Parietal Contributions to Abstract Numerosity Measured With Steady State Visual Evoked Potentials

Abstract

Non-symbolic number changes produce transient Event Related Potentials over parietal electrodes, while numerosity effects measured with Steady-State Visual Evoked Potentials (SSVEPs) appear to originate in occipital cortex. We hypothesized that the stimulation rates used in previous SSVEP studies may be too rapid to drive parietal numerosity mechanisms. Here we recorded SSVEPs and behavioral reports over a slower range of temporal frequencies than previously used. Isoluminant dot stimuli updated at a consistent “carrier” frequency (3-6 Hz) while periodic changes in numerosity (e.g. 8→5) formed an even slower “oddball” frequency (0.5-1 Hz). Each numerosity oddball condition had a matched control condition where the number of dots did not change. Carrier frequencies induced SSVEPs with midline occipital topographies that did not differentiate the presence or absence of numerosity oddballs. By contrast, SSVEPs at oddball frequencies had parietal topographies and responded more strongly when oddballs were present. Consistent with our hypothesis, numerosity effects were stronger at slower stimulation rates. In a second study, the numerosity change was either supra-threshold (e.g. 8→5 dots) or near the threshold required for detecting numerosity changes (e.g. 8→9 dots). We found robust parietal responses for the supra-threshold case only, indicating a numerical distance effect. A third study replicated the parietal oddball SSVEP effect across four distinct suprathreshold numerosity-change conditions and showed that number change direction does not influence the effect. These findings show that SSVEP oddball paradigms can probe parietal computations of abstract numerosity, and may provide a rapid, portable approach to quantifying number sense within educational settings.

Automatic Processing of Numerosity in Human Neocortex Evidenced by Occipital and Parietal Neuromagnetic Responses

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“…Then the EEG signals were re-referenced to the common average of all channels and segmented into 1.17-s epochs. Epochs with more than 10% of time samples exceeding threshold (30 -80 μV) were excluded further on a channel-by-channel basis 69 .…”

“…Epochs with more than 10% of time samples exceeding threshold (30 -80 μV) were excluded on a channelby-channel basis 71 . S2 shows the number of epochs (1.1667-s each) we acquired before and after data pre-processing summing across all five categories.…”

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