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Effort-Based Reinforcement Processing and Functional Connectivity Underlying Amotivation in Medicated Patients with Depression and Schizophrenia.

Park IHo, Lee BChul, Kim J-J, Kim JIl, Koo M-S
J Neurosci. 2017 Apr 19; 37(16):4370-4380. PMID: 28283562. Pubmed

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Submitted by Adam Culbreth on

Disparate Neural Mechanisms of Effort-Based Reinforcement-Learning in Depression and Schizophrenia

This comment was co-written by Erin Moran.

Motivational deficits have long been associated with schizophrenia and major depressive disorder (MDD). These symptoms limit functioning of people with schizophrenia or MDD. However, current treatments for motivational impairment in schizophrenia and MDD are not effective for all patients. This limited effectiveness may stem from poor understanding of the mechanisms that give rise to these symptoms. Thus, work examining such mechanisms to elucidate similar/disparate areas of impairment in a transdiagnostic sample is of high relevance to the field.

In this recent article in the Journal of Neuroscience, Park and colleagues examined effort-based decision-making as one potential psychological mechanism for understanding motivational impairments in schizophrenia and MDD. Effort-based decision-making has become an extensively researched construct in the basic sciences with animal (Salamone et al., 2016) and human studies (Westbrook and Braver, 2016) generating a comprehensive picture of its associated neural processes, including dopamine systems, the ventral striatum, and the anterior cingulate cortex. This literature has provided models ripe for translation into clinical domains. Indeed, translational studies have found that individuals with MDD (Treadway et al., 2012; Yang et al., 2014) and schizophrenia (Gold et al., 2015) are less likely to exert effort to obtain monetary rewards compared to controls, and that this deficit correlates with motivational impairment across disorders. Further, studies have suggested roles of the striatum (Wolf et al., 2014; Huang et al., 2016; Yang et al., 2016), the cingulate cortex (Huang et al., 2016), and the dorsolateral prefrontal cortex (Wolf et al., 2014) in aberrant effort-based decision-making in patients with schizophrenia and MDD, suggesting potential preliminary neural mechanisms. However, although both MDD and schizophrenia seem to be associated with aberrant effort-based decision-making, it remains untested whether this seemingly similar deficit arises from similar or disparate neural mechanisms.

To this end, Park and colleagues collected fMRI data from individuals with schizophrenia (N = 19), MDD (N = 19), and healthy controls (N = 30) as they performed an effort-based reinforcement-learning task. On this task, participants were presented with a cue, indicating trial type. Following cue presentation, participants were presented with a start signal to press a button in reaction to this cue. Next, a work phase commenced where two light bulbs were presented and participants needed to quickly press a corresponding button to extinguish the light bulbs as they became lit. Finally, participants received feedback (i.e., gain, no gain, loss, no loss). Trial types varied by effort (i.e., high or low effort, depending on the number of button presses required) and reward type (i.e., positive or negative reinforcement). Behaviorally, the authors examined two dependent variables: reaction time of the cue response (cue/anticipation reaction time) and reaction time of the subject’s final light bulb switch-off (work/effort reaction time). Imaging data were analyzed by modeling the three task phases (anticipation, work, and feedback), as well as reward type and effort level in whole-brain and specific regions of interest analyses. Participants completed a resting-state scan before and after completing the effort task. Following scanning, participants completed a cue preference task, choosing their preferred cue type (i.e., neutral, positive, and negative) by making two alternative forced choices between trial types.

Park and colleagues found that controls showed significantly faster cue reaction time for positive low-effort trials and negative high-effort trials relative to neutral. In contrast, cue reaction time in MDD was only faster in the negative reward/high effort condition, and was not modulated by reward or effort level in schizophrenia. For work reaction time, Park and colleagues found individuals with MDD were slower on all four reinforcement conditions, but schizophrenia patients were slower on only the high-effort trials.

In regard to imaging, the researchers found that low-effort positive reinforcement trials and high-effort negative reinforcement trials were associated with greater putamen and medial orbital frontal cortex (OFC) activity in controls. In regard to group differences, they found that individuals with schizophrenia showed greater activity of the putamen during low-effort trials compared to control and MDD participants. Further, during the work phase, putamen activity was inversely correlated with motivational impairment during low-effort trials for those with schizophrenia, while in MDD putamen activation during the negative reward trials was inversely correlated with motivational impairment. With regard to resting-state functional connectivity, surprisingly, Park and colleagues found that subjects with schizophrenia showed largely similar functional connectivity compared to controls; however, they reported significantly reduced functional connectivity between the left putamen to right OFC in MDD relative to controls and schizophrenia patients. Moreover, the authors found that amotivation in schizophrenia was positively related to right nucleus accumbens and caudate nucleus (NAc/CHN) left medial OFC connectivity while amotivation in depression was positively correlated with left NAc/CHN-left medial OFC functional connectivity. This suggests a common relationship across disorders between amotivation and connectivity in the NAc/CHN-left medial OFC.

Park and colleagues are the first to take a transdiagnostic approach to examining the neural correlates of effort processing. However, interpretation of these results is limited by several factors. First, with regard to the behavioral data, it is not clear that the patients with schizophrenia learned the cues significantly above chance, and it does not appear that their preference for reward cues during the preference test was significantly greater than either the neutral or negative reinforcement cues. Learning of the cue is important to the interpretation of the results, which often involves contrasting various trial types. For example, the authors interpret the lack of modulation in cue reaction time by reward or effort level in individuals with schizophrenia as an overall lack of anticipatory capacity. However, an alternative explanation could be that patients did not sufficiently learn the cues and thus did not modulate reaction time to different cue presentations. This is an important point, given the mixed body of research pointing to the potential impairments of anticipatory response in schizophrenia (Frost and Strauss, 2016). Future work should rule out alternative explanations (e.g., impaired learning or understanding of task) when making claims about impaired anticipatory capacity in schizophrenia.

Second, it is unclear whether the authors’ measure of work RT assesses effort or a persistence/fatigue effect. Interestingly, individuals with MDD displayed slower work RT on all conditions, except neutral, while individuals with schizophrenia showed slowed work RT on high-effort trials compared to controls. It may be that the baseline motoric response of the patients is simply slower than the controls, particularly after repeated button presses, and it is likely that this slowness has no relation to effort processes. Further, this measure was not described in the original Croxson paper, limiting interpretation of the replicability of this measure.

With regard to the neuroimaging data, the authors often did not provide a comprehensive account of the statistical analyses, omitting effects for certain patient groups for various contrasts. Similarly, when interaction terms were discussed, most were not unpacked, leaving the reader unable to fully interpret the significance of the result or the direction of various effects. At times in the manuscript, it was unclear whether all diagnostic groups were included in a particular model or whether diagnostic groups were modeled separately. Such reporting makes the results section difficult to follow, and makes clear interpretation of the results challenging. Finally, the authors conducted a number of different tests with various contrasts, but found few significant group-level results. The small sample sizes of the patient groups limit the ability of the authors to make strong claims about negative findings, as these could simply reflect insufficient power to detect effects. As such, one useful topic for discussion would have been the replication or failure to replicate the initial Croxson and colleagues' study (Croxson et al., 2009). However, the authors did not discuss the original study outside of the methods section, and did not seem to replicate key findings of the Croxson paper, including effects in the ventral striatum and cingulate during effort/reward anticipation.

In summary, effort-based decision-making represents an intriguing contributory mechanism for motivational impairment across psychiatric disorders. Park and colleagues provide a novel study examining the neural correlates of aberrant effort-based decision-making in MDD, schizophrenia, and control participants. Such transdiagnostic samples are rare and allow for insights into seldom-posed questions including whether a similar behavioral deficit might arise from disparate neural mechanisms. However, interpretative challenges limit a full realization of the implications of their findings, which would have been helped by a more extensive reporting of statistical results, larger sample sizes (particularly in the patient groups), greater justification for the choice of behavioral measures and their construct validity as measures of effort-based decision-making, and a greater ability to rule out alternative explanations for the results. Taken together, these concerns raise questions about the authors’ interpretation of these data―an interpretation that could be misleading to the field. Future work is needed to provide replication and construct validity before we can conclude that there is clear evidence for differences between MDD and schizophrenia in the neural correlates of impaired effort-based decision-making.

Acknowledgements: We would like to thank Drs. Deanna Barch, James Waltz, and James Gold for helpful comments on an initial draft of this manuscript.