Rapid instructed task learning: A new window into the human brain’s unique capacity for flexible cognitive control

Abstract

The human ability to flexibly adapt to novel circumstances is extraordinary. Perhaps the most illustrative yet underappreciated form of this cognitive flexibility is rapid instructed task learning (RITL) – the ability to rapidly reconfigure our minds to perform new tasks from instruction. This ability is important for everyday life (e.g., learning to use new technologies), and is used to instruct participants in nearly every study of human cognition. We review the development of RITL as a circumscribed domain of cognitive neuroscience investigation, culminating in recent demonstrations that RITL is implemented via brain circuits centered on lateral prefrontal cortex. We then build on this and other insights to develop an integrative theory of cognitive flexibility and cognitive control, identifying theoretical principles and mechanisms that may make RITL possible in the human brain. Insights gained from this new theoretical account have important implications for further developments and applications of RITL research.

There are limits to the effects of task instructions: Making the automatic effects of task instructions context-specific takes practice.

“…Although verbal instructions are omnipresent in daily life and psychological research, the mechanisms via which they influence behavior are still poorly understood. In line with this observation, Cole, Laurent, and Stocco (2013) recently stressed the need for a more systematic investigation into this unique ability, to help accelerate the insights in what is now still a relatively small research domain.…”

Higher Intelligence Is Associated with Less Task-Related Brain Network Reconfiguration

“…Next, we investigated whether this pattern across multiple nodes was driven by a subset of specific regions or if this efficiency effect is truly a general property across the entire brain. We assessed each network's contribution by calculating a whole-brain FC configuration similarity score for each network separately (as identified in Power et al, 2011;Cole et al, 2013b). This score was based on task-rest similarity of each network's FC pattern with the entire rest of the brain.…”

“…The FPN was somewhat specific in that it was not involved in the language task, but it was general in that its update efficiency was related to performance of the reasoning and the working memory tasks. Regions within the FPN have many connections to other regions (Cole et al, 2010) and this network is thought to play a major role in cognitive control processes (Cole and Schneider, 2007;Vincent et al, 2008;Cole et al, 2013b). These findings suggest that efficiency in the FPN is important for tasks requiring flexibility and increased cognitive control (reasoning and working memory) relative to lessdemanding (Schneider and Shiffrin, 1977;Cole and Schneider, 2007) tasks such as listening to a story (as in the language task).…”

“…For example, changes in FC patterns have been used to predict how well a participant learns (Bassett et al, 2011). As another example, patterns in FC strength between the frontoparietal control network (FPN) and the rest of the brain have been used to decode which tasks were being performed (Cole et al, 2013b). FC data can also be used to decode various stimulus-response mappings and cognitive states (Heinzle et al, 2012;Shirer et al, 2012).…”

Using game authoring platforms to develop screen-based simulated functional assessments in persons with executive dysfunction following traumatic brain injury

“…EDF is extremely common in neurological and neuropsychiatric pathologies with either severe or mild impairments, such as brain tumors [22], traumatic brain injury (TBI) [23], stroke [24], multiple sclerosis [25], Gilles de la Tourette syndrome [26], schizophrenia [27], obsessive-compulsive disorder [28], and neurological patients with frontal pathology [29][30][31][32][33].…”