Foteini Christidi

Efstratios Karavasilis

Michail Rentzos

Georgios Velonakis

Vasiliki Zouvelou

Sofia Xirou

Ioannis Georgios Argyropoulos

Ioannis Papatriantafyllou

Varvara Pantolewn

Panagiotis Ferentinos

Nikolaos Kelekis

Ioannis Seimenis

Ioannis Evdokimidis

Peter Bede
email: bedep@tcd.ie

Hippocampal pathology in amyotrophic lateral sclerosis: selective vulnerability of subfields and their associated projections

Keywords: Amyotrophic Lateral Sclerosis, Alzheimer's disease, Hippocampus, Memory, Motor Neuron Disease, Multimodal MRI, Diffusion Tensor Imaging, Tractography Tensor Imaging, EMM = estimated marginal mean, FA = fractional anisotropy

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

ALS is now universally recognised as a multisystem condition affecting frontotemporal, subcortical and cerebellar regions beyond its hallmark motor cortex and spinal cord pathology.

In contrast to the extensive literature of frontal and temporal changes in ALS, hippocampal involvement and memory deficits remain relatively under recognised, despite pioneering longitudinal neuropsychology and neuroimaging studies (Christidi, et al., 2018b).

Early neuropsychology studies in ALS have overwhelmingly focused on executive dysfunction (Abrahams, et al., 1995a,Abrahams, et al., 1995b), which were subsequently complemented by the characterisation of behavioural, visuospatial and language deficits [START_REF] Burke | Measurement of Social Cognition in Amyotrophic Lateral Sclerosis: A Population Based Study[END_REF],Christidi, et al., 2018a,Finegan, et al., 2019a[START_REF] Montuschi | Cognitive correlates in amyotrophic lateral sclerosis: a population-based study in Italy[END_REF][START_REF] Phukan | The syndrome of cognitive impairment in amyotrophic lateral sclerosis: a population-based study[END_REF][START_REF] Pinto-Grau | The Study of Language in the Amyotrophic Lateral Sclerosis -Frontotemporal Spectrum Disorder: a Systematic Review of Findings and New Perspectives[END_REF]. Memory deficits have only recently been recognised in ALS [START_REF] Beeldman | The cognitive profile of ALS: a systematic review and meta-analysis update[END_REF],Christidi, et al., 2018b) and are thought to impact on compliance with assistive devices, participation in clinical trials, adherence to therapy, and activities of daily living (Burke, et al., 2017a[START_REF] Caga | The Impact of Cognitive and Behavioral Symptoms on ALS Patients and Their Caregivers[END_REF].

Pharmacological studies of ALS continue to rely on survival and clinical scores as key outcomes measures overlooking the biomarker potential of quantitative neuroimaging measures (Bede, et al., 2018b,Chipika, et al., 2019[START_REF] Schuster | Development of an Automated MRI-Based Diagnostic Protocol for Amyotrophic Lateral Sclerosis Using Disease-Specific Pathognomonic Features: A Quantitative Disease-State Classification Study[END_REF]. Furthermore, clinical trials in ALS overwhelmingly focus on motor disability and respiratory function and do not take extramotor manifestations of the disease into account. Extra-motor involvement is an important contributor to clinical heterogeneity in ALS (Burke, et al., 2017b[START_REF] Feron | Extrapyramidal deficits in ALS: a combined biomechanical and neuroimaging study[END_REF][START_REF] Omer | Neuroimaging patterns along the ALS-FTD spectrum: a multiparametric imaging study[END_REF] which is recognised as a key barrier to successful clinical trials [START_REF] Mitsumoto | Clinical trials in amyotrophic lateral sclerosis: why so many negative trials and how can trials be improved?[END_REF].

Despite the co-occurrence of ALS and AD [START_REF] Frecker | Association between Alzheimer disease and amyotrophic lateral sclerosis?[END_REF][START_REF] Segers | Adult polyglucosan body disease masquerading as "ALS with dementia of the Alzheimer type": an exceptional phenotype in a rare pathology[END_REF] and similar memory profiles [START_REF] Machts | Memory deficits in amyotrophic lateral sclerosis are not exclusively caused by executive dysfunction: a comparative neuropsychological study of amnestic mild cognitive impairment[END_REF], it is unclear if ALS is associated with a characteristic hippocampal signature distinct from AD. While the majority of hippocampal studies in ALS focus on grey matter pathology (Bede, et al., 2013b[START_REF] Westeneng | Subcortical structures in amyotrophic lateral sclerosis[END_REF], hippocampal subfields and their respective white matter projections are ideally studied together to test emerging concepts of trans-synaptic spread and connectivity based disease propagation.

Accordingly, we sought to characterise the hippocampal profile of ALS in contrast to healthy-controls and disease-controls using multimodal neuroimaging and test the hypothesis that ALS is associated with a unique hippocampal signature.

Methods

Ethics approval

This prospective neuroimaging study has been approved by the institutional review board of the Aeginition University Hospital and all participants provided informed consent prior to inclusion.

Participants

Fifty ALS patients with a diagnosis of 'definite' or 'probable' ALS based on the revised El Escorial criteria [START_REF] Ludolph | A revision of the El Escorial criteria -2015[END_REF] have been included. A group of 18 unselected Alzheimer's disease (AD) patients were included as disease controls, and 40 healthy controls (HC) were also included. The National Institute on Aging and Alzheimer's Association (NIA-AA) criteria were used to establish the diagnosis of AD [START_REF] Mckhann | The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimer's & dementia : the journal of the Alzheimer[END_REF]. All AD patients were "probable AD" by the current categorisation guidelines. AD-mimics have been reassuringly out ruled by standardised assessments for structural, vascular and inflammatory brain changes (MRI), endocrine, infectious and haematological profiling, and screening for depression by the Geriatric Depression Scale [START_REF] Yesavage | Development and validation of a geriatric depression screening scale: a preliminary report[END_REF]. The majority of AD patients (n = 11) had CSF analyses for beta-amyloid and tau, and their CSF profile was consistent with the diagnosis of AD. Exclusion criteria for study participation included comorbid neurological conditions, established psychiatric illness, psychoactive medications that may affect memory performance, and a clinical diagnosis of FTD. Demographic and representative clinical data are shown in Table 1.

-----Table 1 here -----

Memory assessment

Memory performance was evaluated using the Rey Auditory Verbal Learning Test 2), as part of a larger cognitive battery assessing other cognitive domains [START_REF] Christidi | Trail Making Test error analysis in classic motor neuron disease[END_REF]. To exclude the confounding effect of depression or low-mood, the ALS Depression Inventory (ADI) [START_REF] Ferentinos | Prevalence of major depression in ALS: comparison of a semi-structured interview and four self-report measures[END_REF][START_REF] Hammer | Validity of the ALS-Depression-Inventory (ADI-12)--a new screening instrument for depressive disorders in patients with amyotrophic lateral sclerosis[END_REF] was also administered.

-----Table 2 here -----

MRI data acquisition

All participants underwent standardised brain imaging on a 3 Tesla Philips Achieva-Tx MR scanner. A 3D-T1-weighted sequence was acquired with a time of repetition (TR): 9.9ms, echo time (TE): 3.7ms, flip angle: 7 ο , voxel-size 1×1×1mm, matrix size 244×240, 170 slices. DTI data were acquired with an axial single-shot spin-echo echo-planar imaging sequence with 30 diffusion encoding directions and the following parameters: TR: 7299ms, TE: 68ms, flip angle: 90 ο , field of view: 256×256 mm, voxel size: 2×2×2 mm, 70 slices. FLAIR data were acquired with TR: 11000ms, TI: 2800ms, TE: 125ms, acquisition matrix 384x186, slice thickness 4mm.

MRI data analysis

Grey matter analyses

A multimodal approach was implemented to comprehensively characterise mesial temporal lobe pathology in the three study groups. Total hippocampal volumes were estimated, hippocampal segmentation was performed to estimate volumes of specific subfields, vertex analyses were undertaken to reflect on shape deformation, and supplementary brain morphometry was carried out to confirm disease-specific cerebral grey matter signatures.

First, total intracranial volume (TIV) was estimated for each participant to be used as a covariate for volumetric analyses. TIV was estimated by linearly aligning each subject's skullstripped brain to the standard MNI152 brain image in MNI space, calculating the inverse of the determinant of the affine registration matrix and multiplying it by the size of the template.

Registration to template was undertaken using FSL-FLIRT [START_REF] Jenkinson | A global optimisation method for robust affine registration of brain images[END_REF], and FSL-FAST was used for tissue type segmentation [START_REF] Zhang | Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm[END_REF].

The hippocampus was segmented into cytologically-defined subfields (Figure 1A) using version 6.0 of the FreeSurfer image analysis suite [START_REF] Fischl | [END_REF]. The pre-processing pipeline included the removal of non-brain tissue, segmentation of the subcortical white matter and deep grey matter structures, intensity normalization, tessellation of the grey matter-white matter boundary, and automated topology correction. The hippocampal stream of the FreeSurfer package was used for the accurate segmentation of the following hippocampal subfields: CA1, CA2/3, CA4, fimbria, hippocampal fissure, presubiculum, subiculum, hippocampal tail, parasubiculum, molecular layer; granule cell layer of the dentate gyrus (GC-DG), hippocampalamygdala transition area (HATA) [START_REF] Iglesias | A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI[END_REF].

Vertex analyses were performed using FMRIB's subcortical segmentation and registration tool FIRST to provide quantitative, surface-projected information about focal hippocampal involvement. Vertex locations of individual subjects were projected on the surface of an average template shape as scalar values, positive value being outside the surface and negative values inside. Design matrices included age, gender and education.

To confirm disease-specific grey mater signatures beyond the hippocampus, supplementary morphometric analyses were carried out in the FSL environment [START_REF] Smith | Advances in functional and structural MR image analysis and implementation as FSL[END_REF]. Following brain extraction and tissue-type segmentation, grey-matter partial volume images were aligned to the MNI152 standard space using affine registration [START_REF] Good | A voxel-based morphometric study of ageing in 465 normal adult human brains[END_REF].

The resulting images were averaged and flipped along the x-axis to create a left-right symmetric, study-specific grey matter template. All native grey matter images were non-linearly coregistered to the study-specific template, modulated by a Jacobian field warp and smoothed with an isotropic Gaussian kernel with a sigma of 3 mm. The threshold-free cluster-enhancement (TFCE) method [START_REF] Smith | Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference[END_REF] and permutation-based nonparametric inference were used for the comparison of study groups controlling for age, gender and education.

White matter analyses

White matter tractography was conducted using the Brainance DTI Suite (Advantis Medical Imaging, Eindhoven, the Netherlands). First, the raw DWI datasets were motion and eddy-current corrected. Three ROIs were used for the reconstruction of perforant pathway zone (PPZ); (1) on a coronal slice at the middle of the splenium of the corpus callosum the perforant pathway was identified subjacent the corpus callosum, (2) on a coronal slice anterior to the first one at the level of the cerebellar dentate nucleus and (3) the white matter area of the mesial temporal lobe just underlying the hippocampus on a coronal slice anterior to the pons at the level where the projections of the posterior limb of internal capsule are prominent (Figure 1B). For the reconstruction of the fornix, three ROIs were placed along the fornix in three coronal slices where the fornix was visible as one bundle (Figure 1C). The following parameters were used for tracking: PPZ: FA threshold: 0.20 and angle threshold: 6; Fornix: FA threshold: 0.25 and angle threshold: 60. In order to provide a multifaceted characterisation of white matter integrity changes, the following diffusivity metrics were extracted for each tract: fractional anisotropy (FA); axial diffusivity (Dax); and radial diffusivity (Drad). Intra-and inter-rater reliability were assessed for all tracts in each participant and showed high intra-class correlation [(ICC) > 0.8].

Statistical analyses

Assumptions of normality were examined using the Kolmogorov-Smirnov test. Since all variables followed a normal distribution, parametric statistics were applied. Considering the patients' heterogeneous memory performance, a hierarchical cluster analysis using Ward's method of minimum variance with a squared Euclidean distance measure was conducted within the ALS cohort to identify clusters of memory performance (i.e. 'ALS-high performers'; 'ALSlow performers') based on episodic memory measures (i.e. RAVLT-Total Learning, Immediate Recall, Delayed Recall; BSRT-Immediate Recall, Delayed Recall). Ward's method was chosen because of its efficiency to model quantitative variables and its resilience to outlier effects. The squared Euclidean distance coefficient was calculated as it is the most widely used distance coefficient in neuropsychological studies and detects performance levels and patterns within the clusters [START_REF] Allen | Cluster Analysis in Neuropsychological Research Recent Applications[END_REF]. The following multivariate analyses of covariance (MANCOVAs) were conducted to examine differences in hippocampal subfields and tractography measures (1) HC, ALS and AD and (2) HC, ALS-High, ALS-Low and AD using age, gender, education and TIV (for subfield volumes) as covariates. If a significant main effect of group membership was found (p < 0.05), post hoc group comparisons were performed using the false discovery rate (FDR) correction for multiple comparisons. Correlation analyses (Pearson r) were also conducted within ALS group between MRI metrics and patients' clinical data. The significance level was set at p < 0.05.

Results

The volumetric profile of hippocampal subfields

The adjusted estimated marginal means and standard error of hippocampal subfield volumes are presented in Table 3. Significant differences were observed in total hippocampal volumes between the ALS and AD (p < 0.001), and between HC and AD (p < 0.001). Significant main effects of group were observed for all subfields with the exception of the parasubiculi.

Compared to HC, patients with ALS showed significant volume reductions in bilateral CA2/3, left fimbria, bilateral molecular layer, left GC-DG, left hippocampus-amygdala transition area (HATA) and increased bilateral hippocampal fissure volumes. Compared to AD patients, patients with ALS showed higher volumes in all CA subfields, fimbria, presubiculum and subiculum, hippocampal tail, molecular layer, GC-DG and hippocampal fissure. With the exception of the hippocampal fissures and hippocampal tail, the AD group exhibited widespread hippocampal atrophy in all hippocampal subfields compared to HC.

Regarding the neuropsychologically-defined ALS subgroups, no significant hippocampal volume differences were identified between HC and ALS-High. ALS-Low performers showed significantly reduced volume in right hippocampus compared to ALS-High (p = 0.018) and higher volume bilaterally compared to AD (p < 0.001). With regards to hippocampal subfields, the ALS-High cohort exhibited higher bilateral hippocampal fissure volumes (left: p = 0.013; right: p = 0.026) and decreased left HATA volumes (p = 0.016) compared to HC. The direct comparison on subfields between the two ALS groups revealed volume reductions in the ALSlow group in the left fimbria, bilateral hippocampal tails, right CA1, right molecular layer and right GC-DG.

The most affected hippocampal subfields in the study groups were identified using percentage of change with reference to HC and averaging left and right volumes of respective subfields. Figure 2 illustrates the hippocampal profile of the study groups using estimated marginal means adjusted for age, gender, education and TIV. Based on normative reference values, the HATA and CA2/3 are the most affected subfields in ALS, the presubiculum and subiculum in AD, and the fimbria are affected in both ALS and AD. In the neuropsychologically-defined ALS groups, fimbria and HATA are particularly atrophic in the ALS-Low group and HATA and CA2/3 are the most affected subfields in the ALS-High cohort.

-----Table 3 here -----

Vertex analyses

Vertex analyses demonstrated that the inferior and superior aspects of both left and right hippocampi are more affected in AD than ALS. No significant differences were identified between ALS-High performers and HCs. Compared to ALS-Low performers, the AD group revealed considerable surface projected atrophy in the right hippocampus at p < 0.05 and a trend of atrophy at p < 0.07 in the left hippocampus (Figure 3). The contrast between the neuropsychologically defined ALS-High and ALS-Low groups also revealed significant shape differences in the lateral aspect of the left hippocampus.

Whole-brain morphometric analyses

Our VBM-type analyses confirmed disease-associated cerebral signatures. The AD group exhibited widespread bi-temporal and bi-parietal atrophy, while the ALS cohort showed degenerative changes in the bilateral motor cortices (Figure 4).

DTI metrics

The adjusted estimated marginal means of white matter tracts for HC, ALS and AD are summarized in Table 3. No significant group effect was identified for FA values in bilateral PPZ. Compared to HC, patients with ALS exhibit significantly lower FA in fornix, higher Dax in right PPZ and higher Dax and Drad in fornix. Compared to AD, ALS patients also exhibited significantly higher FA in fornix, lower Dax and Drad in the bilateral PPZ and fornix. The comparison between HC and AD confirmed widespread white matter pathology in both the PPZ and fornix.

The direct comparison of DTI metrics in ALS-High and ALS-Low performers did not reach statistical significance using FDR corrections. Compared to AD patients, ALS-Low performers exhibited higher FA in the fornix and lower Dax and Drad in both the PPZ and fornix.

Correlation with clinical and memory variables

To avoid type II error, correlation analyses were restricted to imaging metrics showing significant differences between HC and ALS. Following correction for multiple comparisons, neither disease duration, ALSFRS-r, nor memory scores correlated with grey or white matter metrics.

Discussion

Our findings indicate that ALS is associated with widespread hippocampal pathology which is independent from disease duration and motor disability and is distinct from AD. The novelty of our study lies in the integration of grey and white matter metrics and the ascertainment of divergent hippocampal signatures in ALS and AD.

Radiological insights into hippocampal pathology in ALS and AD

There is ample pathological evidence of hippocampal pathology in ALS, but the neuroimaging literature is relatively sparse (Christidi, et al., 2018b). Hippocampal atrophy has been demonstrated in both C9orf72-negative and C9orf72-positive ALS patients (Bede, et al., 2013b[START_REF] Floeter | Longitudinal diffusion imaging across the C9orf72 clinical spectrum[END_REF] and is not due to the inclusion of patients with comorbid FTD [START_REF] Abdulla | Hippocampal degeneration in patients with amyotrophic lateral sclerosis[END_REF][START_REF] Westeneng | Subcortical structures in amyotrophic lateral sclerosis[END_REF]. The majority of existing MRI studies in ALS evaluate entire hippocampal volumes and rely on healthy controls alone as opposed to disease controls [START_REF] Abdulla | Hippocampal degeneration in patients with amyotrophic lateral sclerosis[END_REF],Bede, et al., 2013b[START_REF] Bueno | Structural and functional papez circuit integrity in amyotrophic lateral sclerosis[END_REF],Christidi, et al., 2018b[START_REF] Machts | Global Hippocampal Volume Reductions and Local CA1 Shape Deformations in Amyotrophic Lateral Sclerosis[END_REF][START_REF] Westeneng | Subcortical structures in amyotrophic lateral sclerosis[END_REF]. We identified selective subfield involvement in ALS in bilateral CA2/CA3, left fimbria, with the relative sparing of the subiculum and presubiculum. A more widespread anatomical pattern of hippocampal change was identified in AD with the preferential involvement of the subiculum and presubiculum. The independence of hippocampal pathology from motor disability is an important finding, as clinical trials of ALS continue to overwhelmingly rely on motor metrics [START_REF] Mitsumoto | Clinical trials in amyotrophic lateral sclerosis: why so many negative trials and how can trials be improved?[END_REF] despite evidence of considerable disease burden in non-motor regions (Christidi, et al., 2018a).

Hippocampal subfields are routinely assessed in studies of normal aging, mild cognitive impairment (MCI) and AD [START_REF] De Flores | Structural imaging of hippocampal subfields in healthy aging and Alzheimer's disease[END_REF] but seldom evaluated in ALS [START_REF] Westeneng | Subcortical structures in amyotrophic lateral sclerosis[END_REF]. Our findings highlight the utility of subfield analyses versus whole-hippocampal volumetry and underlines the selective vulnerability of specific subfields, with distinct cytoarchitecture, dedicated functions and distinct connections [START_REF] Duvernoy | Human Hippocampus Functional Anatomy, Vascularization and Serial Sections with MRI[END_REF]. The entire ALS group, irrespective of neuropsychological performance, exhibited hippocampal atrophy. Following the stratification of ALS patients based on memory performance, vertex-wise and volumetric differences were identified between ALS-High and ALS-Low performers underscoring the detection sensitivity of neuropsychological tests to capture hippocampal pathology.

The most affected subfields in ALS are CA2/CA3 and HATA, the presubiculum and subiculum in AD and the fimbria is affected in both groups. Fimbria is a white matter subfield which runs along the superomedial edge of the hippocampus and then at the posterior part of the hippocampus and transitions into the crux of the fornix. Fimbria and HATA have not been previously studied in ALS as a distinct hippocampal subfield due to the methodological constraints of older segmentation approaches [START_REF] Westeneng | Subcortical structures in amyotrophic lateral sclerosis[END_REF]. The involvement of the fimbria in ALS, particularly its atrophy in the ALS-Low cohort, is in line with its role [START_REF] Zheng | The Volume of Hippocampal Subfields in Relation to Decline of Memory Recall Across the Adult Lifespan[END_REF] in memory function and consistent with previous studies suggesting that fornix metrics may indicate AD risk in cognitively normal persons and may also act as prognostic indicators for conversion from MCI and AD [START_REF] Nowrangi | The Fornix in Mild Cognitive Impairment and Alzheimer's Disease[END_REF].

Our findings also need to be discussed from a 'tau' vs 'TDP' perspective. The AD cohort in this study is likely to represent a relatively homogenous group pathologically as they had no evidence motor involvement, their VBM analysis confirmed disease specific bi-temporal and biparietal pathology, and fulfilled clinical criteria, therefore representing an archetypic AD cohort without clinical and radiological features suggestive of TDP. The hippocampal imaging signature of our AD cohort is also consistent with larger imaging studies [START_REF] Evans | Subregional volumes of the hippocampus in relation to cognitive function and risk of dementia[END_REF].

Conversely, our ALS cohort is less likely to be pathologically homogenous and may include patients with co-existing tau pathology [START_REF] Frecker | Association between Alzheimer disease and amyotrophic lateral sclerosis?[END_REF][START_REF] Segers | Adult polyglucosan body disease masquerading as "ALS with dementia of the Alzheimer type": an exceptional phenotype in a rare pathology[END_REF]. Thus, fimbria changes detected in the ALS cohort may, in part, be manifestations of coexisting AD pathology.

Network-wise degeneration in ALS

Our study demonstrates the benefit of using multiple complementary imaging techniques and systematically evaluating grey and white matter structures. [START_REF] Bede | Lessons of ALS imaging: Pitfalls and future directions -A critical review[END_REF] Subfield volumetrics and shape analysis provided complementary insights; vertex analyses captured differences between ALS-High and ALS-Low performers, whereas subfield volumetrics revealed selective hippocampal vulnerability. The selective degeneration of cellspecific hippocampal regions is also well recognised in healthy aging [START_REF] Haigler | Acetylcholine, aging and anatomy: differential effects in the hippocampus[END_REF]).

An additional advantage of appraising multiple grey and white matter metrics is the establishment of their respective sensitivity profiles. From a motor perspective, corticospinal white matter degeneration is invariably detected irrespective of disease duration (Bede andHardiman, 2018,Pyra, et al., 2010), but the detection of cortical grey matter involvement depends on disease stage, UMN predominance and imaging techniques (Bede, et al., 2013a). In contrast, our study indicates that hippocampal grey matter metrics (subfields volumes and vertex metrics) readily detect mesial temporal lobe pathology. The ranking of the detection sensitivity of various imaging metrics is indispensable to establish which index may be used in diagnostic, monitoring or prognostic applications. [START_REF] Schuster | Presymptomatic and longitudinal neuroimaging in neurodegeneration--from snapshots to motion picture: a systematic review[END_REF],Schuster, et al., 2017) Our findings also confirm the concomitant degeneration of associated grey and white matter structures in ALS (Bede, et al., 2018a[START_REF] Nasseroleslami | Characteristic Increases in EEG Connectivity Correlate With Changes of Structural MRI in Amyotrophic Lateral Sclerosis[END_REF]. The fimbria was the most affected hippocampal subfield in both ALS and AD which is consistent with the widespread diffusivity changes identified in the fornix. The perforant pathway linking the entorhinal cortex, dentate gyrus, CA and subiculum is preferentially affected in our AD cohort, which is consistent with the selective degenerative changes observed in the hippocampal subfields it connects. The evaluation of multiple diffusivity metrics helps the biological characterisation of white matter degeneration. While FA is widely regarded a composite proxy of white matter integrity, Dax is primarily regarded as an axonal marker and Drad also reflects on myelin related pathology [START_REF] Song | Demyelination increases radial diffusivity in corpus callosum of mouse brain[END_REF][START_REF] Sun | Noninvasive detection of cuprizone induced axonal damage and demyelination in the mouse corpus callosum[END_REF].

Pathological correlates

The lack of correlations between clinical measures and radiological findings do not directly support a sequential model of pathological spread in ALS and highlight a possible inconsistency between radiological observations and the pathological staging. In ALS, pathological TDP-43 can be detected in the hippocampal CA4-CA1/subiculum in 25% of post mortem samples [START_REF] Geser | Evidence of multisystem disorder in wholebrain map of pathological TDP-43 in amyotrophic lateral sclerosis[END_REF]. Pathological TDP-43 burden in the anteromedial temporal lobe and the hippocampal formation is now regarded as a stage-defining feature of a widely used pathological staging system in ALS [START_REF] Brettschneider | Stages of pTDP-43 pathology in amyotrophic lateral sclerosis[END_REF], corresponding to 'Stage 4' of the disease.

According to the three-stage model of PPZ degeneration, stage I ("inclusion stage") is characterized by TDP-43-positive cytoplasmatic inclusions in the granular cells of the dentate gyrus, stage II (i.e. "early perforant stage") by gliosis and neuronal loss in the transentorhinal cortex and stage III (i.e. "advanced perforant stage") by the degeneration of the molecular layer of the dentate gyrus [START_REF] Takeda | Progression of hippocampal degeneration in amyotrophic lateral sclerosis with or without memory impairment: distinction from Alzheimer disease[END_REF]. These stages of hippocampal pathology are closely linked to its white matter architecture, suggestive of connectivity-based disease propagation [START_REF] Schmidt | Simulating disease propagation across white matter connectome reveals anatomical substrate for neuropathology staging in amyotrophic lateral sclerosis[END_REF] and supports the notion that interconnected grey matter regions become gradually affected as opposed to contiguous spread [START_REF] Braak | Amyotrophic lateral sclerosis-a model of corticofugal axonal spread[END_REF]. This is further supported by the observation the despite anatomical proximity certain subfields, such as the subiculum are not affected in ALS.

Clinical relevance

Our findings may have implications for caregiver support, screening strategies and clinical trial designs. Memory impairment in ALS remains relatively under recognised despite its quality of life implications and potential effect on compliance with assistive devices, engagement in rehabilitation efforts, and participation in clinical trials [START_REF] Lomen-Hoerth | Are amyotrophic lateral sclerosis patients cognitively normal?[END_REF][START_REF] Olney | The effects of executive and behavioral dysfunction on the course of ALS[END_REF]. Pharmacological studies of ALS continue to rely on survival and clinical scores as key outcomes measures overlooking the biomarker potential of quantitative neuroimaging measures which are widely used in studies of other neurological disorders. [START_REF] Chipika | Tracking a Fast-Moving Disease: Longitudinal Markers, Monitoring, and Clinical Trial Endpoints in ALS[END_REF] Furthermore, current clinical trials overwhelmingly focus on mobility, motor deficits, and respiratory dysfunction as endpoints despite irrefutable evidence of widespread extra-motor involvement in ALS [START_REF] Beeldman | The cognitive profile of ALS: a systematic review and meta-analysis update[END_REF],Christidi, et al., 2018a). Frontotemporal involvement is a key contributor to clinical heterogeneity in ALS, it has survival [START_REF] Elamin | Executive dysfunction is a negative prognostic indicator in patients with ALS without dementia[END_REF][START_REF] Ishaque | Evaluating the cerebral correlates of survival in amyotrophic lateral sclerosis[END_REF] and caregiver burden implications [START_REF] Caga | The burden of apathy for caregivers of patients with amyotrophic lateral sclerosis[END_REF]), yet it is not evaluated in most clinical trials. At a time when ALS-specific cognitive instruments have been extensively validated [START_REF] Abrahams | Screening for cognition and behaviour changes in ALS[END_REF] and non-invasive neuroimaging techniques readily capture motor and extra-motor changes, the incorporation of cognitive testing and quantitative imaging protocols into pharmacological trials seems overdue.

Study limitations and future directions

This study is not without limitations. The biggest shortcoming of this report is the the small sample size of our AD group which was included as a disease control group. Despite the sample size limitation of the AD cohort, this group exhibits disease-associated atrophy patterns typical of AD. Due to disease-specific characteristics, the AD cohort of our study is older than the ALS patients and healthy controls included in our imaging analyses. While age was strictly included as a covariate in all of our statistical models, in order to ensure that age-differences have not influenced our findings, an additional sub-analysis was conducted with an age (p = 0.135), education (p = 0.078) and gender (p = 0.334) matched sub-cohort of AD patients and controls. The structural differences identified by this age-matched supplementary analysis were consistent with our main findings indicating that the identified hippocampal patterns are disease related and not driven by age. This study focused on ALS, but as relatively little is known of the hippocampal profile of other motor neuron disease phenotypes, the inclusion of additional "disease controls", such as primary lateral sclerosis, Kennedy's disease or spinal muscular atrophy patients would have potentially contributed important additional insights (Finegan, et al., 2019b,Querin, et al., 2018[START_REF] Querin | The spinal and cerebral profile of adult spinal-muscular atrophy: A multimodal imaging study[END_REF]. Our choice of a two-cluster model to stratify our ALS cohort for memory performance was also driven by sample size considerations. Another potential limitation of our study is the risk of partial volume effects on the tractographic reconstruction of the fornix. CSF contamination however typically affects axial and radial diffusivity metrics, and FA is thought to be less influenced by it [START_REF] Douet | Fornix as an imaging marker for episodic memory deficits in healthy aging and in various neurological disorders[END_REF]. Dedicated acquisition methods [START_REF] Baron | Acquisition strategy to reduce cerebrospinal fluid partial volume effects for improved DTI tractography[END_REF] and post-processing approaches [START_REF] Chad | Re-examining age-related differences in white matter microstructure with free-water corrected diffusion tensor imaging[END_REF][START_REF] Metzler-Baddeley | How and how not to correct for CSF-contamination in diffusion MRI[END_REF] would be required if the primary focus of the study would be the characterisation of fornix integrity. Our fornix findings however are in line with previous studies of ALS and AD and consistent with recent reports in neuropsychologically unaffected subjects with elevated Aβ burden [START_REF] Rabin | Synergism between fornix microstructure and beta-amyloid accelerates memory decline in clinically normal older adults[END_REF]. An additional drawback of the study is the lack of comprehensive genetic profiling to explore whether C9orf72 hexanucleotide repeats may contribute to the hippocampal disease burden observed in this study. However, the potential influence of C9orf72 hexanucleotide carriers in our sample is not considered substantive since our sample only included sporadic ALS cases, and the prevalence of C9orf72 hexanucleotide carriers in the Greek population is 8% in sporadic cases [START_REF] Mok | High frequency of the expanded C9ORF72 hexanucleotide repeat in familial and sporadic Greek ALS patients[END_REF].

Previous studies indicate that while C9orf72 negative ALS patients exhibit overall hippocampal pathology [START_REF] Machts | Basal ganglia pathology in ALS is associated with neuropsychological deficits[END_REF], which may be more marked in hexanucleotide carriers (Bede, et al., 2013b). Finally, spinal fluid panels for tau, amyloid and neurofilaments in the ALS cohort would have provided important additional insights to reflect on the molecular substrate of hippocampal pathology. Notwithstanding these limitations, our study demonstrates the divergent mesial temporal lobe profile of ALS and AD highlighting the need for further wet-biomarker supported and histopathologically validated studies. Emerging imaging modalities such as neurite orientation dispersion and density imaging (NODDI) [START_REF] Barritt | Emerging Magnetic Resonance Imaging Techniques and Analysis Methods in Amyotrophic Lateral Sclerosis[END_REF] and high field MR imaging [START_REF] Cardenas | Pathology of callosal damage in ALS: An ex-vivo, 7 T diffusion tensor MRI study[END_REF] may help to characterise mesial temporal lobe degeneration in ALS further.

Conclusions

Patients with ALS exhibit disease-specific patterns of hippocampal pathology which is distinct from AD. The preferential involvement of specific hippocampal subfields connected by selectively affected white matter projections suggests network-based disease propagation as opposed to contagious spread. The comprehensive characterisation of mesial temporal lobe degeneration in ALS has implications for screening practices, supportive interventions, clinical trial designs and expanding the extra-motor profile of ALS. [START_REF] Messinis | Normative data and discriminant validity of Rey's Verbal Learning Test for the Greek adult population[END_REF][START_REF] Meyers | Rey Complex Figure Test and Recognition Trial: Professional Manual[END_REF][START_REF] Zalonis | Assessing episodic memory: normative data and discriminant properties for a Greek version of Babcock Story Recall Test[END_REF]) [START_REF] Messinis | Normative data and discriminant validity of Rey's Verbal Learning Test for the Greek adult population[END_REF][START_REF] Zalonis | Assessing episodic memory: normative data and discriminant properties for a Greek version of Babcock Story Recall Test[END_REF]; Meyers *Available for 16 ALS-High and 21 ALS-Low performers. Absolute hippocampal subfields volumes (mm 3 ) and DTI metrics (FA, Dax, Drad) are presented for each group. Age, gender, education and TIV (for hippocampal subfields) were used as covariates in the MANCOVA analyses. n/a: post-hoc comparisons were not conducted due to non-significant (p > 0.05) F-test. Bold post-hoc comparisons are significant after false-discovery rate (FDR) correction for multiple comparisons.

(

  RAVLT); Babcock Story Recall Test (BSRT) and the Rey-Osterrieth Complex Figure Test (ROCFT) in the ALS group (Table

Figure 5

 5 Figure 5 depicts the DTI profile of the PPZ and fornix in ALS, AD, ALS-High and ALS-Low performers with reference to HCs. Fornix (specifically on Drad) was the most affected tract in both ALS and AD. Drad and Dax indices of the right PPZ were the second most affected metrics in the study groups.

Figure 1 .

 1 Figure 1. Left: Hippocampal segmentation and resulting subfields in coronal (1), sagittal (2) and axial views (3) Right: the tractographic reconstruction of the right perforant pathway (4) and the fornix (5) with their respective region-of-interest gates on fractional anisotropy maps.

Figure 2 .

 2 Figure 2. The regional hippocampal profile of each study group: ALS (A), AD (B), ALS-High (C) and ALS-Low (D), and their comparative volumetric profile (E) with reference to healthy controls/ Subfield volumes are averaged across left and right. CA = Cornu Ammonis; GC-DG = granule cell layer of dentate gyrus; HATA = hippocampus-amygdala transition area; ALS = Amyotrophic Lateral Sclerosis; AD = Alzheimer disease; HCs = healthy controls.

Figure 3 .

 3 Figure 3. The comparative hippocampal atrophy profile of the AD, ALS-High and ALS-Low cohorts. Surface projected patterns of atrophy are highlighted in orange and yellow and the underlying hippocampal mesh volumes are represented in green, pink and blue. Comparisons are adjusted for age, gender and education. ALS = Amyotrophic Lateral Sclerosis; AD = Alzheimer's disease.

Figure 4 .

 4 Figure 4. Cortical atrophy patterns in ALS and AD identified by voxel-based morphometry using age, gender and education as covariates. ALS = Amyotrophic Lateral Sclerosis; AD = Alzheimer's disease.

Figure 5 .

 5 Figure 5. The diffusivity profile of the perforant pathway and fornix in each study group: ALS (A), AD (B), ALS-High (C) and ALS-Low (D), and their comparative profile (E) with reference to healthy controls. L = Left; R = Right; PPZ = perforant pathway zone; Fx = fornix; FA = fractional anisotropy; Dax = axial diffusivity; Drad = radial diffusivity; ALS = Amyotrophic Lateral Sclerosis; AD = Alzheimer disease; HCs = healthy controls

  controls; ALS = amyotrophic lateral sclerosis; AD = Alzheimer disease; CA = Cornu Ammonis; GC-DG = granule cell layer of dentate gyrus; HATA = hippocampus-amygdala transition area; WM = white matter; DTI = diffusion tensor imaging; PPZ = perforant pathway zone; Lt / Rt = left / right; FA = fractional anisotropy; Dax = axial diffusivity; Drad = radial diffusivity; SD = standard deviation.

Table 1 .

 1 The demographic and clinical profile of study participants

			Tables
		ALS	AD	HC
					Statistical differences
		(n = 50)	(n = 18)	(n = 40)
					AD>HC (p<0.001)
	Age (years)	61.70 ± 10.22	76.28 ± 6.37	59.00 ± 6.28	AD>ALS (p<0.001)
					AD vs HC (p=0.012),
	Gender (M / F)	28 / 22	2 / 16	18 / 22	AD vs. ALS (p=0.001)
					HC>ALS,AD (p<0.001)
	Education (years)	10.62 ± 3.53	7.89 ± 5.06	14.00 ± 2.43	ALS>AD (p=0.014)
	Handedness (Rt / Lt)	50 / 0	18 / 0	40 / 0	Ns
	Disease duration from symptom onset (m)	17.72 ± 18.34	33.67 ± 21.60	-	ALS<AD (p=0.004)
	ALSFRS-R	39.80 ± 6.10	-	-	-
	ALS onset (S / B)	38 / 12	-	-	-
	Riluzole (Y / N)	14 / 36
					HC>ALS, AD (p < 0.001)
	MMSE	26.08 ± 2.22	23.00 ± 3.07	28.50 ± 1.06	ALS>AD (p = 0.001)

ALS = amyotrophic lateral sclerosis; AD = Alzheimer's dementia; HC = healthy controls; M / F = male / female; Rt / Lt = right / left; m = months; ALSFRS-R = Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised; S / B = spinal / bulbar; Y / N = Yes / No; MMSE = Mini-Mental State Examination. Differences in MMSE are adjusted for age, gender and education.

Table 2 .

 2 Memory profile of the ALS groups and ALS-High and ALS-Low subgroups

		ALS		ALS-High		ALS-Low
		Raw	Z-score	Raw	Z-score	Raw	Z-score
	RAVLT-Learning 38.44±9.03 -0.49±1.95 46.22±5.97 0.67±1.84 31.81±4.94 -1.47±1.45
	RALVT-IR	7.14±3.00 -0.34±2.98 9.35±2.27 1.36±2.54 5.26±2.16 -1.79±2.55
	RAVLT-DR	5.84±2.96 -1.86±3.15 7.48±2.71 -0.76±3.06 4.44±2.49 -2.79±2.96
	BSRT-IR	10.02±2.17 -0.82±1.22 10.87±2.24 -0.56±1.32 9.30±1.86 -1.03±1.11
	BSRT-DR	8.22±3.50 -1.53±1.78 9.96±3.88 -0.81±1.91 6.74±2.31 -2.14±1.43
	ROCFT-IR*	13.32±6.11 -0.69±1.17 16.56±5.94 -0.25±1.16 10.86±5.09 -1.02±1.08
	ALS = amyotrophic lateral sclerosis; RAVLT = Rey Auditory Verbal Learning Test; BSRT =
	Babcock Story Recall Test; ROCFT = Rey Osterreith Complex Figure Test; IR = Immediate
	Recall; DR = Delayed Recall. Z-scores were calculated based on available normative data
	((

Table 3 .

 3 Volumes of specific hippocampal subfields and the entire hippocampus. The white matter profile of the PPZ and the fornix in ALS, AD and HC.

		HC	ALS	AD	ALS-High	ALS-Low	ALS vs	ALS vs	AD	ALS-	ALS-	ALS-
		(N = 40)	(N = 50)	(N = 18)	(N = 23)	(N = 27)	HC	AD	vs HC	High	High vs	Low vs
										vs	ALS-	AD
										HC	Low
				Mean ± SD					p-values
				Total hippocampal volumes
	Left	3423.84±422.85 3223.46±458.38 2415.54±342.73 3305.07±396.81 3153.95±501.84		<0.001 <0.001			<0.001
	Right	3506.29±444.01 3308.92±446.37 2542.70±393.01 3412.04±396.29 3221.09±474.55		<0.001 <0.001		0.018 <0.001
				Subfields in the left hemisphere
	CA1	632.03±91.25	594.36±97.22	467.90±73.10	607.49±98.07	583.17±96.91		<0.001 <0.001			0.016
	CA2/CA3	202.25±28.90	189.14±33.09	143.51±27.90	187.66±21.51	190.40±40.85	0.049 <0.001 <0.001			0.005
	CA4	251.70±31.25	237.39±35.51	176.04±30.25	240.23±27.62	234.97±41.44		<0.001 <0.001			0.001
	Fimbria	72.98±12.41	61.73±19.64	34.67±10.65	69.27±19.77	55.31±17.40	0.007	0.002 <0.001		0.013	0.037
	Hippocampal	150.35±27.08	178.57±35.13	169.57±37.40	172.17±40.14	184.02±29.93	<0.001 0.040		0.013
	fissure
	Presubiculum	313.52±47.34	299.03±47.62	219.01±32.57	303.36±42.99	295.35±51.76		<0.001 <0.001			0.001
	Subiculum	448.95±61.43	425.82±62.08	310.31±48.79	434.56±55.44	418.37±67.31		<0.001 <0.001			0.001
	Hippocampal tail	520.62±74.85	508.34±89.37	390.52±55.91	535.10±78.09	485.54±93.37		0.010			0.035
	Parasubiculum	56.33±12.56	53.37±13.65	48.58±9.48	51.10±10.37	55.31±15.86
	Molecular layer	571.55±73.67	531.82±81.33	388.06±59.30	546.62±72.15	519.22±87.77	0.020 <0.001 <0.001			0.001
	GC-DG	293.12±37.40	270.44±42.22	194.88±32.86	276.19±33.44	265.54±48.56	0.021 <0.001 <0.001			0.001
	HATA	60.77±11.94	52.02±8.52	42.07±5.10	53.49±7.84	50.76±9.01	<0.001		0.002 0.016
				Subfields in the right hemisphere
	CA1	648.04±92.79	618.67±84.67	489.56±83.20	639.21±80.30	601.18±85.81		<0.001 <0.001		0.041	0.005
	CA2/CA3	224.59±36.50	207.10±35.01	164.06±28.12	211.76±31.46	203.14±37.91	0.026	0.006 <0.001			0.041
	CA4	265.54±35.90	249.90±36.22	197.82±32.50	256.37±32.21	244.40±39.06		<0.001 <0.001			0.005
	Fimbria	70.31±15.10	63.92±20.17	40.05±16.89	69.91±18.28	58.82±20.62		0.021	0.009
	Hippocampal	162.18±29.38	191.63±36.39	180.33±42.81	182.63±37.29	199.30±34.45	<0.001 0.002		0.026		0.001
	fissure
	Presubiculum	298.44±42.44	283.27±47.40	211.78±39.68	287.14±47.40	279.97±48.05		<0.001 <0.001			0.001
	Subiculum	443.93±59.09	426.36±62.48	319.66±58.91	434.01±53.34	419.84±69.66		<0.001 <0.001			0.001
	Hippocampal tail	545.56±74.13	518.59±84.42	400.22±60.40	542.76±77.47	498.01±85.99		0.002			0.026	0.036
	Parasubiculum	55.57±12.31	53.54±13.82	43.53±8.99	51.63±12.94	55.16±14.56

Acknowledgments

We acknowledge the generosity and kindness of our patients for participating in ALS imaging studies worldwide.

Funding information

Foteini Christidi is supported by the State Scholarships Foundation (I.K.Y.; Postdoctoral Support; EP ANADEDBM/ESPA 2014-2020). Peter Bede is supported by the Health Research Board (HRB -Ireland; HRB EIA-2017-019), the Andrew Lydon scholarship, the Irish Institute of Clinical Neuroscience IICN -Novartis Ireland Research Grant, the Iris O'Brien Foundation, and the Research Motor Neuron (RMN-Ireland) Foundation. The sponsors of this study had no impact on the contents, analyses and conclusions of this paper or the decision to submit it for publication.

Conflict of interest: None


Germán Prados

Florian Chouchou

Sara Carrión-Pantoja

Laura Fernández-Puerta

José Manuel Pérez-Mármol

Javier Albayay

Patricia Villarroel-Gruner

Claudio Bascour-Sandoval

Valentina Parma

Germán Gálvez-García

Germán Gálvez-García

Psychometric properties of the Spanish version of the Sleep Hygiene Index

Keywords: Edinburgh Handedness Inventory, handedness, confirmatory factor analysis, reliability

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The concept of handedness refers to a person's consistent tendency or preference to use one hand instead of the other when performing a certain task [START_REF] Donaldson | The clinical relevance of hand preference and laterality[END_REF][START_REF] Adamo | Establishing hand preference: Why does it matter?[END_REF]. Handedness reflects the habitual preference of acting with one hand, but one's habitual preference to use one hand cannot be equated with a strong asymmetry in dexterity, the ability to perform skilled hand actions. Some individuals with a strong right-hand preference may perform a unimanual motor skill equally well with both hands (or even slightly better with the left non-dominant hand, [START_REF] Hervé | Finger tapping, handedness and grey matter amount in the Rolando's genu area[END_REF]. For instance, a recent study on circle drawing confirmed that the asymmetry in dexterity and handedness for a given skill may vary substantially at the individual level [START_REF] Angstmann | Microstructural asymmetry of the corticospinal tracts predicts right-left differences in circle drawing skill in right-handed adolescents[END_REF].

Despite the study of genetic [START_REF] De Kovel | The molecular genetics of hand preference revisited[END_REF] and epigenetic factors [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF] and the ability to infer it pre-birth [START_REF] Parma | The origin of human handedness and its role in pre-birth motor control[END_REF], handedness -possibly the most studied asymmetry in basic and clinical research -does not produce a consensus on its origin [START_REF] Scharoun | Hand preference, performance abilities, and hand selection in children[END_REF] or how to measure it. Indeed, throughout the years different tools have been developed to accurately evaluate handedness over time. Such tools rely on the assessment of the two main dimensions of motor asymmetry, namely direction and degree of handedness [START_REF] Edlin | On the use (and misuse?) of the Edinburgh Handedness Inventory[END_REF]. The direction of handedness identifies whether an individual habitually prefers to use their right or left hand for unimanual actions [START_REF] Andersen | Mapping dexterity and handedness: Recent insights and future challenges[END_REF]. Nearly 90% of the human population is estimated to be right-handed [START_REF] Adamo | Establishing hand preference: Why does it matter?[END_REF][START_REF] Jang | Are there differences in brain morphology according to handedness?[END_REF][START_REF] Mcmanus | The history and geography of human handedness[END_REF] and the remaining 10% left-handed [START_REF] Edlin | On the use (and misuse?) of the Edinburgh Handedness Inventory[END_REF]. The second dimension -the degree of handedness -refers to how consistently (irrespective of direction) the preferred hand is employed [START_REF] Lyle | Bimanual coordination positively predicts episodic memory: A combined behavioral and MRI investigation[END_REF]. Inconsistent handedness is more prevalent among left-handers (~80%) than right-handers (~40%; [START_REF] Christman | Half Oaks, Half Willows: Degree, Not Direction, of Handedness Underlies Both Stable Prevalence in the Human Population and Species-Beneficial Variations in Cognitive Flexibility[END_REF][START_REF] Prichard | Degree of Handedness, but not Direction, is a Systematic Predictor of Cognitive Performance[END_REF].

Although strictly dichotomous models have been proposed [START_REF] Mcmanus | Right-and left-hand skill: Failure of the right shift model[END_REF], measuring hand preference nowadays includes at least one intermediate category defined based on within-task (ambiguous handedness) and across-task variability (mixed handedness). The term ambiguous-handedness has been used to categorize people who may randomly use the left or the right hand in a given task, without necessarily highlighting differences in performance. Instead, the term mixed-handedness has been used to classify individuals who prefer to use one hand skillfully for a designated task, but would use the opposite hand skillfully for a different task [START_REF] Fazio | Elevated rates of atypical handedness in paedophilia: Theory and implications[END_REF].

Neuroscientists and psychologists have often acknowledged the importance that handedness plays in individual neural, behavioral and cognitive differences. Handedness is an important indicator of the lateralization of cognitive function (e.g., language, [START_REF] Knecht | Handedness and hemispheric language dominance in healthy humans[END_REF]approach motivation, Brookshire &[START_REF] Brookshire | Approach motivation in human cerebral cortex[END_REF]visuo-spatial cognition, Willems et al., 2010), whereas less clear results have been reported regarding its association with the lateralization of brain anatomy (for a review, see [START_REF] Papadatou-Pastou | Chapter 7 -Handedness and cognitive ability: Using metaanalysis to make sense of the data[END_REF]. Arning et al. (2013) advanced (although not conclusively, de Kovel and Francks, 2019) that such inconsistencies may be associated with tandem repeat variation in the PCSK6 gene, for which a role in the pathway for left-right cerebral asymmetry has been suggested. All in all, understanding handedness helps scientists explore the architecture of the human brain and cognition. As pointed out by [START_REF] Papadatou-Pastou | Chapter 7 -Handedness and cognitive ability: Using metaanalysis to make sense of the data[END_REF], confounding findings might be caused by the way handedness is conceptualized (e.g., direction vs. degree), measured (e.g., observation vs. self-report), and classified (e.g., dichotomous models vs. models including intermediate categories).

To validly and reliably capture handedness, researchers have been moving away from mere dichotomous observations of direction of handedness and embracing the greater complexity that emerges from self-reports, behavioral performance, neural and genetic investigations. Importantly, both direction and degree of hand preference have been associated with variability in different i) cognitive processes, such as memory [START_REF] Lyle | Consistency of handedness, regardless of direction, predicts baseline memory accuracy and potential for memory enhancement[END_REF], attention [START_REF] Kourtis | Evidence for dissociable effects of handedness and consistency of hand preference in allocation of attention and movement planning: An EEG investigation[END_REF], cognitive flexibility [START_REF] Gunstad | Handedness and cognition across the healthy lifespan[END_REF] and approach motivation [START_REF] Brookshire | Approach motivation in human cerebral cortex[END_REF], and ii) personal tendencies, such as anxiety [START_REF] Lyle | Is handedness related to anxiety? New answers to an old question[END_REF], creativity [START_REF] Badzakova-Trajkov | Magical ideation, creativity, handedness, and cerebral asymmetries: A combined behavioural and fMRI study[END_REF], extraversion [START_REF] Grimshaw | A sinister plot? Facts, beliefs, and stereotypes about the left-handed personality[END_REF] and risk-taking [START_REF] Christman | Individual differences in risk perception versus risk taking: Handedness and interhemispheric interaction[END_REF].

When looking at the neural correlates associated with handedness, both structural and functional differences have emerged. For instance, a recent study on large-scale brain tractography concluded that right-handers show greater intra-hemispheric clusterization in the topology of the white matter as compared to left-handers [START_REF] Li | Handednessand hemisphere-related differences in small-world brain networks: a diffusion tensor imaging tractography study[END_REF]. This pattern of results is mirrored at the functional level when considering the activation of the supplementary motor area [START_REF] Pool | Handedness and effective connectivity of the motor system[END_REF]. These differences in inter-hemispheric interaction could be due to less prominent lateralization of manual abilities for left-handers [START_REF] Andersen | Mapping dexterity and handedness: Recent insights and future challenges[END_REF]. Although linking functional and structural differences in the corticospinal motor system to handedness has produced mixed outcomes, some recent studies demonstrate that both the direction and the degree of handedness produce effects measurable at the cortical level. For instance, the direction of handedness influences the cortical organization of upper limb muscles in M1, with right-handers showing wider and more postero-lateral representations in the non-dominant hemisphere than left-handers [START_REF] Nicolini | Human motor cortical organization is influenced by handedness[END_REF]. Additionally, the degree of handedness predicts whether electrically stimulating the frontal cortex via tDCS increases or decreases lateralized approach motivation, which manifests in opposite tendencies in left-and right-handers [START_REF] Brookshire | Approach motivation in human cerebral cortex[END_REF]. When moving to structural observations, consistent handedness is associated with decreased callosal thickness [START_REF] Luders | When more is less: Associations between corpus callosum size and handedness lateralization[END_REF], which may provide a reason why consistent right-handers show decreased functional interaction between processes lateralized in opposite hemispheres [START_REF] Christman | Mixed-handedness advantages in episodic memory obtained under conditions of intentional learning extend to incidental learning[END_REF][START_REF] Christman | Factor analysis of the Edinburgh Handedness Inventory: Inconsistent handedness yields a two-factor solution[END_REF], while inconsistent handers show better coordination of hemispherically-segregated processing in the prefrontal lobes while performing demanding episodic retrieval tasks [START_REF] Lyle | Handedness is related to memory via hemispheric interaction: Evidence from paired associate recall and source memory tests[END_REF].

It becomes clear how any tool that informs reliably on hand preference is in the service of the greater endeavor of understanding the relationship between handedness and cognitive ability. Given the ease, speed and cost-effectiveness of their administration, selfreported questionnaires are the most common tool to determine handedness. Throughout the years different questionnaires measuring direction and degree of handedness have been created and optimized, with the Annett Questionnaire [START_REF] Annett | A classification of hand preference by association analysis[END_REF] and the Edinburgh Handedness Inventory (EHI; [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF] being the most popular [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Williams | Handedness inventories: Edinburgh versus Annett[END_REF].

Among the self-reported questionnaires, the EHI [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF] is the most frequently cited instrument [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Veale | Edinburgh Handedness Inventory -Short Form: A revised version based on confirmatory factor analysis[END_REF][START_REF] Yang | Translation, cultural adaption, and test-retest reliability of Chinese versions of the Edinburgh Handedness Inventory and Waterloo Footedness Questionnaire[END_REF]. As evidence of its popularity, in the past five years the citation index of the EHI [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF]) increased from ~11,000 [START_REF] Veale | Edinburgh Handedness Inventory -Short Form: A revised version based on confirmatory factor analysis[END_REF] to more than 24,400 (as of September 2019, Scopus). The EHI has been used to evaluate handedness in the United Kingdom [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF][START_REF] Williams | Handedness inventories: Edinburgh versus Annett[END_REF], Germany [START_REF] Büsch | The dimensionality of the Edinburgh Handedness Inventory: An analysis with models of the item response theory[END_REF], Italy [START_REF] Begliomini | The Neural Correlates of Grasping in Left-Handers: When Handedness Does Not Matter[END_REF][START_REF] Viggiano | Hand preference in Italian students[END_REF]), Portugal (Espírito-Santo et al., 2017), the Czech Republic [START_REF] Komarc | Psychometric properties of the Edinburgh Handedness Inventory in children[END_REF], Serbia [START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF], Algeria [START_REF] Nedjar | La préférence manuelle dans une population d'étudiants algériens francophones et comparaison avec la population française[END_REF], China [START_REF] Yang | Translation, cultural adaption, and test-retest reliability of Chinese versions of the Edinburgh Handedness Inventory and Waterloo Footedness Questionnaire[END_REF], Korea [START_REF] Kang | Handedness and footedness in Korean college students[END_REF], Australia [START_REF] Dragovic | Towards an improved measure of the Edinburgh Handedness Inventory: A one-factor congeneric measurement model using confirmatory factor analysis[END_REF][START_REF] Mcfarland | Factor stability of the Edinburgh Handedness Inventory as a function of test-retest performance, age and sex[END_REF], Canada [START_REF] Fazio | Factor Structure of the Edinburgh Handedness Inventory Versus the Fazio Laterality Inventory in a Population With Established Atypical Handedness[END_REF], the United States [START_REF] Corey | Right and Left Handedness Defined A Multivariate Approach Using Hand Preference and Hand Performance Measures[END_REF][START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF], Brazil [START_REF] Brito | Lateral preferences in Brazilian adults: An analysis with the Edinburgh Inventory[END_REF], Mexico [START_REF] Cuencas | El inventario de Edimburgo: Evaluación de la lateralidad cerebral en una población mexicana[END_REF] and Chile [START_REF] Camposano | Effects of stimulation intensity, gender and handedness upon auditory evoked potentials[END_REF][START_REF] Letelier | Implementación y validación de protocolo de estimulación por comprensión de lenguaje oral en resonancia magnética funcional: resultados preliminares[END_REF], among others.

As pointed out by [START_REF] Edlin | On the use (and misuse?) of the Edinburgh Handedness Inventory[END_REF], many variations of the EHI have been used experimentally, resulting in the EHI including different items, response formats and classification rules of right-handed individuals across versions. The poor translation of an instrument, when not certified with the state-of-the-art back-translation [START_REF] Sousa | Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and userfriendly guideline[END_REF] and committee approaches [START_REF] Furukawa | A committee approach maintaining cultural originality in translation[END_REF], can lead to bias in the response pattern and reduce the comparability of findings across studies [START_REF] Beaton | Guidelines for the process of cross-cultural adaptation of self-report measures[END_REF]. This is the case of the currently available Spanish versions of the EHI, for which the translation process has not been thoroughly documented and a careful psychometric evaluation is lacking. Additionally, the role of socio-demographic influences on handedness (e.g., age and region of residence, [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF] has not yet been evaluated in samples of Spanish speakers.

Given the lack of a valid and reliable Spanish version of the EHI, the aim of this study was to appropriately translate the EHI into Spanish and assess its psychometric properties [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF]. Based on previous research (e.g., [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Fazio | Factor Structure of the Edinburgh Handedness Inventory Versus the Fazio Laterality Inventory in a Population With Established Atypical Handedness[END_REF], we expect to replicate a single factor structure via a confirmatory factor analysis in a sample of Chilean university students accounting for possible sociodemographic influences.

Method

Participants

A sample of 348 Chilean university students (mean age = 21 years old, SD = 3.7, age range = 19-34 years old) was selected using non-probability convenience sampling. This sample size is deemed to be adequate for the execution of a confirmatory factor analysis (CFA; N ≥ 300 according to [START_REF] Moshagen | Sample Size Requirements of the Robust Weighted Least Squares Estimator[END_REF]. The sample was composed of students from five Chilean universities enrolled in different programs. At the time of participation, 70.1% of the participants were enrolled in physiotherapy, 18.4% in nutrition and dietetics, 6% in psychology and 5.5% in business. The participants volunteered to participate in the study, without receiving any type of compensation.

Participants took part in the study in large groups in the classroom. Those who volunteered to participate were provided a written informed consent as well as a paper version of the questionnaires. On average the procedure was completed in 10-15 minutes. This study was approved by the Science Ethics Committee of the Universidad de La Frontera and implemented according to its guidelines and based on the principles of the Declaration of Helsinki (World Medical Association, 2013).

Instruments

This study included a 10-item self-reported version of the Edinburgh Handedness Inventory (EHI, [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF]. The EHI measures the participant's hand preference during certain tasks (see Table 1). In the present study, we used the instructions and response format proposed by [START_REF] Veale | Edinburgh Handedness Inventory -Short Form: A revised version based on confirmatory factor analysis[END_REF]. To obtain a measurement equivalent to this version of the EHI, the instrument was translated into neutral Spanish following a backtranslation procedure (see [START_REF] Sousa | Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and userfriendly guideline[END_REF] in line with recent validation studies of the EHI [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Yang | Translation, cultural adaption, and test-retest reliability of Chinese versions of the Edinburgh Handedness Inventory and Waterloo Footedness Questionnaire[END_REF]. First, a translator not connected to the purposes of the study and a bilingual psychologist translated the instructions, items and response options on the EHI from English into Spanish. Both the English and the Spanish translations were then reviewed by a second bilingual psychologist, and minor observations were discussed with the investigators. Then, a second external translator and a third psychologist who was not part of the study back-translated the instrument into English. Finally, both the forward and back translations were compared to produce the final version of the instrument in Spanish, which was evaluated for clarity by native Spanish speakers from Chile and Spain. To evaluate possible issues with this Spanish version of the EHI, the instrument was tested on 12 university students (mean age = 19.7 years old, SD = 1.4). None of the participants indicated difficulties in completing the inventory during debriefing; these participants were not included in the final sample of this study.

The original instructions of the EHI ask the participant to mark the symbol "+" for each item in one of two columns assigned for left-or right-hand preference. When the preference is so strong that the other hand would never be used unless forced, the participant is asked to mark "++" in one of the columns. If they are indifferent, they are asked to mark "+" in both columns. Some activities require the use of both hands. In these cases, the part of the task or object for which the determination of hand preference is to be made is indicated in parentheses. It has been previously shown that these instructions frequently lead to misinterpretation by the participants [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF][START_REF] Fazio | An Improved Measure of Handedness: The Fazio Laterality Inventory[END_REF]. To improve adherence to the instructions (following [START_REF] Christman | Factor analysis of the Edinburgh Handedness Inventory: Inconsistent handedness yields a two-factor solution[END_REF][START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF][START_REF] Veale | Edinburgh Handedness Inventory -Short Form: A revised version based on confirmatory factor analysis[END_REF] we changed the response format to a 5-point Likert-type response scale (1 = always right, 2 = usually right, 3 = both equally, 4 = usually left, 5 = always left) as in [START_REF] Veale | Edinburgh Handedness Inventory -Short Form: A revised version based on confirmatory factor analysis[END_REF], who obtained reliable data in line with previous research [START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF]. The instructions, items and response format of the Spanish version of the EHI are shown in Table 1.

To determine the role of socio-demographic variables on handedness as measured by the new version of the Spanish EHI, a brief socio-demographic survey was included to characterize the sample in terms of sex, area of residence (rural vs. urban), belonging to an indigenous people or community (yes or no, if yes, which one?) and university program.

Table 1. Spanish Version of the Edinburgh Handedness Inventory

Instrucciones. Por favor, indica tus preferencias en el uso de las manos en las siguientes actividades. Algunas de las actividades requieren de ambas manos. En estos casos, la parte de la tarea u objeto para la cual se busca la preferencia manual, se indica entre paréntesis.

[Instructions. Please indicate your preferences in the use of hands in the following activities. Some of the activities require both hands. In these cases the part of the task, or object, for which hand preference is wanted is indicated in brackets.]

Items

Data analysis

A laterality quotient (LQ) was estimated based on the following calculation: LQ = (R-L) / (R+L) × 100, assigning two points to L or R for each item marked always left or always right, respectively, one point for L or R for those indicated as usually left or usually right correspondingly, and one point for both L and R for each item where both equally was indicated. The LQ were compared across sex (female vs. male), area of residence (urban vs. [START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF]. As pointed out by Dragovic (2004a), a cutoff value between 50 and 70 provides the greatest agreement with classification based on statistical criteria, whereas cutoffs below 50 and greater than 70 were progressively lower in agreement with statistical criteria, producing a higher number of misclassifications. On the other hand, in order to determine whether participants were categorized as ambiguous due to a high proportion of "either" responses or due to a contrast between "left" or "right" responses, we distinguished between ambiguous-handedness and mixed-handedness.

Although the methodology to determine these categories has not yet reached a consensus, based on Espírito-Santo et al. ( 2017) we classified participants as follows: truly ambiguous (i.e., five or more "either" responses), mixed-handed (i.e., 0-1 "either" and 0-9 "left" or 0-1"right" responses, with at least one "left" and one "right), right-handed (i.e., 6-10 "right" and 0-4 "either" or 0-1 "left" responses) and left-handed (i.e., 6-10 "left" and 0-4 "either" responses). Cramer's V was used to test the association between the two types of handedness categorization (i.e., the one based on the cutoff score of 60 and the one that distinguishes between ambiguous and mixed-handed).

To confirm the factorial structure of the EHI [a first-order latent factor (handedness) and 10 indicators (inventory items)], we ran a CFA, considering the following goodness-offit indicators: chi-squared (χ²), the comparative fit index (CFI ≥ 0.95), the Tucker-Lewis index (TLI ≥ 0.90), the root mean square error of approximation (RMSEA ≤ 0.06) and the standardized root mean square residual (SRMR ≤ 0.08) according to the cutoff scores established by [START_REF] Hu | Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives[END_REF]. If in case of statistical significance of Mardia's multivariate normality test, the maximum likelihood estimation was used with the Satorra-Bentler robust correction [START_REF] Satorra | Scaling corrections for chi-square statistics in covariance structure analysis[END_REF].

From a perspective centered on the comparison of models [START_REF] Mcelreath | Statistical rethinking: A Bayesian course with examples in R and Stan[END_REF], the Akaike information criterion (AIC) was estimated to account for the model with the best fit of the data (i.e., lowest relative AIC). The internal consistency of the instrument was also evaluated using Cronbach's alpha coefficient, while composite reliability (CR ≥ 0.7) and the average variance extracted (AVE ≥ 0.5) were estimated to assess the reliability and convergent validity of the instrument, respectively, according to the guidelines of [START_REF] Fornell | Evaluating Structural Equation Models with Unobservable Variables and Measurement Error[END_REF]. The statistical analyses were performed using the STATA 14.1 MP software [START_REF] Statacorp | Stata Statistical Software: Release 14[END_REF].

Results

Adopting a cutoff score of 60 for the LQ of the EHI (mean = 73, SD = 42), 82.2% of the sample was characterized as right-handed, 13.2% as ambiguous and 4.6% as left-handed, not being equally distributed, χ 2 (2) = 377.586, p < 0.001. Considering the pattern of responses to distinguish between truly ambiguous and mixed-handed individuals, 75% of the sample was characterized as right-handed, 3.7% as left-handed, 4.9% as truly ambiguous and 16.4% as mixed-handed. Following this classification, the individuals categorized as ambiguous based on the cutoff of 60, 56.5% were truly ambiguous and 43.5% mixed-handed. As the two types of handedness categorization were significantly associated, χ 2 (6) = 442.963, p < 0.001, Cramer's V = 0.798, the description of the sample is shown in Table 2 based on the established cutoff criteria. No significant differences were found when considering area of residence, χ 2 (1) = 1.131, p = 0.288 and belonging to an indigenous people or community, χ 2 (1) = 0.151, p = 0.698. However, sex provides a trending result: χ 2 (1) = 3.520, p = 0.061, with women being more frequently right-handed than men. The mean and standard deviation (SD) of the socio-demographic variables by LQ are shown in Table 3. The following results are derived via maximum likelihood estimation with the Satorra-Bentler robust correction [START_REF] Satorra | Scaling corrections for chi-square statistics in covariance structure analysis[END_REF]. The standardized factor loadings of the indicators of a unifactorial model including the 10 items of the EHI (see Figure 1) varied between 0.38 and 0.98 (all values p < 0.001). However, considering that the goodness-of-fit indicators of this model were not within the selected criteria [START_REF] Hu | Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives[END_REF]; see upper row of Table 4), and given the presence of collinearity between items one and two (writing and drawing, respectively; r = 0.97), a second model was estimated. with the requirements for the study [START_REF] Hu | Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives[END_REF]; see lower row of Table 4). The computed models were compared using a likelihood-ratio test. The test was statistically significant (p < 0.001), indicating that the second model produced a better solution than the first. The comparison of the models and their respective goodness-of-fit indicators are shown in Table 4. In addition, Cronbach's alpha coefficient was 0.92, demonstrating that the instrument has very high internal consistency. According to the criteria followed in this study [START_REF] Fornell | Evaluating Structural Equation Models with Unobservable Variables and Measurement Error[END_REF], model two accounted for a suitable composite reliability (CR = 0.91) and convergent validity (AVE = 0.53). Note: The goodness-of-fit indicators were adjusted using the Satorra-Bentler robust correction. ***p < 0.001.

Discussion

The aim of this study was to analyze the psychometric properties of a rigorously translated Spanish version of the EHI [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF], confirming its unifactorial structure, in a sample of Chilean university students and to test the possible confounders included by different socio-demographic variables. In line with previous evidence, the vast majority of the sample was characterized as right-handed in a proportion similar to previously analyzed samples. Additionally, the percentage of left-handed people was inferior to that of the individuals categorized as ambiguous (both truly ambiguous and mixed-handed) in line with previous psychometric evaluations [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF][START_REF] Komarc | Psychometric properties of the Edinburgh Handedness Inventory in children[END_REF][START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF][START_REF] Williams | Handedness inventories: Edinburgh versus Annett[END_REF]. In this regard, in contrast to the findings obtained with the Annett Questionnaire [START_REF] Annett | A classification of hand preference by association analysis[END_REF], [START_REF] Williams | Handedness inventories: Edinburgh versus Annett[END_REF] noted that individuals tend to respond both equally rather than choosing left as the alternative response [START_REF] Papadatou-Pastou | Measuring hand preference: A comparison among different response formats using a selected sample[END_REF]. In a similar vein, Espírito-Santo et al.

(2017), who used different methods to calculate hand preference on the basis of the LQ, reported that the categorical classification of handedness largely depends on the cutoff scores used, which renders comparison between studies difficult (see also [START_REF] Edlin | On the use (and misuse?) of the Edinburgh Handedness Inventory[END_REF]. For their part, [START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF], by using a reduced and modified version of the EHI, were able to unfairly classify likely right-handed individuals as belonging to the mixed category, which is sometimes associated with pathologies.

As expected, the results of this study corroborate the 10-item unifactorial structure of the EHI [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF], providing evidence of excellent goodness-of-fit indicators, very high internal consistency, suitable composite reliability and suitable convergent validity for this Spanish version of the EHI. Although previous studies have criticized the unidimensionality of the EHI [START_REF] Büsch | The dimensionality of the Edinburgh Handedness Inventory: An analysis with models of the item response theory[END_REF][START_REF] Christman | Factor analysis of the Edinburgh Handedness Inventory: Inconsistent handedness yields a two-factor solution[END_REF], several psychometric analyses have corroborated this factor structure. Studies that have used CFA [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Fazio | Factor Structure of the Edinburgh Handedness Inventory Versus the Fazio Laterality Inventory in a Population With Established Atypical Handedness[END_REF] have reproduced the unifactorial structure of the instrument when some items were eliminated [START_REF] Dragovic | Towards an improved measure of the Edinburgh Handedness Inventory: A one-factor congeneric measurement model using confirmatory factor analysis[END_REF][START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF]. For example, [START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF] determined that the measurement properties of the EHI were poor, suggesting a brief version that eliminated problematic items, such as broom and open a box. It is worth noting that although the results of this study corroborated the validity and reliability of the EHI, these two items were the ones that presented the lowest, albeit fair, factor loadings (> 0.45 according to [START_REF] Tabachnick | Using multivariate statistics[END_REF]. This is not uncommon when dealing with the adaptation of an instrument to a new context [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF]. However, [START_REF] Milenkovic | Modification of the Edinburgh Handedness Inventory: A replication study[END_REF] also labeled the items writing and drawing as problematic, eliminating the latter, given the presence of collinearity. This was also the case in this study, but when modeling a correlation between these two items, instead of eliminating one of them, factor loadings, goodness-of-fit indicators and AIC were optimized. It has been suggested that the differences in the factor solutions may be due to differences in the way in which handedness is assessed, a result of cultural differences and the difficulty in following the instructions [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF]. The latter seems less likely with regard to the present study, since a rigorous translation process was followed [START_REF] Sousa | Translation, adaptation and validation of instruments or scales for use in cross-cultural health care research: a clear and userfriendly guideline[END_REF], and simplified instructions and a Likert-type response format were adopted [START_REF] Christman | Factor analysis of the Edinburgh Handedness Inventory: Inconsistent handedness yields a two-factor solution[END_REF][START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF][START_REF] Veale | Edinburgh Handedness Inventory -Short Form: A revised version based on confirmatory factor analysis[END_REF].

However, the initial argument of Espírito-Santo et al. ( 2017) seems more appropriate if we consider that not all the studies mentioned followed the same exact instructions [START_REF] Edlin | On the use (and misuse?) of the Edinburgh Handedness Inventory[END_REF].

Although carefully conducted, this study is not free of limitations. To the best of our knowledge, this is the first evaluation of the psychometric properties of a version of the EHI rigorously translated into Spanish. However, like many other studies, it is confined to a student sample for practical reasons (e.g., ease of access to the sample and cost reduction).

Thus, generalization of the results of this study must await the application of this instrument to more heterogeneous samples; nevertheless, it represents a useful resource for the vast corpus of studies that include university students as participants [START_REF] Hanel | Do Student Samples Provide an Accurate Estimate of the General Public?[END_REF]. Importantly, the validation of this Spanish version of the EHI following rigorous statistical criteria is a tool that can benefit research in communities that speak Spanish, the second most spoken language worldwide by number of native speakers (Eberhard et al., 2019).

On the whole, the present study revealed that the Spanish version of the EHI is a valid tool for measuring handedness in Chilean individuals, with the potential for use in other Spanish-speaking countries. The Spanish EHI version is intended to be representative of typical individuals and it should very cautiously be generalized to pathological populations (as explored in [START_REF] Fazio | Elevated rates of atypical handedness in paedophilia: Theory and implications[END_REF]. Taking into account this consideration, researchers intending to work with Spanish speakers can make use of this tool, for instance, to study the effect/association of handedness on/with a phenomenon of interest (e.g., cognitive functioning). Many researchers might be interested also in selecting or excluding individuals on the basis of hand preferences to control a certain amount of variability (e.g., in order to compare groups matched regarding handedness; [START_REF] Edlin | On the use (and misuse?) of the Edinburgh Handedness Inventory[END_REF]. However, although the practice of excluding left-handed individuals from studies is not uncommon, it is known that this represents a limitation in the generalization of results and, ultimately, in the understanding of brain functioning [START_REF] Willems | On the other hand: including lefthanders in cognitive neuroscience and neurogenetics[END_REF].

Finally, with the general aim of detailing the features of our convenience sample, we have paid great attention to including a series of socio-demographic variables. None of the controlled socio-demographic variables in this study significantly modulated handedness, and this could be dependent on the low heterogeneity of the sample. In line with previous studies [START_REF] Oldfield | The assessment and analysis of handedness: The Edinburgh Inventory[END_REF][START_REF] Yang | Translation, cultural adaption, and test-retest reliability of Chinese versions of the Edinburgh Handedness Inventory and Waterloo Footedness Questionnaire[END_REF], women tend to be categorized more often as right-handed than men as reflected in a higher LQ (however see [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Williams | Handedness inventories: Edinburgh versus Annett[END_REF] for lack of sex differences). Although the area of residence has scarcely been studied in terms of handedness, Espírito-Santo et al. (2017) showed that the EHI classified individuals as right-handed less frequently in suburban than in rural areas, suggesting that this phenomenon may reflect geographic and cultural pressure to be right-handed. It should be pointed out that our study included urban and rural areas, and like Espírito-Santo et al. ( 2017) found no differences. Finally, this study included the variable belonging to an indigenous people or community, given its high local relevance. Considering that all the cases of indigenous people or community identified as Mapuche, it should be emphasized that in this culture right is strongly associated with the concepts of good and life, whereas left is strongly associated with bad and evil [START_REF] Faron | Symbolic Values and the Integration of Society Among the Mapuche of Chile[END_REF]. Despite the low sample size of this Mapuche subsample, the cultural pressure to be right-handed does not seem to be distinctive to this group. Instead, cultural right-handed bias may be shared by multiple groups [START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Harris | Chapter 8 Cultural Influences on Handedness: Historical and Contemporary Theory and Evidence[END_REF].

Overall, this adapted, Spanish version of the EHI has proven to be a valid and reliable instrument to measure hand preference in university students, being a rapid and cost-effective tool that is easy to administer. It contributes to the greater purpose of ultimately aiding the understanding of human cognitive and neural architecture, which is bounded to the availability of tools that measure accurately both direction and degree of handedness. By making the EHI available to the Spanish population at large, researcher and clinicians will produce a robust and large amount of data used to this end. Additionally to gain a better understanding of the anatomical bases of handedness, the application of valid and reliable versions of the EHI will contribute to broader related areas of research, such as the ontogenesis and clinical significance of hemispheric asymmetries (e.g., [START_REF] Francks | LRRTM1 on chromosome 2p12 is a maternally suppressed gene that is associated paternally with handedness and schizophrenia[END_REF]Arning et al., 2013;[START_REF] Ocklenburg | Handedness: a neurogenetic shift of perspective[END_REF] and their effects on cognition and behavior.

Figure captions

  rural) and belonging to an indigenous people or community (indigenous vs. nonindigenous) by means of Kruskal-Wallis tests following assessment of the non-normality of LQ via the Kolmogorov-Smirnov test (p < 0.001). The frequency of the hand preference categories was contrasted using a one-way chi-square test. Considering a cutoff score of 60, the LQ was used to classify the hand preference of each participant as left-handed (-100 to -61), ambiguous (-60 to 60) or right-handed (61 to 100) in line with previous studies that have evaluated the performance of the EHI[START_REF] Espírito-Santo | Preliminary validation of the Portuguese Edinburgh Handedness Inventory in an adult sample[END_REF][START_REF] Fazio | The original instructions for the Edinburgh Handedness Inventory are misunderstood by a majority of participants[END_REF]

Figure 1 .

 1 Figure 1. Confirmatory factor analysis of model 1. The digits close to the arrows refer to the standardized factor loadings. Error variances are represented in the circles at the bottom.

Figure 2 .

 2 Figure 2. Confirmatory factor analysis of model 2. The digits close to the arrows refer to the standardized factor loadings. Error variances are represented in the circles at the bottom.

Figure 1 .

 1 Figure 1. Confirmatory factor analysis of model 1. The digits close to the arrows refer to the standardized factor loadings. Error variances are represented in the circles at the bottom.

Figure 2 .

 2 Figure 2. Confirmatory factor analysis of model 2. The digits close to the arrows refer to the standardized factor loadings. Error variances are represented in the circles at the bottom.

Table 2 .

 2 Socio-demographic characterization of the sample.

	Variables	Total (N = 348)	Right-handed (n = 286)	Handedness Ambiguous (n = 46)	Left-handed (n = 16)
	Sex
	Female	68.1%	84.4%	11.0%	4.6%
	Male	31.9%	77.5%	18.0%	4.5%
	Area of residence
	Rural	11.2%	79.5%	20.5%	0.0%
	Urban	88.8%	82.5%	12.3%	5.2%
	Belonging to an indigenous
	people or community
	Yes	19.3%	88.0%	7.5%	4.5%
	No	80.7%	80.8%	14.6%	4.6%

Note: The participants who indicated they belonged to an indigenous people or community identified as Mapuche.

Table 3 .

 3 Laterality quotients.

	Variables	Mean ± SD	Range
	Sex
	Female	75.1 ± 41.3	-100 -100
	Male	68.6 ± 43.5	-100 -100
	Area of residence
	Rural	76.2 ± 23.3	-17.7 -100
	Urban	72.6 ± 43.9	-100 -100
	Belonging to an indigenous
	people or community
	Yes	74.4 ± 40.8	-100 -100
	No	72.7 ± 42.4	-100 -100

Table 4 :

 4 Comparison of models and goodness-of-fit indicators.

	Model	χ 2 (df)	Δχ 2	CFI	TLI	RMSEA	SRMR	AIC
	1	291.22(35)***		0.850	0.807	0.145	0.093	7681.224
	2	74.03(34)***	217.19***	0.977	0.969	0.058	0.036	7370.286

Acknowledgements

This research was partially supported by the National Fund for Scientific and Technological Development (FONDECYT), project number 1160368, granted by the National Commission for Scientific and Technological Research (CONICYT), and by the Home Office Research from the Universidad de La Frontera (DI19-1012). Thanks to Felipe Rivera-Cepeda for his help with the data acquisition. Thanks to Dr. Helen M. Lowry for proofreading the article.

Competing interests

The authors declare no competing interests.

Author's contributions

JA, PV-G and CB-S collected and analyzed the data. JA, PV-G, CB-S, VP and GG-G wrote the manuscript. All of the authors read and approved the final version of the manuscript.