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Localized microstimulation of primate pregenual cingulate cortex induces negative decision-making.

Amemori K, Graybiel AM - Nat. Neurosci. (2012)

Bottom Line: In healthy individuals, the pACC is involved in cost-benefit evaluation.We found that the macaque pACC has an opponent process-like organization of neurons representing motivationally positive and negative subjective value.This cortical zone could be critical for regulating negative emotional valence and anxiety in decision-making.

View Article: PubMed Central - PubMed

Affiliation: McGovern Institute for Brain Research, and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

ABSTRACT
The pregenual anterior cingulate cortex (pACC) has been implicated in human anxiety disorders and depression, but the circuit-level mechanisms underlying these disorders are unclear. In healthy individuals, the pACC is involved in cost-benefit evaluation. We developed a macaque version of an approach-avoidance decision task used to evaluate anxiety and depression in humans and, with multi-electrode recording and cortical microstimulation, we probed pACC function as monkeys performed this task. We found that the macaque pACC has an opponent process-like organization of neurons representing motivationally positive and negative subjective value. Spatial distribution of these two neuronal populations overlapped in the pACC, except in one subzone, where neurons with negative coding were more numerous. Notably, microstimulation in this subzone, but not elsewhere in the pACC, increased negative decision-making, and this negative biasing was blocked by anti-anxiety drug treatment. This cortical zone could be critical for regulating negative emotional valence and anxiety in decision-making.

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Behavioral patterns. (a) Avoidance (red square) and approach (blue cross) choice made by monkey S in a single session of the Ap-Av task. Black line indicates the decision boundary calculated by logistic regression. Light blue and orange lines indicate 90% and 10% probability, respectively, of choosing approach estimated by the regression model. (b, c) Decision (b; red: approach, blue: avoidance) and reaction times (c; red: slow, blue: fast) averaged over all experiments for the Ap-Av task and plotted according to pseudocolor scales at right. Dotted lines indicate decision boundaries calculated based on all the accumulated data. (d) Choice of square (red square) and cross (blue cross) targets in a single session of the Ap-Ap task, by monkey S. Black, light blue and orange lines represent 50%, 90%, and 10% probabilities of choosing cross target, calculated by logistic regression. (e, f) Target choice (e) and reaction times (f) averaged over all Ap-Ap experiments. Dotted lines indicate decision boundary.
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Figure 2: Behavioral patterns. (a) Avoidance (red square) and approach (blue cross) choice made by monkey S in a single session of the Ap-Av task. Black line indicates the decision boundary calculated by logistic regression. Light blue and orange lines indicate 90% and 10% probability, respectively, of choosing approach estimated by the regression model. (b, c) Decision (b; red: approach, blue: avoidance) and reaction times (c; red: slow, blue: fast) averaged over all experiments for the Ap-Av task and plotted according to pseudocolor scales at right. Dotted lines indicate decision boundaries calculated based on all the accumulated data. (d) Choice of square (red square) and cross (blue cross) targets in a single session of the Ap-Ap task, by monkey S. Black, light blue and orange lines represent 50%, 90%, and 10% probabilities of choosing cross target, calculated by logistic regression. (e, f) Target choice (e) and reaction times (f) averaged over all Ap-Ap experiments. Dotted lines indicate decision boundary.

Mentions: The monkeys systematically varied their decisions to approach or to avoid depending on the relative sizes of the food rewards and airpuffs indicated by the cues. Fig. 2a shows a scatter plot of decisions made by monkey S during a block of trials in the Ap-Av task, and Fig. 2b illustrates the decisions made in the Ap-Av block averaged across sessions. Based on Bayesian information criteria (Supplementary Fig. 1), we adopted the logistic behavioral model that could best characterize the behavioral choice of monkey. With this model, the decision boundary between approach and avoidance decisions was linear (black line in Fig. 2a; dotted line in Fig. 2b). The fact that the mean reaction times increased along the decision boundary indicated conflict in the monkey's decision-making, especially for low values of indicated reward (Fig. 2c).


Localized microstimulation of primate pregenual cingulate cortex induces negative decision-making.

Amemori K, Graybiel AM - Nat. Neurosci. (2012)

Behavioral patterns. (a) Avoidance (red square) and approach (blue cross) choice made by monkey S in a single session of the Ap-Av task. Black line indicates the decision boundary calculated by logistic regression. Light blue and orange lines indicate 90% and 10% probability, respectively, of choosing approach estimated by the regression model. (b, c) Decision (b; red: approach, blue: avoidance) and reaction times (c; red: slow, blue: fast) averaged over all experiments for the Ap-Av task and plotted according to pseudocolor scales at right. Dotted lines indicate decision boundaries calculated based on all the accumulated data. (d) Choice of square (red square) and cross (blue cross) targets in a single session of the Ap-Ap task, by monkey S. Black, light blue and orange lines represent 50%, 90%, and 10% probabilities of choosing cross target, calculated by logistic regression. (e, f) Target choice (e) and reaction times (f) averaged over all Ap-Ap experiments. Dotted lines indicate decision boundary.
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Related In: Results  -  Collection

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Figure 2: Behavioral patterns. (a) Avoidance (red square) and approach (blue cross) choice made by monkey S in a single session of the Ap-Av task. Black line indicates the decision boundary calculated by logistic regression. Light blue and orange lines indicate 90% and 10% probability, respectively, of choosing approach estimated by the regression model. (b, c) Decision (b; red: approach, blue: avoidance) and reaction times (c; red: slow, blue: fast) averaged over all experiments for the Ap-Av task and plotted according to pseudocolor scales at right. Dotted lines indicate decision boundaries calculated based on all the accumulated data. (d) Choice of square (red square) and cross (blue cross) targets in a single session of the Ap-Ap task, by monkey S. Black, light blue and orange lines represent 50%, 90%, and 10% probabilities of choosing cross target, calculated by logistic regression. (e, f) Target choice (e) and reaction times (f) averaged over all Ap-Ap experiments. Dotted lines indicate decision boundary.
Mentions: The monkeys systematically varied their decisions to approach or to avoid depending on the relative sizes of the food rewards and airpuffs indicated by the cues. Fig. 2a shows a scatter plot of decisions made by monkey S during a block of trials in the Ap-Av task, and Fig. 2b illustrates the decisions made in the Ap-Av block averaged across sessions. Based on Bayesian information criteria (Supplementary Fig. 1), we adopted the logistic behavioral model that could best characterize the behavioral choice of monkey. With this model, the decision boundary between approach and avoidance decisions was linear (black line in Fig. 2a; dotted line in Fig. 2b). The fact that the mean reaction times increased along the decision boundary indicated conflict in the monkey's decision-making, especially for low values of indicated reward (Fig. 2c).

Bottom Line: In healthy individuals, the pACC is involved in cost-benefit evaluation.We found that the macaque pACC has an opponent process-like organization of neurons representing motivationally positive and negative subjective value.This cortical zone could be critical for regulating negative emotional valence and anxiety in decision-making.

View Article: PubMed Central - PubMed

Affiliation: McGovern Institute for Brain Research, and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

ABSTRACT
The pregenual anterior cingulate cortex (pACC) has been implicated in human anxiety disorders and depression, but the circuit-level mechanisms underlying these disorders are unclear. In healthy individuals, the pACC is involved in cost-benefit evaluation. We developed a macaque version of an approach-avoidance decision task used to evaluate anxiety and depression in humans and, with multi-electrode recording and cortical microstimulation, we probed pACC function as monkeys performed this task. We found that the macaque pACC has an opponent process-like organization of neurons representing motivationally positive and negative subjective value. Spatial distribution of these two neuronal populations overlapped in the pACC, except in one subzone, where neurons with negative coding were more numerous. Notably, microstimulation in this subzone, but not elsewhere in the pACC, increased negative decision-making, and this negative biasing was blocked by anti-anxiety drug treatment. This cortical zone could be critical for regulating negative emotional valence and anxiety in decision-making.

Show MeSH
Related in: MedlinePlus