A left-to-right bias in spatial numerical associations with dots and symbols

A left-to-right bias in spatial numerical associations with dots and symbols | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results A left-to-right bias in spatial numerical associations with dots and symbols View ORCID Profile Eccher Elena , Caparos Serge , Buiatti Marco , Manuela Piazza , View ORCID Profile Giorgio Vallortigara doi: https://doi.org/10.1101/2025.07.28.666512 Eccher Elena 1 CIMeC, University of Trento ( Italy ) Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Eccher Elena For correspondence: elena.eccher-1{at}unitn.it Caparos Serge 2 Laboratoire DysCo , Université Paris 8, Saint-Denis, France 3 Institut Universitaire de France , Paris, France Find this author on Google Scholar Find this author on PubMed Search for this author on this site Buiatti Marco 1 CIMeC, University of Trento ( Italy ) Find this author on Google Scholar Find this author on PubMed Search for this author on this site Manuela Piazza 1 CIMeC, University of Trento ( Italy ) Find this author on Google Scholar Find this author on PubMed Search for this author on this site Giorgio Vallortigara 1 CIMeC, University of Trento ( Italy ) Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Giorgio Vallortigara Abstract Full Text Info/History Metrics Preview PDF Abstract Number and space are intertwined in human and non-human cognition. A substantial body of research has shown that numerical magnitudes are mentally represented along a spatial continuum, akin to a “mental number line”. Some suggested that its directionality is determined by culture and context. Nevertheless, evidence from preverbal infants and non-human animals indicates a consistent left-to-right directional mapping of numerosities, suggesting a biologically predisposed Spatial-Numerical Association (SNA) that may precede cultural factors. A recent study has shown that an implicit association between “left” and “small” emerges not only in literate adults, but also in unschooled indigenous populations and preschool Western children. This finding suggests that SNAs may originate from universal innate mechanisms rather than being solely a by-product of cultural learning. However, while the study reported a strong association between “left” and “decreasing” numerosity, there was only a very weak association between “right” and “increasing” numerosity. This asymmetry was not predicted and needs further investigations to be understood. Here we further investigated the number/space association in implicit tasks in educated Western adults by using more variable and better controlled stimuli compared to the ones used in the previous study, and also manipulating stimulus format, using both dot patterns and symbolic numbers. Fifty-one adult participants performed a numerical comparison task within a Go-No-Go paradigm on subsequent pairs of visual stimuli (with ratios spanning from 0.75 to 0.94) that could appear on the left or on the right of a fixation point and completed two different tasks: “press when more” and “press when less”. Results revealed distinct response patterns depending on the symbolic/non-symbolic nature of the stimuli. When non-symbolic stimuli were used, a consistent association between small numerosities and the left side and large numerosities and the right side was observed. When symbolic stimuli were used, only an association between large numerosities and the right side was observed. These findings support the hypothesis that SNAs may reflect a biological predisposition associated with brain asymmetry, and that task demands may interact with the underlying hemispheric specializations. INTRODUCTION Animals are constantly taking into account numerosity information for their survival, from hunting strategies to interaction with mates or predators, and this is observed widely across the animal kingdom, from humans to invertebrates ( Bortot et al., 2021 ; Butterworth et al., 2018 ; Giurfa, 2019 ; Nieder, 2019 ; Vallortigara, 2018 ). The Approximate Number System (ANS), or Number Sense , has been identified as the putative system that enables individuals to perceive, estimate, and internally manipulate numerical quantities in a non-symbolic manner ( Dehaene, 2011 ). This “Core System” for numbers would not emerge from formal learning, but it would rather be rooted in our evolutionary history and available since birth ( Di Giorgio et al., 2019 ; Lorenzi et al., 2025 ; Spelke, 2000 ). One of the main features of the ANS is that, similarly to other perceptual abilities, it obeys Weber’s law, being numerosity discrimination less accurate with increasing quantities (so-called size effect ) and with smaller differences among them (so-called distance effect; Ditz & Nieder, 2016 ; Sasanguie et al., 2017 ; Skorupski et al., 2018 ; see also Nieder, 2019 for a review). These two combined determine that ANS works solely on a ratio-dependent limit: the ability to distinguish between two numerosities depends on their ratio. At the neural level the ANS has been linked to networks centered on the intraparietal sulcus (IPS) and prefrontal cortex in the mammalian brain (review in Piazza & Eger, 2016 ) and in other pallial areas in the avian ( Kobylkov et al., 2023 ; Nieder, 2021 ) and zebrafish ( Luu et al., 2024 ) brains, where number-selective neurons, which activity also obeys to Weber’s law, have been described. Functional neuroimaging has repeatedly shown that in humans the IPS is recruited during non-symbolic number processing tasks, such as estimating the number of visual objects or comparing sets of differing magnitudes ( Piazza et al., 2004 ; Castaldi et al., 2019). The horizontal portion of IPS (hIPS) responds to numerosity irrespectively of stimulus modality, e.g., visual or auditory ( Piazza et al., 2006 ), or presentation mode, e.g., simultaneous or sequential ( Dormal et al., 2010 ). Moreover, it has been shown that IPS activity is modulated by numerical distance in adaptation paradigms ( Piazza et al., 2004 , 2007 ), reflecting the same ratio-dependent processing found in behavioral responses (see Piazza & Eger, 2016 for a review). Neuroimaging studies also suggest a degree of hemispheric specialization within the ANS. Exact calculation seems to be more affected by damage to the left hemisphere, while approximate numerical judgments are affected by damage to the right hemisphere ( Dehaene & Cohen, 1991 ). Piazza et al., (2007) found that human subjects exhibited reduced left IPS activation when confronted with non-symbolic deviants among symbolic stimuli, suggesting that the neuronal population of the two hemispheres might be differently involved in the processing of non-symbolic versus symbolic representation of numerosities. Specifically, the acquisition of number symbols might reshape numerical representations, particularly in the left hemisphere ( Piazza et al., 2007 ; Verguts & Fias, 2004 ). This idea is also supported by the evidence coming from developmental studies. While a right lateralized IPS activity is observed in response to numerosity in infants ( Hyde et al., 2010 ; Izard et al., 2008 ) and in young children ( Cantlon et al., 2006 ), a shift through the left IPS is observed as children get acquainted with symbolic stimuli ( Rivera et al., 2005 ). It therefore appears that, as language and symbolic number systems develop, the early right-lateralized response to numerical quantity evolves into a more bilateral pattern, reflecting the growing role of the left hemisphere in symbolic number processing ( Ansari & Dhital, 2006 ). Another lateralized aspect of numerosity processing is associated with the phenomenon of Spatial-Numerical Associations (SNA), in which numerical values are mapped onto spatial dimensions. One example is provided by the Spatial-Numerical Association of Response Codes (SNARC, Dehaene et al., 1993 ), where subjects are faster to complete a parity judgment task with their left hand in response to small numbers and with their right hand in response to large numbers. On the contrary, Iranian participants showed either the opposite or no effect at all ( Dehaene et al., 1993 ). The authors interpreted these results as evidence that numbers are spatially organized on a so-called Mental Number Line (MNL, Galton, 1880 ; Restle, 1970 ), and that its orientation is determined by the direction of reading/writing habits. In the following years, several studies seemed to confirm this cultural explanation for the direction of the SNA, especially stressing that the directionality of reading and writing might account for the observed effects. For example, left-to-right readers often show a left-to-right SNARC effect, while right-to-left readers may exhibit reversed or absent effects ( Fischer et al., 2009 ; Fischer & Rottmann, 2005 ; Göbel et al., 2011 ; Nuerk et al., 2004 ; Zebian, 2005 ; Zohar-Shai et al., 2017 ). Moreover, a study conducted in an indigenous population with no writing system and only an oral tradition supported the idea that, in the absence of cultural references, SNAs may not emerge, as participants showed no consistent spatial-numerical mapping when asked to order numerosities on a line. ( Pitt et al., 2021 ). However, a concurrent line of research proposes that the SNA might not be determined by cultural factors, but rather it can be modulated by them. This position is determined by the fact that some forms of SNA are present in non-human animal species (that clearly lack knowledge of written language or culture-based counting or ordering practices), such as monkeys ( Adachi, 2014 ; Brannon & Terrace, 1998 ; Rugani et al., 2024 ), birds ( Rugani et al., 2010 , 2015 , 2020 ), and even bees ( Giurfa et al., 2022 ). Similarly, preverbal infants and neonates exhibit a consistent left-to-right mapping, suggesting that, also in humans, space-number mappings might start well before the acquisition of spatialized cultural practices ( Bulf et al., 2016 ; De Hevia et al., 2014 ; de Hevia, Veggiotti, et al., 2017 ; Di Giorgio et al., 2019 ). It has been suggested that this spontaneous left-to-right spatial-numerical mapping could be the result of lateralized brain functions. Vallortigara (2018) hypothesised that SNA may stem from hemispheric specialisation for approach and withdrawal behaviours, with the left hemisphere processing positive-valence (approach) stimuli and the right hemisphere processing negative-valence (withdrawal) stimuli ( Davidson, 2004 ). In this view, increasing numerosities, typically associated with positive valence in experimental tasks (e.g., associated with rewards), would bias attention to the right hemispace, while decreasing numerosities, linked to negative valence, would shift attention to the left hemispace ( Vallortigara, 2018 ). This growing body of research has led to the hypothesis that, in human adults, SNA may arise from a combination of biological and culturally-mediated mechanisms ( Guida et al., 2018 ). Thus, while SNA might be universal in its origin, cultural context, individual experiences, and task demands can modulate its specific appearance. In particular, the demands of the tasks used to study SNA might influence the possibility of eliciting different aspects of it, either in favour of the biological predisposition or in favour of the cultural acquisitions. Evidence from implicit SNA tasks in human adults, similar to those found in non-human animals and preverbal infants, suggests a role for biologically grounded spatial-numerical associations, whereas more explicit tasks may rely on culturally acquired spatial-numerical mappings shaped by reading and writing habits ( Eccher et al., 2025 ). To test this, in our previous work, we compared performance on two tasks across three groups with different literacy exposure: Italian adults (high literacy), Italian preschoolers (minimal literacy), and Himba adults (an indigenous population from northern Namibia with an oral culture and no writing system). In the explicit card-ordering task, where participants were consciously aware of both numerical content and spatial layout, only Italian adults showed a consistent left-to-right SNA aligned with their cultural reading direction, while preschoolers and Himba participants showed no directional bias despite favouring lateral arrangements. In contrast, in the implicit Go/No-Go task, where test stimuli spatial position was irrelevant, all three groups, including the Himba, exhibited similar SNAs, suggesting that implicit number-space associations may rely on biologically rooted mechanisms rather than on acquired cultural practices ( Eccher et al., 2025 ). While our previous study does indeed suggest that a dissociation between explicit and implicit form of SNA might reflect the different contributions of biological predispositions and cultural acquisitions, an interesting and unexpected asymmetrical congruency effect during the implicit task was observed: participants performed faster and more accurately when numerically smaller stimuli appeared in the left visual field in the decreasing task, while no significant effect was observed for larger stimuli appearing in the right visual field in the increasing task. This pattern held across differences in participants’ age and cultural background. We hypothesized that this asymmetry may stem from the non-symbolic nature of the stimuli we used and related it to the typical right-hemispheric lateralization of the ANS. According to this interpretation, the right hemisphere may have been more strongly engaged during non-symbolic numerosity processing, facilitating performance in the left visual field during the decreasing task and masking the effect in the right visual field during the increasing one. However, if this brain asymmetric effect was the only factor determining subjects’ behaviour, we should have observed not a null effect but rather a reversed congruency effect in the increasing task. Thus, the fact that we did not observe it, suggests that the results cannot be solely explained by the hemispheric superiority for non-symbolic numerosity. We thus hypothesized that the asymmetry of our effect could also be partially due to an inherent difference in difficulty across the increasing and decreasing tasks. In the literature, there is indeed evidence of a broader cognitive advantage for processing increases (see also, for example, the so-called “addition advantage”, Barth et al., 2006 , 2008; Gilmore & Spelke, 2008 ; Kamii et al., 2001 ). Given the adaptive advantages of rapidly detecting increases in critical resources, the human brain may be evolutionarily biased toward rising numerosities. For example, it is well known that since early infancy, we have an advantage for processing increasing vs. decreasing ordinal sequences (de Hevia, Addabbo, et al., 2017 ; Macchi Cassia et al., 2012 ), and asymmetry emerges also in adults when comparing task instructions in SNARC paradigms ( Patro et al., 2015 ; Patro & Haman, 2011 ; Shaki et al., 2012 ). It is therefore possible that facilitating mechanisms for processing increasing changes in numerosity ( Ben-Meir et al., 2012 ; Ganor-Stern, 2015 ; Müller & Schwarz, 2008 ) led to faster responses for the increasing task in our first study, which might have masked the more subtle SNA effect. In sum, it is possible that in our original study, SNA-related mechanisms may have been obscured in the increasing task condition, either due to differential hemispheric recruitment or to task demands or both. To test these hypotheses, we designed a new study with a modified version of our original task. While retaining the core design, we introduced two critical manipulations. First, we varied the numerosity presentation modality by including both symbolic and non-symbolic stimuli, allowing us to test the impact of the representational format. Specifically, we expected to reverse the asymmetrical pattern observed in Eccher et al. (2025) , such that symbolic stimuli would show an advantage in the right hemispace reflecting left-hemispheric dominance for symbolic processing. Second, we increased the difficulty of the numerical comparisons, hypothesizing that more cognitively demanding tasks would reduce the impact of the facilitatory effect of the increasing task, and thus enhance the likelihood of detecting SNA patterns. METHODS The study adhered to the principles outlined in the Declaration of Helsinki. All Italian participants gave written informed consent after receiving a comprehensive explanation of the study’s purpose and procedures. A small monetary reward was provided for their participation. In the same session, we conducted three separate experiments, each utilizing a distinct modality of stimulus presentation. The task was modeled after the Numerosity Comparison Task described in our earlier study ( Eccher et al., 2025 ), with minor procedural variations (see below). Participants Fifty-one healthy adults from the Trentino region in Italy (40 females; mean age = 24.63 ± 5.25 years) were recruited through a social media group affiliated with the University of Trento. All participants completed the Dots experiment, while thirty-nine of them also took part in the Digits and Words experiments. Stimuli We included one non-symbolic and two symbolic stimulus formats, each used in a distinct task. In all conditions, the reference stimulus was 16, and the test stimuli were 12, 13, 14, 15, 17, 18, 19, and 20. While the reference stimulus was always presented at the center of the screen, the test stimuli were displayed 15° to the left or right of the central fixation point. Dots The non-symbolic stimuli consisted of randomly arranged black squares of a constant size (1.3 x 1.3 degrees of visual angle) presented against a white background of 17 x 17 degrees, similarly to the paradigm used in Eccher et al., 2025 ( Fig. 1A ). Download figure Open in new tab Figure 1. Schematic representation of paradigm and stimuli Panel A) Stimuli used in the Dots experiment. On the top, from left to right, numerosities from 12 to 15; in the center, reference numerosity 16; in the bottom, from left to right, numerosities from 17 to 20. Panel B) Schematic representation of the paradigm design, from top to bottom, an example trial with the three different types of stimuli used (Dots arrays, Arabic digits, and Number Words). Digits Symbolic stimuli in the digit format were Arabic numbers shown in white Arial font (85 pt) on a black background. Words Symbolic stimuli in the word format were displayed as capitalized letters in white Arial font (57 pt) against a black background. Procedure Participants were tested in a dimly lit lab at the Center for Mind/Brain Sciences of the University of Trento. Stimuli were shown on a computer monitor, positioned about 50 cm from the participant. The full session lasted around 40 minutes, and participants were allowed to take breaks between each task, if needed. For each stimulus modality (Dots, Digits, Words) subjects performed two tasks: Increasing and Decreasing (see below). Each stimulus modality was tested independently, meaning that no task involved a comparison between two different stimulus modalities. To avoid priming effects, the Dots task was always performed first. The symbolic tasks (Digits and Words) followed, with their order counterbalanced among participants. The order of increasing/decreasing tasks was also counterbalanced across subjects. The reference stimulus was fixed at “16” in every trial. Each trial began with a 1-second central fixation cross, followed by the reference stimulus for 500 ms. After a 200 ms blank screen, the test stimulus appeared on either the left or right side. It remained visible until the participant responded or until 3 seconds elapsed ( Fig. 1B ). Participants were instructed to press a central key as quickly as possible, using their dominant hand, only if the test stimulus had fewer items than the reference (Decreasing Task) or more items (Increasing Task). Feedback was given throughout the entire experiment, using a green happy face for correct answers and a red sad face for incorrect ones, both displayed for 1 second. Each condition (increasing and decreasing) included 50 trials: 32 Go trials (8 per numerosity pair) and 18 No-Go trials. This imbalance across conditions mirrored the one present in the original experiment ( Eccher et al, 2025 ). Statistical analyses All data analyses and graphical outputs were carried out using R (version 4.1.3) within the RStudio environment. An alpha level of.05 was adopted for determining statistical significance. For effect size reporting, we computed the effect size r for Wilcoxon tests (i.e., )For ANOVAs, partial eta squared served as the measure of effect size. Reaction times (RTs) were gathered in Go trials under both congruent and incongruent conditions for each participant. As in Eccher et al., 2025 we defined the congruency condition with respect to the left-to-right space-to-number mapping: targets that were smaller than the reference and appeared on the left, as well as those that were larger and appeared on the right, were classified as congruent. Conversely, smaller targets on the right and larger targets on the left were considered incongruent. Prior to the statistical analysis, outlier trials were removed for each experimental condition (Dots, Digits, Words). Specifically, trials were excluded if RTs fell below the first quartile minus 1.5 times the interquartile range (IQR) or exceeded the third quartile plus 1.5 times the IQR. First, we examined the influence of numerical distance between the reference and test stimuli on reaction times using a 3 (Format) × 4 (Numerical Distance) repeated-measure ANOVA. Then, we conducted a repeated measures ANOVA with three within-subject factors: Format (Dots, Digits, Words), Task Instruction (Increasing, Decreasing), and Congruency (Congruent, Incongruent). In cases where Mauchly’s test indicated a violation of the sphericity assumption (p ≤ .05), the Greenhouse-Geisser correction was applied to the affected factors, and adjusted results are reported accordingly. Wilcoxon signed-rank tests were used for post hoc comparisons between congruent and incongruent conditions within each Task and Stimulus format. To replicate the analytical approach used in Eccher et al, 2025 , we also calculated the RTs congruency effect for each task using the formula: We then performed a 3 (Format) × 2 (Task Instruction) repeated measures ANOVA to examine the effects of experimental condition and task instruction. The congruency effect was further evaluated against zero using a two-tailed Wilcoxon signed-rank test. It is important to note that, due to incomplete participation across all experimental conditions, the repeated measures ANOVAs were limited to the 39 participants who completed every experiment. Instead, post-hoc analyses were conducted using the full available dataset for each condition, as indicated by the degrees of freedom in the results tables. Finally, to be able to better discuss the results in comparison to our previous findings, two-tailed two-sample Wilcoxon rank-sum tests were carried out to compare the reaction times from the present work with the data from Eccher et al., 2025 (see Supplementary Materials). Results As a sanity check to ensure that the task involved the ANS, we investigated the distance effect as its main signature. To do so, we performed a 3×4 repeated measure ANOVA which revealed a main effect of the Numerical Distance (F (1.47, 54.32) = 93.471, p <.001, ηp 2 2 = 0.716), as expected, and of Format (F (1.44, 53.39) = 65.270, p <.001, ηp p 2 = 0.638). Numerical Distance also interacted with Format (F (1.69, 62.39) = 16.146, p <.001, ηp p 2 = 0.304, see Figure S1 ). We therefore confirmed the involvement of the ANS, especially in the non-symbolic task ( Table 1 , Fig. S1 ) View this table: View inline View popup Download powerpoint Table 1. Means and Standard Errors of the mean for each numerical distance in each format Given the limited number of trials per subject for each test numerosity, and our primary interest in the overall direction of numerosity changes (which in the current paradigm was equivalent to Task Instruction), we then collapsed reaction times across the different levels of test numerosity within each of the two task instructions. This allowed us to examine the effect of congruency between the direction of numerosity change and the type of stimulus format ( Fig. 2 ). Download figure Open in new tab Figure 2. Mean reaction times Reaction Times were measured for each Congruency Condition for each Format and Task Instruction. In the graph, mean values and standard errors of the mean are reported. Two-tailed two-sample paired Wilcoxon signed-rank test statistic, significance levels are defined as follows: * = pvalue <0.05, ** = pvalue =.01, *** = pvalue <0.001 The 3×2×2 Anova revealed a main effect of Format, Congruency condition, and a significant interaction between the Format*Task Instructions, Task Instructions*Congruency Conditions, Format*Task Instruction*Congruency Condition ( Table 2 ). View this table: View inline View popup Download powerpoint Table 2. Three-Way Analysis of Variance of Reaction Times for each Format by Task instruction and Congruency condition. Greenhouse-Geisser correction for the violation of the sphericity assumption has been applied. Significant p value for.05 significance level in bold We then conducted pairwise comparisons between the two Task Instructions within each Format to test whether detecting increasing changes was facilitated. A significant difference emerged only for the non-symbolic format ( Table 3 ). View this table: View inline View popup Download powerpoint Table 3. Reaction Times comparison between the two Task instructions for each Format. Significant p value for.05 significance level in bold Given the significant triple interaction of Format *Task instruction*Congruency Condition, we also ran the pairwise comparisons between congruent and incongruent congruency conditions for each Format and Task Instruction ( Table 4 ). View this table: View inline View popup Download powerpoint Table 4. Reaction Times comparison between the two Congruency conditions for Task instruction for each Format. Significant p value for.05 significance level in bold Similarly to the previous study, we also tested the Congruency Effect. The 3×2 Anova revealed no main effects of Format (F (2, 76) = 2.850, p value =.064, η 2 p = 0.070), while a significant main effect of Task (F (1,38) = 6.069, p value =.018, η 2 p = 0.138), and interaction emerged (F (1.66, 63.27) = 5.046, p value =.013, η p 2 = 0.117). Comparison against chance level revealed a significant congruency effect for both the decreasing and increasing Task instructions in the Dots experiment. On the other hand, a significant congruency effect for the increasing Task only was found in the Digits and Words experiment ( Table 5 , Fig. 3 ). View this table: View inline View popup Download powerpoint Table 5. Statistical analysis against chance level for Congruency Effect for Format and Task, significant pvalue for.05 significance level in bold Download figure Open in new tab Figure 3. Reaction Times congruency effect Congruency Effect for each Task Instructions and Format. Means and standard errors of the mean are reported. Statistical significance for Two-tailed one-sample Wilcoxon signed rank test against chance level (µ = 0) is reported as follows: * = pvalue<.05, *** = pvalue <.001. Discussion In our previous work, we demonstrated that when using an implicit task, SNAs emerge independently from different cultural backgrounds, specifically, independently from reading/writing habits ( Eccher et al., 2025 ). However, while we found that small numerosities were responded to more efficiently when they were presented on the left hemifield (thus emerging in our “decreasing”, or “press when smaller” task), we failed to detect a convincing symmetrical facilitation for large numerosities presented on the right visual hemifield (that should, but did not, emerge in our “increasing”, or “press when more” task). We hypothesised that this asymmetry might have been a consequence of either of two factors (or their combination): first, numerosity tends to be better represented in the right hemisphere, masking the congruency SNA effect to emerge when stimuli were presented in the right hemifield; second, it is generally known that increasing changes tend to be faster and more automatically perceived, thus potentially masking congruency SNA effect to emerge when subjects performed this task ( Ben-Meir et al., 2012 ; Ganor-Stern, 2015 ; Müller & Schwarz, 2008 ). In the current study, to test these hypotheses, we modified the original paradigm in two ways: first, to reduce the automaticity in the detection of increasing numerosities and thus make the task more difficult, we introduced more numerosities at test, spanning 4 levels of distance from the reference stimulus; second, to verify the idea that some of the asymmetry observed in the previous work might have been due to right hemispheric superiority in non-symbolic number processing, together with dot patterns we also presented digits and words, symbolic stimuli that are known to elicit a stronger left-hemispheric lateralization. The first analyses of reaction times confirmed that overall our stimuli were more difficult to evaluate compared to those used in the initial study in both task Instructions ( Eccher et al., 2025 ,(see Supplementary Materials, Table S1 and Fig. S2 ), and that, as expected, they were modulated by distance, with slower responses for small distances ( Table1 and Fig. S1 ) and faster for large ones. Indeed, and potentially as a consequence of such an increase in difficulty, with these novel dot stimuli we found a congruency effect in both task conditions, indicating that in this implicit task decreasing numerosities are faster responded to when they appear on the left rather than the right (replicating Eccher et al., 2025 ), and increasing numerosities are responded to faster when they appear on the right compared to the left. With respect to the other types of stimulus format (digits and number words), the results are in line with our predictions: for both digits and number words, we observe a faster response when increasing numbers are presented on the right vs. left, and no facilitatory response when decreasing numbers are presented on the left. ( Figure 3 ). It seems likely that hemispheric specialization for one or the other numerical stimulus format ( Piazza et al., 2007 ) can interfere with the ability to detect SNA using this paradigm. Symbolic stimuli preferentially activate the left hemisphere, leading to right hemispace attention during the task, thus masking the SNA effect in the decreasing condition. Nevertheless, this left hemisphere dominance alone cannot explain the effect observed, as notably, no significant effect was found for the incongruent condition in the decreasing task (i.e., right hemispace). Rather, as it happened in Eccher et al., 2025 , these findings seem to be the result of the combined effect of ANS hemispheric specialization and SNA. Moreover, with respect to our hypothesis about inherited differences in detecting increasing and decreasing changes in numerosity, we found a significant difference between the two tasks in response to the non-symbolic stimuli only. Indeed, we observed faster reaction times in the increasing task ( Table 2 ), similarly to our original study. However, while in Eccher et al., 2025 the faster responses in the increasing task could have masked the SNA effect, here, with slower overall RTs, we were able to find a congruency effect in both task conditions (although with a smaller effect size), likely due to higher task demands. Specifically, the numerical comparisons used in this study (spanning from 0.75 to 0.94 ratios) were more difficult than those in the original paradigm (0.3 ratio), resulting in overall slower RTs (see Supplementary Materials, Fig. S2 and Table S1 ). Supporting this interpretation, previous research has shown that the strength of the SNARC effect is positively correlated with reaction times, with slower responses yielding stronger spatial-numerical associations ( Cipora et al., 2019 ; Gevers et al., 2006 ). However, our findings present a more complex picture of RTs and SNA correlations. Indeed, in the Arabic digits task, participants showed a strong SNA effect despite shorter RTs. Moreover, a significant difference between RTs in increasing and decreasing tasks ( Table 1 ) is found only in the non-symbolic task, which, nevertheless, is also the task where we found SNA effect in both conditions. On the contrary, in the symbolic tasks, where there is no difference in RTs between increasing and decreasing tasks ( Table 1 ), a SNA effect emerges only in one of the tasks, specifically the increasing one. Thus, these results seem to suggest that task demands, at least as reflected by RT durations, do not straightforwardly correlate with the SNA phenomenon in this type of task. It is possible that the relationship between task demands, RTs, and SNA might not be linear, but instead could follow a reversed U-shaped curve (e.g., Yerkes & Dodson, 1908 ). According to this hypothesis, there may be an optimal response time window within which the SNA effect emerges most clearly. In general, the interaction between RTs and hemispheric activity, depending on stimulus format, might be an explanation for this complex set of results. In conclusion, our results provide further evidence that SNA is a complex phenomenon shaped by both biological and cultural factors. In this study, we found that left-to-right SNA in human adults emerge differently depending on the modality of stimulus used, as specific format notations might influence attentional shift in favour of one hemispace over the other. While these results offer new insights, further research is needed to deepen our understanding of the relationship between stimulus characteristics, task demands, and SNA, and to clarify the neural mechanisms underlying these effects. Contributions G.V. provided funding and resources; E.E., G.V., and M.P. jointly conceptualized the study; G.V., M.P., and S.C. developed the methodology while E.E. developed the stimulation software; E.E., collected the data; E.E., M.B., and M.P. conducted the data analysis; E.E. wrote the original draft, and all the authors contributed to the final version of the manuscript. Supplementary Materials Download figure Open in new tab Figure S1. Reaction Times for numerical distance between reference and stimulus test, in absolute value, for each Format. In the graph, the means and the standard error of the mean are reported by the black dots and error bars. Two-tailed two-sample Wilcoxon signed-rank test statistic, * = p value <.05, ** = p value <.01 and *** = p value <.001 Download figure Open in new tab Figure S2. Reaction Times in Decreasing (left) and Increasing (right) tasks collected in Eccher et al., 2025 (red) and in the current work (blue). In the graph, the means and the standard error of the mean are reported by the black dots and error bars. Two-tailed two-sample Wilcoxon rank-sum test statistic, *** = pvalue <0.001 View this table: View inline View popup Download powerpoint Table S1. Statistical comparisons between Reaction Times in the two experiments for each task instruction Acknowledgements This work was supported by funding from the European Research Council under the European Union’s Horizon 2020 research and innovation program (Grant Agreement 833504 SPANUMBRA) to G.V. Funder Information Declared European Council , 833504 SPANUMBRA References ↵ Adachi , I. ( 2014 ). Spontaneous Spatial Mapping of Learned Sequence in Chimpanzees: Evidence for a SNARC-Like Effect . PLOS ONE , 9 ( 3 ), e90373 . doi: 10.1371/JOURNAL.PONE.0090373 OpenUrl CrossRef PubMed ↵ Ansari , D. , & Dhital , B. ( 2006 ). Age-related changes in the activation of the intraparietal sulcus during nonsymbolic magnitude processing: An event-related functional magnetic resonance imaging study . Journal of Cognitive Neuroscience , 18 ( 11 ), 1820 – 1828 . doi: 10.1162/JOCN.2006.18.11.1820 OpenUrl CrossRef PubMed Web of Science Barth , H. , Beckmann , L. , & Spelke , E. S. ( 2008 ). 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Share A left-to-right bias in spatial numerical associations with dots and symbols Eccher Elena , Caparos Serge , Buiatti Marco , Manuela Piazza , Giorgio Vallortigara bioRxiv 2025.07.28.666512; doi: https://doi.org/10.1101/2025.07.28.666512 Share This Article: Copy Citation Tools A left-to-right bias in spatial numerical associations with dots and symbols Eccher Elena , Caparos Serge , Buiatti Marco , Manuela Piazza , Giorgio Vallortigara bioRxiv 2025.07.28.666512; doi: https://doi.org/10.1101/2025.07.28.666512 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Neuroscience Subject Areas All Articles Animal Behavior and Cognition (7635) Biochemistry (17691) Bioengineering (13892) Bioinformatics (41937) Biophysics (21452) Cancer Biology (18588) Cell Biology (25504) Clinical Trials (138) Developmental Biology (13378) Ecology (19899) Epidemiology (2067) Evolutionary Biology (24320) Genetics (15609) Genomics (22506) Immunology (17736) Microbiology (40394) Molecular Biology (17181) Neuroscience (88605) Paleontology (666) Pathology (2832) Pharmacology and Toxicology (4824) Physiology (7641) Plant Biology (15156) Scientific Communication and Education (2045) Synthetic Biology (4294) Systems Biology (9825) Zoology (2271)