Numbers in action during cognitive flexibility – A neurophysiological approach on numerical operations underlying task switching

Petruo, Vanessa A.; Mückschel, Moritz; Beste, Christian

doi:10.1016/j.cortex.2019.03.017

Cited by 9 publications

(11 citation statements)

References 86 publications

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“…Further, it is not possible from the results of Experiment 1 alone to rule out the influence of taskspecific factors in producing the decline in switch rate rather than a more general process such as fatigue or effort avoidance that would occur in other voluntary task switching paradigms. For example, while the number Stroop has been used previously in task switching literature (Orr et al, 2012(Orr et al, , 2019Orr & Banich, 2014;Petruo et al, 2019), it introduces more conflict than other task switching paradigms due to stimulus congruency effects and the use of bivalent stimuli; the resulting demands on cognitive load might affect the rate of fatigue or the rate at which effort expenditure is reduced. Therefore, generalizing the results of Experiment 1 to a different voluntary task switching paradigm which did not include these additional sources of conflict would be fruitful in helping to rule out the possibility of task-specific factors as an underlying cause of switch rate declines.…”

Section: Discussionmentioning

confidence: 99%

Dynamic cognitive flexibility

Imburgio¹,

Orr²

2021

Preprint

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Cognitive flexibility, or the ability to flexibly switch between different task sets, is often operationalized using performance on voluntary task switching (VTS) paradigms. In VTS paradigms, performance is commonly measured by examining reaction time, accuracy, the effects of switching tasks on reaction time and accuracy, and the rate at which participants choose to switch tasks. Previous literature has frequently examined these measures in terms of overall task averages. Instead, the current work examines whether these measures change during task performance, as well as the degree to which individual differences in these changes might inform individual differences in external measures. A series of three experiments, two of which utilized publicly available datasets from previous publications, examined changes in these measures throughout the performance of different VTS paradigms administered by different labs. In the first two experiments, significant group-level declines in switch rates were present, consistent with increased effort avoidance and early fatigue effects. In the third experiment, no such decline was present at a group level; however, subject-level changes in switch rates were related to scores on BIS/BAS subscales, while subject average switch rates were not. The current work suggests that examining changes in switch rates throughout a task might provide valuable information not captured by average switch rates that future VTS studies might wish to explore. Future work should attempt to clarify the conditions in which group-level declines in switch rate can be produced as well as which cognitive mechanisms might underlie these declines.

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Section: Discussionmentioning

confidence: 99%

Dynamic cognitive flexibility

Imburgio¹,

Orr²

2021

Preprint

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“…When a person suddenly appears in front of the car, in most cases, the reaction is faster in the latter situation than the former. The current study was interested in the context effect on individual's cognitive flexibility, which is one of the core components of executive function (Crone & Steinbeis, 2017; Deak & Wiseheart, 2015; Diamond, 2013; Jurado & Rosselli, 2007; Petruo et al., 2019).…”

Section: Introductionmentioning

confidence: 99%

More change in task repetition, less cost in task switching: Behavioral and event‐related potential evidence

Zhuo

Zhu

Cao

et al. 2021

Eur J of Neuroscience

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Previous studies have shown that the probability of task switching can vary the level of cognitive control and modulate the size of switch costs. However, it is unclear whether switch costs would be affected by a task‐repetition context formed by varying the degree of response (and task‐relevant stimulus property) change within the task repetition sequences while the probability of task switching remains constant. In the present study, participants were presented with a string of digits (e.g., ②②②). Basing on stimulus color, they were required to indicate either the presented digit, or the number of presented digits. Before task switching, stimulus and response in consecutive task‐repeat trials varied more or less frequently. Behavioral results showed that the frequent‐change context elicited smaller switch costs than the rare‐change context. Event‐related potential (ERP) results indicated that: (1) the frequent‐change context evoked greater fronto‐central N2 amplitudes for both task‐repeat and task‐switch trials, implying that cognitive control increased due to the variation of stimulus and response associations; (2) for the task switch trials, smaller P300 amplitudes were evoked in the frequent‐change context than the rare‐change context, reflecting the promoted task‐set reconfiguration. These findings suggest that, the more change in stimulus and response during task repetition, the higher the overall level of cognitive control and the higher efficiency of task‐switching.

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“…We describe behavioral and MVPA results obtained from an experiment that required cognitive flexibility. Participants had to perform a task switching ( Gajewski et al., 2011 ; Petruo et al., 2018 , 2019 ; Wolff et al., 2016 ), which consists of two different blocks, a cued and a memory-based block. In both blocks, three task rules must be applied interchangeably.…”

Section: Resultsmentioning

confidence: 99%

“…Since the C-cluster likely reflects stimulus-response translation (response selection) processes ( Ouyang et al., 2015 , 2017 ; Verleger et al., 2014 ) the source localization findings are also in line with a theoretical proposition derived from imaging data that (inferior) parietal regions are central for mechanisms updating internal task sets during response selection ( Geng and Vossel, 2013 ). Moreover, other evidence shows that inferior and posterior parietal cortical regions are involved in task switching ( Armbruster et al., 2012 ; Cooper et al., 2016 ; Kubanek and Snyder, 2015 ; Liu et al., 2015 ; Petruo et al., 2019 ; Philipp et al., 2013 ; Vallesi et al., 2015 ; Yin et al., 2015 ; Zhang et al., 2016a , 2016b ). Since response selection processes are a relevant function of medial frontal areas ( Ridderinkhof et al., 2004 ; Rushworth et al., 2004 , 2005 ; Shenhav et al., 2013 ), that finding is reasonable.…”

Section: Discussionmentioning

confidence: 99%

“…How could variability differences between classes lead to below-chance decoding? During the task, it is likely, that participants maintained the order of task rules by repeating them internally ( Petruo et al., 2018 , 2019 ). However, with more practice, the active maintenance of the order is not necessary any more, and more automatized processes might guide the response preparation.…”

Section: Discussionmentioning

confidence: 99%

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Multi-level decoding of task sets in neurophysiological data during cognitive flexibility

et al. 2021

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Summary Cognitive flexibility is essential to achieve higher level goals. Cognitive theories assume that the activation/deactivation of goals and task rules is central to understand cognitive flexibility. However, how this activation/deactivation dynamic is implemented on a neurophysiological level is unclear. Using EEG-based multivariate pattern analysis (MVPA) methods, we show that activation of relevant information occurs parallel in time at multiple levels in the neurophysiological signal containing aspects of stimulus-related processing, response selection, and motor response execution, and relates to different brain regions. The intensity with which task sets are activated and processed dynamically decreases and increases. The temporal stability of these activations could, however, hardly explain behavioral performance. Instead, task set deactivation processes associated with left orbitofrontal regions and inferior parietal regions selectively acting on motor response task sets are relevant. The study shows how propositions from cognitive theories stressing the importance task set activation/deactivation during cognitive flexibility are implemented on a neurophysiological level.

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Numbers in action during cognitive flexibility – A neurophysiological approach on numerical operations underlying task switching

Cited by 9 publications

References 86 publications

Dynamic cognitive flexibility

Dynamic cognitive flexibility

More change in task repetition, less cost in task switching: Behavioral and event‐related potential evidence

Multi-level decoding of task sets in neurophysiological data during cognitive flexibility

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