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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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Classification of units recorded in the pACC region. (a) Results of stepwise regression analysis for the Ap-Av task. Regression variables are offered reward (Rew), offered airpuff (Ave), choice (Cho), chosen reward (Cho*Rew), chosen airpuff (Cho*Ave), reaction times (RT), expected utility (Eutil) and conflict in decision (Conf). Y-axis indicates the number of recorded units best characterized by one or a combination of the variables identified in the matrix below. Black squares in the matrix along X-axis indicate the variable or variables selected by the stepwise regression procedure. Many units (397 units) were characterized by the single variables that we chose. These units were further classified by whether the activity was positively (red) or negatively (blue) correlated with the variable. Another 159 units were characterized by particular combinations of variables indicated by black squares in the matrix. (b) Results of multidimensional scaling performed based on the correlation distance of the firing patterns of each type of unit. X-axis shows the principal feature dimension, and y-axis shows the second feature dimension extracted by this procedure. Types of units located closely to each other indicate that their firing patterns are similar. Blue circles indicate the locations of units with activity negatively correlated with the indicated variable. Red circle indicate the locations of units with activity positively correlated with the indicated variable. Units were classified by the similarity derived in the primary feature, N-type (light blue region) and P-type (light red region). (c) Cortical distribution of N-type (blue circle) and P-type (red circle) units. In the ventral bank of the cingulate sulcus (blue shading), N-type units significantly outnumbered P-type units (Fisher's exact test, P < 0.05).
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Figure 3: Classification of units recorded in the pACC region. (a) Results of stepwise regression analysis for the Ap-Av task. Regression variables are offered reward (Rew), offered airpuff (Ave), choice (Cho), chosen reward (Cho*Rew), chosen airpuff (Cho*Ave), reaction times (RT), expected utility (Eutil) and conflict in decision (Conf). Y-axis indicates the number of recorded units best characterized by one or a combination of the variables identified in the matrix below. Black squares in the matrix along X-axis indicate the variable or variables selected by the stepwise regression procedure. Many units (397 units) were characterized by the single variables that we chose. These units were further classified by whether the activity was positively (red) or negatively (blue) correlated with the variable. Another 159 units were characterized by particular combinations of variables indicated by black squares in the matrix. (b) Results of multidimensional scaling performed based on the correlation distance of the firing patterns of each type of unit. X-axis shows the principal feature dimension, and y-axis shows the second feature dimension extracted by this procedure. Types of units located closely to each other indicate that their firing patterns are similar. Blue circles indicate the locations of units with activity negatively correlated with the indicated variable. Red circle indicate the locations of units with activity positively correlated with the indicated variable. Units were classified by the similarity derived in the primary feature, N-type (light blue region) and P-type (light red region). (c) Cortical distribution of N-type (blue circle) and P-type (red circle) units. In the ventral bank of the cingulate sulcus (blue shading), N-type units significantly outnumbered P-type units (Fisher's exact test, P < 0.05).

Mentions: Stepwise regression analyses (Supplementary Note) indicated that among 875 task-related units, many (556 units, 63.5%) had activity during the decision period of the Ap-Av task that was significantly well characterized by linear combinations of these eight factors (F-test, P < 0.05; Fig. 3a). Among these, the majority (397 units, 71.4%) had activity patterns that were characterized by one of these variables. Because many of these units were uniquely characterized by a single variable, but not by a combination of these variables, the majority of units encoded, within the detection limits of the regression model, a single factor specifically characterized by the variable. We focused on the 397 units that had cue-period activity accounted for by single variables (Supplementary Fig. 5).


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

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

Classification of units recorded in the pACC region. (a) Results of stepwise regression analysis for the Ap-Av task. Regression variables are offered reward (Rew), offered airpuff (Ave), choice (Cho), chosen reward (Cho*Rew), chosen airpuff (Cho*Ave), reaction times (RT), expected utility (Eutil) and conflict in decision (Conf). Y-axis indicates the number of recorded units best characterized by one or a combination of the variables identified in the matrix below. Black squares in the matrix along X-axis indicate the variable or variables selected by the stepwise regression procedure. Many units (397 units) were characterized by the single variables that we chose. These units were further classified by whether the activity was positively (red) or negatively (blue) correlated with the variable. Another 159 units were characterized by particular combinations of variables indicated by black squares in the matrix. (b) Results of multidimensional scaling performed based on the correlation distance of the firing patterns of each type of unit. X-axis shows the principal feature dimension, and y-axis shows the second feature dimension extracted by this procedure. Types of units located closely to each other indicate that their firing patterns are similar. Blue circles indicate the locations of units with activity negatively correlated with the indicated variable. Red circle indicate the locations of units with activity positively correlated with the indicated variable. Units were classified by the similarity derived in the primary feature, N-type (light blue region) and P-type (light red region). (c) Cortical distribution of N-type (blue circle) and P-type (red circle) units. In the ventral bank of the cingulate sulcus (blue shading), N-type units significantly outnumbered P-type units (Fisher's exact test, P < 0.05).
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Figure 3: Classification of units recorded in the pACC region. (a) Results of stepwise regression analysis for the Ap-Av task. Regression variables are offered reward (Rew), offered airpuff (Ave), choice (Cho), chosen reward (Cho*Rew), chosen airpuff (Cho*Ave), reaction times (RT), expected utility (Eutil) and conflict in decision (Conf). Y-axis indicates the number of recorded units best characterized by one or a combination of the variables identified in the matrix below. Black squares in the matrix along X-axis indicate the variable or variables selected by the stepwise regression procedure. Many units (397 units) were characterized by the single variables that we chose. These units were further classified by whether the activity was positively (red) or negatively (blue) correlated with the variable. Another 159 units were characterized by particular combinations of variables indicated by black squares in the matrix. (b) Results of multidimensional scaling performed based on the correlation distance of the firing patterns of each type of unit. X-axis shows the principal feature dimension, and y-axis shows the second feature dimension extracted by this procedure. Types of units located closely to each other indicate that their firing patterns are similar. Blue circles indicate the locations of units with activity negatively correlated with the indicated variable. Red circle indicate the locations of units with activity positively correlated with the indicated variable. Units were classified by the similarity derived in the primary feature, N-type (light blue region) and P-type (light red region). (c) Cortical distribution of N-type (blue circle) and P-type (red circle) units. In the ventral bank of the cingulate sulcus (blue shading), N-type units significantly outnumbered P-type units (Fisher's exact test, P < 0.05).
Mentions: Stepwise regression analyses (Supplementary Note) indicated that among 875 task-related units, many (556 units, 63.5%) had activity during the decision period of the Ap-Av task that was significantly well characterized by linear combinations of these eight factors (F-test, P < 0.05; Fig. 3a). Among these, the majority (397 units, 71.4%) had activity patterns that were characterized by one of these variables. Because many of these units were uniquely characterized by a single variable, but not by a combination of these variables, the majority of units encoded, within the detection limits of the regression model, a single factor specifically characterized by the variable. We focused on the 397 units that had cue-period activity accounted for by single variables (Supplementary Fig. 5).

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