Neural mechanisms of high-level cognitive processes in task preparation and implementation

Abstract

To adjust our behavior based in goals is a core human ability that allows us to rapidly adapt to new demands or new environments. Cognitive control, that is, the mechanism that regulates our thought and actions upon internal representations of our goals (Norman & Shallice, 1980), is thought to underlie this ability. Due to its central role in our cognitive activity, control is involved in a plethora of phenomena, and therefore it can be analyzed from different perspectives. Specifically, this thesis takes advantage of a temporal classification: reactive versus prospective control. While reactive control refers to the immediate deployment of control upon conflict detection, prospective processes allow the anticipation and corresponding adjustment to forthcoming demands (Braver, 2012). The main aim of this thesis is to advance our knowledge about proactive control. All of our experiments highlight the predominance of top-down influences in preparatory mechanisms. However, bottom-up elements also play a role in controldemanding context. The biggest piece of evidence in this line comes from Experimental Series 1, which revealed an unconscious bias in task set selection. This result is coherent with previous studies showing unconscious influences in high-level processes (van Gaal et al., 2012). It therefore shows that at least some proactive control mechanisms can be altered by bottom-up information. Subsequently, in conjunction with previous similar studies (e.g. De Pisapia et al., 2011), they suggest the dissociation between proactive control and consciousness (Hommel, 2017). Experiments I and II also show how some stimuli, such as instructions, can elicit control processes automatically (Liefooghe, Wenke, & De Houwer, 2012). The evolutive relevance of fast learning (Cole et al., 2013) can underlie this automatic effect of instructions. Despite the relative automaticity described before, our data show an overwhelming predominance of top-down effects in proactive control. First, in Experimental Series I, the unconscious effect is only found when the executive setting is configured properly according to conscious expectations (Kiefer, 2012). Therefore, subliminal perception can affect but not initiate control processes (van Gaal et al., 2012). Moreover, in Experiment I, conscious expectations regarding future demands were shown to modulate brain activity during preparation. In the proactive control framework (Braver, 2012), the reported category specific activations can be understood as the outcome of a top-down influence, originating in control regions, on incoming information. Last, Experiment II reveals how actively preparing to implement novel task sets involves a large set of control areas. Moreover, category specific information could be decoded from selective processing regions seconds before target onset, which shows again a bias in the processing of incoming information based on internal goals. Altogether, our results suggest that proactive cognitive control sets up our informationprocessing system in a top-down manner to allow some extent of automaticity (Dehaene & Naccache, 2001; Kiefer, 2012; Kiefer & Martens, 2010). This, in turn, would make our control systems more efficient by reducing costs associated to maintained monitoring, and therefore, optimizing the consecution of our goals (Kiefer, 2012). In sum, the present thesis reveals a dynamic relationship between bottom-up and top-down processes. We interpret this relationship within the predictive coding framework (Friston, 2005), which suggests that our psychological experience is the result of an iterative interaction between bottom-up information and top-down predictions that bias this information to guide perception. Such mechanism would allow the evolutive development of a proactive control system (Buschman & Miller, 2014).