Neural mechanisms of goal-directed behavior: outcome-based response selection is associated with increased functional coupling of the angular gyrus

Abstract

Goal-directed behavior is based on representations of contingencies between a certain situation (S), a certain (re)action (R) and a certain outcome (O). These S-R-O representations enable flexible response selection in different situations according to the currently pursued goal. Importantly however, the successful formation of such representations is a necessary but not sufficient precondition for goal-directed behavior which additionally requires the actual usage of the contingency information for action control. The present fMRI study aimed at identifying the neural basis of each of these two aspects: representing vs. explicitly using experienced S-R-O contingencies. To this end, we created three experimental conditions: S-R-O contingency present and used for outcome-based response selection, S-R-O contingency present but not used, and S-R-O contingency absent. The comparison between conditions with and without S-R-O contingency revealed that the angular gyrus is relevant for representing S-R-O contingencies. The explicit usage of learnt S-R-O representations in turn was associated with increased functional coupling between angular gyrus and several subcortical (hippocampus, caudate head), prefrontal (lateral orbitofrontal cortex (OFC), rostrolateral prefrontal cortex (RLPFC)) and cerebellar areas, which we suggest represent different explicit and implicit processes of goal-directed action control. Hence, we ascribe a central role to the angular gyrus in associating actions to their sensory outcomes which is used to guide behavior through coupling of the angular gyrus with multiple areas related to different aspects of action control.

Frontal Midline Theta Reflects Cognitive Control During Planning

“…This can be explained by the requirement of high cognitive functions such as working memory and attentional control to perform the execution of the plan. All these observations are in line with the theoretical assumption of cognitive planning (Hayes-Roth & Hayes-Roth, 1979;Wilensky, 1983;Grafman & Hendler, 1991;Zwosta, Ruge & Wolfensteller, 2015).…”

“…The behavioral results for the planning condition were in line with our predictions. Since the planning task implies a high cognitive function (Lezak, 1995;Zwosta, Ruge & Wolfensteller, 2015), we predicted higher time responses and less accurate performances during the planning condition (complex task: plan a path in a complex map) than during the control condition (simple task: they only have to follow a marked path and decide whether it followed the rules). Moreover, in both periods of the planning condition (the planning period and the execution planning period) reaction times were always greater than the control condition (the control period and the execution control period) reflecting how difficult and cognitively demanding the planning condition is (Owen et al, 1996;Voytek et al, 2015;Ossandón et al, 2012).…”

“…Cognitive control or Executive functions (EFs) are a theoretical construct that include a wide range of higher order cognitive functions associated with goal-directed behavior (Lezak, 1995;Shallice, 1991;Stuss, 1992;Zwosta, Ruge & Wolfensteller, 2015;Cooper, 2010). One of the high-order cognitive control function is planning (Collins & Koechlin, 2012;Sira & Mateer, 2014;Lunt et al 2012), which consists on the ability of developing a sequenced plan to achieve a goal in an organized, strategic and efficient manner (Hayes-Roth & Hayes-Roth, 1979).…”

Unhealthy Yet Avoidable – How Cognitive Bias Modification Alters Behavioral And Brain Responses To Food Cues In Obesity

“…For unhealthy food avoidance, we found increased post -training task-related connectivity between the rAG and the dorsal striatum, which is related to stimulus-response learning, executive attention and exerting cognitive control 39-43 . Increased connectivity between the dorsal striatum and rAG was previously related to explicit usage of learned stimulus-response-outcome associations 44 . This could be interpreted as a complementary effect of training.…”

On Matching Faces with Temporal Variations using Representation Learning

“…Singh-Curry and Husain[117] performed a meta-analysis to ascertain the role of IPL in audio and visual vigilance tasks which required detecting small variations which occur at random time instances. As humans are naturally trained by social experiences in detecting and processing variations in facial features due to age progression, significant activation difference in IPL might be linked to visual vigilance task for verifying age-separated stimuli face pairs with temporal variations.Apart from IPL, activations in left angular gyrus may be linked with spatiovisual attention and memory retrieval[150] which may indicate a greater requirement of attention for processing age-separated face pairs. Brain areas such as postcentral gyrus and precentral gyrus may have been activated due to the pressing of the controller button to provide the response.…”