep deprivation remains impaired despite extended practice and an afternoon nap

International audienceThe negative impact of sleep loss on procedural memory is well established, yet it remains unclear how extended practice opportunities or daytime naps can modulate the effect of a night of sleep deprivation. Here, participants underwent three training and test conditions on a sequential finger tapping task (SFTT) separated by at least one week. In the first condition they were trained in the evening followed by a night of sleep. Two further conditions took place where evening training was followed by a night of total sleep deprivation (TSD). One of the TSD conditions included a one-hour nap opportunity (15:00). Compared to the condition in which sleep was permitted, a night of TSD resulted in poorer performance across 4 practices the following day (10:00–19:00). The deleterious effect of a single night of TSD on procedural performance, was neither clearly alleviated by an afternoon nap nor by multiple practice opportunities. Interestingly, significant gains in performance were observed in all conditions after a one-week delay. Recovery sleep on subsequent nights thus appeared to nullify the effect of a single night of sleep deprivation, underscoring the importance of offline consolidation on the acquisition of procedural skill

Effects of phase-locked acoustic stimulation during a nap on EEG spectra and declarative memory consolidation

AbstractObjectivesAcoustic stimulation synchronized to slow waves (SWs) can enhance these sleep features and facilitate memory consolidation during nocturnal sleep. Here, we investigated whether a similar benefit could be accrued following stimulation during an afternoon nap. We also evaluated the event-related dynamics of associated EEG spectral changes and their correlation with memory performance.MethodsSixteen healthy young adults (mean age: 22 ± 1.4 years; nine males) were studied under two conditions: stimulation (STIM) and no stimulation (SHAM), in counter-balanced order. In the STIM condition, acoustic stimulation was delivered using blocks of five tones, each phase-locked to the SW up-state during a 90-min nap opportunity. In the SHAM condition, these time points were marked, but tones were not presented. Prior to the nap, participants learned 40 semantically related word pairs and immediate recall was tested. A delayed recall test was administered 45 min after awakening.ResultsCompared to the SHAM condition, acoustic stimulation increased SW amplitude, theta, and fast spindle activity and attenuated the forgetting of word pairs (p values < 0.05).ConclusionPhase-locked acoustic stimulation can promote sleep-dependent declarative memory during a daytime nap. This can be achieved by stimulation in Stage 2 and SWS without a requirement for high-amplitude slow wave detection

The influence of working-from-home and digital device use on sleep, physical activity, and wellbeing following COVID-19 lockdown and reopening

The COVID-19 pandemic imposed massive changes to daily lives worldwide. While lockdowns arrived abruptly, the continuation of social-distancing measures like working from home could have longer-term influences. We longitudinally tracked lifestyle behaviors (sleep/physical activity/phone use) and mental wellbeing through lockdown and reopening in Singapore. Earlier sleep and increased physical activity benefited from offices reopening for in-person work. However, this was offset by higher stress and poorer mood. Changes were proportional to the degree of hybrid work adoption. Counter to expectation, smartphone usage did not decrease after reopening, and usage around bedtime increased marginally. Cluster analysis showed that while heavier bedtime smartphone use was associated with later sleep initiation and lower physical activity, intermediate bedtime usage was associated with more favorable wellbeing indicators. As hybrid work arrangements and expanded e-device use will likely persist during the pandemic and its aftermath, our findings could inform strategies on adapting to new societal norms