Mental comparison

Grune, Kerstin; Mecklinger, Axel; Ullsperger, Peter

doi:10.1097/00001756-199309000-00016

Cited by 23 publications

(4 citation statements)

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“…However, notation effects on the N1 latency and amplitude were considerable, supporting the idea that N1 effects were related to differences in sensory processing (Libertus et al, 2007). Additionally, similar to previous results (Grune et al, 1993;Dehaene, 1996;Schwarz and Heinze, 1998;Jiang et al, 2010), our study showed DEs on the occipital-parietal P300 component in the digit task, which was characterized with more positive amplitudes and shorter latencies for far conditions than for close conditions. As close conditions are harder and need more effort than far conditions, our results revealed that larger amplitudes and shorter latencies of P300 were corresponding to easier comparison problems (with far distance).…”

Section: Discussionsupporting

confidence: 91%

Numerical magnitude processing in abacus-trained children with superior mathematical ability: an EEG study

Huang

Yao

et al. 2015

J. Zhejiang Univ. Sci. B

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Distance effect has been regarded as the best established marker of basic numerical magnitude processes and is related to individual mathematical abilities. A larger behavioral distance effect is suggested to be concomitant with lower mathematical achievement in children. However, the relationship between distance effect and superior mathematical abilities is unclear. One could get superior mathematical abilities by acquiring the skill of abacus-based mental calculation (AMC), which can be used to solve calculation problems with exceptional speed and high accuracy. In the current study, we explore the relationship between distance effect and superior mathematical abilities by examining whether and how the AMC training modifies numerical magnitude processing. Thus, mathematical competencies were tested in 18 abacus-trained children (who accepted the AMC training) and 18 non-trained children. Electroencephalography (EEG) waveforms were recorded when these children executed numerical comparison tasks in both Arabic digit and dot array forms. We found that: (a) the abacus-trained group had superior mathematical abilities than their peers; (b) distance effects were found both in behavioral results and on EEG waveforms; (c) the distance effect size of the average amplitude on the late negative-going component was different between groups in the digit task, with a larger effect size for abacus-trained children; (d) both the behavioral and EEG distance effects were modulated by the notation. These results revealed that the neural substrates of magnitude processing were modified by AMC training, and suggested that the mechanism of the representation of numerical magnitude for children with superior mathematical abilities was different from their peers. In addition, the results provide evidence for a view of non-abstract numerical representation.

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Section: Discussionsupporting

confidence: 91%

Numerical magnitude processing in abacus-trained children with superior mathematical ability: an EEG study

Huang

Yao

et al. 2015

J. Zhejiang Univ. Sci. B

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“…In an event-related potential study (ERP), Schwarz and Heinze (1998) found that congruity between numerical and spatial size of the presented digits affected the latency of the P300 component over centro-parietal electrodes. Since the amplitude of the P300 component is thought to vary with numerical distance in the context of numerical cognition experiments (Grune et al, 1993), this result supports the idea of an early interaction between numerical and size information. Conversely, Schwarz and Heinze (1998) did not observe any response preparation due to the irrelevant dimension in the lateralized readiness potentials, again speaking against the late interaction hypothesis.…”

Section: Introductionsupporting

confidence: 65%

Micro and macro pattern analyses of fMRI data support both early and late interaction of numerical and spatial information

Koten

Lonnemann

Willmes

et al. 2011

Front. Hum. Neurosci.

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Numbers and space are two semantic primitives that interact with each other. Both recruit brain regions along the dorsal pathway, notably parietal cortex. This makes parietal cortex a candidate for the origin of numerical–spatial interaction. The underlying cognitive architecture of the interaction is still under scrutiny. Two classes of explanations can be distinguished. The early interaction approach assumes that numerical and spatial information are integrated into a single representation at a semantic level. A second approach postulates independent semantic representations. Only at the stage of response selection and preparation these two streams interact. In this study we used a numerical landmark task to identify the locus of the interaction between numbers and space. While lying in an MR scanner participants decided on the smaller of two numerical intervals in a visually presented number triplet. The spatial position of the middle number was varied; hence spatial intervals were congruent or incongruent with the numerical intervals. Responses in incongruent trials were slower and less accurate than in congruent trials. By combining across-vertex correlations (micro pattern) with a cluster analysis (macro pattern) we identified large-scale networks that were devoted to number processing, eye movements, and sensory–motor functions. Using support vector classification in different regions of interest along the intraparietal sulcus, the frontal eye fields, and supplementary motor area we were able to distinguish between congruent and incongruent trials in each of the networks. We suggest that the identified networks participate in the integration of numerical and spatial information and that the exclusive assumption of either an early or a late interaction between numerical and spatial information does not do justice to the complex interaction between both dimensions.

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“…Neural activity during the late period of target word processing reflected higher-order processes including conflict detection/resolution and cognitive adjustments (Grune et al, 1993; Liotti et al, 2000). ERPs during the late period exhibited a more complex pattern of temporal dynamics in response to cognitive fatigue.…”

Section: Resultsmentioning

confidence: 99%

“…Based on prior ERP studies of the Stroop task, we selected two times of interest (TOI) for analysis: (1) the Early Period (150–300 ms), in which sensory and early attentional processes are active (Weinstein, 1995; Atkinson et al, 2003); and (2) the Late Period (300–1000 ms), in which higher-order attention and conflict-related processing are active (West, 2003; Larson et al, 2004; Perlstein et al, 2006), along with response-related cognitive adjustments and adaptation processes (Grune et al, 1993; Liotti et al, 2000).…”

Section: Methodsmentioning

confidence: 99%

Compensatory Neural Responses to Cognitive Fatigue in Young and Older Adults

Samuel

Wang

Burke

et al. 2019

Front. Neural Circuits

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Prolonged performance of a demanding cognitive task induces cognitive fatigue. We examined the behavioral and neural responses to fatigue-induced cognitive impairments in young and older adults. Particular emphasis was placed on whether the brain exhibited compensatory neural activity in response to cognitive fatigue. High-density EEG was recorded from a young ( n = 16; 18–33 years of age) and an older ( n = 18; 60–87 years of age) cohort who performed a Stroop task continuously for ∼2 h with no breaks. In the young cohort, behavioral performance declined as the experiment progressed, reflecting the deleterious effects of cognitive fatigue. Neurophysiologically, in addition to declining neural activity as cognitive fatigue developed, there is also evidence of region- and time-specific increase in neural activity, suggesting neural compensation. The compensatory activities followed patterns paralleling that of posterior-anterior shift in aging (PASA) and early to late shift in aging (ELSA) observed in cognitive aging and helped to moderate fatigue-induced behavioral deterioration. In the older cohort, behavioral performance did not decline as the experiment progressed, and neural activity either declined or stayed unchanged, showing no evidence of neural compensation, in contrast to the young. These results suggest that young and older adults coped with cognitive fatigue differently by exhibiting differential responses as a function of time-on-task at both the behavioral level and the neural level.

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Mental comparison

Cited by 23 publications

References 0 publications

Numerical magnitude processing in abacus-trained children with superior mathematical ability: an EEG study

Numerical magnitude processing in abacus-trained children with superior mathematical ability: an EEG study

Micro and macro pattern analyses of fMRI data support both early and late interaction of numerical and spatial information

Compensatory Neural Responses to Cognitive Fatigue in Young and Older Adults

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