Briend F Phd
email: briend@cyceron.fr

A new toolbox to compare target localizations for non-invasive brain stimulation: An application of rTMS treatment for auditory hallucinations in schizophrenia

Keywords: Schizophrenia, rTMS, T3P3, auditory verbal hallucinations, geodesic distance, software

Background: Most repetitive transcranial magnetic stimulation (rTMS) studies aiming to reduce auditory verbal hallucinations (AVH) in schizophrenia target the left temporo-parietal junction (TPJ), but the efficacy of this approach remains controversial. The observed differences in efficacy could be attributed to inaccurate target localization. Here, to precisely quantify anatomical bias induced by localization method, we developed a free open-source software (GeodesicSlicer) that computes shortest curved path (i.e. geodesic) between rTMS targets. Here we compare a personalized target with accurate anatomical criteria with a standardized target based on the 10-20 EEG system (the middle between T3 and P3 electrodes: T3P3).

Methods: We compare in 69 patients with schizophrenia the geodesic distances of two approaches for rTMS target localization within the left TPJ. In addition, we characterize the personalized target according to the 10-20 EEG system.

Results: A differential of 3 cm in term of geodesic distance between rTMS localization approaches was observed. Moreover, this personalized target to treat AVH is located at 25% in the T3-P3 axis.

Conclusions: This software for rTMS localization comparison demonstrates the difference between standardized and personalized rTMS target. This difference has the potential to explain a part of the dissonant clinical results found in previous rTMS studies.

Introduction

Repetitive transcranial magnetic stimulation (rTMS) over the left temporo-parietal junction (TPJ) has emerged as a treatment to reduce auditory verbal hallucinations (AVH) in schizophrenia (Dollfus et al., 2016a;[START_REF] Hoffman | Transcranial magnetic stimulation of left temporoparietal cortex in three patients reporting hallucinated "voices[END_REF][START_REF] Hoffman | Transcranial magnetic stimulation and auditory hallucinations in schizophrenia[END_REF]. The TPJ is involved in both language processes and AVH [START_REF] Kühn | Quantitative Meta-Analysis on State and Trait Aspects of Auditory Verbal Hallucinations in Schizophrenia[END_REF], however previous studies targeting rTMS to the left TPJ have reported inconsistent efficacies (Dollfus et al., 2016a;[START_REF] Kennedy | Efficacy of non-invasive brain stimulation on the symptom dimensions of schizophrenia: A meta-analysis of randomized controlled trials[END_REF][START_REF] Montagne-Larmurier | Repetitive transcranial magnetic stimulation in the treatment of auditory hallucinations in schizophrenic patients[END_REF][START_REF] Slotema | Review of the Efficacy of Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations[END_REF]. These inconsistencies could be due to the study design (sham condition or not, type of clinical study, the type of coil used, …) (Dollfus et al., 2016b), different stimulation frequency [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF](Dollfus et al., , 2016b)), and inaccurate site determination, depending on different approaches to target the TPJ rTMS site [START_REF] Donaldson | Noninvasive stimulation of the temporoparietal junction: A systematic review[END_REF][START_REF] Sack | Optimizing functional accuracy of TMS in cognitive studies: a comparison of methods[END_REF]. The TPJ is a supramodal association area, with no consensus on coordinates or anatomical landmarks [START_REF] Bzdok | Characterization of the temporo-parietal junction by combining data-driven parcellation, complementary connectivity analyses, and functional decoding[END_REF]. This large area contrasts with the sharp shape focality of the rTMS magnetic field [START_REF] Cohen | Effects of coil design on delivery of focal magnetic stimulation. Technical considerations[END_REF].

Consequently, rTMS efficacy might be improved by a better target identification that might decrease the inter-subjects variability [START_REF] Nathou | Cortical Anatomical Variations and Efficacy of rTMS in the Treatment of Auditory Hallucinations[END_REF][START_REF] Ruohonen | Navigated transcranial magnetic stimulation[END_REF]. One way is to take into account the anatomical variability since previous reports have shown that the effects of the stimulation are proportional to the distance from the stimulation to the target [START_REF] Cohen | Effects of coil design on delivery of focal magnetic stimulation. Technical considerations[END_REF][START_REF] Fadini | H-coil: Induced electric field properties and input/output curves on healthy volunteers, comparison with a standard figure-of-eight coil[END_REF]. However, most clinical applications are based on standardized targeting methods that do not take into account for individual anatomy, which can contribute to suboptimal clinical responses compared to other methods such as personalized targeting techniques based on individual brain imaging [START_REF] Herbsman | Anatomically based targeting of prefrontal cortex for rTMS[END_REF].

Currently, there are two methods for targeting the TPJ. On one hand, the Standardized Target method (ST) uses the standardized T3P3 site according to the International 10-20 system of electroencephalogram (EEG) electrode positioning [START_REF] Jasper | The ten twenty electrode system of the international federation[END_REF][START_REF] Klem | The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology[END_REF]. This site determination is widely applied for positioning the coil in the cognitive neurosciences and in psychiatric treatments, but is known to be a rough estimation, especially given its variable projections on the individual brain [START_REF] Herwig | Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation[END_REF]. On the other hand, the Personalized Target (PT) method based on the magnetic resonance imaging (MRI) [START_REF] Sommer | Toward personalized treatment of hallucinations[END_REF][START_REF] Sommer | Can fMRI-guidance improve the efficacy of rTMS treatment for auditory verbal hallucinations?[END_REF] uses the subject's own structural or functional images to guide target placement [START_REF] Herwig | The navigation of transcranial magnetic stimulation[END_REF][START_REF] Sack | Optimizing functional accuracy of TMS in cognitive studies: a comparison of methods[END_REF]. While the findings of Sack and colleagues revealed a systematic behavioral difference between these TMS localization approaches [START_REF] Sack | Optimizing functional accuracy of TMS in cognitive studies: a comparison of methods[END_REF], no tools allow to compare the rTMS site determination.

Recently in a PT study, we observed a significant improvement of AVH after delivering rTMS at one accurate anatomical site [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF]. We therefore postulated that choosing ST using 10-20 EEG system over PT using anatomical landmarks could induce an anatomical bias able to explain clinical outcomes. In order to precisely quantify this anatomical bias, and because using different TMS targeting methods will lead to somewhat different scalp targets, we developed a free open-source software: GeodesicSlicer [START_REF] Briend | GeodesicSlicer: a Slicer Toolbox for Targeting Brain Stimulation[END_REF], that computes the shortest path at scalp-surface between any rTMS targets, whether localized by MRI-guided neuronavigation or by the 10-20 EEG system.

Material and methods

GeodesicSlicer: Toolbox for rTMS localization comparison

The ST localization corresponding to a particular scalp position (T3P3) and the PT localization determined by computerized cortical MRI scan must be in a common space to be properly compared. To reach this goal, we developed the open-source tool GeodesicSlicer (The code and description are available in the Wikipage) [START_REF] Briend | GeodesicSlicer: a Slicer Toolbox for Targeting Brain Stimulation[END_REF]. This software is based on the geodesic distance measurement (defined as the shortest path between two points in a curved space) at scalp-surface calculated on a mesh morphed to participantspecific brain MRI. The provided toolbox creates 3D mesh morphed to the structural MRI head data of the participant and implements Dijkstra's algorithm to calculate the shortest path to the vertices of a triangle on a mesh [START_REF] Curran | A note on two problems in connexion with graphs[END_REF]. Thanks to the Dijkstra's algorithm and according to the international guidelines of the 10-20 EEG [START_REF] Jasper | The ten twenty electrode system of the international federation[END_REF][START_REF] Klem | The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology[END_REF], an individualized 10-20 system EEG was projected onto the head surface of the participant (see Fig. 1). Finally, the software calculates the geodesic distances between any given rTMS localizations. The guidelines to realize that is described in the toolbox documentation on our Wikipage (via the steps of the "Parameters to find the shortest path" module of the software: https://www.slicer.org/wiki/Documentation/Nightly/Modules/GeodesicSlicer#Parameters_to_ find_the_shortest_path).

Standardized site determination (ST)

Sixty-nine T1-weighted images of schizophrenia patients (SZ; 37.81 ± 8.86 years; 26 women, DSM IV-TR (American Psychiatric Association, 2000)) recruited from our previous studies [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF][START_REF] Maïza | Impact of Repetitive Transcranial Magnetic Stimulation (rTMS) on Brain Functional Marker of Auditory Hallucinations in Schizophrenia Patients[END_REF][START_REF] Montagne-Larmurier | Repetitive transcranial magnetic stimulation in the treatment of auditory hallucinations in schizophrenic patients[END_REF] were included to locate ST on their individual meshes.

Imaging was performed with a 3-Tesla scanner (Intera Achieva 3T, Philips Medical System, the Netherlands) to acquire a T1-weighted whole-brain anatomical image [3D-FFE-TFE sequence; matrix size, 256 × 256 with 180 contiguous slices; field of view: 256 mm; isotropic resolution, 1 mm; sagittal slice orientation; repetition time: 20 ms; echo time: 4.6 ms; flip angle: 101°; inversion time: 800 ms; SENSE factor, 2].

Triangle meshes morphed to participant-specific MRI native space were reconstructed from the 69 T1-weighted whole-brain anatomical image using 3D Slicer software [START_REF] Fedorov | 3D Slicer as an image computing platform for the Quantitative Imaging Network[END_REF][START_REF] Pieper | The NA-MIC Kit: ITK, VTK, pipelines, grids and 3D slicer as an open platform for the medical image computing community[END_REF] (http://www.slicer.org, "editor toolbox" version 4.10, implemented in GeodesicSlicer).Then four anatomical landmarks based on the standard landmarks of the skull used in the 10-20 system EEG were manually placed by a neuroimaging expert for the essential positioning of the electrodes: the nasion, the inion, and the left and right tragi. Finally, the GeodesicSlicer toolbox reconstructed the 10-20 system EEG onto the head surface with T3P3 (here designated ST) in the center of the segment delimited by T3 and P3 according to the 10-20 electrode system of the International Federation [START_REF] Jasper | The ten twenty electrode system of the international federation[END_REF][START_REF] Klem | The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology[END_REF] (Fig. 1). For localization approaches comparison, each set of ST coordinates (n=69) were then individually transformed to a normalized stereotactic space (MNI) with SPM12 and plotted on the scalp of the MNI MRI single-subject mesh.

Validity of the measure

Eight controls (35.77 ± 5.29 years; 2 women) were included to assess the validity of the GeodesicSlicer method. The placement of the nasion, inion, and the two tragi determines the position of the electrodes in the 10-20 system EEG [START_REF] Klem | The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology[END_REF]. We measured the distances from the nasion to the inion and from the left tragus and the right tragus in the controls with a measuring tape, as established in the 10-20 EEG guidelines [START_REF] Klem | The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology[END_REF], and compared them to the same distances calculated by GeodesicSlicer. A Bland-Altman plot was used to assess test reliability from these two measurements [START_REF] Bland | Measuring agreement in method comparison studies[END_REF].

MNI Location of ST

An in-house MATLAB program was used to determine the anatomical appellation of the area corresponding to the ST and PT coordinates reported in the automated anatomical labeling (AAL) atlas of the MNI MRI single-subject brain [START_REF] Tzourio-Mazoyer | Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain[END_REF].

The scalp position T3P3 was projected to the brain surface with the way how TMS effects project to the brain (i.e., perpendicular to the scalp-surface).

Personalized site determination (PT)

One parallel, randomized, double-blinded, and sham-controlled study using the PT method with significant AVH reduction was selected. This study reported a site anatomically determined at the crossing between the projection of the ascending branch of the left lateral sulcus and the left superior temporal sulcus named as PTD (see Supplementary Data Video 1 in [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF]). PTD was first manually placed on the 69 T1-weighted images and then each location was individually transformed to a normalized stereotactic space (MNI) with SPM12. Each PT point (n=69) was then plotted on the scalp of the MNI MRI singlesubject mesh (cf. Fig. 2).

Comparison of the PT and ST locations

We plotted the 95% confidence ellipsoids [START_REF] Friendly | Elliptical Insights: Understanding Statistical Methods through Elliptical Geometry[END_REF] where F is the Fisher distribution, the dimensionality p = 3, and the number of target positions is designated as RPT n=69 and RST n=69.

Hotelling's T²-test [START_REF] Hotelling | The Generalization of Student's Ratio[END_REF] was used to test for differences in location between groups (PT vs. ST) at an alpha level of 0.05 (using the "Hotelling" package in R [START_REF] Curran | A note on two problems in connexion with graphs[END_REF]). The geodesic distances between the centers of the two ellipsoids (μ PT, μ ST)

were calculated to characterize the mean distance between PT and ST on the MNI MRI single-subject mesh and on each 69 participant-specific MRI native space meshes.

The geodesic distances between PT (μ PT) and the T3 electrode and PT (μ PT) and the P3 electrode were determined in order to describe the mean PT position in terms of the landmarks of a 10-20 system EEG.

All the geodesic distances were computed with GeodesicSlicer.

Results

Standardized site determination (ST)

Validity of the measure

The limits of agreement of Bland-Altman plots of the nasion-inion distances were from -0.82 to 1.96 cm, with a mean difference of both measures of 0.57 ± 0.70 cm (range, -0.64 to 1.59 cm), and from -0.52 to 1.82 cm for the tragus-tragus with a mean difference of 0.65 ± 0.59 cm (range, -0.16 to 1.53 cm), showing that the reliability between the measures calculated by GeodesicSlicer and manually was consistent.

MNI Location of ST

The standardized site determination showed that projected T3P3 targets were widespread: 1.44% points were in the left inferior parietal gyrus, 1.44% were in the left inferior temporal gyrus, 4.34% were in the left angular gyrus, 4.34% were in the left superior temporal gyrus, 30.43% were in the left supramarginal gyrus, and 57.97% were in the left middle temporal gyrus. In contrast for PT, 1.4% points were in the left supramarginal gyrus, 7.2% were in the left temporal superior gyrus and 91.3% were in the left temporal middle gyrus.

Comparison of the PT and ST locations

Figure 2 shows both PT and ST patterns and their confidence regions. No RPT points (where μ PT; x= -84.17, y= -39.12, z= 1.95) was contained in the confidence region of RST (where μ ST; x= -77.39, y= -63.42, z=15.67). The group location difference was significant (T 2 3,134 = 1150.04, P < 0.001), and PT was below and in front of ST at a distance of 3.01 cm on the MNI MRI single-subject mesh or at a mean of 2.95 ± 0.73 cm (n=69) on participantspecific MRI native space meshes.

In native spaces, the distances between on one hand PT (μ PT) and T3 and on the other hand P3 and T3 were 2.76 ± 0.79 cm and 11.09 ± 0.90 cm, respectively, in the 10-20 system EEG. Thus, PT was located at the junction between the first and the second quarter of the T3P3 segment.

Discussion

Although hypothetical in nature, the highly variable TMS locations are causally related to inconsistent clinical outcomes in previous TMS-AVH studies. Here we demonstrate, thanks to a new and free open-source software (GeodesicSlicer) as a common easy-to-use software for rTMS localization comparison, a differential of nearly 3 cm (geodesic distance) between personalized rTMS target efficient on AVH [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF] and the standardized T3P3 method. These 3 cm represent a large distance since the electric field induced by rTMS drops by more than two at a distance of 2 cm from the center of the coil in the brain tissue [START_REF] Cohen | Effects of coil design on delivery of focal magnetic stimulation. Technical considerations[END_REF][START_REF] Fadini | H-coil: Induced electric field properties and input/output curves on healthy volunteers, comparison with a standard figure-of-eight coil[END_REF].

The T3P3 localization

The likelihood of experiencing AVH is influenced by impaired activity in the vicinity of the posterior part of the superior and middle temporal gyrus which is part of the TPJ [START_REF] Kühn | Quantitative Meta-Analysis on State and Trait Aspects of Auditory Verbal Hallucinations in Schizophrenia[END_REF]. However, the present results show that more than one third of ST locations were outside this focal area. The remaining two thirds of the ST sites were located over the left superior or middle temporal gyrus that borders the superior temporal sulcus, supporting the large variability of the location of ST and the fact that the stimulation target does not necessary correspond to the intended target. This is probably due to the large interindividual anatomical variability [START_REF] Herwig | Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation[END_REF] and could explain the discrepancy in terms of efficacy when using ST (Dollfus et al., 2016a;[START_REF] Slotema | Review of the Efficacy of Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations[END_REF]. These results support the need for more precise rTMS localization.

The personalized target localization

Recent findings suggest that focal brain stimulation should be guided in a personalized manner [START_REF] Lahti | Making Progress Toward Individualized Medicine in the Treatment of Psychosis[END_REF][START_REF] Sommer | Toward personalized treatment of hallucinations[END_REF] since personalized medicine for the treatment of psychosis allows for the consideration of substantial inter-individual variability [START_REF] Lahti | Making Progress Toward Individualized Medicine in the Treatment of Psychosis[END_REF].

Interestingly, recent parallel, randomized, double-blinded, and sham-controlled studies in which rTMS was delivered by individualized neuronavigation over the left superior temporal sulcus (separating the superior temporal gyrus from the middle temporal gyrus, both regions imply in AVH [START_REF] Kühn | Quantitative Meta-Analysis on State and Trait Aspects of Auditory Verbal Hallucinations in Schizophrenia[END_REF]) around the Wernicke's area showed consistent AVH improvements [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF][START_REF] Hoffman | Transcranial magnetic stimulation of Wernicke's and right homologous sites to curtail "voices:" a randomized trial[END_REF][START_REF] Kindler | Reduced Neuronal Activity in Language-Related Regions After Transcranial Magnetic Stimulation Therapy for Auditory Verbal Hallucinations[END_REF]. In contrast, a clinical trial that directly compared the 10-20 method with a personalized method guided by maximal fMRI activation did not find superiority of the personalized method and did not even find superiority to sham stimulation [START_REF] Slotema | Can Low-Frequency Repetitive Transcranial Magnetic Stimulation Really Relieve Medication-Resistant Auditory Verbal Hallucinations? Negative Results from a Large Randomized Controlled Trial[END_REF]. In the same way, another research team used neuronavigation systems integrating morphological and functional imaging data to determine that Heschl's gyrus as the stimulation target rather than Wernicke's area [START_REF] Blumberger | MRI-targeted repetitive transcranial magnetic stimulation of Heschl's gyrus for refractory auditory hallucinations[END_REF]. AVHs were not significantly improved in that study, probably because Heschl's gyrus is in the depth of the lateral sulcus and above and in front of Wernicke's region. Taken together, these findings highlights the importance of accurate rTMS site determination, and enlighten Wernicke's region seems to be a site-optimized protocol for some clinical benefit in patients with persistent AVH [START_REF] Donaldson | Noninvasive stimulation of the temporoparietal junction: A systematic review[END_REF][START_REF] Hoffman | Transcranial magnetic stimulation of Wernicke's and right homologous sites to curtail "voices:" a randomized trial[END_REF]. In addition to anatomical variability, rTMS efficacy could also be related to different frequencies and study designs used [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF](Dollfus et al., , 2016b)). A strong effort to individualize these approaches should have be done, as for example calculating the correction factors for each patient to adjust the rTMS dose for the treatment [START_REF] Briend | GeodesicSlicer: a Slicer Toolbox for Targeting Brain Stimulation[END_REF].

In addition to the inter-individual differences found with the T3P3 method, these results clearly indicate a need for better and more accessible localization techniques for rTMS optimization. We determined an accurate anatomical site in the left TPJ within the left Wernicke's region considered to be the best region for stimulation to reduce AVH [START_REF] Hoffman | Probing the pathophysiology of auditory/verbal hallucinations by combining functional magnetic resonance imaging and transcranial magnetic stimulation[END_REF] that can be easily identified and reproducible in clinical practice [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF]. It is close to the PT sites used in other studies reporting rTMS efficacy for the reduction of AVH [START_REF] Hoffman | Transcranial magnetic stimulation of Wernicke's and right homologous sites to curtail "voices:" a randomized trial[END_REF], supporting the fact that the posterior part of the left STG is a relevant region for AVH treatment by rTMS [START_REF] Dollfus | High-Frequency Neuronavigated rTMS in Auditory Verbal Hallucinations: A Pilot Double-Blind Controlled Study in Patients With Schizophrenia[END_REF][START_REF] Hoffman | Transcranial magnetic stimulation of Wernicke's and right homologous sites to curtail "voices:" a randomized trial[END_REF][START_REF] Montagne-Larmurier | Repetitive transcranial magnetic stimulation in the treatment of auditory hallucinations in schizophrenic patients[END_REF].

Our results also suggest that a stimulation target around the junction between the first and the second quarter of the T3P3 segment should be used when individualized methods based on neuroimaging techniques and/or neuronavigation system are not available. However, it is important to remember that ST does not account for inter-subject differences in cortical anatomy or skull size.

GeodesicSlicer

GeodesicSlicer is implemented as a free extension of the widely used 3D Slicer medical image visualization and analysis application platform (http://www.slicer.org [START_REF] Fedorov | 3D Slicer as an image computing platform for the Quantitative Imaging Network[END_REF][START_REF] Pieper | The NA-MIC Kit: ITK, VTK, pipelines, grids and 3D slicer as an open platform for the medical image computing community[END_REF]). GeodesicSlicer uses cortical stimulation target from either functional or anatomical image to provide functionality specifically designed for Non-invasive brain stimulation therapy research. This module can compute geodesic paths between any rTMS targets, whether localized by MRI-guided TMS neuronavigation or localized by 10-20 EEG position. Based on Andoh's triangulation-based MRI-guided method [START_REF] Andoh | A triangulation-based magnetic resonance image-guided method for transcranial magnetic stimulation coil positioning[END_REF], this module could also calculates the geodesic distances between the projected stimulation target and the position of the 3 nearest electrodes in the individualized 10-20 system EEG in order to guide the stimulation [START_REF] Briend | GeodesicSlicer: a Slicer Toolbox for Targeting Brain Stimulation[END_REF]. Please refer to the toolbox documentation on our Wikipage for detailed steps. This method provides a reliable and inexpensive way to position the TMS coil that can be used in case of unavailable online neuronavigation like in a clinical setting [START_REF] Briend | GeodesicSlicer: a Slicer Toolbox for Targeting Brain Stimulation[END_REF], but also in comparing different localizations due to different target modalities via the "Parameters to find the shortest path" module of the software. For any sort of questions, feedback, suggestions, or critique, please visit the 3D slicer support forum.

Study limitations

This study has some limitations. First, the different ST and PT locations were not analyzed in view of clinical outcomes, highlighting the need for further prospective and controlled studies. Second, the ST location was not directly located on the subject head but was calculated with Dijkstra's algorithm via GeodesicSlicer and then was compared with PT target. The path precision calculated by the Dijkstra's algorithm depends on the length of the triangle edges determined by the of triangles created during the mesh generation and could add some variability. However, the triangle size is low compared to the difference found between the two approaches for rTMS target localization and the Bland-Altman plot showed a good reliability of GeodesicSlicer. Moreover, we compared ST and PT exact points, but it would have been good to evaluate if previous ST studies place or not the magnetic coil exactly on top of T3P3 or little more anteriorly to that point to reach more posterior part of the temporal gyrus, but usually no precise descriptions, like MNI coordinates, was given in the ST studies (Dollfus et al., 2016a).

Conclusions

In summary, the discrepant efficacy results previously reported in rTMS studies [START_REF] Slotema | Review of the Efficacy of Transcranial Magnetic Stimulation for Auditory Verbal Hallucinations[END_REF] may be related to the choice of a generic target site located at T3P3 [START_REF] Fitzgerald | A double-blind sham-controlled trial of repetitive transcranial magnetic stimulation in the treatment of refractory auditory hallucinations[END_REF][START_REF] Herwig | Using the international 10-20 EEG system for positioning of transcranial magnetic stimulation[END_REF], which does not necessarily overlap with the left language areas involved in AVH [START_REF] Hoffman | Transcranial magnetic stimulation and auditory hallucinations in schizophrenia[END_REF][START_REF] Kühn | Quantitative Meta-Analysis on State and Trait Aspects of Auditory Verbal Hallucinations in Schizophrenia[END_REF]. It is why -84.17, y= -39.12, z= 1.95 (once projected). Ellipsoids represent 95% confidence regions associated with distributions of personalized targets in yellow and standardized targets in purple.

  associated with the PT (n=69) and ST (n=69) distributions to characterize the PT and ST locations. Because PT and ST point distributions (D) followed normal distributions (N), DPT ~N (μ PT, 𝛴 PT) and DST ~N (μ ST, 𝛴 ST) in which μ is the center of mass of D and 𝛴 is the covariance matrix of D, the confidence regions R(D) were computed as follows: 𝑅 = (𝐷 -μ) ′ 𝛴 -1 (𝐷 -μ) ≤ 𝑝 (𝑛-𝑝) 𝐹 0.05,𝑝,𝑛-𝑝(1)

  we propose a new and free open-source software (GeodesicSlicer) as a common easy-to-use software for rTMS localization comparison.

Fig. 1 .

 1 Fig. 1. Screen-shot of the GeodesicSlicer program. The user: 1) Enters the T1-weighted

Fig. 2 .

 2 Fig. 2. 3D mesh morphed from the structural MNI MRI single-subject brain with different

Acknowledgements:

The authors would like to thank A. Nourry, Dr. A. Lasso and Dr. K.

Yoshimi for their valuable help with the VTK library.

Funding source: This work was supported by a Perceneige-Fondamental foundation prize, the French Health Ministry (Programme Hospitalier de Recherche Clinique), Normandie Council and Univeristy of Caen.

Conflict of interest:

The authors have no conflicts of interest to declare.


E Galy
email: egaly@univ-tlse2.fr

Claudine Mélan
email: cmelan@univ-tlse2.fr

M Cariou
email: cariou@univ-tlse2.fr

Moline Fookson

Pollak

; Monk

Carrier

; Casagrande

Violani

& Curcio

Bertini

Spijkers, Kiesswetter ; Heuer

Schmidtke

Macdonald, Tucker, Sytnik, Totterdell ; Owens

Investigation of task performance variations according to task requirements and alertness across the 24-h day in shift-workers

Keywords: perception < Psychological Aspects, memory < Psychological Aspects, attention and vigilance< Psychological Aspects, industrial ergonomics < Application Shift-workers, Alertness, Reaction time, Non-verbal Discrimination, Memory Tasks

The study investigated time-of-day effects on task performance in shift-workers in different tasks (reaction-time, discrimination, probe recognition, free recall), by varying task-specific features. On each of six recordings, each programmed on a different day and in a randomized order, operators rated alertness and performed different tasks. Self-rated alertness varied according to a typical diurnal trend. Time of day also affected reaction time (slower responses at 03:00), discrimination performance (lower accuracy at 03:00 in the most difficult condition), and recall (superior recall at 07:00 and 11:00 following deeper processing at encoding). The data demonstrated time-of-day effects on cognitive processes also involved in many real-job activities, despite the lack of control for a number of exogenous factors known to interfere with performance in work settings. Since in the cognitively more loaded tasks, time-of-day effects depended on task conditions, the findings are of operational concern in shift-work situations involving differential task requirements.

to favour more demanding processing, involving, in particular, semantic attributes from long term memory sources (Folkard, 1979;Folkard & Monk, 1981). This interpretation may also account for the differences of recall performance across the 24-h day according to the recall procedure, as reported by a previouslymentioned field study (Mélan et al., 2007), but also in a controlled laboratory study (Lorenzetti & Natale, 1996). The latter study indeed revealed superior recall in the afternoon when subjects had been instructed to use a free recall procedure, and in the morning when they had been informed to use a recognition procedure.

Greater degrees of elaboration would be necessary for free recall (relying on subjects' ability to actively retrieve memory traces) compared to recognition (requiring subjects to simply discriminate memory traces; Brébion, David, Bressan, & Pilowski, 2005;Prince, Daselaar, & Cabeza, 2005). A similar hypothesis has been proposed to account for recall performance differences over the 24-h day according to item modality. Auditory presented items would benefit from a longer-lasting sensory trace, and/or automatic phonological encoding compared to visually presented items (Baddeley, 1986;Penney, 1989;[START_REF] Cowan | Deconfounding serial recall[END_REF]. This would explain that only recall for visually presented items was reduced when alertness was low (Mélan et al., 2007).

The present study tested these hypotheses in a real shift-work setting by investigating operators' task performance across the 24-h day in a set of experimental tasks. In a repeated measures design operators (in charge of in-door security of a nuclear power plant) provided alertness self-ratings every four hours and performed tasks involving cognitive functions ranging from psychomotor reaction time to elaborate processing of meaningful words. While a nocturnal performance decrement was expected for all tasks, diurnal performance peaks were expected to vary between tasks. Performance would peak in the morning for visual discrimination and probe recognition, involving more automatic processing, and later during the day for free recall, requiring more elaborate processing. In each task, the overall trend should be modulated by an interaction with the task component that was manipulated, i.e. difficulty in the discrimination task (parallel bars shifted by 0, 1, 2, or 3 pixels), item modality in the probe recognition task (visual and auditory list and probe presentation), and item attributes in the free recall task (typographic, structural and semantic encoding conditions). In agreement with the variations observed in laboratory studies, we expected to find later performance peaks or larger performance variations in the more demanding task conditions.

Method

Subjects

The study was carried out with 23 volunteer shift-workers supervising, on various control monitors, the in-door security of a nuclear plant in the south-west of France. They were issued from six teams of operators (total of 36), and were all men, aged 41.5 years (range 35 to 53 years), working in shift-work systems for 11.8 years (range 4 to 20 years). They worked a continuous rapidly forward rotating shift-system, with 3 mornings, 2 afternoons, 2 nights followed by 5 days off. The 8-h shifts started at 06:00, 14:00, and 22:00 respectively. Satellite controllers completed Thayer's check-list and performed four different neuropsychological tasks on each of six testing times that were distributed over the 24-h day. Testing took place in a quiet room, during duty-pauses introduced for the sake of the study, by avoiding meal-times and shift-changeover times, i.e. at 03:00, 07:00, 11:00, 15:00, 19:00 and 23:00. The subject first completed the check-list, then performed a discrimination task, followed by two memory tasks (starting randomly with either) and a reaction-time task. To ensure no confounding effects of time of day and practice, testing times were randomized across participants, with a single testing time per day for a given subject. Prior to the beginning of the study, operators completed Horne and Östberg's (1977) questionnaire. The results indicated that no participant displayed extreme morningness or eveningness.

Material and procedure

Alertness: Participants completed a French paper-and-pencil version of

Thayer's activation-deactivation adjective checklist (Thayer, 1978). They quoted, for each of 20 adjectives, one of the following responses "not at all", "don't' know", "little", "much", having an assigned weight respectively of 1, 2, 3 and 4. Two adjectives, however, have a negative weight assigned to them. The scores were grouped into four factors, general activation (GA), deactivation sleep (DS), high activation (HA), and general deactivation (GD). The ratio GA/DS provided an index of subjects' alertness.

Visual discrimination:

Each of 24 trials started with the display of two horizontal parallel bars, 3-cm long and 0.5 cm apart. Depending on the trial, the bars were either shifted horizontally to each other by 1, 2 or 3 pixels (in each case, 1/4 of trials), or they were not shifted (1/4 of the trial). Items were displayed in the centre of a computer screen while the following instruction occurred on the bottom of the screen "The lines are shifted (press the key M) / The lines are not shifted (press key Q)". The participant's response initiated a 2-sec inter-trialinterval, before the next trial started. Software, specifically designed for this study, presented the four discrimination conditions randomly, and recorded the subject's response accuracy and latency.

Probe recognition:

On each of 32 trials, six common French nouns were presented, one by one (750 ms), at a rate of one word per second. Four seconds after presentation of the last list-item, a probe item was presented together with the following response instruction "The word figured in the list (press M-button) /

The word did not figure in the list (press Q-button)". The subject's response initiated a 5-sec ITT, followed by a brief sound signalling the start of the next trial. The list-items were randomly selected from a 24-item set and on half the trials the probe had occurred in the list. Item-lists and probes could be presented either in the visual modality (centre of a computer screen), or in the auditory modality (loud-speakers). The four trial types resulting from presentation modality of lists and probes (auditory-visual, auditory-auditory, visual-visual, visual-auditory) were randomized across trials by the aforementioned tailor-made software. To rule out practice effects across the six testing times, six different item-sets were used. All items of a set belonged to the same word category (fruit, vegetables, music instruments, furniture, and animals). 2.2.4. Free recall: This protocol was previously described by Maury and Queinnec (1992). Briefly, on each of 18 trials, a common French noun was presented in the middle of a computer screen (300 ms), immediately preceded by a question that induced processing of the word's typographical attributes ("Is the word written in capitals", 1/3 trials), structural attributes ("Do the vowels of the word occur in an alphabetical order", 1/3 trials), or semantic aspects (1/3 trials). In the latter case, the question varied according to the item presented, like "Is it used to open a door", followed by the item "handle". Simultaneously with each word, the following instruction occurred on the bottom of the screen: "Response 'Yes', press key M; Response 'No', press key Q". The response initiated an interpolated reaction-time task (see below) before the next trial started. Following the last trial, subjects were asked to write on a white sheet all the words they could remember from the 18-item list.

Reaction-time:

This task was interpolated after each trial in the free recall task, in order to prevent maintenance rehearsal. The response after each question/word sequence in the free recall task automatically generated a 1-px spot that moved randomly on the screen during several seconds and finally 'exploded'.

Following this event, the subject had to press the 'space' bar as rapidly as possible, which initiated a second, and then a third trial. Thereafter, the program shifted back to the recall task, with the presentation of a question starting the second trial, and so on.

Statistics

All measures recorded were analysed by parametric tests. ANOVAs with repeated measures across time of day (TOD) were used to analyse subjects' self-reported alertness (1-way ANOVA), and factorial ANOVAs investigated time-of-day effects together with task-specific components in the cognitive tasks. Tukey's test was used for post hoc analyses. We further explored whether task performance variations observed across time of day were associated with variations in subjects' alertness. This hypothesis was tested by using Pearson's correlation test as follows. Correlations were computed within participants (n=6 for each person separately), by using alertness/test scores at the 6 time-of-day values. Then, the 23 r values were tested against the null hypothesis by using a 1-sample t test. Though this procedure violates the assumption of independence of scores, it provides an indication whether, in general, alertness was correlated with test performance.

Results

Operators' alertness curve obtained by concurrent ratings on six recordings across the 24-h day is represented by Figure 1. A one-way ANOVA with repeated measures revealed a significant time-of-day effect (F(5,5) = 3.73, p < .01), with significant lower alertness at 03:00 than at 15:00 and 19:00.

The effects of time of day (TOD) on operators' performance in the cognitive tasks were explored together with task-specific factors by using factorial ANOVAs. In the visual discrimination task, a 2-way ANOVA of TOD (repeated measures) and discrimination condition revealed a significant effect of discrimination condition on response accuracy (F(3,23) = 199.13, p < .001; Figure 2), and an interaction between response accuracy and TOD (F(5,23) = 1,5639, p < .05). Post-hoc analyses indicated that the latter effect resulted from less accurate responding at 03:00 compared to 11:00 in the 1 pixel shift condition (p < .01). Furthermore, Figure 3 illustrates the mean number of correct responses in a verbal probe recognition task according to TOD, and presentation modality of the verbal items.

A 2-way ANOVA with repeated measures revealed that task performance was affected by presentation modality of the item lists (F(1,23) = 22.11, p < .001), and of the probes (F(1,23) = 9.66, p < .01), indicating better performance following auditory rather than visual item presentation, both at encoding and recall. Further, TOD interacted with presentation modality (F(5,23) = 2.166, p<.05), due to significant higher recall at 03:00 following auditory compared to visually encoded words (p < .001).

In a free recall task, the mean number of words recalled according to TOD was analysed together with the type of question that was presented prior to each word at encoding (Figure 4), and the position in the list (Table 1). The figure indicates more marked TOD effects following questions inducing processing of semantic or typographic aspects rather than of structural aspects. Furthermore, whether items were issued from the initial (positions 1 to 6), intermediary (positions 7-12), or end (positions 3-18) portion of the list, recall performance was overall higher on day-time compared to night-time recordings. A 3-way ANOVA of these factors revealed significant effects for encoding question type (F(2,23) = 22.30, p < .001), and list-portion (F(2,23) = 3.9, p < .05), and an interaction between each of these factors and time of day (TOD x question type F(10,23) = 1.99, p < .05 ; TOD x list portion F(10,23) = 2.01, p < .05); (F(4,23) = 5.97, p < .001). Post-hoc analyses revealed superior recall for words preceded by a semantic question rather than by a structural question at 07:00 and 11:00 (respectively, p < .05, and p < .01), or by a typographic question at 11:00. (p < .01). In addition, items issued from the initial list-portion were better recalled at 07:00 than at 19:00 (p < .05). Moreover, a significant interaction between question type and list-portion indicated significant higher recall performance when words issued from the initial listportion were preceded by a semantic question rather than by a structural or typographical question (p < .001 in each case). A similar effect was observed when items issued from the end-portion of the list were preceded by a semantic rather than by a typographical question (p < .01).

A similar analysis was performed for operators' performance in a detection task that was interpolated following each question/word presentation in the free recall task. Time-of-day effects on subjects' mean response latencies on each of three successive trials (Table 2) were investigated by including two additional factors (Table 3), i.e. the question type preceding the detection task (structural, typographic, and semantic), and the list portion (initial, intermediary, and endportions). A four-way ANOVA of these factors revealed a significant effect of time of recording (F(5,161) = 2.94, p < .05), indicating slower responses at 03:00 compared to 07:00 (p < .05), and 19:00 (p < .01). Furthermore, highly significant differences between trials (F(2,161) = 40.86, p < .001), and list-portions (F(2,161) = 10.24, p < .001), resulted from slower responses on the first compared to the second and third trials (p < .001, in each case), and on trials inserted in the To investigate whether trends of task performance and self-reported alertness trends were associated, correlations across time of day were calculated between alertness scores and either performance measure for each participant. Table 4 summarizes ranges of individual correlation values for each performance measure and the corresponding mean correlation. Testing the 23 r values against the null hypothesis revealed overall significant correlations across time of day between alertness on one hand, and discrimination latency, visual recognition performance and free recall performance on the other hand (Table 4).

Discussion

In real-job conditions, operators displayed reliable alertness variations and task performance variations across the 24-h day. A nocturnal drop was found for task performance and self-reported alertness, despite a lack of control for a number of factors that have been shown to affect psychological measures in controlled laboratory conditions, including light exposure, noise and motivation (Smith, McEvoy, & Gevins, 2002;Wright et al., 2002). In shift-workers, the nocturnal decline of psychological measures is generally aggravated by chronic sleep deprivation (Akerstedt, 1991;Dinges et al., 1996;Fletcher & Dawson, 2001;Pilcher et al., 2000). The disruptive effects of shift-work have been shown to depend on various shift-scheduling features. Somewhat smaller effects have been shown for rapid compared to slow rotations, for systems including a limited (Della Rocco & Nesthus, 2005;Knauth, 1996;Tucker et al., 1998). As in the present job-situation operators worked according to a rapid forward rotating shiftscheduling system that included a maximum of two or three successive nightshifts, and late night-to-morning shift changeover, the disruptive effects on the nocturnal decline of operators' psychological measures may have been less pronounced than may have been expected in other shift-scheduling systems.

Operators' self-rated alertness displayed a typical day-oriented trend that peaked at 19:00 and reached its minimum at 03:00. The finding of a trend similar to those reported in other real work settings (Akerstedt, 1991;Dinges et al., 1997;Tucker et al., 1998), supports the hypothesis of a strong dependency of alertness on the endogenous systems underlying circadian rhythms (Achermann & Borbély, 1994;Folkard & Ackerstedt, 1992). The marked differences between day-and nighttime reported in the present study contrasted, however, with the restricted range of alertness ratings reported in another shift-work study (Tucker et al., 1998). This difference may be related to methodological differences, given that in the present study operators rated alertness concurrently on four hourly intervals, rather than retrospectively on a single session. In addition, the alertness score was computed from responses to a list of adjectives rather than by quoting a single-item scale, and could thus provide a more precise description of operators' functional state.

Though other factors may explain the finding of more or less shaded alertness curves in shift-work studies, the idea that the rating method used contributes to this difference may deserve further investigation. On the other hand, the possibility cannot be excluded that in real-job conditions operators rate alertness This latter interpretation may, however, not account for the task performance variations observed over the 24-hr day in the present study. The role of practice effects may also be excluded, given that performance trends were obtained by randomizing the order of the six recording sessions across participants, and by performing a single session on a given day. Similarly, in the memory tasks learning effects were, in principle, ruled out by randomizing different task versions across participants and recordings. In light of these considerations, task performance variations according to time of day most probably resulted from operators' functional state at the time of testing. Thus, with increasing alertness during day-time, operators' displayed significant superior performance in several cognitively more or less demanding tasks. More specifically, they responded more rapidly in a reaction time task, performed more accurate responses in a non-verbal visual discrimination task, and recalled more verbal items in the memory tasks.

The finding that time of day affected different performance measures may indicate that operators' nocturnal performance drop resulted from the impairment of some general non specific capacity involved during information processing. This is in agreement with the hypothesis that sleep deprivation reduces the non-specific arousal level of the body, but has no specific effects (see for instance Wilkinson, 1992). According to this point of view, sleep deprivation effects on reaction time and trough-put in cognitively more loaded tasks would result from the monotony and lack of novelty that characterize these tasks. In contrast, tasks that are "too complex, too interesting, too variable and, above all, too short" would intrinsically encourage sleep-deprived people to apply compensatory efforts and to perform normally (pp. 254-256). Likewise, Balkin et al. (2004) found that monotonous tests that demanded constant attention, like psychomotor vigilance tests, were most sensitive to partial sleep deprivation compared to tests involving higher cognitive load, like logical reasoning, problem-solving and decision-making, which were least sensitive (Balkin, Bliese, Belenky, Sing, Thorne, Thomas, et al., 2004).

Accordingly, the present results may reflect a differential sensitivity of the tasks to sleep deprivation as shift-work is associated with systematic partial sleep loss (Pilcher et al., 2000). Our results only partly support this assumption. On the one hand, task performance decrements in early morning hours have been observed for reaction time. This finding is also in agreement with a number of studies performed under controlled conditions in the laboratory (Monk et al., 1985;Monk & Carrier, 1997;[START_REF] Casagrande | Assessing vigilance through a brief pencil and paper letter cancellation task (LCT): Effects of one night of sleep deprivation and of the time of day[END_REF][START_REF] Heuer | Effects of sleep loss, time of day, and extended mental work on implicit and explicit learning of sequences[END_REF]Owens et al., 2000;[START_REF] De | Visual search performance across 40 h of continuous wakefulness: Measures of speed and accuracy and relation with oculomotor performance[END_REF]Wright et al., 2002), in simulated shift-work conditions (Fröberg et al., 1975;[START_REF] Colquhoun | Experimental studies of shift-work I: A comparison of 'rotating' and 'stabilized' 4-hour shift systems[END_REF]Johnson et al., 1992), and in real shift-work settings (Tilley et al., 1982;[START_REF] Hossain | Subjective and objective evaluation of sleep and performance in daytime versus nighttime sleep in extended hours shift-workers at an underground mine[END_REF]. On the other hand, in the more demanding cognitive tasks, time-of-day effects interacted with the task components that were manipulated. Thus, time of day impaired response accuracy in the discrimination task only in two out of four task conditions, i.e. when the difference between items to be discriminated was least obvious, while no such effect was found in those conditions involving a more marked to-be-discriminated difference. Likewise, recognition performance was superior on early morning hours for auditory compared to visually encoded words. In a free recall task, operators displayed superior recall during day-time, but only when elaborate processing was favoured during encoding, rather than processing of structural or physical word attributes. [START_REF] Harrison | The impact of sleep deprivation on decision making: A review[END_REF] proposed to differentiate those cognitive demanding tasks involving divergent skills, such as innovating and updating strategies, from those based on convergent rule-based skills. The authors reported a number of studies demonstrating sleep deprivation effects in the former but not in the latter tasks. Though the tasks used in the present study were rule-based, it may be that the changing task conditions involved strategy changes that may have increased the task-sensitivity to time-of-day effects. Strategy changes in relation to arousal changes have also been proposed to account for performance variations observed in laboratory studies. In the morning, when arousal was low, performance was shown to peak in those tasks involving more automatic processing, while increasing arousal across the day would favour more elaborate processing, like processing of semantic aspects from long-term memory (Baddeley et al., 1970;Folkard, 1979;Folkard et al., 1976;Folkard & Monk, 1980;Lorenzetti & Natale, 1996;Oakhill & Davies, 1989). This hypothesis was favoured by the finding of significant correlations between operators' self-rated alertness and their task performance. More especially, when they rated alertness at a low level, their response speed in the discrimination task and their recall and recognition performance were also reduced, and vice versa. In addition, as reported above, significant time-of-day effects were observed in all the neuropsychological tests used, with overall higher performance during the day. However, no clear performance peak was observed in either task in the present study. This may be related to the marked inter-individual task performance differences, evidenced by large standard errors, in particular in the cognitively more loaded tasks. Inter- individual task performance differences may be related to differences in operators' sleepiness, workload, adjustment to shift-work, and work conditions (Akerstedt, 2007;[START_REF] Bustamante | Effects of varying the threshold of alarm systems and workload on human performance[END_REF][START_REF] Costa | Ageing, working hours and work ability[END_REF], in addition to the afore-mentioned lack of control for external factors.

Accordingly, future field studies of the present kind should include objective sleep measures, in addition to subjective alertness or sleepiness ratings in order to explore the effects of sleepiness and adjustment to shift-work on operators' task performance (Tucker et al., 1998). The tests used in the present study may be of limited ecological value as far as job-task complexity, real-job performance, and consequences of performance impairments on safety and security are concerned.

In this respect it may be useful to include in future studies a workload index, as discussed in several recent studies (Pretorius & Cilliers, 2007;Noyes & Bruneau, 2007 ;Roth, Scott, Deutsch, Kuper, Schmidt, et al ., 2006). Thus, though no direct relation may exist between the present results and real-job performance, the neuropsychological tests enabled suitable outcome measures reflecting cognitive processes also involved in real-job operations. Furthermore, data provided evidence of subtle changes in operators' information processing strategies in relation to time of day. This further confirmed that time-of-day effects on memory depend on specific task-related factors (Mélan et al., 2007). Moreover, the data emphasize that organizing shift-work and work-break systems to maintain adequate concentration and avoid fatigue and boredom is still a major concern, in particular for safety-related occupations. Practical implications also include oftenoverlooked recommendations based on laboratory studies, and in particular on the findings of systematic performance variations according to presentation modality and depth of processing of verbal material (see INTRODUCTION). The 1. Mean number of words recalled (+/-S.E.) according to their position in the list (initial list-portion: positions 1 to 6, intermediary list-portion: positions 7 to 12, terminal list-portion: positions 13 to 18). Type of Structural 0.41 (.14) 0.34 (.10) 0.41 (.10) 0.37 (.04) 0.35 (.05) 0.36 (.03) inducing Typographic 0.37 (.09) 0.36 (.08) 0.36 (.06) 0.45 (.10) 0.36 (.04) 0.38 (.05) question Semantic 0.40 (.12) 0.36 (.05) 0.40 (.08) 0.39 (.05) 0.37 (.06) 0.36 (.04) List Beginning 0.24 (.02) 0.35 (.06) 0.38 (.07) 0.43 (.09) 0.42 (.07) 0.36 (.07) portion Intermediary 0.55 (.22) 0.39 (.09) 0.40 (.06) 0.47 (.13) 0.37 (.06) 0.32 (.

Statement of relevance

In a real-job setting, performance variations were observed according to time-ofday and task-requirements in a set of cognitively more or less demanding tasks.

Task-specific research across the 24-h day enables a better understanding of operators' tasks and the development of supporting technology. The demonstration of an interaction of circadian phase and time awake in the regulation of performance came from laboratory studies under controlled conditions and/or manipulation of the sleep/wake cycle (for a review, Akerstedt, 2007). Several theoretical models conceptualized this interaction by proposing an optimal position and duration for sleep, with any deviation impairing performance and alertness (Folkard & Akerstedt, 1992;Achermann & Borbély, 1994;Van Dongen, Maislin, Mullington, & Dinges, 2003). Systematic performance measures in relation to different simulated shift systems further confirmed a sharp performance drop in the early morning hours [START_REF] Colquhoun | Experimental studies of shift-work. 3. Stabilized 12-hour shift system[END_REF]. This was observed in most tasks that require sustained attention, such as reaction time performance or throughput in cognitive tasks (Fröberg, 1975;[START_REF] Colquhoun | Experimental studies of shift-work I: A comparison of 'rotating' and 'stabilized' 4-hour shift systems[END_REF]Johnson, 1992). At the same time, physiological, and subjective arousal were reported to strongly decrease (Akerstedt & Gillberg, 1990). A simulation study revealed that at high fatigue levels errors involving a failure to act (errors of omission) were increased, whereas incorrect responses (errors of commission)

were decreased in a simulated train driving task (Dorrian, Roach, Fletcher, & Dawson, 2007). The differential effect of fatigue on error type was explained by a cognitive disengagement with the virtual train, which increased accident risk.

In real shift-work settings, the findings of higher occurrences of risk and accidents on night-compared to day-duty, further stressed the potential consequences of reduced arousal on safety and security (Folkard & Tucker, 2003). Shift-work would further aggravate the nocturnal decline in cognitive abilities observed under controlled conditions due to a chronic sleep debt that shift-workers carry over to the night-shift and also to day-shifts following early morning-shift start (Akerstedt, 1991;Dinges, Pack, Williams, Gillen, Powell, et al., 1997;Fletcher & Dawson, 2001;Pilcher, Lambert, & Huffcutt, 2000). Though a nocturnal work performance drop has been reported in several studies (for a review: Folkard & Tucker, 2003), reliable performance measures may not be available in all occupational settings. In addition, masking effects of work performance changes across the 24-h day have been suggested for work activity itself (Andorre & Queinnec, 1998) and for incentives (Blake, 1971).

Several field studies collected, instead, interpolated performance measures by using simple and short neuropsychological tests. They reported reduced performance on the night-shift for reaction time, mental arithmetic, and search performance (Tilley, Wilkinson, Warren, Watson, & Drud, 1982;[START_REF] Hossain | Subjective and objective evaluation of sleep and performance in daytime versus nighttime sleep in extended hours shift-workers at an underground mine[END_REF]Wojtczak-Jaroszova, Makowska, Rzepecki, Banaszkiewicz, and Romejko, 1978). However, performance changes have not systematically been reported in field studies, for instance for serial reaction time, digit symbol substitution, and manual tracking [START_REF] Costa | Re-entrainment of diurnal variation of psychological and physiological performance at the end of a slowly rotated shift system in hospital workers[END_REF]Lowden, Kecklund, Axelsson, & Akerstedt, 1998). Further, in memory tasks, 24-h performance variations have been shown to depend on task requirements. Thus, process controllers' recall performance was higher at 18:00 compared to 02:00 for words associated with semantic encoding, while the contrary was observed for words processed according to physical attributes (Maury & Queinnec, 1992). Another study revealed that air traffic controllers' recall performance depended on the modality of presentation and the recall procedure used (Mélan, Galy, & Cariou, 2007). In a free recall task they remembered systematically fewer words during the night and early morning hours. In a probe recognition task this effect was only observed when they had to recall visual items but not auditory items.

Taken together, these findings indicate that performance trends depend both on the task used, and on the task components under investigation. This interpretation is in agreement with the results obtained by more systematic investigations of performance variations in controlled laboratory studies. In perceptual-motor tasks, such as simple reaction time tasks restricted to immediate throughput of information, performance was usually shown to peak in the evening (Monk, Fookson, Moline, & Pollak, 1985;Monk & Carrier, 1997;[START_REF] Casagrande | Assessing vigilance through a brief pencil and paper letter cancellation task (LCT): Effects of one night of sleep deprivation and of the time of day[END_REF][START_REF] Heuer | Effects of sleep loss, time of day, and extended mental work on implicit and explicit learning of sequences[END_REF]Owens, Macdonald, Tucker, Sytnik, Totterdell, & et al., 2000;[START_REF] De | Visual search performance across 40 h of continuous wakefulness: Measures of speed and accuracy and relation with oculomotor performance[END_REF]Wright, Hull, & Czeisler, 2002). A reduction in response speed during the night coincident with an increase in response accuracy, suggested a strategy change rather than a global nocturnal performance drop (Monk & Carrier, 1997). When the emphasis was on short-term memory processing, superior performance was reported in the morning, while for longterm memory tasks performance peaks were observed on the late afternoon (Baddeley, Hatter, Scott & Snashall, 1970;Folkard, Knauth, Monk, & Rutenfranz, 1976;Folkard & Monk, 1980;Oakhill & Davies, 1989).

These findings have been interpreted as indicating that low arousal in the morning would favour more automatic processes, such as maintenance rehearsal in shortterm memory. Progressive increment of arousal as the day progresses would tend to favour more demanding processing, involving, in particular, semantic attributes from long term memory sources (Folkard, 1979;Folkard & Monk, 1981). This interpretation may also account for the differences of recall performance across the 24-h day according to the recall procedure, as reported by a previouslymentioned field study (Mélan et al., 2007), but also in a controlled laboratory study (Lorenzetti & Natale, 1996). The latter study indeed revealed superior recall in the afternoon when subjects had been instructed to use a free recall procedure, and in the morning when they had been informed to use a recognition procedure.

Greater degrees of elaboration would be necessary for free recall (relying on subjects' ability to actively retrieve memory traces) compared to recognition (requiring subjects to simply discriminate memory traces; Brébion, David, Bressan, & Pilowski, 2005; Prince, Daselaar, & Cabeza, 2005). A similar hypothesis has been proposed to account for recall performance differences over the 24-h day according to item modality. Auditory presented items would benefit from a longer-lasting sensory trace, and/or automatic phonological encoding compared to visually presented items (Baddeley, 1986;Penney, 1989;[START_REF] Cowan | Deconfounding serial recall[END_REF]. This would explain that only recall for visually presented items was reduced when alertness was low (Mélan et al., 2007).

The present study tested these hypotheses in a real shift-work setting by investigating operators' task performance across the 24-h day in a set of experimental tasks. In a repeated measures design operators (in charge of in-door security of a nuclear power plant) provided alertness self-ratings every four hours and performed tasks involving cognitive functions ranging from psychomotor reaction time to elaborate processing of meaningful words. While a nocturnal performance decrement was expected for all tasks, diurnal performance peaks were expected to vary between tasks. Performance would peak in the morning for visual discrimination and probe recognition, involving more automatic processing, and later during the day for free recall, requiring more elaborate processing. In each task, the overall trend should be modulated by an interaction with the task component that was manipulated, i.e. difficulty in the discrimination task (parallel bars shifted by 0, 1, 2, or 3 pixels), item modality in the probe recognition task (visual and auditory list and probe presentation), and item attributes in the free recall task (typographic, structural and semantic encoding conditions). In agreement with the variations observed in laboratory studies, we expected to find later performance peaks or larger performance variations in the more demanding task conditions.

Method

Subjects

The study was carried out with 23 volunteer shift-workers supervising, on various control monitors, the in-door security of a nuclear plant in the south-west of France. They were issued from six teams of operators (total of 36), and were all men, aged 41.5 years (range 35 to 53 years), working in shift-work systems for 11.8 years (range 4 to 20 years). They worked a continuous rapidly forward rotating shift-system, with 3 mornings, 2 afternoons, 2 nights followed by 5 days off. The 8-h shifts started at 06:00, 14:00, and 22:00 respectively. Satellite controllers completed Thayer's check-list and performed four different neuropsychological tasks on each of six testing times that were distributed over the 24-h day. Testing took place in a quiet room, during duty-pauses introduced for the sake of the study, by avoiding meal-times and shift-changeover times, i.e.

Material and procedure

at 03:00, 07:00, 11:00, 15:00, 19:00 and 23:00. The subject first completed the check-list, then performed a discrimination task, followed by two memory tasks (starting randomly with either) and a reaction-time task. To ensure no confounding effects of time of day and practice, testing times were randomized across participants, with a single testing time per day for a given subject. Prior to the beginning of the study, operators completed Horne and Östberg's (1977) questionnaire. The results indicated that no participant displayed extreme morningness or eveningness.

Alertness: Participants completed a French paper-and-pencil version of

Thayer's activation-deactivation adjective checklist (Thayer, 1978). They quoted, for each of 20 adjectives, one of the following responses "not at all", "don't' know", "little", "much", having an assigned weight respectively of 1, 2, 3 and 4.

Two adjectives, however, have a negative weight assigned to them. The scores were grouped into four factors, general activation (GA), deactivation sleep (DS), high activation (HA), and general deactivation (GD). The ratio GA/DS provided an index of subjects' alertness. 2.2.4. Free recall: This protocol was previously described by Maury and Queinnec (1992). Briefly, on each of 18 trials, a common French noun was presented in the middle of a computer screen (300 ms), immediately preceded by a question that induced processing of the word's typographical attributes ("Is the word written in capitals", 1/3 trials), structural attributes ("Do the vowels of the word occur in an alphabetical order", 1/3 trials), or semantic aspects (1/3 trials). In the latter case, the question varied according to the item presented, like "Is it used to open a door", followed by the item "handle". Simultaneously with each word, the following instruction occurred on the bottom of the screen: "Response 'Yes', press key M; Response 'No', press key Q". The response initiated an interpolated reaction-time task (see below) before the next trial started. Following the last trial, subjects were asked to write on a white sheet all the words they could remember from the 18-item list.

Visual discrimination:

Reaction-time:

This task was interpolated after each trial in the free recall task, in order to prevent maintenance rehearsal. The response after each question/word sequence in the free recall task automatically generated a 1-px spot that moved randomly on the screen during several seconds and finally 'exploded'.

Following this event, the subject had to press the 'space' bar as rapidly as possible, which initiated a second, and then a third trial. Thereafter, the program shifted back to the recall task, with the presentation of a question starting the second trial, and so on.

Statistics

All measures recorded were analysed by parametric tests. ANOVAs with repeated measures across time of day (TOD) were used to analyse subjects' self-reported alertness (1-way ANOVA), and factorial ANOVAs investigated time-of-day effects together with task-specific components in the cognitive tasks. Tukey's test was used for post hoc analyses. We further explored whether task performance variations observed across time of day were associated with variations in subjects' alertness. This hypothesis was tested by using Pearson's correlation test as follows. Correlations were computed within participants (n=6 for each person separately), by using alertness/test scores at the 6 time-of-day values. Then, the 23 r values were tested against the null hypothesis by using a 1-sample t test. Though this procedure violates the assumption of independence of scores, it provides an indication whether, in general, alertness was correlated with test performance.

Results

Operators' alertness curve obtained by concurrent ratings on six recordings across the 24-h day is represented by Figure 1. A one-way ANOVA with repeated measures revealed a significant time-of-day effect (F(5,5) = 3.73, p < .01), with significant lower alertness at 03:00 than at 15:00 and 19:00.

The effects of time of day (TOD) on operators' performance in the cognitive tasks were explored together with task-specific factors by using factorial ANOVAs. In the visual discrimination task, a 2-way ANOVA of TOD (repeated measures) and discrimination condition revealed a significant effect of discrimination condition on response accuracy (F(3,23) = 199.13, p < .001; Figure 2), and an interaction between response accuracy and TOD (F(5,23) = 1,5639, p < .05). Post-hoc analyses indicated that the latter effect resulted from less accurate responding at 03:00 compared to 11:00 in the 1 pixel shift condition (p < .01). Furthermore, Figure 3 illustrates the mean number of correct responses in a verbal probe recognition task according to TOD, and presentation modality of the verbal items.

A 2-way ANOVA with repeated measures revealed that task performance was affected by presentation modality of the item lists (F(1,23) = 22.11, p < .001), and of the probes (F(1,23) = 9.66, p < .01), indicating better performance following auditory rather than visual item presentation, both at encoding and recall. Further, TOD interacted with presentation modality (F(5,23) = 2.166, p<.05), due to significant higher recall at 03:00 following auditory compared to visually encoded words (p < .001).

In a free recall task, the mean number of words recalled according to TOD was analysed together with the type of question that was presented prior to each word at encoding (Figure 4), and the position in the list (Table 1). The figure indicates more marked TOD effects following questions inducing processing of semantic or typographic aspects rather than of structural aspects. Furthermore, whether items were issued from the initial (positions 1 to 6), intermediary (positions 7-12), or end (positions 3-18) portion of the list, recall performance was overall higher on day-time compared to night-time recordings. A 3-way ANOVA of these factors revealed significant effects for encoding question type (F(2,23) = 22.30, p < .001), and list-portion (F(2,23) = 3.9, p < .05), and an interaction between each of these a structural question at 07:00 and 11:00 (respectively, p < .05, and p < .01), or by a typographic question at 11:00. (p < .01). In addition, items issued from the initial list-portion were better recalled at 07:00 than at 19:00 (p < .05). Moreover, a significant interaction between question type and list-portion indicated significant higher recall performance when words issued from the initial listportion were preceded by a semantic question rather than by a structural or typographical question (p < .001 in each case). A similar effect was observed when items issued from the end-portion of the list were preceded by a semantic rather than by a typographical question (p < .01).

A similar analysis was performed for operators' performance in a detection task that was interpolated following each question/word presentation in the free recall task. Time-of-day effects on subjects' mean response latencies on each of three successive trials (Table 2) were investigated by including two additional factors (Table 3) To investigate whether trends of task performance and self-reported alertness trends were associated, correlations across time of day were calculated between alertness scores and either performance measure for each participant. Table 4 summarizes ranges of individual correlation values for each performance measure and the corresponding mean correlation. Testing the 23 r values against the null hypothesis revealed overall significant correlations across time of day between alertness on one hand, and discrimination latency, visual recognition performance and free recall performance on the other hand (Table 4).

Discussion

In real-job conditions, operators displayed reliable alertness variations and task performance variations across the 24-h day. A nocturnal drop was found for task performance and self-reported alertness, despite a lack of control for a number of factors that have been shown to affect psychological measures in controlled laboratory conditions, including light exposure, noise and motivation (Smith, McEvoy, & Gevins, 2002;Wright et al., 2002). In shift-workers, the nocturnal decline of psychological measures is generally aggravated by chronic sleep deprivation (Akerstedt, 1991;Dinges et al., 1996;Fletcher & Dawson, 2001;Pilcher et al., 2000). (Della Rocco & Nesthus, 2005;Knauth, 1996;Tucker et al., 1998). As in the present job-situation operators worked according to a rapid forward rotating shiftscheduling system that included a maximum of two or three successive nightshifts, and late night-to-morning shift changeover, the disruptive effects on the nocturnal decline of operators' psychological measures may have been less

pronounced than may have been expected in other shift-scheduling systems.

Operators' self-rated alertness displayed a typical day-oriented trend that peaked at 19:00 and reached its minimum at 03:00. The finding of a trend similar to those reported in other real work settings (Akerstedt, 1991;Dinges et al., 1997;Tucker et al., 1998), supports the hypothesis of a strong dependency of alertness on the endogenous systems underlying circadian rhythms (Achermann & Borbély, 1994;Folkard & Ackerstedt, 1992). The marked differences between day-and nighttime reported in the present study contrasted, however, with the restricted range of alertness ratings reported in another shift-work study (Tucker et al., 1998). This difference may be related to methodological differences, given that in the present study operators rated alertness concurrently on four hourly intervals, rather than retrospectively on a single session. In addition, the alertness score was computed from responses to a list of adjectives rather than by quoting a single-item scale, and could thus provide a more precise description of operators' functional state.

Though other factors may explain the finding of more or less shaded alertness curves in shift-work studies, the idea that the rating method used contributes to this difference may deserve further investigation. On the other hand, the possibility cannot be excluded that in real-job conditions operators rate alertness (Balkin, Bliese, Belenky, Sing, Thorne, Thomas, et al., 2004).

Accordingly, the present results may reflect a differential sensitivity of the tasks to sleep deprivation as shift-work is associated with systematic partial sleep loss (Pilcher et al., 2000). Our results only partly support this assumption. On the one hand, task performance decrements in early morning hours have been observed

for reaction time. This finding is also in agreement with a number of studies performed under controlled conditions in the laboratory (Monk et al., 1985;Monk & Carrier, 1997;[START_REF] Casagrande | Assessing vigilance through a brief pencil and paper letter cancellation task (LCT): Effects of one night of sleep deprivation and of the time of day[END_REF][START_REF] Heuer | Effects of sleep loss, time of day, and extended mental work on implicit and explicit learning of sequences[END_REF]Owens et al., 2000;[START_REF] De | Visual search performance across 40 h of continuous wakefulness: Measures of speed and accuracy and relation with oculomotor performance[END_REF]Wright et al., 2002), in simulated shift-work conditions (Fröberg et al., 1975;[START_REF] Colquhoun | Experimental studies of shift-work I: A comparison of 'rotating' and 'stabilized' 4-hour shift systems[END_REF]Johnson et al., 1992), and in real shift-work settings (Tilley et al., 1982;[START_REF] Hossain | Subjective and objective evaluation of sleep and performance in daytime versus nighttime sleep in extended hours shift-workers at an underground mine[END_REF]. On the other hand, in the more demanding cognitive tasks, time-of-day effects interacted with the task components that were manipulated. Thus, time of day impaired response accuracy in the discrimination task only in two out of four task conditions, i.e. when the difference between items to be discriminated was least obvious, while no such effect was found in those conditions involving a more marked to-be-discriminated changes have also been proposed to account for performance variations observed in laboratory studies. In the morning, when arousal was low, performance was shown to peak in those tasks involving more automatic processing, while increasing arousal across the day would favour more elaborate processing, like processing of semantic aspects from long-term memory (Baddeley et al., 1970;Folkard, 1979;Folkard et al., 1976;Folkard & Monk, 1980;Lorenzetti & Natale, 1996;Oakhill & Davies, 1989). This hypothesis was favoured by the finding of significant correlations between operators' self-rated alertness and their task performance. More especially, when they rated alertness at a low level, their response speed in the discrimination task and their recall and recognition performance were also reduced, and vice versa. In addition, as reported above, significant time-of-day effects were observed in all the neuropsychological tests used, with overall higher performance during the day. However, no clear performance peak was observed in either task in the present study. This may be related to the marked inter-individual task performance differences, evidenced by large standard errors, in particular in the cognitively more loaded tasks. Inter- individual task performance differences may be related to differences in operators' sleepiness, workload, adjustment to shift-work, and work conditions (Akerstedt, 2007;[START_REF] Bustamante | Effects of varying the threshold of alarm systems and workload on human performance[END_REF][START_REF] Costa | Ageing, working hours and work ability[END_REF], in addition to the afore-mentioned lack of control for external factors.

Accordingly, future field studies of the present kind should include objective sleep measures, in addition to subjective alertness or sleepiness ratings in order to explore the effects of sleepiness and adjustment to shift-work on operators' task performance (Tucker et al., 1998). The tests used in the present study may be of limited ecological value as far as job-task complexity, real-job performance, and consequences of performance impairments on safety and security are concerned.

In this respect it may be useful to include in future studies a workload index, as discussed in several recent studies (Pretorius & Cilliers, 2007;Noyes & Bruneau, 2007 ;Roth, Scott, Deutsch, Kuper, Schmidt, et al ., 2006). Thus, though no direct relation may exist between the present results and real-job performance, the neuropsychological tests enabled suitable outcome measures reflecting cognitive processes also involved in real-job operations. Furthermore, data provided evidence of subtle changes in operators' information processing strategies in relation to time of day. This further confirmed that time-of-day effects on memory depend on specific task-related factors (Mélan et al., 2007) Type of Structural 0.41 (.14) 0.34 (.10) 0.41 (.10) 0.37 (.04) 0.35 (.05) 0.36 (.03) inducing Typographic 0.37 (.09) 0.36 (.08) 0.36 (.06) 0.45 (.10) 0.36 (.04) 0.38 (.05) question Semantic 0.40 (.12) 0.36 (.05) 0.40 (.08) 0.39 (.05) 0.37 (.06) 0.36 (.04) List Beginning 0.24 (.02) 0.35 (.06) 0.38 (.07) 0.43 (.09) 0.42 (.07) 0.36 (.07) portion Intermediary 0.55 (.22) 0.39 (.09) 0.40 (.06) 0.47 (.13) 0.37 (.06) 0.32 (.

  more accurately in the most obvious discrimination conditions (3-px shift, no-shift) compared to the 1-and 2-pixel shift conditions (in each case, p < .01), and in the 2-pixel compared to the 1-pixel discrimination condition (p< .001). Discrimination condition also affected subjects' response latency (F(3,23) = 4.783, p < .01), with more rapid responding in the 3-px shift condition compared to the remaining conditions (in each case, p < .01).

  < .001) and end portions (p < .001) of the list compared to the initial list-portion. No interaction was found between task factors and TOD.

  what they should feel like while being at work or what they expect to feel like given the time of day.

  recall for auditory compared to visual material is of particular relevance given the rather limited use of auditory compared to visual interfaces in many job-situations, even for signalling emergency conditions.Page 21 of 68 URL: http://mc.manuscriptcentral.com/terg E-mail: ergonomics@tandf.co.Froberg, J.E., Karlsson, C., Levi, L. and Lidberg, L., 1975. Circadian rhythms of catecholamine excretion, shooting range performance, and self self-ratings of fatigue during sleep deprivation. Biological Psychology, 2, 175-188.Galy, E., Camps, J.F. and[START_REF] Galy | Influence of the perceptual mode on serial probe recognition across the 24-hr day in experienced shift-workers[END_REF] Influence of the perceptual mode on serial probe recognition across the 24-hr day in experienced shift-workers.CognitiveSystems, 6, 249-254. Galy, E., Mélan, C. and Cariou, M., 2006. Alertness and tension in air traffic controllers: Investigation of time of day, time on duty and workload. In 26 th Meeting of the European Association in Aviation Psychology, 24-28 septembre 2006, Postdam, G, 54-55. Gennaro de L., Ferrara, M., Curcio, G. and Bertini, M., 2001. Visual search performance across 40 h of continuous wakefulness: Measures of speed and accuracy and relation with oculomotor performance. Physiology and Behavior, 74, 197-204. Harrison, Y. and Horne, J.A., 2000. The impact of sleep deprivation on decision making: A review. Journal of Experimental Psychology: Applied, 6, 236-249. Heuer, H., Spijkers, W., Kiesswetter, E. and Schmidtke, V., 1998. Effects of sleep loss, time of day, and extended mental work on implicit and explicit learning of sequences. Journal of Experimental Psychology: Applied, 4, 139-162. Horne, J.A. and Ostberg, O., 1976. A self-assessment questionnaire to determine morningness-eveningness in human circadian rhythms. International Journal of Chronobiology, 4, 97-110. Hossain, J.L., Reinish, L.W., Heslegrave, R.J., Hall, G.W., Kayumov L., Chung, S.A., et al., 2004. Subjective and objective evaluation of sleep and performance in daytime versus nighttime sleep in extended hours shift-workers at an underground mine. Journal of Occupational and Environmental Medicine, 46(3), 212-226.

  Tilley, A.J., Wilkinson, R.T., Warren, P.S.G.,Watson, B. and Drud, M., 1982. The sleep and performance of shift workers. HumanFactors, 24, 629-41. Van Dongen, H.P.A., Maislin, G., Mullington, J.M. and Dinges, D.F., 2003. The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep, 26, 117-126. Wilkinson, R.T., 1992. The measurement of sleepiness. In: R.J. Broughton and R. Ogivie, eds. Sleep, arousal and performance. Boston: Birkhauser, 254-265.Wojtczak-Jaroszowa, J.,Makowska, Z., Rzepecki, H., Banaszkiewicz, A. and Romejko, A., 1978. Changes in psychomotor and mental task performance following physical work in standard conditions, and in a shift-working situation.Ergonomics , 21, 801-809.Wright, K.P., Hull, J.T. and Czeisler, C.A., 2002. Relationship between alertness, performance, and body temperature in humans. American Journal of Physiology, 253, R1370-R1377.

Figure 1 .

 1 Figure 1. Mean (+/-S.E.) self-ratings of alertness on a check-list provided every 4

Figure 2

 2 Figure 2. a) Mean (+/-S.E.) number of errors and b) mean (+/-S.E.) response

Figure 3 .

 3 Figure 3. Mean (+/-S.E.) number of correct responses in a probe recognition task

Figure 4 .

 4 Figure 4. Mean (+/-S.E.) number of words recalled according to the type of

  few decades, a number of studies showed how performance measures are affected by sleep drive (homeostatic influence) and circadian phase.

  Each of 24 trials started with the display of two horizontal parallel bars, 3-cm long and 0.5 cm apart. Depending on the trial, the bars were either shifted horizontally to each other by 1, 2 or 3 pixels (in each case, trials), or they were not shifted (1/4 of the trial). Items were displayed in the centre of a computer screen while the following instruction occurred on the bottom of the screen "The lines are shifted (press the key M) / The lines are not shifted (press key Q)". The participant's response initiated a 2-sec inter-trialinterval, before the next trial started. Software, specifically designed for this study, presented the four discrimination conditions randomly, and recorded the subject's response accuracy and latency.2.2.3. Probe recognition:On each of 32 trials, six common French nouns were presented, one by one (750 ms), at a rate of one word per second. Four seconds after presentation of the last list-item, a probe item was presented together with the following response instruction "The word figured in the list (press M-button) /The word did not figure in the list (press Q-button)". The subject's response initiated a 5-sec ITT, followed by a brief sound signalling the start of the next trial. The list-items were randomly selected from a 24-item set and on half the trials the probe had occurred in the list. Item-lists and probes could be presented either in the visual modality (centre of a computer screen), or in the auditory modality (loud-speakers). The four trial types resulting from presentation modality of lists and probes(auditory-visual, auditory-auditory, visual-visual, visual-auditory) were randomized across trials by the aforementioned tailor-made software. To rule out practice effects across the six testing times, six different item-sets were used. All items of a set belonged to the same word category (fruit, vegetables, music instruments, furniture, and animals).

  more accurately in the most obvious discrimination conditions (3-px shift, no-shift) compared to the 1-and 2-pixel shift conditions (in each case, p < .01), and in the 2-pixel compared to the 1-pixel discrimination condition (p< .001). Discrimination condition also affected subjects' response latency (F(3,23) = 4.783, p < .01), with more rapid responding in the 3-px shift condition compared to the remaining conditions (in each case, p < .01).

  of day (TOD x question type F(10,23) = 1.99, p < .05 ; TOD x list portion F(10,23) = 2.01, p < .05); (F(4,23) = 5.97, p < .001). Post-hoc analyses revealed superior recall for words preceded by a semantic question rather than by

  , i.e. the question type preceding the detection task (structural, typographic, and semantic), and the list portion (initial, intermediary, and endportions). A four-way ANOVA of these factors revealed a significant effect of time of recording (F(5,161) = 2.94, p < .05), indicating slower responses at 03:00 compared to 07:00 (p < .05), and 19:00 (p < .01). Furthermore, highly significant differences between trials (F(2,161) = 40.86, p < .001), and list-portions (F(2,161) = 10.24, p < .001), resulted from slower responses on the first compared to the second and third trials (p < .001, in each case), and on trials inserted in the .001) and end portions (p < .001) of the list compared to the initial list-portion. No interaction was found between task factors and TOD.

Figure 1 .

 1 Figure 1. Mean (+/-S.E.) self-ratings of alertness on a check-list provided every 4

Figure 2

 2 Figure 2. a) Mean (+/-S.E.) number of errors and b) mean (+/-S.E.) response

Figure 3 .

 3 Figure 3. Mean (+/-S.E.) number of correct responses in a probe recognition task

Figure 4 .

 4 Figure 4. Mean (+/-S.E.) number of words recalled according to the type of

Table captions Table

 captions

Table 2 .

 2 Mean response latencies (+/-S.E.) in a visual detection task according to time of day and trial.

Table 3 .

 3 Mean response latencies (+/-S.E.) across trials in the detection task according to time of day, type of inducing question (upper panel), and list-portion (lower panel).

Table 4 .

 4 Ranges and mean (+/-SD) values for Perason's correlation test computed across time of day between alertness scores and each performance measure in the different tasks. The asterisk in the last column indicates that mean r values differed from the null hypothesis, with p< .05.

	Tables
	F o r
	P
	e
	e r
	R e v
	i e
	w
	O n l
	y

Table 1 .

 1

	Time of day

Table 2 .

 2

				Time of day
		3:00	7:00	11:00	15:00	19:00	23:00
	Trial 1	0.28 (.03)	0.29 (.03)	0.42 (.07)	0.35 (.06)	0.29 (.03) 0.30 (.04)
	Trial 2	0.28 (.04)	0.31 (.05)	0.46 (.09)	0.47 (.14)	0.41 (.08) 0.23 (.07)
	Trial 3	0.53 (.17)	0.40 (.08)	0.31 (.06)	0.35 (.08)	0.46 (.08) 0.40 (.09)

URL: http://mc.manuscriptcentral.com/terg E-mail: ergonomics@tandf.co.uk

Table 3 .

 3

			Time of day
	03:00	07:00	11:00	15:00	19:00	23:00

Table 4 .

 4

		Performance	Range of r	Mean r values	t(22)
		measure	values
	Discrimination	Latency	-0.91 -0.75	-.24 (.11)	-2.21*
		Errors	-0.68 to 0.44	-.11 (0.09	-1.18
	Probe	Auditory	-0.77 to 0.72	0.13 (0.11)	1.25
	Recognition	Visual	-0.58 to 0.86	.25 (.09)	2.68*
	Free Recall	Physical	-0.64 to 0.83	.22 (.10)	2.23*
		Structural	-0.72 to 0.96	21 (.09)	2.38*
		Semantic	-0.42 to 0.86	.19 (.08)	2.36*

  Though the tasks used in the present study were rule-based, it may be that the changing task conditions involved strategy changes that may have increased the task-sensitivity to time-of-day effects. Strategy changes in relation to arousal

	processing was favoured during encoding, rather than processing of structural or
	physical word attributes.
	Harrison and Horne (2000) proposed to differentiate those cognitive demanding
	tasks involving divergent skills, such as innovating and updating strategies, from
	those based on convergent rule-based skills. The authors reported a number of
	studies demonstrating sleep deprivation effects in the former but not in the latter
	tasks.	F r o
		P
		e
		e r
		R e v
		i e
		w
		O n l
		y
	difference. Likewise, recognition performance was superior on early morning
	hours for auditory compared to visually encoded words. In a free recall task,
	operators displayed superior recall during day-time, but only when elaborate

  demonstration of superior recall for auditory compared to visual material is of particular relevance given the rather limited use of auditory compared to visual interfaces in many job-situations, even for signalling emergency conditions. Tilley, A.J., Wilkinson, R.T., Warren, P.S.G.,Watson, B. and Drud, M., 1982. The sleep and performance of shift workers. Human Factors, 24, 629-41.Van Dongen, H.P.A., Maislin, G., Mullington, J.M. andDinges, D.F., 2003. The cumulative cost of additional wakefulness: Dose-response effects on neurobehavioral functions and sleep physiology from chronic sleep restriction and total sleep deprivation. Sleep, 26, 117-126. Wilkinson, R.T., 1992. The measurement of sleepiness. In: R.J. Broughton and R. Ogivie, eds. Sleep, arousal and performance. Boston: Birkhauser, 254-265.Wojtczak-Jaroszowa, J.,Makowska, Z., Rzepecki, H., Banaszkiewicz, A. and Romejko, A., 1978. Changes in psychomotor and mental task performance following physical work in standard conditions, and in a shift-working situation.Ergonomics , 21, 801-809.Wright, K.P., Hull, J.T. and Czeisler, C.A., 2002. Relationship between alertness, performance, and body temperature in humans. American Journal of Physiology, 253, R1370-R1377.

	Page 53 of 68	Ergonomics Ergonomics	Page 60 of 68
	F o r F o r F o r F o r F o r F o r F o r F o r F o r
	P P P P P P P P P
	e e e e e e e e e
	e r e r e r e r e r e r e r e r e r
		R e v R e v R e v R e v R e v R e v R e v R e v R e v
		i e i e i e i e i e i e i e i e i e
		w w w w w w w w w
	. Moreover, the data O n l O n l O n l O n l O n l O n l O n l O n l O n l emphasize that organizing shift-work and work-break systems to maintain y y y y y y y y y
	adequate concentration and avoid fatigue and boredom is still a major concern, in
	particular for safety-related occupations. Practical implications also include often-
	overlooked recommendations based on laboratory studies, and in particular on the
	findings of systematic performance variations according to presentation modality
	and depth of processing of verbal material (see INTRODUCTION). The

URL: http://mc.manuscriptcentral.com/terg E-mail: ergonomics@tandf.co.uk URL: http://mc.manuscriptcentral.com/terg E-mail: ergonomics@tandf.co.uk

Table captions Table 1 .

 captions1 Mean number of words recalled (+/-S.E.) according to their position in the list (initial list-portion: positions 1 to 6, intermediary list-portion: positions 7 to 12, terminal list-portion: positions 13 to 18).

Table 2 .

 2 Mean response latencies (+/-S.E.) in a visual detection task according to time of day and trial.

Table 3 .

 3 Mean response latencies (+/-S.E.) across trials in the detection task according to time of day, type of inducing question (upper panel), and list-portion (lower panel).

Table 4 .

 4 Ranges and mean (+/-SD) values for Perason's correlation test computed across time of day between alertness scores and each performance measure in the different tasks. The asterisk in the last column indicates that mean r values differed from the null hypothesis, with p< .05.

	Tables
	Table 1.
				Time of day
	List-portion 3:00	7:00	11:00	15:00	19:00	23:00
	initial	1.83 (.30)	2.57 (.27)	2.45 (.26)	2.00 (.27)	1.75 (.29)	2.14 (.27)
	F intermediary 1.91 (.31) o r 1.39 (.26) terminal 1.87 (.33) 1.61 (.23)	1.77 (.27) 1.91 (.35)	1.77 (.27) 1.95 (.26)	1.95 (.27) 2.20 (.32)	1.33 (.24) 1.62 (.28)
		P
			e
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					O n l
						y

Table 2 .

 2

				Time of day
		3:00	7:00	11:00	15:00	19:00	23:00
	Trial 1	0.28 (.03)	0.29 (.03)	0.42 (.07)	0.35 (.06)	0.29 (.03) 0.30 (.04)
	Trial 2	0.28 (.04)	0.31 (.05)	0.46 (.09)	0.47 (.14)	0.41 (.08) 0.23 (.07)
	Trial 3	0.53 (.17)	0.40 (.08)	0.31 (.06)	0.35 (.08)	0.46 (.08) 0.40 (.09)

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Table 3 .

 3

			Time of day
	03:00	07:00	11:00	15:00	19:00	23:00

  06) End 0.38 (.07) 0.35 (.05) 0.40 (.09) 0.33 (.06) 0.41 (.08) 0.41 (.07)

Table 4 .

 4

		Performance	Range of r	Mean r values	t(22)
		measure	values
	Discrimination	Latency	-0.91 -0.75	-.24 (.11)	-2.21*
		Errors	-0.68 to 0.44	-.11 (0.09	-1.18
	Probe	Auditory	-0.77 to 0.72	0.13 (0.11)	1.25
	Recognition	Visual	-0.58 to 0.86	.25 (.09)	2.68*
	Free Recall	Physical	-0.64 to 0.83	.22 (.10)	2.23*
		Structural	-0.72 to 0.96	21 (.09)	2.38*
		Semantic	-0.42 to 0.86	.19 (.08)	2.36*