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  4. Glutamine-to-glutamate ratio in the nucleus accumbens predicts effort-based motivated performance in humans
 
research article

Glutamine-to-glutamate ratio in the nucleus accumbens predicts effort-based motivated performance in humans

Strasser, Alina Veronika Irene  
•
Luksys, Gediminas
•
Xin, Lijing
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2020
Neuropsychopharmacology

Substantial evidence implicates the nucleus accumbens in motivated performance, but very little is known about the neurochemical underpinnings of individual differences in motivation. Here, we applied 1H magnetic resonance spectroscopy (1H-MRS) at ultra-high-field in the nucleus accumbens and inquired whether levels of glutamate (Glu), glutamine (Gln), GABA or their ratios predict interindividual differences in effort-based motivated task performance. Given the incentive value of social competition, we also examined differences in performance under self-motivated or competition settings. Our results indicate that higher accumbal Gln-to-Glu ratio predicts better overall performance and reduced effort perception. As performance is the outcome of multiple cognitive, motor and physiological processes, we applied computational modeling to estimate best-fitting individual parameters related to specific processes modeled with utility, effort and performance functions. This model-based analysis revealed that accumbal Gln-to-Glu ratio specifically relates to stamina; i.e., the capacity to maintain performance over long periods. It also indicated that competition boosts performance from task onset, particularly for low Gln-to-Glu individuals. In conclusion, our findings provide novel insights implicating accumbal Gln and Glu balance on the prediction of specific computational components of motivated performance. This approach and findings can help developing therapeutic strategies based on targeting metabolism to ameliorate deficits in effort engagement.

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s41386-020-0760-6.pdf

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Publisher's Version

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http://purl.org/coar/version/c_970fb48d4fbd8a85

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openaccess

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CC BY

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1.15 MB

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Adobe PDF

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b00631ba05ce2453ac8ea56078d9abcf

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