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Journal of Integrative Neuroscience 00 (20xx) 1–20 1DOI 10.3233/JIN-170058IOS Press1 1

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Neural activation patterns and connectivity invisual attention during Number andNon-number processing: An ERP studyusing the Ishihara pseudoisochromatic plates

Faraj Al-Marri a,b, Faruque Reza a,∗, Tahamina Begum a, Wan Hazabbah Wan Hitam c,Goh Khean Jin d and Jing Xiang e

a Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, 16150 KubangKerian, Kota Bharu, Kelantan, MalaysiaE-mails: faruque@usm, faruquereza@gmail.comb Department of Neuroscience, College of Medicine, King Faisal University, 31982 Hofuf, Al-Ahsa,Saudi Arabiac Department of Ophthalmology, School of Medical Sciences, Universiti Sains Malaysia, 16150 KubangKerian, Kota Bharu, Kelantan, Malaysiad Division of Neurology, Faculty Of Medicine, Universiti Malaya, 50603 Kuala Lumpur, Malaysiae Division of Neurology, MEG Center, Cincinnati Children’s Hospital Medical Center, 3333 BurnetAvenue, Cincinnati, OH 45220, USA

Received 22 August 2017Accepted 17 October 2017

Abstract. Visual cognitive function is important to build up executive function in daily life. Perception of visual Number form(e.g., Arabic digit) and numerosity (magnitude of the Number) is of interest to cognitive neuroscientists. Neural correlates andthe functional measurement of Number representations are complex occurrences when their semantic categories are assimi-lated with other concepts of shape and colour. Colour perception can be processed further to modulate visual cognition. TheIshihara pseudoisochromatic plates are one of the best and most common screening tools for basic red-green colour visiontesting. However, there is a lack of study of visual cognitive function assessment using these pseudoisochromatic plates. Werecruited 25 healthy normal trichromat volunteers and extended these studies using a 128-sensor net to record event-relatedEEG. Subjects were asked to respond by pressing Numbered buttons when they saw the Number and Non-number plates ofthe Ishihara colour vision test. Amplitudes and latencies of N100 and P300 event related potential (ERP) components wereanalysed from 19 electrode sites in the international 10–20 system. A brain topographic map, cortical activation patterns andGranger causation (effective connectivity) were analysed from 128 electrode sites. No major significant differences betweenN100 ERP components in either stimulus indicate early selective attention processing was similar for Number and Non-numberplate stimuli, but Non-number plate stimuli evoked significantly higher amplitudes, longer latencies of the P300 ERP com-ponent with a slower reaction time compared to Number plate stimuli imply the allocation of attentional load was more inNon-number plate processing. A different pattern of asymmetric scalp voltage map was noticed for P300 components with ahigher intensity in the left hemisphere for Number plate tasks and higher intensity in the right hemisphere for Non-number platetasks. Asymmetric cortical activation and connectivity patterns revealed that Number recognition occurred in the occipital and

*Corresponding author. Tel.: Office Ext- (609) 767 6316, HP: +6-017-9556137; Fax: (609) 767 6315; E-mails: faruque@usm,faruquereza@gmail.com.

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0219-6352/17/$35.00 © 2017 – IOS Press and the authors. All rights reserved

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left frontal areas where as the consequence was limited to the occipital area during the Non-number plate processing. Finally,the results displayed that the visual recognition of Numbers dissociates from the recognition of Non-numbers at the level ofdefined neural networks. Number recognition was not only a process of visual perception and attention, but it was also relatedto a higher level of cognitive function, that of language.

Keywords: Visual number recognition, event-related potential, pseudoisochromatic plates, attention, effective connectivity

1. Introduction

The brain and eye communicate with each other to analyse the visual perception of brightness, move-ment, shape and colour of objects (DeYoe and Van Essen [18]; Köhler et al. [40]) even in the mentalimagery of motion and static visual features (Chang and Pearson [10]; Roldan [64]). The three basiccolour receptors of blue, green and red have their own photo pigments that react to light to evoke thereceptor potentials in the visual pathway. The Ishihara test is one type of test where we use a chart todetect weakness or missing of L-cones (red) and M-cones (green), but not S-cones (blue) (Sharpe et al.[70]; Smith and Pokorny [72]). Different coloured plates are usually used in this test, where primary andsecondary dots correspond to Number or Non-number shapes. Secondary dots play a role in the back-ground of the plates (Belcher et al. [6]). Subjects are classified as having impaired colour vision if two ormore plates are recognized incorrectly (Dain [14]). Impaired colour vision influences the visual cognitivefunctions that are involved with object recognition, colour memory, colour consistency and discountingof the illuminant (Arend et al. [2]; Fairchild [23]; Schirillo et al. 1990). However, Visual informationprocessing can be divided into two broad pathways: a neural pathway for vision from retina to cortexand a multi-synaptic corticocortical pathway of visual streams. The former consists of the retina, opticnerve, optic chiasm, optic tract, lateral geniculate body (LGN) of the thalamus, geniculocalcarine tractor optic radiations and primary visual cortex (V1, also known as Brodmann’s area 17). These anatomicalvisual pathways are of great concern to ophthalmologists and neurologists with injury or impairment ofvision. The latter consists of a widely believed ‘ventral stream’ (also called the what pathway) and ‘dor-sal stream’ (also called the where pathway) (Goodale and Milner [28]; Mortimer et al. [53]), which haveattracted much attention from cognitive neuroscientists. The ventral stream originates from V1 of the oc-cipital lobe and spreads along the ventral surface of the temporal lobe (occipitotemporal) and is involvedin the processing of the recognition of objects, forms, face, colour and numerals. Conversely, the dorsalstream also originates from V1 and spreads along the dorsal surface of the parietal lobe (occipitoparietal)and is involved in the processing of spatial location of objects. Likewise, numerical information from avisual scene encoded and process along the Occipitoparietal (dorsal stream) pathway and finally projectto number-selective circuits of the bilateral intraparietal sulcus (IPS) (Knops [39]). Such hemisphericactivation or lateralization identified by the Triple Code Model (TCM) also originate not only in thenumber processing but also in the arithmetic skill processing which has been assessed recently by thefunctional Transcranial Doppler Ultrasonography (fTCD) in adults (Connaughton et al. [12]). The TCMof number processing is a theoretical framework organized through three circuits – a linguistically me-diated verbal code associated with the left hemisphere, a visual number code for recognition of Arabicdigits associated with bilateral fusiform and lingual regions of ventral stream (what pathway) of objectrecognition, and the bilateral number magnitude code (cardinal value/numerosity) (Dehaene [15]).

On the other hand, cognitive function, simply said, is the mental process that takes internal or exter-nal input and transforms, minimizes, elaborates, stores, retrieves and finally utilizes it (Neisser [54]).

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The term cognition makes up a variety of functions such as attention, memory, learning, calculating,problem-solving, decision-making, reasoning and planning (Barsalou [4]; Maria A. Brandimonte et al.2006; Mayzner [48]). Among all those sub components of cognitive function, attention has a great rolein regulating cognitive function (Miller and Cohen [49]). The brain areas activated by visual stimuli havebeen investigated by different neuroimaging modalities such as MEG, fMRI, PET and others. Recentlya review article (Yeo et al. [83]) on a functional neuroimaging meta-analysis highlighted that NumberForm Area (NFA) which is proposed to be specialized for Arabic numerical processing is in the rightinferior temporal gyrus, bilateral parietal regions and superior and inferior right frontal regions. Event-related potential (ERP) studies are another way to measure visual cognitive function (attention) at theelectrophysiological level. Due to higher temporal resolution, EEG/ERP has great importance in cog-nitive neuroscience research, in addition to fMRI, which has better spatial resolution. Moreover, usingelectrophysiological techniques, the connectivity of the brain has recently received more attention, whichhas supported the development of brain cognition and action that can determine a temporal correlation(Sporns et al. [75]).

We are considering a stimulus that has the characteristics of processing coloured Numbers and Non-numbers simultaneously in the brain to determine how the brain processes activation, connectivity, in-tegration or segregation of these different visual features in our visual systems. This stimulus could bean important test tool for translating certain brain disorders, such as attention deficit disorder, and con-nectivity disorders in different sensing areas of the brain. Several researchers consider that connectivitycan be reformed by various reasons in mental tasks (Esposito et al. [22]), by sleep (Horovitz et al. [34]),by learning (Bassett et al. [5]) and by consciousness (Hutchison et al. [36]). There was less connectivityin the fronto-parietal network among persons with reading difficulty (Dosenbach et al. [19]; Koyama etal. [41]), and this network is vital for visual attention during reading (Vogel et al. [80]). There is alsoevidence that enhanced connectivity within visual processing components is also increased between vi-sual processing components and temporal-occipital components (Horowitz-Kraus et al. [35]), moreover,left temporal-parietal connectivity is stronger during the processing of arithmetic principle and languagethan during computation, whereas parietal-occipital connectivities are stronger during computation thanduring the processing of arithmetic principles and language (Liu et al. [43]). One example of connectiv-ity disorders in different sensing areas of the brain is synaesthesia, which is a neurological phenomenonin which an individual sees a specific colour when seeing a specific Number (Galton [25]), and it canhappen with a letter for a colour and a taste for a shape. For grapheme synaesthesia, when someonesees colour upon seeing letters and Numbers, this phenomenon arise from cross connectivity betweena colour area and a Number area in the fusiform gyrus of the brain. Researchers verified that Arabicnumerals but not Roman numerals induced the colour, demonstrating that it was the visual image, or“grapheme” of the Number that is predominant, rather than the numerical concept (Ramachandran andHubbard [63]; Brang et al. [7]). Ramachandran and Hubbard [1] also showed that synaesthetic subjectsare significantly better in identifying the embedded shape than Non-synesthetic subjects, which is com-parable to the way healthy people see coloured patterns in the Ishihara colour-vision test. Moreover,attention plays a vital role in modulating synaesthesia; during attention-demanding tasks, colour oftenweakens synaesthetic experiences (Mattingley et al. [47]).

Visual attention is a one of the primary steps to build up executive function. For that purpose, we canmeasure reaction or response time (RT) to examine visual attention (Moore and Zirnsak [52]; Posner etal. [62]). RT is the time gap between the starting of stimuli and a participant’s voluntary response. RT canmeasure the awareness of a person in their daily life activities. Gender, age, level of fatigue, and healthproblems can influence RT (Baayen 2010). There are three types of RTs: simple, recognition and choice

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RT, with one response, no response and multiple responses, respectively (Luce et al. 1968; Welford etal. 1980). Choice RT is more important than other RTs in our everyday life. Visual or auditory inputs areimportant to measure visual or auditory choice RT measurement. Due to the different wavelength sensi-tivities of red, green and blue colours, RTs are faster or slower (Lit et al. [42]). Visual choice RT is fasterin males than females and in hand dominant persons (Misra et al. [50]). Faster RT emphasizes fasternervous system processing time with faster muscular movement (Spirduso et al. 1975), which defines ashigher cognitive function (Gavkare et al. [26]). Interestingly a recent study investigated the ‘mental num-ber line’ which is oriented from left to right on the SNARC (spatial-numerical association of responsecodes) effect (faster response to the small number on the left side and to the large numbers on the rightside) using kinematics of fingers movement besides response time and found that numerical processingaffects action execution (Rugani et al. [66]). Therefore, we used RT as a marker of cognitive processingspeed in this study together with ERP. There are several components of ERP waveforms depending onstimuli. ERP waveforms can be evoked during visual stimuli. The N100 or N1 ERP component is thenegative deflection that is evoked approximately 100 ms after stimuli (Sur and Sinha [77]; Du et al. [20]).N100 is the sensory component that imitates the selective attention and voluntary discrimination process(Rugg et al. [67]; Vogel and Luck [81]) with matching priming stimuli (Delb et al. [17]). On the otherhand, P300 or P3 is the positive ERP component evoked approximately 300 ms after stimuli (Stelt et al.[76]; Picton [59]). P300 is the cognitive component, where higher amplitude indicates higher cognitivefunction, which means higher attention (Polich and Kok [61]).

While colour and texture are processed in medial temporal-occipital areas, geometric features areprocessed in lateral temporal-occipital areas (Cavina-Pratesi et al. [9]). Though there are some studiesusing simple colour stimuli (Cavina-Pratesi et al. [9]; Rumaisa et al. 2016), there is a comprehensivelack of the study of visual cognitive function assessment using pseudoisochromatic plates. Therefore,we investigated here the visual numerical cognitive function using the Ishihara test with indexing ofthe ERP procedure, RT and EC analysis. In addition, brain topography was done to comprehend thehemispheric lateralization during the two stimuli.

2. Methodology

2.1. Ethics and sample size

We received ethical permission from the human ethical committee of Universiti Sains Malaysia (USM)[USM/KK/PPP/JePeM 232.3(8)]. Subjects were recruited via the internet, email notification and per-sonal communication. All participants gave their written informed consent before starting the exper-iment. A total of 25 (13 male and 12 female) healthy subjects were recruited who had normal orcorrected-to-normal vision and no neurological or other major diseases. Sample size was calculatedusing power and sample size (PS) software (PS version 3.1.2) with the support of the data from a relatedstudy (Fonteneau and Davidoff [24]). The inputs for sample size calculation were α = 0.05, power =0.9, δ = 3.9 and σ = 5.8. This study was performed in the MEG/ERP laboratory of Hospital UniversitiSains Malaysia (HUSM).

2.2. Study procedure

All participants sat in a sound-treated and dimly lit room with a 128-channel geodesic sensor net(GSN) from Electrical Geodesic Inc. (EGI) (Eugene, OR) on their head. Before application, the net head

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circumference of the subject was measured for calculation of the proper net size, and the net was soakedwith an electrolyte solution. After each use, the net was rinsed and disinfected for the next participants.We used a simple visual oddball paradigm by using 18 Ishihara colour vision tests plates, including 9Number (transformation and vanishing type) and 9 Non-number plates. The 18 plates were used threetimes, and a total of 54 stimuli (27 Numbers and 27 Non-numbers) were used in one session. E-primesoftware (v 2.0) was used for presentation of the stimuli.

2.3. Experimental procedure

Subjects were 80 cm in front of a 22˝ LCD computer monitor where all stimuli were presented atthe centre of the monitor for the subject’s response. Subjects were asked to press button ‘1’ if they sawNumber plates and button ‘2’ if they saw Non-number plates as quickly and as correctly as possible.The stimuli lasted for 1 sec with a 0.5 sec fixation (+), and the inter stimulus interval (ISI) was 1.5 sec(Fig. 1).

2.4. Data recording and analysis

2.4.1. Reaction timeThe reaction time was recorded during the button press event, and the significant t-tests from all

correct and incorrect responses were analysed.

2.4.2. ERP analysisEEG data was recorded with a Net Amps 300 amplifier and Net station software. The sampling rate

was 250 Hz, and impedances for electrodes were below 50 K�. Data were filtered with 30 Hz low-passand 0.3 Hz high-pass filters, segmented 100 ms before stimuli and 800 ms after stimuli, and a baselinewas corrected before 100 ms of stimuli. Eye movement, eye blink and movement artefacts were removedwith an artefact removal tool. Then, N100 and P300 ERP components’ amplitudes and latencies were

Fig. 1. Graphical representation of experimental procedure with Number and Non-number plates of Ishihara colour vision test.

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computed from 19 electrodes that were selected from 128 electrodes based on the 10–20 internationalelectrode placement system; all the procedures were conducted with Net station software. After ERP dataextraction from Net station, the data was pre-processed for outliers, there was no correction for outliersfor N100 and P300 latencies. But one subject (subject 14) has outliers in N100 and P300 amplitudefor Number and Non-number stimuli and one subject (subject 18) showed outliers in N100 and P300amplitude for Number plate stimuli. The outliers were identified and replaced by estimation method ofseries mean using Statistical Package for the Social Sciences (SPSS) version 22 software. To determinethe values of amplitudes and latencies of N100 and P300 ERP components that were significant betweenthe two categories of Number and Non-number from the 19 EEG electrodes, both distribution-free non-parametric Wilcoxon signed rank tests and parametric paired T -test were used.

2.4.3. Scalp topography and cortical activationFor brain topography and cortical source localization from all 128 EEG electrodes, we used standard-

ized low-resolution brain electromagnetic tomography (sLORETA) performed with Brainstorm (Tadelet al. [78]), which is documented and freely available for download online under the GNU general publiclicense (http://neuroimage.usc.edu/brainstorm).

2.4.4. Connectivity analysisRegarding analysis and visualization of effective connectivity (Granger causality) from all 128 EEG

electrodes, the MATLAB (MathWorks, Inc)-based connectivity analysis software HERMES (Niso et al.[55]) (http://hermes.ctb.upm.es) was applied.

3. Results

3.1. Reaction time (RT)

Reaction time was significantly longer during the Non-number plate stimuli (570.33 ± 158.43 ms)compared to the Number plate stimuli (557.03 ± 151.91 ms) (p = 0.045) (Fig. 2).

3.2. N100 ERP component

There was a near-significant increase of amplitudes of the N100 ERP component during Number platestimuli at most of the electrode sites (12 sites: Fp1, Fp2, F4, F8, C4, P3, P4, O1, O2, Fz, Cz and Pz)compared with the Non-number stimuli. The significant higher amplitude was found at the Fp2 electrodeposition, p = 0.028 (t = 2.33, df = 24) at paired t-test but the significance disappeared at distributionfree non-parametric Wilcoxon test (Table 1).

In the case of N100 latencies, a trend of shorter latencies were observed at the 10 electrode sites (Fp1,F7, Fp2, F4, F8, T3, T4, T6, O2, and Fz) during Number plate stimuli compared with the Non-numberplate stimuli in which only Fp2 site showed significant at Wilcoxon test (p = 0.032) (Table 2).

3.3. P300 ERP component

Most of the electrode positions (12 sites out of 19: F4, C3, C4, P3, P4, T3, T4, T5, T6, O1, O2, andCz) showed higher amplitudes of the P300 ERP component during Non-number plate stimuli in whichT4 and T6 showed highly significant at both non-parametric and parametric tests compared with theNumber plate stimuli, a tendency of higher amplitude was observed at the left frontal hemisphere (Fp1,

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Fig. 2. Mean Reaction Time (RT) during presentation of Number (white dotted column with standard error bars) and Non-num-ber (black column with standard error bars) plates of Ishihara colour vision test. The reaction time significantly increased inNon-number plates indicating the participants responded to Number plates faster than Non-number plates.

Table 1

Result of peak amplitude in μV (mean ± SD) for N100 ERP component

Number plate Non-number plate Wilcoxon Paired T -testSites Mean ± SD Variance Mean ± SD Variance Z-value p-value t df p-valueFp1 1.91 2.22 4.91 1.43 1.92 3.70 −1.197b 0.231 1.36 24 0.186F3 1.47 2.43 5.92 1.66 1.66 2.76 −0.632c 0.527 −0.54 24 0.598F7 1.18 1.49 2.23 1.32 1.31 1.72 −1.117c 0.264 −0.45 24 0.657Fp2 2.22 2.30 5.28 1.37 2.05 4.19 −1.897b 0.058 2.33 24 0.028*F4 1.94 1.81 3.29 1.51 1.72 2.97 −1.009b 0.313 1.30 24 0.206F8 1.64 1.14 1.29 1.14 1.25 1.57 −1.628b 0.104 1.82 24 0.082C3 1.58 1.41 1.98 1.73 1.61 2.60 −0.256c 0.798 −0.61 24 0.550C4 1.79 1.26 1.58 1.60 1.23 1.53 −0.444b 0.657 0.75 24 0.464T3 0.99 1.11 1.23 1.57 1.16 1.34 −1.870c 0.061 −1.95 24 0.063T4 1.72 1.21 1.47 2.02 1.82 3.33 −0.309c 0.757 −0.81 24 0.429P3 1.77 1.30 1.69 1.60 1.16 1.34 −0.659b 0.510 0.73 24 0.473T5 2.08 2.19 4.81 2.15 1.47 2.18 −0.498c 0.619 −0.19 24 0.853P4 2.61 1.07 1.14 2.30 1.36 1.84 −1.251b 0.211 1.05 24 0.306T6 3.09 1.65 2.71 3.17 2.45 5.99 −0.309b 0.757 −0.18 24 0.855O1 2.42 2.77 7.66 2.18 2.08 4.34 −1.170b 0.242 0.57 24 0.577O2 2.88 2.68 7.18 2.62 2.34 5.50 −0.605b 0.545 0.72 24 0.479Fz 1.68 1.86 3.46 1.63 1.84 3.39 −0.040c 0.968 0.16 24 0.871Cz 1.90 1.89 3.58 1.89 1.59 2.52 −0.256c 0.798 0.04 24 0.971Pz 2.02 1.48 2.20 1.82 1.48 2.19 −0.955b 0.339 0.55 24 0.586b, c based on positive & negative ranks respectively, * significant if p < 0.050.

Fp2, F3 and F7) for Number stimuli in which Fp1 showed significant (t = 2.35, df = 24) at parametrictest only (Table 3). At about the P300 ERP latency, Non-number plates evoked longer latencies at mostof the sites (15 sites: Fp1, F3, F7, F8, C3, T3, P3, P4, T5, T6, O1, O2, Fz, CZ, and Pz). A significantlylonger latency was found at the Pz location at both Wilcoxon (p = 0.036) and paired T -test (t = −2.07,df = 24) and the remaining electrode locations showed a tendency towards longer (Table 4).

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Table 2

Result of latencies in ms (mean ± SD) for N100 ERP component

Number plate Non-number plate Wilcoxon Paired T -testSites Mean ± SD Variance Mean ± SD Variance Z-value p-value t df p-valueFp1 109.44 19.93 397.17 111.84 17.79 316.64 −0.419b 0.675 −0.52 24 0.610F3 105.44 17.88 319.84 104.8 19.83 393.33 −0.284c 0.776 0.13 24 0.900F7 112.48 25.75 663.09 120.48 25.07 628.43 −1.22b 0.222 −1.38 24 0.182Fp2 107.36 22.59 510.24 117.28 22.62 511.63 −2.14b 0.032* −1.80 24 0.085F4 102.88 16.15 260.69 105.92 20.30 412.16 −0.263b 0.792 −0.81 24 0.423F8 107.84 20.86 435.31 116.8 23.41 548.00 −1.88b 0.060 −1.58 24 0.128C3 102.88 17.30 299.36 98.4 17.93 321.33 −0.681c 0.496 1.05 24 0.306C4 103.04 19.71 388.37 99.68 20.33 413.23 −0.163c 0.871 0.68 24 0.506T3 109.12 25.76 663.36 120 27.54 758.67 −1.77b 0.076 −1.85 24 0.076T4 110.08 31.18 972.16 115.84 28.55 815.31 −0.987b 0.324 −0.82 24 0.422P3 103.68 26.86 721.23 100.32 25.84 667.89 −0.618c 0.537 0.47 24 0.641T5 116.64 30.65 939.57 116.48 32.28 1041.76 −0.443b 0.658 0.03 24 0.980P4 112.32 30.29 917.23 106.56 28.07 787.84 −1.10c 0.270 1.01 24 0.321T6 110.4 31.03 962.67 118.72 32.84 1078.29 −1.08b 0.280 −1.14 24 0.267O1 121.44 27.73 769.17 120.8 28.59 817.33 −0.130b 0.897 0.14 24 0.891O2 122.08 27.43 752.16 125.76 26.96 726.77 −0.919b 0.358 −0.73 24 0.473Fz 105.76 18.48 341.44 112.16 19.30 372.64 −1.76b 0.078 −1.41 24 0.172Cz 105.28 19.76 390.29 103.52 17.75 315.09 −0.192c 0.848 0.66 24 0.515Pz 115.36 25.89 670.24 116.32 27.30 745.23 −0.114b 0.909 −0.17 24 0.870b, c based on positive & negative ranks respectively, * significant if p < 0.050.

Grand averaged waveforms from the twenty five subjects are shown at Fig. 3 with their N100 andP300 ERP components at 19 electrode channels: Fp1, Fp2, F3, F4, F7, F8, C3, C4, T3, T4, T5, T6, P3,P4, O1, O2, Fz, Cz, and Pz.

3.4. Brain topography and cortical activation

A scalp topography map for the N100 ERP components showed nearly similar patterns for both Num-ber and Non-number plate conditions except for a more intense map at the occipital area in Numberplates, which is also reflected in the Non-significant increase in amplitude, as seen in the Figs 4 & 5.However, interestingly, a scalp topography map for the P300 components showed different patterns,such as in case of the Number plate: it is more intense in the left hemisphere, which is opposite theNon-number plate that was more intense in the right hemisphere.

Cortical activation patterns during Number (Fig. 4) and Non-number plate tasks (Fig. 5) in relationto N100 and P300 ERP components are shown in Table 5. Interestingly, in terms of Brodmann’s cor-tical area, the activation pattern of P300 ERP components for the Number plate was limited to twoBrodmann’s regions for each hemisphere, whereas for Non-number plates, there were three for eachhemisphere; moreover, inter- and intra-hemispheric differences were noticed in these two stimuli.

3.5. Connectivity analysis of the evoked response

For effective connectivity (Granger causality measure), a causal effect was observed, interestingly, inthe area of the left inferior frontal lobe (near F7) and temporal lobe (near T3), near the mid-parietal

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Table 3

Result of peak amplitude in μV (mean ± SD) for P300 ERP component

Number plate Non-number plate Wilcoxon Paired T -testSites Mean SD Variance Mean SD Variance Z-value p-value t df p-valueFp1 4.28 3.50 12.27 2.84 3.62 13.10 −0.256b 0.798 2.35 24 0.027*F3 3.08 3.18 10.09 2.77 2.35 5.51 −1.709b 0.088 0.49 24 0.632F7 1.48 2.73 7.47 1.45 2.43 5.92 −0.525c 0.600 0.04 24 0.966Fp2 4.91 3.80 14.48 4.21 4.01 16.09 −1.144b 0.253 1.38 24 0.179F4 3.19 1.79 3.19 3.23 1.65 2.73 −0.013b 0.989 −0.11 24 0.913F8 1.86 2.16 4.68 1.81 1.48 2.18 −0.094c 0.925 0.12 24 0.907C3 2.97 2.20 4.84 3.28 2.55 6.51 −0.309c 0.757 −0.62 24 0.542C4 3.85 1.89 3.59 4.20 1.95 3.78 −0.982c 0.326 −0.99 24 0.331T3 1.99 2.33 5.43 2.43 2.59 6.69 −1.520c 0.128 −0.79 24 0.44T4 2.25 3.02 9.15 3.76 3.94 15.55 −2.919c 0.004* −3.26 24 0.003*P3 2.82 2.40 5.77 2.88 1.81 3.28 −0.605c 0.545 −0.15 24 0.879T5 2.12 1.96 3.84 2.79 2.24 5.04 −1.359c 0.174 −1.38 24 0.179P4 2.83 1.88 3.55 3.31 2.08 4.34 −1.574c 0.115 −1.68 24 0.105T6 1.62 2.65 7.03 2.98 3.02 9.11 −2.839c 0.005* −2.66 24 0.014*O1 1.70 2.76 7.64 1.99 2.65 7.05 −1.063c 0.288 −0.63 24 0.533O2 1.24 2.50 6.24 1.61 3.01 9.04 −0.632c 0.527 −0.85 24 0.404Fz 3.35 2.51 6.30 3.06 2.32 5.38 −0.767b 0.443 0.84 24 0.409Cz 3.99 2.93 8.60 4.41 2.29 5.23 −0.740c 0.459 −0.71 24 0.485Pz 3.30 2.92 8.51 2.89 2.68 7.17 −0.955b 0.339 0.63 24 0.535b, c based on positive & negative ranks respectively, * significant if p < 0.050, * bold & italic significant at both Wilcoxon &paired t-test.

(Pz) and occipital lobe (O2) during Number plate tasks (Fig. 6), but the causal effect was almost solelylocalized in the occipital area near O1 during Non-number plate tasks (Fig. 7).

4. Discussion

We have investigated visual cognitive function using Ishihara colour vision test plates, where Numberand Non-number plates were the stimuli. Reaction time (RT), amplitudes and latencies of N100 and P300ERP components, brain topography and Granger causation (effective connectivity) were analysed. Therewere no significant differences between N100 ERP components in either stimulus, but Non-number platestimuli evoked significantly higher amplitudes and longer latencies of the P300 ERP component com-pared to Number plate stimuli. In the same way, the reaction time was slower in Non-number platetasks. Interestingly, a scalp topography map for P300 components showed different patterns of asymme-try, with a higher intensity in the left hemisphere for Number plate tasks and higher intensity in the righthemisphere for Non-number plate tasks. Similarly, the result of effective connectivity revealed that therewas a clear and strong interaction between occipital and left frontal cortices during Number plate tasks.During Number recognition, the direction of coupling was from the visual occipital area towards the lan-guage area of semantic coding, but the effect was restricted to the occipital area during the Non-numberplate task. Non-number plates evoked longer RTs, higher amplitudes and longer latencies of the P300ERP component at most of the electrode sites reinforced by two significant sites when compared withthe Number plate stimuli. Moreover, left/right asymmetry in the areas of cortical activation, interaction

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Table 4

Result of latencies in ms (mean ± SD) for P300 ERP component

Number plate Non-number plate Wilcoxon Paired T -testSites Mean SD Variance Mean SD Variance Z-value p-value t df p-valueFp1 508.8 160.43 25737.33 511.2 162.47 26397.33 −0.568b 0.570 −0.08 24 0.938F3 488.64 113.02 12772.91 522.24 112.24 12597.44 −1.339b 0.181 −1.60 24 0.124F7 416.16 131.12 17191.31 433.12 118.80 14114.03 −0.639b 0.523 −0.58 24 0.569Fp2 516.16 160.41 25729.97 488 155.05 24041.33 −0.834c 0.404 1.01 24 0.325F4 518.08 121.31 14716.16 511.04 116.47 13564.37 −0.557c 0.577 0.23 24 0.820F8 504.16 152.21 23168.64 512.64 146.27 21394.24 −0.341b 0.733 −0.27 24 0.789C3 501.12 132.44 17540.69 528.16 95.16 9055.307 −0.672b 0.502 −0.87 24 0.391C4 549.12 117.73 13859.36 544.16 93.18 8681.973 −0.757c 0.449 0.22 24 0.829T3 475.52 132.17 17468.43 483.84 147.53 21764.64 −0.390b 0.697 −0.40 24 0.691T4 508.16 138.56 19197.97 497.6 125.14 15660 −0.304c 0.761 0.31 24 0.761P3 468.64 127.63 16290.24 494.72 95.17 9056.96 −0.972b 0.331 −0.93 24 0.363T5 419.52 101.20 10241.76 438.4 119.78 14346.67 −0.900b 0.368 −0.90 24 0.375P4 456.64 116.85 13652.91 509.28 124.93 15606.29 −1.272b 0.203 −2.00 24 0.057T6 404.16 97.98 9599.307 459.36 125.62 15780.91 −1.758b 0.079 −2.04 24 0.053O1 401.76 119.86 14365.44 418.24 121.41 14740.11 −1.188b 0.235 −0.74 24 0.467O2 407.52 150.21 22564.43 423.04 134.20 18009.71 −1.413b 0.158 −0.56 24 0.584Fz 499.84 136.75 18700.64 503.36 130.76 17098.24 −0.061b 0.951 −0.10 24 0.921Cz 531.84 113.29 12835.31 548.64 89.61 8030.24 −0.486b 0.627 −0.68 24 0.506Pz 461.12 144.99 21023.36 521.12 122.52 15011.36 −2.100b 0.036* −2.07 24 0.049*b, c based on positive & negative ranks respectively, * significant if p < 0.050, * bold & italic significant at both Wilcoxon &paired t-test.

and direction of the effect of attention control during Number and Non-number tasks were demonstratedclearly in this study.

Reaction times (RTs) indicate the time interval of stimuli and voluntary response of the participants.Ghuntla et al. [1] stated that the reaction time is one of the substantial physiological parameters thatcontribute information about how fast and quickly the participant can respond to a stimulus. Faster RTsindicate quicker nervous system processing times with faster muscular movements (Spirduso et al. 1975)and are an indicator of higher cognitive function (Gavkare et al. [26]). Correspondingly, with our study,the reaction time was different during visual presentation tasks of Number and Non-number plates. Thereaction time was significantly slower for the Non-number plates than for the Number plates. Due to thesimilarly coloured dot shape design of Number and Non-number plates, numerical error (Miyahara [51])and confusion (Cosstick et al. [1] are obvious in Ishihara testing, even for trichromats; these difficultiesadded to visual searching and identification of the Non-number plate, because after encoding the stimuli,the subjects need to match the target with the memorized shape of the Arabic digit to achieve the accurateresponses for Non-number pseudoisochromatic plates for the decision made. The significant increase inthe mean of the RT indicated that the participants were taking more time to elicit a convenient intentionalresponse for the relatively complex Non-number plates compared with Number plates. Luck [1] notedthat reaction time is usually affected by the complexity of the stimulus.

The key ERP components of this study were the N100 and P300 ERP components. Different colours,shapes or any visual stimuli can evoke the N100 ERP component (Van Overwalle et al. [79]) whenthe subjects are previously experienced with this stimulus (Delb et al. [17]). N100 is the marker ofvisual perception, and P300 is an indicator of higher cognitive function of attention processing in the

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Fig. 3. Layout of Grand average waveform of ERP components at 19 scalp sites of electrode channels during presentationsession of Number (grey line) and Non-number plates (black line), small vertical solid and dotted bars are representing assegment time = 0 & stimulation presenting time respectively. Rectangle in the middle is the scale bar.

brain (Spence et al. 2010). No significant differences in N100 between Number and Non-number platesdemonstrated that selective attention and a sensory gating mechanism of attention are almost similar forthese two stimuli. Regarding the neural sources of N100, based on the result of a scalp topographicalmap, N100 was rather similarly distributed bilaterally in both stimuli, but with higher intensity in theNumber plates at occipital (O1 and O2), parietal (P3, P4, and Pz) and frontal (Fp1, Fp2, F4, and F8)locations. Though this finding was not significant, it was consistent with other studies (Hopf et al. [33];Eimer [21]; Chayer and Freedman [11]).

The P300 ERP component can be evoked during visual stimulation (Hansenne [31]; Patrick et al.[57]). Significant differences in P300 between Number and Non-number plates suggested that duringthe Non-number plate task, the subjects allocate more attention and memory processing than in the

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Fig. 4. EEG waveform, scalp topography and cortical activations during Number plate task. Upper left panel of figure (A),EEG time series of all 128 channels, y-axis and x-axis represented amplitude (μV) & time (ms) respectively, white dottedline represented stimulation present time marked at 0 ms and red line denoted as the peak of N100 ERP response marked at104 millisecond, upper right panel showed scalp topographic map plotted from N100 peak. Lower panel of figure (A), corticalactivations of N100 peak response are displayed on MRI 3D view with colour bar (left side) and on the axial MRI viewer withcolour bar (right side). Lower left panel of figure (B), EEG time series of 128 channels, y-axis and x-axis represented amplitude(μV) & time (ms) respectively, white dotted line represented stimulation present time marked at 0 ms and red line denoted thepeak of P300 ERP response marked at 492 millisecond, upper right panel showed scalp topographic map plotted from P300peak. Lower panel of figure (A), cortical activations of P300 peak response are displayed on MRI 3D view with colour bar (leftside) and on the axial MRI viewer with colour bar (right side).

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Fig. 5. EEG waveform, scalp topography and cortical activations during Non-number plate task. Upper left panel of figure (A),EEG time series of all 128 channels, y-axis and x-axis represented amplitude (μV) & time (ms) respectively, white dottedline represented stimulation present time marked at 0 ms and red line denoted the peak of N100 ERP response marked at 100millisecond, upper right panel showed scalp topographic map plotted from N100 peak. Lower panel of figure (A), corticalactivations of N100 peak response are displayed on MRI 3D view with colour bar (left side) and on the axial MRI viewer withcolour bar (right side). Lower left panel of figure (B), EEG time series of 128 channels, y-axis and x-axis represented amplitude(μV) & time (ms) respectively, white dotted line represented stimulation present time marked at 0 ms and red line denoted thepeak of P300 ERP response marked at 540 millisecond, upper right panel showed scalp topographic map plotted from P300peak. Lower panel of figure (A), cortical activations of P300 peak response are displayed on MRI 3D view with colour bar (leftside) and on the axial MRI viewer with colour bar (right side).

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Table 5

Cortical activation patterns during Number and Non-number plate viewing in relation to N100 and P300 ERP components withcloser EEG electrode positions (19 electrodes in 10–20 international system)

ERP components MNI x, y & zcoordinates

(millimetres)

Brodmann’sarea (BA),

L-left,R-right

Cortical regions EEGelectrodepositions

NumberN100 −54 −57 14 LBA39 Inferior Parietal Lobule − Intraparietal sulcus −

Angular gyrusP3, T5

−56 −28 14 LBA41 Temporal lobe − Auditory cortex T317 70 6 RBA10 Prefrontal Cortex Fp2

P300 −44 −29 14 LBA40 Inferior Parietal Lobule − Supramarginal gyrus C3, P3−47 17 0 LBA45 Inferior Frontal gyrus − Pars Triangularis (Broca’s Area) F7, F350 −49 24 RBA20 Inferior temporal, Fusiform and Parahippocampal gyri T4, F817 69 2 RBA10 Prefrontal cortex Fp2

Non-numberN100 −28 −94 7 LBA18 Occipital lobe − Secondary visual cortex O1

−19 −61 5 LBA23 Posterior Singulate Gyrus Pz

P300 −55 −56 14 LBA39 Inferior parietal lobule − intraparietal sulcus − Angulargyrus

P3, T5

−56 −30 14 LBA22 Superior Temporal Gyrus (Wernicke’s area) T3−10 −76 14 LBA17 Occipital lobe − Primary visual Cortex O146 −78 14 RBA19 Occipital Lobe (Secondary visual cortex) O2, T658 −49 14 RBA39 Inferior parietal lobule − intraparietal sulcus − Angular

gyrusP4, T6

45 −25 14 RBA40 Inferior parietal lobule (Supramarginal gyrus) C4, P4

Number plate task (Polich [60]). Elevated P300 amplitudes were found with more attention (Russo et al.[68]), and they indicated higher consciousness (Dehaene et al. 2003) with quality of selection (Jonkmanet al. [37]). Reduced amplitudes and longer latencies were found during periods of less attention (Kleinet al. 2010; Brookhuis et al. [8]), with longer processing times. In our study, Non-number plate stimulievoked higher amplitudes and longer latencies of the P300 ERP component at most of the electrodesites, and this result means that the subjects paid more voluntary attention to quality selection, whichtook longer information processing time during Non-number plate stimuli compared with the Numberstimuli.

Concerning the neural sources of P300, based on the result of the scalp topographic map, interestingly,the magnitude of distribution for the Non-number plate is more in the right hemisphere, whereas for theNumber plate, it is in the left hemisphere, indicating left/right asymmetry of a neural response pattern ofthese two stimuli in the brain. In addition, based on the result of the cortical activation pattern, remark-ably, some brain areas are commonly activated during Number and Non-number plate tasks, such as thebilateral inferior parietal lobule and temporal lobe, but, strikingly, the frontal lobe activation especiallyin the left inferior frontal gyrus (Broca’s area) was found during only the Number plate task. Numberrecognition was not only a process of visual perception and attention, but it was also related to the higherlevel of cognitive function of language. This propensity was further supported by the effective connectiv-ity analysis of this study and from a previous study in blind people (Abboud et al. [1]). Neural correlatesand functional measurement of Number representations are complex occurrences when their semantic

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Fig. 6. Effective connectivity visualization from grand averaged wave form during presentation of Number plates of Ishiharacolour vision test from all recorded 128 channels of EGI system, but circle is marked for 19 electrode sites in 10–20 internationalsystem.

category is assimilated with other shape and colour categories. Number recognition, which can be inthe abstract form of numerosity as the identification of the magnitude of Number that is believed to beinherent, can be in a visual Number shape (e.g., Arabic digit) that is learned culturally after birth througheducation. Activation of bilateral occipitotemporal cortex for the shape coding of Non-numbers insteadof Numbers is found in this study. Conversely, bilateral occipitotemporal activation for shape coding ofArabic digits and for other Number symbols was found in a study of neurophysiological evidence for aneural code for Numbers, but this was in the macaque monkey’s brain (Piazza and Eger [58]). However,in our study, the right inferior temporal cortex activation during Number plate tasks is rather consistentwith the findings of others (Shum et al. [71]; Grotheer et al. [30]). In addition, during Number platetasks, the language area (LBA45) was activated, which is quite similar to a study of Arabic Numberreading (Roux 2008); nonetheless, language area activation never occurred during Non-number tasks inthis study. Taken together, however, the visual recognition of Numbers dissociates from the recognitionof Non-numbers in both behavioural data and at the neural level, as found in a study of a neural doubledissociation between letter and Number recognition (Park et al. [56]).

Granger causality analysis has received much attention in the study of language processing and inter-actions of brain areas in a large neural network (Gow et al. 2012). Throughout connectivity analysis, our

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Fig. 7. Effective connectivity visualization from grand averaged waveform during presentation of Non-number plates of Ishiharacolour vision test from all recorded 128 channels of EGI system, but circle is marked for 19 electrode sites in 10–20 internationalsystem.

results of effective connectivity revealed that there was a clear and strong interaction between occipi-tal (O1 & O2) and left lateral frontal cortices (near F7 EEG electrode) during the Number plate tasks.The direction of coupling was from a visual occipital area towards a language area of semantic codingduring Number recognition, showing a stimulus-driven bottom-up effect in the defined neural networks.However, this effect was restricted to the occipital area during the Non-number task.

5. Conclusion

In summary, to assess attention during numerical information processing, we have investigated thevisual cognitive function in ERP waveforms using the Ishihara pseudoisochromatic plates. The resultssuggested that visual identification of two stimuli were almost identical, but the Number informationprocesses spontaneously and was faster than the processing of Non-number information. Attention loadwas relatively higher and delayed in the decision-making process during the Non-number task. Moreinterestingly, distributions of the source of attention control and the effects of attention on informationprocessing were different in Number and Non-number tasks. Finally, this is the first study using easilyadministrable and readily available pseudoisochromatic plates to evaluate visual numerical cognition.

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These plates could be an important test tool for attention deficit and connectivity disorders in anatomi-cally and physiologically distinct brain networks.

Acknowledgement

This work was supported by Short term grant of Universiti Sains Malaysia (USM) (304/PPSP/61311092) for the author T.B.

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