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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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Response properties of N-type (a–e) and P-type (f–j) units. (a, b, f, g) Population cue-period activity (color scale to right) of N-type (a and b) and P-type (f and g) units relative to the visual cue in the Ap-Av (a and f) and Ap-Ap (b and g) tasks. Black dotted line indicates the decision boundary. (c, d, h, i) Population activity across task-time for N-type (c and d) and P-type (h and i) units in the Ap-Av (c and h) and Ap-Ap (d and i) tasks. Line colors correspond to expected utility as indicated by color bar at right. Before averaging across sessions, the expected utility was normalized in each session so that the maximum expected utility is set to 1 and minimum expected utility to 0. F: fixation, C: cue, M: movement, A: airpuff, R: reward. Yellow shading indicates the cue period. (e, j) Scatterplots of correlation coefficients between cue-period activity and expected utility calculated for N-type (e) and P-type (j) units. Dotted line indicates regression slope. X-axis represents correlation coefficients between cue-period activity in the Ap-Av task and the expected utility calculated for the Ap-Av task. Y-axis represents correlation coefficients between cue-period activity in the Ap-Ap task and the expected utility calculated for the Ap-Ap task. Each circle indicates an N-type (e) or P-type (j) unit for which cue-period activity was significantly correlated with the expected utility calculated for both Ap-Av and Ap-Ap tasks (Pearson's correlation coefficients, P < 0.05). Cross indicates another unit that did not show a correlation between activity and utility in both tasks.
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Figure 4: Response properties of N-type (a–e) and P-type (f–j) units. (a, b, f, g) Population cue-period activity (color scale to right) of N-type (a and b) and P-type (f and g) units relative to the visual cue in the Ap-Av (a and f) and Ap-Ap (b and g) tasks. Black dotted line indicates the decision boundary. (c, d, h, i) Population activity across task-time for N-type (c and d) and P-type (h and i) units in the Ap-Av (c and h) and Ap-Ap (d and i) tasks. Line colors correspond to expected utility as indicated by color bar at right. Before averaging across sessions, the expected utility was normalized in each session so that the maximum expected utility is set to 1 and minimum expected utility to 0. F: fixation, C: cue, M: movement, A: airpuff, R: reward. Yellow shading indicates the cue period. (e, j) Scatterplots of correlation coefficients between cue-period activity and expected utility calculated for N-type (e) and P-type (j) units. Dotted line indicates regression slope. X-axis represents correlation coefficients between cue-period activity in the Ap-Av task and the expected utility calculated for the Ap-Av task. Y-axis represents correlation coefficients between cue-period activity in the Ap-Ap task and the expected utility calculated for the Ap-Ap task. Each circle indicates an N-type (e) or P-type (j) unit for which cue-period activity was significantly correlated with the expected utility calculated for both Ap-Av and Ap-Ap tasks (Pearson's correlation coefficients, P < 0.05). Cross indicates another unit that did not show a correlation between activity and utility in both tasks.

Mentions: To characterize the representative properties of these two distinct populations of pACC neurons, we examined their activity profiles during the cue period (Fig. 4). In the Ap-Av task, the N-type population responded to visual cues that subsequently were followed by an avoidance decision, and they responded maximally to visual cues offering low food and low airpuff (Fig. 4a). The responses of N-type unit population were task-dependent: in the Ap-Ap task, they responded only to visual cues offering low food rewards (Fig. 4b). Under these conditions, both the frequency of omission errors (Supplementary Fig. 8) and the monkeys’ reaction times (Fig. 2c,f) increased, suggesting that they might have been relatively less motivated, experiencing conflict or possible frustration with the low yields cued. The P-type population, by contrast, responded to cues that were followed by approach in the Ap-Av task and fired maximally to the cues that offered large reward and weak airpuff (Fig. 4f). Like the N-type population, the P-type population changed their activity depending on the task version. In the Ap-Ap task, they responded to long red and yellow bars offering large amounts of reward (Fig. 4g).


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

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

Response properties of N-type (a–e) and P-type (f–j) units. (a, b, f, g) Population cue-period activity (color scale to right) of N-type (a and b) and P-type (f and g) units relative to the visual cue in the Ap-Av (a and f) and Ap-Ap (b and g) tasks. Black dotted line indicates the decision boundary. (c, d, h, i) Population activity across task-time for N-type (c and d) and P-type (h and i) units in the Ap-Av (c and h) and Ap-Ap (d and i) tasks. Line colors correspond to expected utility as indicated by color bar at right. Before averaging across sessions, the expected utility was normalized in each session so that the maximum expected utility is set to 1 and minimum expected utility to 0. F: fixation, C: cue, M: movement, A: airpuff, R: reward. Yellow shading indicates the cue period. (e, j) Scatterplots of correlation coefficients between cue-period activity and expected utility calculated for N-type (e) and P-type (j) units. Dotted line indicates regression slope. X-axis represents correlation coefficients between cue-period activity in the Ap-Av task and the expected utility calculated for the Ap-Av task. Y-axis represents correlation coefficients between cue-period activity in the Ap-Ap task and the expected utility calculated for the Ap-Ap task. Each circle indicates an N-type (e) or P-type (j) unit for which cue-period activity was significantly correlated with the expected utility calculated for both Ap-Av and Ap-Ap tasks (Pearson's correlation coefficients, P < 0.05). Cross indicates another unit that did not show a correlation between activity and utility in both tasks.
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Figure 4: Response properties of N-type (a–e) and P-type (f–j) units. (a, b, f, g) Population cue-period activity (color scale to right) of N-type (a and b) and P-type (f and g) units relative to the visual cue in the Ap-Av (a and f) and Ap-Ap (b and g) tasks. Black dotted line indicates the decision boundary. (c, d, h, i) Population activity across task-time for N-type (c and d) and P-type (h and i) units in the Ap-Av (c and h) and Ap-Ap (d and i) tasks. Line colors correspond to expected utility as indicated by color bar at right. Before averaging across sessions, the expected utility was normalized in each session so that the maximum expected utility is set to 1 and minimum expected utility to 0. F: fixation, C: cue, M: movement, A: airpuff, R: reward. Yellow shading indicates the cue period. (e, j) Scatterplots of correlation coefficients between cue-period activity and expected utility calculated for N-type (e) and P-type (j) units. Dotted line indicates regression slope. X-axis represents correlation coefficients between cue-period activity in the Ap-Av task and the expected utility calculated for the Ap-Av task. Y-axis represents correlation coefficients between cue-period activity in the Ap-Ap task and the expected utility calculated for the Ap-Ap task. Each circle indicates an N-type (e) or P-type (j) unit for which cue-period activity was significantly correlated with the expected utility calculated for both Ap-Av and Ap-Ap tasks (Pearson's correlation coefficients, P < 0.05). Cross indicates another unit that did not show a correlation between activity and utility in both tasks.
Mentions: To characterize the representative properties of these two distinct populations of pACC neurons, we examined their activity profiles during the cue period (Fig. 4). In the Ap-Av task, the N-type population responded to visual cues that subsequently were followed by an avoidance decision, and they responded maximally to visual cues offering low food and low airpuff (Fig. 4a). The responses of N-type unit population were task-dependent: in the Ap-Ap task, they responded only to visual cues offering low food rewards (Fig. 4b). Under these conditions, both the frequency of omission errors (Supplementary Fig. 8) and the monkeys’ reaction times (Fig. 2c,f) increased, suggesting that they might have been relatively less motivated, experiencing conflict or possible frustration with the low yields cued. The P-type population, by contrast, responded to cues that were followed by approach in the Ap-Av task and fired maximally to the cues that offered large reward and weak airpuff (Fig. 4f). Like the N-type population, the P-type population changed their activity depending on the task version. In the Ap-Ap task, they responded to long red and yellow bars offering large amounts of reward (Fig. 4g).

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