Quantifying Contextual Information For Cognitive Control

The electrophysiology of sequential adjustments of dual-task order coordination

Performing two tasks simultaneously involves the coordination of their processing. This task coordination is particularly required in dual-task situations with varying task orders. When task order switches between subsequent trials, task order coordination leads to task order switch costs in comparison with order repetitions. However, it is open, whether task order coordination is exclusively controlled by the relation of the task orders of the current and the previous trials, or whether additional conditions such as task order before the previous trial leads to a behavioral and neural adjustment of task order coordination. To answer this question, we reanalyzed the data of two previously published experiments with order-cued dual-task paradigms. We did so with regard to whether task order switch costs and the EEG component order-switch positivity in the current dual-task trial would be modulated by order switches vs. repetitions in the previous trial (Trial N-1). In Experiment 1, we found a modulation of the task order switch costs in RTs and response reversals; these costs were reduced after an order switch compared with order repetitions in Trial N-1. In Experiment 2, there were no effects on the task order switch costs in the behavioral data. Nonetheless, we found the order-switch positivity to be strongly modulated by the order transition of the previous trial in both experiments. The order-switch positivity was substantially reduced if the previous trial was an order switch (compared to an order repetition) by itself. This implies that order coordination of dual tasks is adjusted in a gradual way depending on trial's history.

Motivational context and neurocomputation of stop expectation moderate early attention responses supporting proactive inhibitory control

Alterations in attention to cues signaling the need for inhibitory control play a significant role in a wide range of psychopathology. However, the degree to which motivational and attentional factors shape the neurocomputations of proactive inhibitory control remains poorly understood. The present study investigated how variation in monetary incentive valence and stake modulate the neurocomputational signatures of proactive inhibitory control. Adults (N = 46) completed a Stop-Signal Task (SST) with concurrent EEG recording under four conditions associated with stop performance feedback: low and high punishment (following unsuccessful stops) and low and high reward (following successful stops). A Bayesian learning model was used to infer individual's probabilistic expectations of the need to stop on each trial: P(stop). Linear mixed effects models were used to examine whether interactions between motivational valence, stake, and P(stop) parameters predicted P1 and N1 attention-related event-related potentials (ERPs) time-locked to the go-onset stimulus. We found that P1 amplitudes increased at higher levels of P(stop) in punished but not rewarded conditions, although P1 amplitude differences between punished and rewarded blocks were maximal on trials when the need to inhibit was least expected. N1 amplitudes were positively related to P(stop) in the high punishment condition (low N1 amplitude), but negatively related to P(stop) in the high reward condition (high N1 amplitude). Critically, high P(stop)-related N1 amplitude to the go-stimulus predicted behavioral stop success during the high reward block, providing evidence for the role of motivationally relevant context and inhibitory control expectations in modulating the proactive allocation of attentional resources that affect inhibitory control. These findings provide novel insights into the neurocomputational mechanisms underlying proactive inhibitory control under valence-dependent motivational contexts, setting the stage for developing motivation-based interventions that boost inhibitory control.

Cognitive effort and active inference

This paper aims to integrate some key constructs in the cognitive neuroscience of cognitive control and executive function by formalising the notion of cognitive (or mental) effort in terms of active inference. To do so, we call upon a task used in neuropsychology to assess impulse inhibition-a Stroop task. In this task, participants must suppress the impulse to read a colour word and instead report the colour of the text of the word. The Stroop task is characteristically effortful, and we unpack a theory of mental effort in which, to perform this task accurately, participants must overcome prior beliefs about how they would normally act. However, our interest here is not in overt action, but in covert (mental) action. Mental actions change our beliefs but have no (direct) effect on the outside world-much like deploying covert attention. This account of effort as mental action lets us generate multimodal (choice, reaction time, and electrophysiological) data of the sort we might expect from a human participant engaging in this task. We analyse how parameters determining cognitive effort influence simulated responses and demonstrate that-when provided only with performance data-these parameters can be recovered, provided they are within a certain range.

Sensorimotor inhibition during emotional processing

Visual processing of emotional stimuli has been shown to engage complex cortical and subcortical networks, but it is still unclear how it affects sensorimotor integration processes. To fill this gap, here, we used a TMS protocol named short-latency afferent inhibition (SAI), capturing sensorimotor interactions, while healthy participants were observing emotional body language (EBL) and International Affective Picture System (IAPS) stimuli. Participants were presented with emotional (fear- and happiness-related) or non-emotional (neutral) EBL and IAPS stimuli while SAI was tested at 120 ms and 300 ms after pictures presentation. At the earlier time point (120 ms), we found that fear-related EBL and IAPS stimuli selectively enhanced SAI as indexed by the greater inhibitory effect of somatosensory afferents on motor excitability. Larger early SAI enhancement was associated with lower scores at the Behavioural Inhibition Scale (BIS). At the later time point (300 ms), we found a generalized SAI decrease for all kind of stimuli (fear, happiness or neutral). Because the SAI index reflects integrative activity of cholinergic sensorimotor circuits, our findings suggest greater sensitivity of such circuits during early (120 ms) processing of threat-related information. Moreover, the correlation with BIS score may suggest increased attention and sensory vigilance in participants with greater anxiety-related dispositions. In conclusion, the results of this study show that sensorimotor inhibition is rapidly enhanced while processing threatening stimuli and that SAI protocol might be a valuable option in evaluating emotional-motor interactions in physiological and pathological conditions.

Reconfiguration of response rule is more difficult than that of task goal: Behavior and electrophysiological evidence

Previous studies have investigated the neural mechanisms underlying cognitive control by using the task-switching paradigm, but differentiation from response rule switching (RR-switch) remains poorly explored. In this study, a partial voluntary task-switching (VTS) paradigm was used to explore the electrophysiological differences between task switching (T-switch) and RR-switching. Participants were sequentially presented with Arabic numerals colored red or green. If the color in the current trial was the same as that in the previous trial, the participants had to perform the same task following the same response rule. Otherwise, they had to voluntarily switch tasks (e.g., from parity task to magnitude task) or switch response rules (e.g., from "pressing F for odd and J for even number' to 'pressing J for odd and F for even number"). The behavioral results indicated that RR-switch was infrequently selected, and the performance was less efficient than that of the T-switch. Event-related potential results showed that both T- and RR-switches elicited a larger switch-positivity in the P2 and P3 time windows than that in the repeat condition. Switch-positivity was larger for RR-switch than for T-switch over the frontal sites, suggesting that more attention and cognitive resources were required to update information for the RR-switch than for the T-switch. These findings suggest that in the VTS, the hierarchical relationship between task goals and response rules is relatively loose, resulting in the neural disassociation of task reconfiguration and response change.

A Predictive Processing Account of Card Sorting: Fast Proactive and Reactive Frontoparietal Cortical Dynamics during Inference and Learning of Perceptual Categories

For decades, a common assumption in cognitive neuroscience has been that prefrontal executive control is mainly engaged during target detection [Posner, M. I., & Petersen, S. E. The attention system of the human brain. Annual Review of Neuroscience, 13, 25-42, 1990]. More recently, predictive processing theories of frontal function under the Bayesian brain hypothesis emphasize a key role of proactive control for anticipatory action selection (i.e., planning as active inference). Here, we review evidence of fast and widespread EEG and magnetoencephalographic fronto-temporo-parietal cortical activations elicited by feedback cues and target cards in the Wisconsin Card Sorting Test. This evidence is best interpreted when considering negative and positive feedback as predictive cues (i.e., sensory outcomes) for proactively updating beliefs about unknown perceptual categories. Such predictive cues inform posterior beliefs about high-level hidden categories governing subsequent response selection at target onset. Quite remarkably, these new views concur with Don Stuss' early findings concerning two broad classes of P300 cortical responses evoked by feedback cues and target cards in a computerized Wisconsin Card Sorting Test analogue. Stuss' discussion of those P300 responses-in terms of the resolution of uncertainty about response (policy) selection as well as the participants' expectancies for future perceptual or motor activities and their timing-was prescient of current predictive processing and active (Bayesian) inference theories. From these new premises, a domain-general frontoparietal cortical network is rapidly engaged during two temporarily distinct stages of inference and learning of perceptual categories that underwrite goal-directed card sorting behavior, and they each engage prefrontal executive functions in fundamentally distinct ways.

Prefrontal Computation as Active Inference

The prefrontal cortex is vital for a range of cognitive processes, including working memory, attention, and decision-making. Notably, its absence impairs the performance of tasks requiring the maintenance of information through a delay period. In this paper, we formulate a rodent task—which requires maintenance of delay-period activity—as a Markov decision process and treat optimal task performance as an (active) inference problem. We simulate the behavior of a Bayes optimal mouse presented with 1 of 2 cues that instructs the selection of concurrent visual and auditory targets on a trial-by-trial basis. Formulating inference as message passing, we reproduce features of neuronal coupling within and between prefrontal regions engaged by this task. We focus on the micro-circuitry that underwrites delay-period activity and relate it to functional specialization within the prefrontal cortex in primates. Finally, we simulate the electrophysiological correlates of inference and demonstrate the consequences of lesions to each part of our in silico prefrontal cortex. In brief, this formulation suggests that recurrent excitatory connections—which support persistent neuronal activity—encode beliefs about transition probabilities over time. We argue that attentional modulation can be understood as the contextualization of sensory input by these persistent beliefs.

Electroencephalographic correlates of temporal Bayesian belief updating and surprise

The brain predicts the timing of forthcoming events to optimize responses to them. Temporal predictions have been formalized in terms of the hazard function, which integrates prior beliefs on the likely timing of stimulus occurrence with information conveyed by the passage of time. However, how the human brain updates prior temporal beliefs is still elusive. Here we investigated electroencephalographic (EEG) signatures associated with Bayes-optimal updating of temporal beliefs. Given that updating usually occurs in response to surprising events, we sought to disentangle EEG correlates of updating from those associated with surprise. Twenty-six participants performed a temporal foreperiod task, which comprised a subset of surprising events not eliciting updating. EEG data were analyzed through a regression-based massive approach in the electrode and source space. Distinct late positive, centro-parietally distributed, event-related potentials (ERPs) were associated with surprise and belief updating in the electrode space. While surprise modulated the commonly observed P3b, updating was associated with a later and more sustained P3b-like waveform deflection. Results from source analyses revealed that neural encoding of surprise comprises neural activity in the cingulo-opercular network (CON) and parietal regions. These data provide evidence that temporal predictions are computed in a Bayesian manner, and that this is reflected in P3 modulations, akin to other cognitive domains. Overall, our study revealed that analyzing P3 modulations provides an important window into the Bayesian brain. Data and scripts are shared on OSF: https://osf.io/ckqa5/.

Training and Transfer of Cue Updating in Older Adults Is Limited: Evidence From Behavioral and Neuronal Data

Cognitive control processes, such as updating task-relevant information while switching between multiple tasks, are substantially impaired in older adults. However, it has also been shown that these cognitive control processes can be improved by training interventions, e.g., by training in task switching. Here, we applied an event-related potential (ERP) approach to identify whether a cognitive training improves task-preparatory processes such as updating of relevant task goals. To do so, we applied a pretest-training-posttest design with eight training sessions. Two groups of older adults were either trained in task switching (treatment group) or in performing single tasks (control group) and we compared their performance to a group of untrained younger adults. To foster cue updating in the treatment group, we applied a cue-based switching task in which the two task cues were randomly selected prior to target presentation so that participants had time to prepare for the upcoming task. In contrast, the control group also received task cues but those were redundant as only one task had to be performed. We also examined whether training in cue updating during task switching can be transferred to a similar cognitive control task measuring updating of context information, namely a modified version of the AX-Continuous Performance Task (AX-CPT). The results revealed training-specific improvements in task switching, that is, a larger improvement in blocks requiring switching in comparison to single tasks at the behavioral level. In addition, training specific-effects were also found at the neuronal level. Older adults trained in cue updating while switching showed a reduction in mixing costs in the cue-related P3, indicating an improvement in preparatory updating processes. Additionally, P3 topography changed with training from a very broad to a parietally focused scalp distribution similar to the one found in younger adults. However, we did not obtain training-specific improvements in context updating in the AX-CPT neither at the behavioral level nor at the neuronal level. Results are discussed in the context of the ongoing debate on whether transfer of cognitive training improvements is possible.

Fast fronto-parietal cortical dynamics of conflict detection and context updating in a flanker task

Recent research has found that the traditional target P3 consists of a family of P3-like positivities that can be functionally and topographically dissociated from one another. The current study examined target N2 and P3-like subcomponents indexing conflict detection and context updating at low- and high-order levels in the neural hierarchy during cognitive control. Electroencephalographic signals were recorded from 45 young adults while they completed a hybrid go/nogo flanker task, and Residue Iteration Decomposition (RIDE) was applied to functionally dissociate these peaks. Analyses showed a stimulus-locked frontal N2 revealing early detection and fast perceptual categorization of nogo, congruent and incongruent trials, resulting in frontal P3-like activity elicited by nogo trials in the latency-variable RIDE cluster, and by incongruent trials in the response-locked cluster. The congruent trials did not elicit frontal P3-like activity. These findings suggest that behavioral incongruency effects are related to intermediate and later stages of motor response re-programming.

Inferring What to Do (And What Not to)

In recent years, the "planning as inference" paradigm has become central to the study of behaviour. The advance offered by this is the formalisation of motivation as a prior belief about "how I am going to act". This paper provides an overview of the factors that contribute to this prior. These are rooted in optimal experimental design, information theory, and statistical decision making. We unpack how these factors imply a functional architecture for motivated behaviour. This raises an important question: how can we put this architecture to work in the service of understanding observed neurobiological structure? To answer this question, we draw from established techniques in experimental studies of behaviour. Typically, these examine the influence of perturbations of the nervous system-which include pathological insults or optogenetic manipulations-to see their influence on behaviour. Here, we argue that the message passing that emerges from inferring what to do can be similarly perturbed. If a given perturbation elicits the same behaviours as a focal brain lesion, this provides a functional interpretation of empirical findings and an anatomical grounding for theoretical results. We highlight examples of this approach that influence different sorts of goal-directed behaviour, active learning, and decision making. Finally, we summarise their implications for the neuroanatomy of inferring what to do (and what not to).