Assessing executive functions in free-roaming 2- to 3-year-olds.

Introduction: Core aspects of executive functions (EFs) are known to be related to academic skills such as literacy and numeracy. However, school outcomes may also be related to higher-level functions such as planning. Nevertheless, few studies have considered assessing natural manifestations of higher-level EFs in children who are on the cusp of entering formal schooling. One reason for this is the difficulty of obtaining ecologically valid measures of EFs in preschool-aged children. Method: We describe a novel task - building a striped Duplo tower subject to two constraints - designed to assess planning in real-world multi-action situation. Children were instructed to build a tower to a certain height by alternating between two different colors of blocks. Results: Performance on one of the constraints in this task was found to vary with age. Importantly, distinct components of multiple constraints planning performance predicted laboratory-based measures of inhibitory control and working memory efficacy. Discussion: Thus, this task provides a simple, cheap and effective way of assessing executive function in toddlers through the observation of natural behavior. It also opens up possibilities to investigate the neurodevelopment of EF in the real world.

Left, right, left, right: 24-36-months-olds' planning and execution of simple alternating actions.

This study investigated toddlers' ability to control simple alternating pattern actions, and how this relates to motor competence and executive functions. 70 toddlers between 24 and 36 months of age were instructed to sort coins in an alternating pattern into two boxes; left, right, left, right etc. Executive functions and memory competence performance were assessed in additional small games. The results showed that the ability to plan and execute actions according to a simple extended alternating pattern improved over toddlerhood. Furthermore, working memory and motor competence scores were both independent predictors of the ability to plan and execute simple alternating actions. These findings underscore the fact that between 24 and 36 months of age is a period in which the ability to string together multiple actions in a sequence to achieve a distal goal is still developing.

Everyday Activities.

The ease with which humans usually perform everyday activities masks their inherit complexity. Tasks such as setting a table prior to a meal or preparing a hot beverage require the coordination of several cognitive abilities. At the same time, many everyday activities are simple enough to afford investigation in controlled lab settings. One main goal of this issue is to raise awareness of everyday activities as a topic and a field of study in its own right, which allows investigating (a) selected cognitive abilities with high ecological validity and (b) the interplay and integration of key cognitive abilities. To this end, this topic consists of eight papers that span different aspects of everyday activities, ranging from neuroscience through philosophical considerations and implications to lessons from robotics.

Science with Duplo: Multilevel goal management in preschoolers' toy house constructions.

Executing goal-directed action sequences is fundamental to our behavior. Planning and controlling these action sequences improves greatly over the preschool years. In this study, we examined preschoolers' ability to plan action sequences. A total of 69 3- to 5-year-olds were assessed on an action sequence planning task with a hierarchical goal structure and on several executive function tasks. Planning abilities improved with age. Improvements in inhibition were related to avoidance of actions irrelevant to the goal hierarchy. Updating skill appears to be associated with executing actions relevant to different subgoals. Using optical motion capture, we showed that children who followed the subgoals displayed less movement with their nonreaching hand within a subgoal. This effect was enhanced in children with better inhibitory skills, suggesting that such skills allow greater focus on executing the current subgoal. Thus, we provide evidence that structuring of subgoals in action sequence planning emerges during the preschool years and that improvements in performance in action sequence planning are related to executive functions.

Action Production and Event Perception as Routine Sequential Behaviors.

It is argued that event perception and routine sequential action production share a range of characteristics (e.g., similar levels of automaticity, the involvement of sequentially and hierarchically organized schemata, and the coupled operation of predictive and monitoring processes). With this in mind, and in an effort to develop a mechanistic account of event perception, we consider how an existing model of routine sequential action production might be applied in the domain of event perception. We focus the discussion on the multiple roles of prediction in the two domains, and we consider the implications of the application of the model of action production to event perception and for sequential processing more generally.

On Simulating Neural Damage in Connectionist Networks.

A key strength of connectionist modelling is its ability to simulate both intact cognition and the behavioural effects of neural damage. We survey the literature, showing that models have been damaged in a variety of ways, e.g. by removing connections, by adding noise to connection weights, by scaling weights, by removing units and by adding noise to unit activations. While these different implementations of damage have often been assumed to be behaviourally equivalent, some theorists have made aetiological claims that rest on nonequivalence. They suggest that related deficits with different aetiologies might be accounted for by different forms of damage within a single model. We present two case studies that explore the effects of different forms of damage in two influential connectionist models, each of which has been applied to explain neuropsychological deficits. Our results indicate that the effect of simulated damage can indeed be sensitive to the way in which damage is implemented, particularly when the environment comprises subsets of items that differ in their statistical properties, but such effects are sensitive to relatively subtle aspects of the model's training environment. We argue that, as a consequence, substantial methodological care is required if aetiological claims about simulated neural damage are to be justified, and conclude more generally that implementation assumptions, including those concerning simulated damage, must be fully explored when evaluating models of neurological deficits, both to avoid over-extending the explanatory power of specific implementations and to ensure that reported results are replicable. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s42113-020-00081-z) contains supplementary material, which is available to authorized users.

A neurally plausible schema-theoretic approach to modelling cognitive dysfunction and neurophysiological markers in Parkinson's disease.

The cognitive mechanisms underlying sequential action selection in routine or everyday activities may be understood in terms of competition within a hierarchically organised network of action schemas. We present a neurobiologically plausible elaboration of an existing schema-based cognitive model of action selection in which the basal ganglia implements an activation-based selection process that mediates between assumed cortical representations of rule-based schemas. More specifically, the model employs a network of basal ganglia units with computations performed by individual BG nuclei, embedded in a corticothalamic loop that disinhibits schemas according to the received feedback. We provide bridging assumptions for linking the operation of the model with ERP components that describe the error-related negativity (ERN) and the parietal switch positivity (PSP), and evaluate the model against behavioural and neural markers of performance of the Wisconsin Card Sorting Test by healthy control participants and Parkinson's Disease patients.

Multidisciplinary Flux and Multiple Research Traditions Within Cognitive Science.

Núñez et al. (2019) argue that cognitive science has failed either "to transition to a mature inter-disciplinary coherent field" (p. 782) or "to generate a successful [Lakatosian] research program" (p. 789). We argue that the former was never the intention of many early researchers within the field, while the latter is an inappropriate criterion by which to judge an entire discipline. However, we concur with Núñez et al. (2019) that the individual disciplinary balance within cognitive science has changed over time. Of particular concern is the fact that the use of computational methods appears to be on the wane.

Automatic imitation of multiple agents: A computational model.

There is accumulating evidence that the actions of others are represented in the motor system, leading to automatic imitation. However, whereas early work focused mainly on the effects of observing a single agent, recent studies indicate that the actions of multiple agents can be represented simultaneously. Yet, theorizing has lagged behind. The current study extends the dual-route model of automatic imitation to include multiple agents, and demonstrates, in five simulation studies, that the extended model is able to capture four critical multi-agent effects. Importantly, however, it was necessary to augment the model with a control mechanism regulating response inhibition based on the number of observed actions. Furthermore, additional simulation indicated that this mechanism could be driven by response conflict. Together, our results demonstrate how theories of automatic imitation can be extended from single- to multi-agent settings. As such, they constitute an important step towards a mechanistic understanding of social interaction beyond the dyad.

Set-shifting and place-keeping as separable control processes.

We present three experiments using a sequential binary choice task that explore the relationship between two proposed cognitive control functions: set-shifting and place-keeping (i.e., keeping track of one's place within a sequential task). The task involves switching from one stimulus-response mapping to another across trials, according to a predefined sequence and in the face of occasional brief interruptions. Response-stimulus interval, interruption length and interrupting task were varied. The robust finding across all experiments was that varying response-stimulus interval led to standard effects attributable to set-shifting, while varying interruption length led to standard effects attributable to place-keeping, but in no cases did the factors interact. We interpret the results as supporting the view that set-shifting and place-keeping are achieved by separable control processes and illustrate this interpretation with a computational model of performance on the task.

On the Relation Between Marr's Levels: A Response to Blokpoel (2017).

Blokpoel reminds us of the importance of consistency of function across Marr's levels, but we argue that the approach to ensuring consistency that he advocates-a strict relation through exact implementation of the higher level function at the lower level-is unnecessarily restrictive. We show that it forces overcomplication of the computational level (by requiring it to incorporate concerns from lower levels) and results in the sacrifice of the distinct responsibilities associated with each level. We propose an alternative, no less rigorous, potential characterization of the relation between levels.

Task inhibition, conflict, and the n-2 repetition cost: A combined computational and empirical approach.

Task inhibition (also known as backward inhibition) is an hypothesised form of cognitive inhibition evident in multi-task situations, with the role of facilitating switching between multiple, competing tasks. This article presents a novel cognitive computational model of a backward inhibition mechanism. By combining aspects of previous cognitive models in task switching and conflict monitoring, the model instantiates the theoretical proposal that backward inhibition is the direct result of conflict between multiple task representations. In a first simulation, we demonstrate that the model produces two effects widely observed in the empirical literature, specifically, reaction time costs for both (n-1) task switches and n-2 task repeats. Through a systematic search of parameter space, we demonstrate that these effects are a general property of the model's theoretical content, and not specific parameter settings. We further demonstrate that the model captures previously reported empirical effects of inter-trial interval on n-2 switch costs. A final simulation extends the paradigm of switching between tasks of asymmetric difficulty to three tasks, and generates novel predictions for n-2 repetition costs. Specifically, the model predicts that n-2 repetition costs associated with hard-easy-hard alternations are greater than for easy-hard-easy alternations. Finally, we report two behavioural experiments testing this hypothesis, with results consistent with the model predictions.

Preschool children's control of action outcomes.

Naturalistic goal-directed behaviours require the engagement and maintenance of appropriate levels of cognitive control over relatively extended intervals of time. In two experiments, we examined preschool children's abilities to maintain top-down control throughout the course of a sequential task. Both 3- and 5-year-olds demonstrated good abilities to access goals at the lowest level of the representational hierarchy. However, only 5-year-olds consistently aligned their response choices with goals at superordinate levels. These findings suggest that the ability to maintain top-down control and adjust behavioural responses according to goals at multiple levels of abstraction undergoes a marked improvement throughout the preschool period. Results are discussed in relation to current accounts of cognitive control and the monitoring of conflict in sequential action.

Deep-learning networks and the functional architecture of executive control.

Lake et al. underrate both the promise and the limitations of contemporary deep learning techniques. The promise lies in combining those techniques with broad multisensory training as experienced by infants and children. The limitations lie in the need for such systems to possess functional subsystems that generate, monitor, and switch goals and strategies in the absence of human intervention.

Set-shifting as a component process of goal-directed problem-solving.

In two experiments, we compared secondary task interference on Tower of London performance resulting from three different secondary tasks. The secondary tasks were designed to tap three different executive functions, namely set-shifting, memory monitoring and updating, and response inhibition. Previous work using individual differences methodology suggests that, all other things being equal, the response inhibition or memory tasks should result in the greatest interference. However, this was not found to be the case. Rather, in both experiments the set-shifting task resulted in significantly more interference on Tower of London performance than either of the other secondary tasks. Subsequent analyses suggest that the degree of interference could not be attributed to differences in secondary task difficulty. Results are interpreted in the light of related work which suggests that solving problems with non-transparent goal/subgoal structure requires flexible shifting between subgoals-a process that is held to be impaired by concurrent performance of a set-shifting task.

The planning and execution of natural sequential actions in the preschool years.

Preschool children's abilities to learn from observation has been the focus of considerable theoretical and empirical work. A wealth of developmental research suggests that young children reliably over-imitate modeled actions. Across two experiments, we asked whether a single misleading demonstration significantly impacts preschoolers' planning and execution of a familiar event sequence. In Experiment 1, we found that, despite sufficient task knowledge, 3- and 5-year-olds readily incorporated irrelevant modeled actions into their own performances. In Experiment 2, we found that when the underlying event structure was spatially cued, over-imitation was no longer apparent in preschooler's re-enactment of the sequence. These findings serve as evidence for a tight coupling between perceptual and conceptual processing systems in early action planning. Taken together, findings from both experiments suggest that over-imitation behaviour in these tasks results from a failure to evaluate the observed links between procedural components of the sequence in respect to the overarching goal of the task. These results further contrast with the existing developmental literature by suggesting that, in the context of familiar actions, over-imitation significantly decreases during the preschool period. Findings are discussed in the context of preschoolers' abilities to plan and execute sequential actions.

Beyond single-level accounts: the role of cognitive architectures in cognitive scientific explanation.

We consider approaches to explanation within the cognitive sciences that begin with Marr's computational level (e.g., purely Bayesian accounts of cognitive phenomena) or Marr's implementational level (e.g., reductionist accounts of cognitive phenomena based only on neural-level evidence) and argue that each is subject to fundamental limitations which impair their ability to provide adequate explanations of cognitive phenomena. For this reason, it is argued, explanation cannot proceed at either level without tight coupling to the algorithmic and representation level. Even at this level, however, we argue that additional constraints relating to the decomposition of the cognitive system into a set of interacting subfunctions (i.e., a cognitive architecture) are required. Integrated cognitive architectures that permit abstract specification of the functions of components and that make contact with the neural level provide a powerful bridge for linking the algorithmic and representational level to both the computational level and the implementational level.

Thirty Years After Marr's Vision: Levels of Analysis in Cognitive Science.

Thirty years after the publication of Marr's seminal book Vision (Marr, 1982) the papers in this topic consider the contemporary status of his influential conception of three distinct levels of analysis for information-processing systems, and in particular the role of the algorithmic and representational level with its cognitive-level concepts. This level has (either implicitly or explicitly) been downplayed or eliminated both by reductionist neuroscience approaches from below that seek to account for behavior from the implementation level and by Bayesian approaches from above that seek to account for behavior in purely computational-level terms.

An architecturally constrained model of random number generation and its application to modeling the effect of generation rate.

Random number generation (RNG) is a complex cognitive task for human subjects, requiring deliberative control to avoid production of habitual, stereotyped sequences. Under various manipulations (e.g., speeded responding, transcranial magnetic stimulation, or neurological damage) the performance of human subjects deteriorates, as reflected in a number of qualitatively distinct, dissociable biases. For example, the intrusion of stereotyped behavior (e.g., counting) increases at faster rates of generation. Theoretical accounts of the task postulate that it requires the integrated operation of multiple, computationally heterogeneous cognitive control ("executive") processes. We present a computational model of RNG, within the framework of a novel, neuropsychologically-inspired cognitive architecture, ESPro. Manipulating the rate of sequence generation in the model reproduced a number of key effects observed in empirical studies, including increasing sequence stereotypy at faster rates. Within the model, this was due to time limitations on the interaction of supervisory control processes, namely, task setting, proposal of responses, monitoring, and response inhibition. The model thus supports the fractionation of executive function into multiple, computationally heterogeneous processes.

Artificially created stimuli produced by a genetic algorithm using a saliency model as its fitness function show that Inattentional Blindness modulates performance in a pop-out visual search paradigm.

Salient stimuli are more readily detected than less salient stimuli, and individual differences in such detection may be relevant to why some people fail to notice an unexpected stimulus that appears in their visual field whereas others do notice it. This failure to notice unexpected stimuli is termed 'Inattentional Blindness' and is more likely to occur when we are engaged in a resource-consuming task. A genetic algorithm is described in which artificial stimuli are created using a saliency model as its fitness function. These generated stimuli, which vary in their saliency level, are used in two studies that implement a pop-out visual search task to evaluate the power of the model to discriminate the performance of people who were and were not Inattentionally Blind (IB). In one study the number of orientational filters in the model was increased to check if discriminatory power and the saliency estimation for low-level images could be improved. Results show that the performance of the model does improve when additional filters are included, leading to the conclusion that low-level images may require a higher number of orientational filters for the model to better predict participants' performance. In both studies we found that given the same target patch image (i.e. same saliency value) IB individuals take longer to identify a target compared to non-IB individuals. This suggests that IB individuals require a higher level of saliency for low-level visual features in order to identify target patches.