A common alteration in effort-based decision-making in apathy, anhedonia, and late circadian rhythm

Our bodies are regulated by an internal circadian clock that aligns physiological processes to a 24-hour day-to-night cycle. However, the timing of this rhythm can vary: some people are ‘early birds’ who prefer mornings, while others are ‘night owls’ who prefer to wake up and stay up late.

Circadian rhythms have been closely linked to neuropsychiatric conditions like depression, as well as specific psychiatric symptoms such as reduced motivation. Despite this, the circadian clock is seldom considered when investigating the cognitive and motivational changes associated with mental health conditions.

To address this gap, Mehrhof and Nord designed a study to assess motivational differences in the general population and examine whether there were associations between neuropsychiatric symptoms and circadian rhythms. The study focused on effort-based decisions – where individuals choose whether completing a task is worth the effort of the reward – as disruptions in this process often underpin motivational deficits in neuropsychiatric disorders.

Mehrhof and Nord found that individuals with high neuropsychiatric symptoms were less likely to undertake effort-based tasks, consistent with previous studies. Night owls showed the same motivational deficit – even when taking into account neuropsychiatric differences. However, this loss of motivation only occurred when the night owls were tested in the morning. When tested in the evening, their performance matched that of individuals who had an earlier circadian rhythm.

These findings suggest that the circadian clock and neuropsychiatric conditions affect motivation in independent but parallel manners. In addition, testing someone at times of day that misalign with their circadian rhythm may be skewing the results of psychiatric studies. Further research could explore whether aligning treatment schedules and daily routines to a person’s internal clock improves motivation and other mental health outcomes.

Our circadian rhythm aligns us with our environment, regulating physiological and behavioural processes to follow 24-hr rhythms (Foster, 2020). Circadian integrity is pivotal to mental wellbeing and has been bidirectionally linked to numerous psychiatric disorders (McCarthy, 2019; Logan and McClung, 2019; Walker et al., 2020; Ashton and Jagannath, 2020; Lyall et al., 2018; Vadnie and McClung, 2017; Emens et al., 2009). Yet little is known about the cognitive or computational mechanisms of circadian dysfunction—and their alignment or diversion from mechanisms driving neuropsychiatric symptoms.

Inter-individual differences in circadian timing and alignment manifest behaviourally as chronotypes (i.e., diurnal preference) (Jones et al., 2019; Bailey and Heitkemper, 2001), with individuals commonly categorized as early, late, or intermediate chronotypes (Horne and Ostberg, 1976). A disproportionate number of psychiatric patients have a late chronotype, based on self-report (Kivelä et al., 2018) and genetic analysis (Jones et al., 2019). Within clinical groups, late chronotype has been linked to depression severity and non-remission (Chan et al., 2014), higher rates of psychiatric and general medical comorbidities (Romo-Nava et al., 2020), more severe cognitive impairment, and higher symptoms of apathy (Au and Reece, 2017; Coleman and Cain, 2019). Converging evidence on the importance of circadian alignment in psychiatric pathology has led to proposals of a circadian psychiatric phenotype, either within disorders (Romo-Nava et al., 2020; McGowan and Saunders, 2021) or cutting across diagnostic categories (Carpenter et al., 2021; Crouse et al., 2021).

Syndromes of deficient motivational behaviour, such as apathy and anhedonia, are also observed across neuropsychiatric disorders (Treadway and Zald, 2011; Horan et al., 2006; Mazza et al., 2009; den Brok et al., 2015), suggesting transdiagnostic relevance (Husain and Roiser, 2018). Anhedonia and apathy are associated with worse clinical outcomes (Ducasse et al., 2018; Dimick et al., 2021) and are poorly targeted by current treatments (Calabrese et al., 2014; Gabbay et al., 2015; McMakin et al., 2012). Empirical work suggests a common underlying neurocognitive mechanism: the integration of costs and benefits during effortful decision-making (Husain and Roiser, 2018). Effort-based decision-making is commonly assessed using effort-expenditure tasks: Subjects are asked to decide whether to pursue actions associated with varying levels of effort and reward levels (Treadway et al., 2009). Computational models applied to effort-based decision-making tasks provide a formal mathematical estimate of a subject’s integration of costs and benefits into a subjective value (Treadway et al., 2012a; Pessiglione et al., 2018). Higher costs devalue associated rewards, an effect referred to as effort discounting (Sugiwaka and Okouchi, 2004; Hartmann et al., 2013; Klein-Flügge et al., 2015; Białaszek et al., 2017; Ostaszewski et al., 2013). This computational approach enables measurement of inter- and intra-individual differences on distinct aspects of effort-based decision-making.

One key source of individual differences in motivational behaviour and effort-based decision-making is likely dopamine signalling, especially dopaminergic projections from the ventral tegmental area to the ventral striatum (Husain and Roiser, 2018). Pre-clinical animal studies show dopamine depletion reduces engagement in effortful behaviour (Tran et al., 2002; Robbins et al., 1983), while dopamine enhancement promotes motivational effort exertion (Cagniard et al., 2006; Taylor and Robbins, 1984). In humans, dopamine depletion reduces willingness to exert effort for reward (Cawley et al., 2013; Venugopalan et al., 2011), while pharmacological dopamine enhancement increases motivation in effort-based decision-making (Wardle et al., 2011; Soder et al., 2021). Further, naturally occurring variations in dopamine responsivity are correlated with effort-based decision-making: a higher dopamine responsivity (as quantified with positron emission tomography following d-amphetamine administration) is associated with willingness to exert greater effort for larger rewards (Treadway et al., 2012b).

Bidirectional links between chronobiology and several neurotransmitter systems have been reported, including dopamine (Kiehn et al., 2023). In animals, dopamine transmission and biosynthesis vary diurnally (Castañeda et al., 2004; Ferris et al., 2014), and growing evidence suggests a bidirectional regulation between dopamine signalling and circadian rhythm (Weber et al., 2004; Hampp et al., 2008; Imbesi et al., 2009). In human studies, dopamine availability, dopamine transporter genes, and dopamine receptors have been linked to proxies of circadian rhythm (Holst et al., 2014; Valomon et al., 2014; Zhang et al., 2021) and circadian-regulating gene polymorphisms (Shumay et al., 2012). On a behavioural level, sleep deprivation, poor sleep quality, and insomnia were linked to low motivation in effort-based decision-making (Boland et al., 2022; Boyle et al., 2020; Libedinsky et al., 2013) and evening bright-light exposure enhanced effort willingness, possibly by enhancing dopamine through melatonin suppression (Bijleveld and Knufinke, 2018). Early chronotype predicted treatment effect on motivational behaviour in a sample of depressed subjects with comorbid insomnia (Boland et al., 2019). Chronotype effects are also reported for other reward decision-making tasks, with late chronotypes showing higher delay discounting (Evans and Norbury, 2021), less rational decision-making (Correa et al., 2020), and lower willingness to take risks for rewards (Ingram et al., 2016; Hisler et al., 2023). A circadian effect on decision-making under risk is reported, with the sensitivity to losses decreasing with time-of-day (Bedder et al., 2023). This suggests that chronobiology may contribute to individual differences in effort-based decision-making, potentially in parallel ways with neuropsychiatric syndromes.

Here, we tested the relationship between motivational decision-making and three key neuropsychiatric syndromes: anhedonia, apathy, and depression, taking both a transdiagnostic and categorical (diagnostic) approach. To do this, we validate a newly developed effort-expenditure task, designed for online testing, and gamified to increase engagement. Participants completed the effort-expenditure task online, followed by a series of self-report questionnaires.

Next, we pre-registered a follow-up experiment to directly investigate how circadian preference interacts with time-of-day on motivational decision-making, using the same task and computational modelling approach. While this allows us to test how circadian effects on motivational decision-making compare to neuropsychiatric effects, we do not test for possible interactions between neuropsychiatric symptoms and chronobiology. All analyses were pre-registered (except when labelled as exploratory): see https://osf.io/2x3au and https://osf.io/y4fbe.

Various neuropsychiatric disorders are marked by disruptions in circadian rhythm, such as a late chronotype. However, research has rarely investigated how transdiagnostic mechanisms underlying neuropsychiatric conditions may relate to inter-individual differences in circadian rhythm. Here, combining a large-scale online study with computational modelling, we replicate and extend previous work linking anhedonia, apathy, and depression to a lower bias to accept effort for reward. Crucially, we found participants with a late compared to early chronotype show the same decrease in acceptance bias. Moreover, by testing participants at chronotype-compatible and -incompatible times of day, we discovered late chronotypes show a decreased acceptance bias to exert effort for reward when tested in the morning compared to evening. This reveals neuropsychiatric symptoms and chronotype (interacting with time-of-testing) show paralleling effects on effort-based decision-making. Our results demonstrate a crucial role for circadian rhythm in computational psychiatry, potentially affecting our assessment and treatment of neurocognitive mechanisms.

We replicate and extend effects of aberrant effort-based decision-making in neuropsychiatric syndromes in a large, broadly population-representative sample. Our finding that dimensional measures of apathy and anhedonia predict acceptance bias, a computational parameter describing someone’s tendency to exert effort for reward, aligns with previous reports of impaired effort-based decision-making in psychiatric (Treadway et al., 2012a; Barch et al., 2014; Berwian et al., 2020; Cléry-Melin et al., 2011; Fervaha et al., 2013; Gold et al., 2013; Hershenberg et al., 2016; Wolf et al., 2014; Yang et al., 2014; Zou et al., 2020) and neurodegenerative populations (Chong et al., 2015; Chong et al., 2018; Le Bouc et al., 2016; Le Bouc et al., 2023; Le Heron et al., 2018), as well as studies linking effort-based decision-making with apathy and anhedonia specifically. The positive link between effort-based decision-making and apathy and anhedonia has been observed in both patients (Barch et al., 2014; Yang et al., 2014; Tran et al., 2021) and HCs (Barch et al., 2014; Bonnelle et al., 2015; Jurgelis et al., 2021), though some did not find this effect (Zou et al., 2020).

Our work supports previous theories that impaired effort-based decision-making represents a common, transdiagnostic mechanism across the psychiatric and neurological syndromes of anhedonia and apathy (respectively). We found corresponding effects of apathy and anhedonia on the same computational parameter—acceptance bias—reinforcing the suggestion of possible shared mechanistic underpinnings of the two motivational syndromes (Husain and Roiser, 2018). Aberrant effort-based decision-making may manifest behaviourally as deficient motivation, a symptom category that cuts across traditional disease boundaries of psychiatric, neurological, and neurodevelopmental disorders (Pessiglione et al., 2018).

Our categorical (diagnostic-criteria based) analysis comparing depressed to healthy subjects likewise found depressed patients showed a lower acceptance bias, echoing our dimensional results in apathy and anhedonia. In addition, our categorical analysis revealed a distinct effect of group on effort sensitivity: depressed subjects had lower effort sensitivity, meaning their decisions were less influenced by effort changes. Possibly, this effect stems from decreased perceived differences in effort levels, as recently reported (Silvia et al., 2016), indicating there are both dimensional (transdiagnostic) and potentially some diagnosis-specific effects of mental health on effort-based decision-making.

It is possible that a higher acceptance bias reflects a more optimistic assessment of future task success, in line with work on the optimism bias (Korn et al., 2014); however, our task intentionally minimized unsuccessful trials by titrating effort and reward; future studies should explore this more directly.

We also found circadian effects on effort-based decision-making, paralleling those of apathy, anhedonia, and depression measures in both the affected neurocomputational parameter and the direction of effect. We observed a difference in acceptance bias between chronotypes, with late chronotypes showing a lower tendency to accept to exert effort for reward. Previous studies have suggested late chronotypes were also less accepting of delays (Evans and Norbury, 2021) and risk for reward (Ingram et al., 2016; Hisler et al., 2023).

Most importantly, we found an interaction between chronotype and time-of-day in a synchrony effect manner: early and late chronotypes showed a higher acceptance bias towards accepting effort for reward at their preferred time-of-day. This effect was driven by the late chronotype group, who showed a markedly lower acceptance bias in the morning, but a higher tendency in the evening. This suggests that chronotype effects on neurocomputational parameters such as acceptance bias depend on time-of-testing. Synchrony effects have previously been observed in other cognitive domains including inhibitory control (May and Hasher, 1998), attention (Goldstein et al., 2007), learning (Lehmann et al., 2013), and memory (Barner et al., 2019). One interpretation of our cognitive synchrony effects may be that late chronotype participants show a diminished ability to adapt to suboptimal time-of-day due to reduced cognitive resources (Nowack and Van Der Meer, 2018).

We also report a distinct effect of chronotype on effort-based decision-making that is not paralleled by effects of neuropsychiatric symptoms, nor dependent on time-of-day. Compared to early chronotypes, late chronotypes were more guided by differences in reward value, indicated by higher reward sensitivity parameters. Previous studies report altered reward functioning in late chronotypes, who show a reduced reactivity to reward in the medial prefrontal cortex, a key component of reward circuitry (Forbes et al., 2012; Hasler et al., 2013; Holm et al., 2009). Note this is not incompatible with higher reward sensitivity due to our modelling approach, in which higher reward sensitivity does not imply higher reward valuation, but rather larger subjective value differences between reward levels. Therefore, reduced reactivity to reward could be compatible with late chronotypes devaluing low reward levels more, which in our models would emerge as a reduced reward sensitivity parameter.

It is striking that the effects of neuropsychiatric symptoms on effort-based decision-making largely are paralleled by circadian effects on the same neurocomputational parameter. Exploratory analyses predicting acceptance bias by neuropsychiatric symptoms and circadian measures simultaneously indicate the effects go beyond recapitulating each other, but rather explain separable parts of the variance in acceptance bias. Overall, our results raise the possibility of altered effort–reward processing as a critical mechanism linking neuropsychiatric conditions and circadian rhythm. Previous research demonstrated depressed patients with an evening chronotype show increased diurnal mood variation (Chen et al., 2022). Our finding of time-of-day differences in acceptance bias among late chronotypes illustrates a potential cognitive underpinning for the observed diurnal characteristic within depression and late chronotype. Together, these findings support the idea of a circadian psychiatric phenotype (Romo-Nava et al., 2020; McGowan and Saunders, 2021), which should be considered in measurement (e.g., design of computational psychiatry studies) and potentially treatment (e.g., administration of motivation-based psychological interventions, which could be timed compatibly with chronotype).

To our surprise, we did not find statistical evidence for a relationship between effort-based decision-making and measures of metabolic health (BMI and risk for type-2 diabetes). Our analyses linking BMI to acceptance bias reveal a numeric effect in line with our hypothesis: a higher BMI relating to a lower acceptance bias. However, the 95% HDI for this effect narrowly included zero (95% HDI = [–0.19,0.01]). Possibly, our sample did not have sufficient variance in metabolic health to detect dimensional metabolic effects in a current general population sample. A recent study by our group investigates the same neurocomputational parameters of effort-based decision-making in participants with type-2 diabetes and non-diabetic controls matched by age, gender, and physical activity (Mehrhof et al., 2024). We report a group effect on the acceptance bias parameter, with type-2 diabetic patients showing a lower tendency to exert effort for reward.

Our study results should be considered in light of a few limitations. First, we used online self-report measures of neuropsychiatric symptoms and depression status. There has been a large shift towards online data collection in psychiatric research, and while online data are undoubtedly noisier, results (including our own, presented in the Appendix) usually show excellent accordance with lab-based studies (Gillan and Daw, 2016). Similarly, we lack biological measures of circadian rhythm, the gold standard of chronotype assessment. However, this concern might be mitigated by previous reports of high covariance between biological- and questionnaire-based circadian measures (Kantermann et al., 2015; Santisteban et al., 2018), as well as significant chronobiological differences between the questionnaire-determined chronotypes (Bailey and Heitkemper, 2001; Nebel et al., 1996) we use in our key findings. Nevertheless, future work should incorporate biological measures in attempts to replicate circadian effects on effort-based decision-making. This could take the form of identifying chronotypes by DNA analysis or dim-light melatonin onset, or continuous measurements of circadian proxies, such as core body temperature, heart rate, or actigraphy.

Note also that our time-of-day effects are limited by a between-subjects study design (i.e., the same participants were not tested in morning and evening sessions). It will be interesting to explore such diurnal variation in effort-based decision-making within individuals. The newly developed effort-expenditure task we present here may lend itself particularly well to such endeavours. First, it allows remote testing, meaning subjects can complete the task at different times of the day without in-person testing. Second, we demonstrated good test–retest reliability of task measures when time-of-testing was held constant within participants. This good test–retest reliability of our task contrasts with recent reports of poor test–retest reliability of other tasks and computational modelling parameters (Vrizzi et al., 2023).

Our reported analyses investigating neuropsychiatric and circadian effects on effort-based decision-making simultaneously are exploratory, as our study design was not ideally set out to examine this. Further work is needed to disentangle separable effects of neuropsychiatric and circadian measures on effort-based decision-making. One approach could be a group-based study design enabling the dissociation of the two effects (e.g., examining high-anhedonia participants with early chronotypes and low-anhedonia patients with late chronotypes, as well as the respective other, more common groupings, and testing each group in the morning and evening to examine time-of-day interactions with both anhedonia and chronotype).

Finally, we would like to note that as our study is based on a general population sample, rather than a clinical one. Hence, we cannot speak to transdiagnosticity on the level of multiple diagnostic categories.

Taken together, our results implicate circadian rhythm as an important factor in effort-based decision-making and its relationship to neuropsychiatric conditions. These results have implications for research, clinical interventions, and policy. We demonstrate that neuropsychiatric effects on effort-based decision-making are paralleled by effects of circadian rhythm and time-of-day. Exploratory analyses suggest these effects account for separable parts of the variance in effort-based decision-making. It unlikely that effects of neuropsychiatric effects on effort-based decision-making reported here and in previous literature are a spurious result due to multicollinearity with chronotype. Yet, not accounting for chronotype and time-of-testing, which is the predominant practice in the field, could affect results. This could take the form of either inflating or depressing results in the existing literature. On the one hand, reported neuropsychiatric effects may be inflated by systematic circadian differences between participants (i.e., overrepresentation of late chronotype in patient samples), which could be further amplified by time-of-testing (often the morning, incompatible with late chronotypes, and producing motivational impairments on neurocognitive measures). On the other hand, true effects may be masked by interactions between chronotype and time-of-day: Testing psychiatric subjects with a late chronotype in the evening (e.g., as a consequence of subject-selected testing times) may paint a false picture of group equivalence, as researchers are only observing part of a daily trajectory.

Our growing understanding of the relationship between circadian rhythm and neuropsychiatry may allow for critical advances in improving therapeutic outcomes from treatments (Bhatnagar et al., 2023; Meuret et al., 2016). Such advances are particularly called for in the case of symptoms of apathy and anhedonia, as current treatments often fail to improve motivational deficits (Calabrese et al., 2014; Gabbay et al., 2015; McMakin et al., 2012), but could potentially be coupled with a patient’s chronotype to increase efficacy. At minimum, clinical trials predicting change in motivational measures, such as effort-based decision-making, should assess patients at similar times of day, as this could reduce or inflate treatment effects.

Circadian rhythm and neuropsychiatric syndromes may affect motivation via parallel, as well as distinct, mechanisms—but crucially, this overlap is dependent on time-of-testing. Our work suggests that chronotype and time-of-testing are essential variables to consider in future effort-based decision-making experiments, particularly those measuring effort-based decision-making in patient groups, such as those with depression, high apathy, or high anhedonia. Beyond experimental work, future interventions should consider the role of chronotype in measurement and modulation of motivation.

The anonymous processed data, the R and Stan code to reproduce all simulations, analyses, and visualizations, and all experimental materials are publicly available on GitHub (https://github.com/smehrhof/2024_effort_study; copy archived at Mehrhof, 2025) and published on Zenodo (https://doi.org/10.5281/zenodo.15068968).

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Author details

1. Sara Z Mehrhof

   MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   sara.mehrhof@mrc-cbu.cam.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-8267-3898

2. Camilla L Nord

   1. MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
   2. Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom

   Contribution

   Conceptualization, Supervision, Funding acquisition, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9281-3417

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