DOI: 10.5061/dryad.1zcrjdg13
title: Identifying conceptual neural responses to symbolic numerals

description: The goal of measuring conceptual processing in numerical cognition is
 distanced by the possibility that neural responses to symbolic numerals
 are influenced by physical stimulus confounds. Here, we targeted
 conceptual responses to parity (even vs. odd), using
 electroencephalographic (EEG) frequency-tagging with a symmetry/asymmetry
 design. Arabic numerals (2–9) were presented at 7.5 Hz in 50-s sequences;
 odd and even numbers were alternated to target differential, “asymmetry”
 responses to parity at 3.75 Hz (7.5 Hz/2). Parity responses were probed
 with four different stimulus sets, increasing in intra-numeral stimulus
 variability, and with two control conditions comprised of non-conceptual
 numeral alternations. Significant asymmetry responses were found over the
 occipitotemporal cortex to all conditions, even for the arbitrary
 controls. The large physical-differences control condition elicited the
 largest response in the stimulus set with the lowest level of variability
 (1 font). Only in the stimulus set with the highest level of variability
 (20 drawn, colored exemplars/numeral) did the response to parity surpass
 both control conditions. These findings show that physical differences
 across small sets of Arabic numerals can strongly influence, and even
 account for, automatic brain responses. However, carefully designed
 control conditions and highly variable stimulus sets may be used towards
 identifying truly conceptual neural responses.
description: 1) EEG data for 15 participants. -acquired
 with a BioSemi, ActiveTwo system (.bdf)  -standard 64
 channel headcap active recording electrodes + PO9, I1, I2, and PO10 https://www.biosemi.com/headcap.htm  -We processed this data with LetsWave6, an open-source toolbox running over MATLAB (https://www.letswave.org/). Bdf (BioSemi Data Format) files (https://www.biosemi.com/faq/file_format.htm) can also be accessed directly and with many other common EEG analysis toolboxes for Matlab and Python.  Please see the README document for processing details.  2) Stimuli. 4 sets: 1 font; 10 fonts; 10 mixed; 20 drawn.
description: # Identifying conceptual neural responses to symbolic numerals
 [https://doi.org/10.5061/dryad.1zcrjdg13](https://doi.org/10.5061/dryad.1zcrjdg13) Talia L. Retter, Lucas Eraßmy & Christine Schiltz Proceedings of the Royal Society B: Biological Sciences (2024) ## Description of the data and file structure BioSemi BDF files (EEG data) 15 participants (NumberShape_S01-S15); none excluded CONDITION TRIGGERS: 1 font: parity: 11; small phys.-diff. control: 21; large phys.-diff. control: 31 10 fonts: parity: 12; small phys.-diff. control: 22; large phys.-diff. control: 32 10 mixed: parity: 13; small phys.-diff. control: 23; large phys.-diff. control: 33 20 fonts: parity: 14; small phys.-diff. control: 24; large phys.-diff. control: 34 ## EEG notes and analysis steps Data proceeded with LetsWave 6 ([https://www.letswave.org/](https://www.letswave.org/), running over Matlab R2019b (MathWorks, USA)) IMPORT/BASIC PREPROCESSING 1\. import bdfs 1b. assign electrode labels+coordinates *S05: cut first block, recorded without glasses and unused (from 263 to 3017 s, w/cropper) \**S10: one ep 21 trigger missing, can recover at end of fade-in (1229.0879 s) \***some trigger fixes: S06, 38--&gt;34; S10, 28--&gt;24; S13: 37--&gt;34; S15: 36--&gt;32 2\. bc 3\. Butterworth bandpass filter, hpf 0.1, lpf 80 order 4 *bbpf 4\. Segment -1 for 56 s (1 pre,2 fade-in;2 fade-out,1 post) *epm PREPROCESSING CONTINUED: CLEANING 5\. electrode check - replacements? +delete status *ch68 6\. ICA for blinks &gt;.2/s (3 subj only: S05:IC2,S06:IC1,S07:IC1) 7\. interpolation of noisy channels S01 none S02 P1,F6 S03 FC1,P2 S04 P2,P4 S05 none S06 FP2,PO9 S07 CP1,P9 S08 P1,PO3 S09 CP1 S10 P1,T8 S11 none S12 F7,AF3,AF8 S13 none S14 none S15 FPz,Afz,P2 8\. rereference 9\. Crop epochs by bin *epb (don't merge) 2 s to 25532 bins FREQUENCY-DOMAIN PROCESSING 10\. Average epochs *avg 11\. FFT *fft 12\. Chunk for harmonics -latency: 3.439198774 -duration: 0.621602452 (31 bins) -interval: 3.75 13\. baseline sub 2-11 ex. 1 *sbl 14\. sum epochs (1:3.75 Hz; 3:11.25 Hz; 5:18.75 Hz for asymmetry responses) ## Demographics | | Age | Sex | Handedness | | :-- | :---- | :-- | :--------- | | S01 | 24-26 | F | R | | S02 | 21-23 | M | L | | S03 | 30-32 | F | R | | S04 | 27-29 | F | R | | S05 | 18-20 | F | R | | S06 | 24-26 | F | R | | S07 | 24-26 | F | R | | S08 | 21-23 | F | R | | S09 | 21-23 | F | R | | S10 | 18-20 | F | R | | S11 | 18-20 | F | R | | S12 | 21-23 | M | R | | S13 | 24-26 | F | R | | S14 | 18-20 | F | R | | S15 | 21-23 | F | L | *age given as an approximate range to preserve individual confidentiality  ## Stimuli .jpg image files