EXPRESS: Using Relative-Speed-of-Processing to Explain the Shielding Function of Task Rules

In choice reaction tests, applying task rules instead of responding associatively can help participants shield against interference from distractors. However, the mechanism of such shielding functions remains unclear. Through four experiments, we show how the shielding function can be explained by the Relative-Speed-of-Processing theory. Experiment 1A demonstrated that applying task rules can reduce the relative processing advantage of the distractor by facilitating the target processing speed, thereby eliminating the interference effect. In Experiments 1B, and 1C, we manipulated the relative processing advantage between targets and distractors by adjusting the temporal sequence of the presence of the targets and distractors: stimuli appearing first would gain more relative processing advantage. The results showed that when the relative processing advantage of a distractor was large enough, applying task rules cannot help participants shield against the interference. Contrarily, when the relative processing advantage of the distractor was small, even without applying task rules, participants did not experience the interference. In Experiment 2, we directly manipulated the processing speed of the targets and the distractor, so that participants who responded associatively would facilitate target processing speed, but participants who applied task rules would not. Contrary to previous studies but in line with our prediction, in Experiment 2, only participants who applied task rules had interference effects. Our results suggested that applying the task rule might not help us shield against the interference directly. Instead, applying task rules improves target-processing speed, which in turn reduces the relative processing advantage of the distractor and eliminates the interference.

Transfer of learned cognitive flexibility to novel stimuli and task sets

Adaptive behavior requires learning about the structure of the environment to derive optimal action policies, and previous studies have documented transfer of such structural knowledge to bias choices in new environments. Here, we asked whether people could also acquire and transfer more abstract knowledge across different task environments, in particular, expectations about demands on cognitive control. Over three experiments, participants performed a probabilistic card-sorting task in environments of either a low or high volatility of task rule changes (requiring low or high cognitive flexibility) before transitioning to a medium-volatility environment. Using reinforcement learning modeling, we consistently found that previous exposure to high task rule volatility led to faster adaptation to rule changes in the subsequent transfer phase. This transfer of expectations about demands on cognitive flexibility was both task- (Experiment 2) and stimulus- (Experiment 3) independent, thus demonstrating the formation and generalization of environmental structure knowledge to guide cognitive control.

Using the Relative-Speed-of-Processing to Explain the Shielding Function of Task Rules

In choice reaction tests, applying task rules instead of responding associatively can help participants shield against interference from distractors. However, the mechanism of such shielding functions of task rule remains unclear. In four experiments, we showed that the shielding function can be explained by the Relative-Speed-of-Processing theory. Experiment 1A demonstrated that applying task rules can reduce the relative processing advantage of the distractor by facilitating the target processing speed; therefore, eliminate the interference effect. In Experiment 1B, and 1C, we manipulated the relative processing advantage between targets and distractors by adjusting the temporal sequence of the presence of the targets and distractors: stimuli appeared first would gain more relative processing advantage. The results showed that when the relative processing advantage of a distractor was large enough, applying task rules cannot help participants shield against the interference. In contrast, when the relative processing advantage of the distractor was small, even without applying task rules, participants were not interfered by the distractor. In Experiment 2, we directly manipulated the processing speed of the targets and the distractor, so that participants who responded associatively would facilitate target processing speed, but participants who applied task rule would not. Contrary to previous studies but in line with our prediction, in Experiment 2, only participants who applied task rule had interference effects. Our results suggested that applying the task rule might not help us shield against the interference directly. Instead, applying task rules facilitate the target processing speed which reduces the relative processing advantage of the distractor and eliminates the interference.

A cortical circuit mechanism for coding and updating task structural knowledge in inference-based decision-making

Making decisions based on knowledge about causal environmental structures is a hallmark of higher cognition in mammalian brains. Despite mounting work in psychological and cognitive sciences, how the brain implements knowledge-based decision-making at neuronal circuit level remains a terra incognita. Here we established an inference-based auditory categorization task, where mice performed within-session re-categorization of stimuli by inferring the changing task rules. Using a belief-state reinforcement learning (BS-RL) model, we quantified the hidden variable associated with task knowledge. Using simultaneous two-photon population imaging and projection-specific optogenetics, we found that a subpopulation of auditory cortex (ACx) neurons encoded the hidden task-rule variable, which depended on the feedback input from orbitofrontal cortex (OFC). Chemogenetic silencing of the OFC-ACx projection specifically disrupted re-categorization performance. Finally, imaging from OFC axons within ACx revealed task state-related value signals in line with the modeled updating mechanism. Our results provide a cortical circuit mechanism underlying inference-based decision-making.

Task rule and choice are reflected by layer-specific processing in rodent auditory cortical microcircuits

The primary auditory cortex (A1) is an essential, integrative node that encodes the behavioral relevance of acoustic stimuli, predictions, and auditory-guided decision-making. However, the realization of this integration with respect to the cortical microcircuitry is not well understood. Here, we characterize layer-specific, spatiotemporal synaptic population activity with chronic, laminar current source density analysis in Mongolian gerbils (Meriones unguiculatus) trained in an auditory decision-making Go/NoGo shuttle-box task. We demonstrate that not only sensory but also task- and choice-related information is represented in the mesoscopic neuronal population code of A1. Based on generalized linear-mixed effect models we found a layer-specific and multiplexed representation of the task rule, action selection, and the animal’s behavioral options as accumulating evidence in preparation of correct choices. The findings expand our understanding of how individual layers contribute to the integrative circuit in the sensory cortex in order to code task-relevant information and guide sensory-based decision-making.

Reward boosts neural coding of task rules to optimise cognitive flexibility

Cognitive flexibility is critical for intelligent behaviour. However, its execution is effortful and often suboptimal. Recent work indicates that flexible behaviour can be improved by the prospect of reward, which suggests that rewards optimise flexible control processes. Here we investigated how different reward prospects influence neural encoding of task rule information to optimise cognitive flexibility. We applied representational similarity analysis (RSA) to human electroencephalograms, recorded while female and male participants performed a rule-guided decision-making task. During the task, the prospect of reward varied from trial to trial. Participants made faster, more accurate judgements on high reward trials. Critically, high reward boosted neural coding of the active task rule and the extent of this increase was associated with improvements in task performance. Additionally, the effect of high reward on task rule coding was most pronounced on switch trials, where rules were updated relative to the previous trial. These results suggest that reward prospect can promote cognitive performance by strengthening neural coding of task rule information, helping to improve cognitive flexibility during complex behaviour.Significance StatementThe importance of motivation is evident in the ubiquity with which reward prospect guides adaptive behaviour and the striking number of neurological conditions associated with motivational impairments. In this study, we investigated how dynamic changes in motivation, as manipulated through reward, shape neural coding for task rules during a flexible decision-making task. The results of this work suggest that motivation to obtain reward modulates encoding of task rules needed for flexible behaviour. The extent to which reward increased task rule coding also tracked improvements in behavioural performance under high reward conditions. These findings help inform how motivation shapes neural processing in the healthy human brain.

Cognitive task information is transferred between brain regions via resting-state network topology

Resting-state network connectivity has been associated with a variety of cognitive abilities, yet it remains unclear how these connectivity properties might contribute to the neurocognitive computations underlying these abilities. We developed a new approach – information transfer mapping – to test the hypothesis that resting-state functional network topology describes the computational mappings between brain regions that carry cognitive task information. Here we report that the transfer of diverse, task-rule information in distributed brain regions can be predicted based on estimated activity flow through resting-state network connections. Further, we find that these task-rule information transfers are coordinated by global hub regions within cognitive control networks. Activity flow over resting-state connections thus provides a large-scale network mechanism for cognitive task information transfer and global information coordination in the human brain, demonstrating the cognitive relevance of resting-state network topology.

Functional Specialization within Macaque Dorsolateral Prefrontal Cortex for the Maintenance of Task Rules and Cognitive Control

The abilities of switching between and maintaining task rules are fundamental aspects of goal-oriented behavior. The PFC is thought to implement the cognitive processes underling such rule-based behavior, but the specific contributions of the several cytoarchitecturally distinct subfields of PFC remain poorly understood. Here, we used bilateral cryogenic deactivation to investigate the relative contributions of two regions of the dorsolateral PFC (dlPFC)—the inferior dlPFC (idlPFC) area, consisting of the cortex lining the caudal principal sulcus, and the dorsally adjacent superior dlPFC (sdlPFC)—to different aspects of rule-based behavior. Macaque monkeys performed two variants of a task that required them to alternate unpredictably between eye movements toward (prosaccade) or away from (antisaccade) a visual stimulus. In one version of the task, the current rule was overtly cued. In the second, the task rule was uncued, and successful performance required the animals to detect rule changes on the basis of reward outcome and subsequently maintain the current task rule within working memory. Deactivation of the idlPFC impaired the monkeys' ability to perform pro- and antisaccades in the uncued task only. In contrast, deactivation of the sdlPFC had no effect on performance in either task. Combined deactivation of idlPFC and sdlPFC impaired performance on antisaccade, but not prosaccade, trials in both task variants. These results suggest that the idlPFC is required for mnemonic processes involved in maintenance of task rules, whereas both idlPFC and sdlPFC together are necessary for the deployment of the cognitive control required to perform antisaccades. Together, these data support the concept of a functional specialization of subregions within the dlPFC for rule-guided behavior.