Separating stages of arithmetic verification: An ERP study with a novel paradigm

Avancini, Chiara; Soltész, Fruzsina; Szűcs, Dénes

doi:10.1016/j.neuropsychologia.2015.06.016

Cited by 25 publications

(13 citation statements)

References 54 publications

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“…The proposed result was transiently decoded after its onset, but we did not observe a distance effect for the incorrect trials (absolute distances = 1-4) in both behavioral and electrophysiological levels (no significant decoding scores), which is at odds with previous positive findings (Avancini, Galfano, & Szucs, 2014;Avancini et al, 2015;Dehaene, 1996). We believe that this null finding was probably due to a combination of the small distances used (1-4), and the slow pace of our experimental design.…”

Section: Parsing the Processing Stages Of Arithmetic Decision-makingcontrasting

confidence: 84%

“…By manipulating orthogonal features of the stimuli and the task, the author showed that the ERPs were first modulated by notation (Arabic numerals vs. number words, at ~110-170 ms), followed by the numerical distance (close vs. far, at ~190-300 ms) and finally by the lateralization of motor response (left vs. right, at ~250-400 ms). More recently, using a modified version of the arithmetic verification with ERPs, Avancini, Soltész, and Szucs (2015) identified a series of overlapping cognitive processes during calculation, such as the identification of the stimuli properties, magnitude comparison and judgment of correctness.…”

Section: Introductionmentioning

confidence: 99%

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Decoding the processing stages of mental arithmetic with magnetoencephalography

Pinheiro‐Chagas

Piazza

Dehaene

2019

Cortex

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Elementary arithmetic is highly prevalent in our daily lives. However, despite decades of research, we are only beginning to understand how the brain solves simple calculations. Here, we applied machine learning techniques to magnetoencephalography (MEG) signals in an effort to decompose the successive processing stages and mental transformations underlying elementary arithmetic. Adults subjects verified single-digit addition and subtraction problems such as 3 + 2 = 9 in which each successive symbol was presented sequentially. MEG signals revealed a cascade of partially overlapping brain states. While the first operand could be transiently decoded above chance level, primarily based on its visual properties, the decoding of the second operand was more accurate and lasted longer. Representational similarity analyses suggested that this decoding rested on both visual and magnitude codes. We were also able to decode the operation type (additions vs. subtraction) during practically the entire trial after the presentation of the operation sign. At the decision stage, MEG indicated a fast and highly overlapping temporal dynamics for (1) identifying the proposed result, (2) judging whether it was correct or incorrect, and (3) pressing the response button. Surprisingly, however, the internally computed result could not be decoded. Our results provide a first comprehensive picture of the unfolding processing stages underlying arithmetic calculations at a single-trial level, and suggest that externally and internally generated neural codes may have different neural substrates.

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Section: Parsing the Processing Stages Of Arithmetic Decision-makingcontrasting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Decoding the processing stages of mental arithmetic with magnetoencephalography

Pinheiro‐Chagas

Piazza

Dehaene

2019

Cortex

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“…This hypothesis might explain the different time courses of the audio/visual correspondence effect on ERPs in the two experiments. We could speculate that in Experiment 1 visual features are ignored to facilitate numerical processing, consistent with recent theories regarding the cognitive basis of enumeration (Avancini et al, ; Semenza & Benavides‐Varela, ).…”

Section: Discussionsupporting

confidence: 85%

“…These ERPs emerge when participants are presented, for instance, with a numerical problem (e.g., 3 × 1 = ?) and are then requested to detect whether a proposed result does match (e.g., 3) or not (e.g., 2) their numerical expectations (Avancini, Soltész, & Szűcs, ; Hsu & Szűcs, ; Szűcs & Csépe, ). It is thus plausible that similar mechanisms were elicited in our study when participants compared the numerosity of sounds (e.g., 3) with the incoming numerosity input (e.g., 2), giving rise to the “semantic like” numerical correspondence ERP effect peaking around 400 ms.…”

Section: Discussionmentioning

confidence: 99%

N2pc reflects two modes for coding the number of visual targets

et al. 2018

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Humans share with a variety of animal species the spontaneous ability to detect the numerical correspondence between limited quantities of visual objects and discrete auditory events. Here, we explored how such mental representation is generated in the visual modality by monitoring a parieto-occipital ERP component, N2pc, whose amplitude covaries with the number of visual targets in explicit enumeration. Participants listened to an auditory sequence of one to three tones followed by a visual search display containing one to three targets. In Experiment 1, participants were asked to respond based on the numerical correspondence between tones and visual targets. In Experiment 2, participants were asked to ignore the tones and detect a target presence in the search display. The results of Experiment 1 showed an N2pc amplitude increase determined by the number of visual targets followed by a centroparietal ERP component modulated by the numerical correspondence between tones and visual targets. The results of Experiment 2 did not show an N2pc amplitude increase as a function of the number of visual targets. However, the numerical correspondence between tones and visual targets influenced N2pc amplitude. By comparing a subset of amplitude/latency parameters between Experiment 1 and 2, the present results suggest N2pc reflects two modes for representing the number of visual targets. One mode, susceptible to subjective control, relies on visual target segregation for exact target individuation, whereas a different mode, likely enabling spontaneous cross-modal matching, relies on the extraction of rough information about number of targets from visual input.

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“…In fact, most experiments using digits, and even some using number words, appear to feature the positivity in response to correct solutions (Bassok et al, 2009; Fisher et al, 2010; Guthormsen et al, 2016; Martinez-Lincoln, Cortinas, & Wicha, 2015; Salillas & Wicha, 2012; Szűcs & Csépe, 2004), but this positivity has not been reported as such in most of these studies. Avancini, Soltész, and Szűcs (2015) acknowledge the presence of positivities for both correct and incorrect solutions, but oddly argue that a latency shift between them resulted in the emergence of the “N400-like” response. Critically, the early positivity for correct responses may be the primary contributor to both the amplitude and the timing of the reported arithmetic effect.…”

Section: Introductionmentioning

confidence: 98%

When 2 × 4 is meaningful: the N400 and P300 reveal operand format effects in multiplication verification

et al. 2018

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Arithmetic problems share many surface-level features with typical sentences. They assert information about the world, and readers can evaluate this information for sensibility by consulting their memories as the statement unfolds. When people encounter the solution to the problem 3 × 4, the brain elicits a robust ERP effect as a function of answer expectancy (12 being the expected completion; 15 being unexpected). Initially, this was labeled an N400 effect, implying that semantic memory had been accessed. Subsequent work suggested instead that the effect was driven by a target P300 to the correct solutions. The current study manipulates operand format to differentially promote access to language-based semantic representations of arithmetic. Operands were presented either as spoken number words or as sequential Arabic numerals. The critical solution was always an Arabic numeral. In Experiment 1, the correctness of solutions preceded by spoken operands modulated N400 amplitude, whereas solutions preceded by Arabic numerals elicited a P300 for correct problems. In Experiment 2, using only spoken operands, the delay between the second operand and the Arabic numeral solution was manipulated to determine if additional processing time would result in a P300. With a longer delay, an earlier N400 and no distinct P300 were observed. In brief, highly familiar digit operands promoted target detection, whereas spoken numbers promoted semantic level processing-even when solution format itself was held constant. This provides evidence that the brain can process arithmetic fact information at different levels of representational meaningfulness as a function of symbolic format.

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Separating stages of arithmetic verification: An ERP study with a novel paradigm

Cited by 25 publications

References 54 publications

Decoding the processing stages of mental arithmetic with magnetoencephalography

Decoding the processing stages of mental arithmetic with magnetoencephalography

N2pc reflects two modes for coding the number of visual targets

When 2 × 4 is meaningful: the N400 and P300 reveal operand format effects in multiplication verification

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