کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10215527 | 1678892 | 2019 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Inhibitory and excitatory mechanisms in the human cingulate-cortex support reinforcement learning: A functional Proton Magnetic Resonance Spectroscopy study
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
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چکیده انگلیسی
The dorsal anterior cingulate cortex (dACC) is crucial for motivation, reward- and error-guided decision-making, yet its excitatory and inhibitory mechanisms remain poorly explored in humans. In particular, the balance between excitation and inhibition (E/I), demonstrated to play a role in animal studies, is difficult to measure in behaving humans. Here, we used functional magnetic-resonance-spectroscopy (1H-fMRS) to measure the brain's major inhibitory (GABA) and excitatory (Glutamate) neurotransmitters during reinforcement learning with three different conditions: high cognitive load (uncertainty); probabilistic discrimination learning; and a control null-condition. Participants learned to prefer the gain option in the discrimination phase and had no preference in the other conditions. We found increased GABA levels during the uncertainty condition, potentially reflecting recruitment of inhibitory systems during high cognitive load when trying to learn. Further, higher GABA levels during the null (baseline) condition correlated with improved discrimination learning. Finally, glutamate and GABA levels were correlated during high cognitive load. These results suggest that availability of dACC inhibitory resources enables successful learning. Our approach helps elucidate the potential contribution of the balance between excitation and inhibition to learning and motivation in behaving humans.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 184, 1 January 2019, Pages 25-35
Journal: NeuroImage - Volume 184, 1 January 2019, Pages 25-35
نویسندگان
Vered Bezalel, Rony Paz, Assaf Tal,