Publications by authors named "Jonas Richiardi"

30 Publications

  • Page 1 of 1

Deep Learning to Automate Reference-Free Image Quality Assessment of Whole-Heart MR Images.

Radiol Artif Intell 2020 May 27;2(3):e190123. Epub 2020 May 27.

Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (D.P., R.D., J.H., J.R., T.K.); Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Rue de Bugnon 46, BH 8.80, 1011 Lausanne, Switzerland (D.P., J.H., J.Y., L.D.S., J.R., T.K., M.S.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (D.P., J.R., T.K.); Institute of Electrical Engineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D.); Institute of Bioengineering/Center for Neuroprosthetics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (R.D., D.V.D.V.); Center for Biomedical Imaging (CIBM), Lausanne, Switzerland (J.Y., M.S.); Division of Cardiology and Cardiac MR Center, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (P.G.M., J.S.); and Department of Radiology and Medical Informatics, University Hospital of Geneva (HUG), Geneva, Switzerland (D.V.D.V.).

Purpose: To develop and characterize an algorithm that mimics human expert visual assessment to quantitatively determine the quality of three-dimensional (3D) whole-heart MR images.

Materials And Methods: In this study, 3D whole-heart cardiac MRI scans from 424 participants (average age, 57 years ± 18 [standard deviation]; 66.5% men) were used to generate an image quality assessment algorithm. A deep convolutional neural network for image quality assessment (IQ-DCNN) was designed, trained, optimized, and cross-validated on a clinical database of 324 (training set) scans. On a separate test set (100 scans), two hypotheses were tested: that the algorithm can assess image quality in concordance with human expert assessment as assessed by human-machine correlation and intra- and interobserver agreement and that the IQ-DCNN algorithm may be used to monitor a compressed sensing reconstruction process where image quality progressively improves. Weighted κ values, agreement and disagreement counts, and Krippendorff α reliability coefficients were reported.

Results: Regression performance of the IQ-DCNN was within the range of human intra- and interobserver agreement and in very good agreement with the human expert ( = 0.78, κ = 0.67). The image quality assessment during compressed sensing reconstruction correlated with the cost function at each iteration and was successfully applied to rank the results in very good agreement with the human expert.

Conclusion: The proposed IQ-DCNN was trained to mimic expert visual image quality assessment of 3D whole-heart MR images. The results from the IQ-DCNN were in good agreement with human expert reading, and the network was capable of automatically comparing different reconstructed volumes.© RSNA, 2020.
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http://dx.doi.org/10.1148/ryai.2020190123DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082371PMC
May 2020

Plasma neurofilament light and phosphorylated tau 181 as biomarkers of Alzheimer's disease pathology and clinical disease progression.

Alzheimers Res Ther 2021 03 25;13(1):65. Epub 2021 Mar 25.

Old age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland.

Background: To assess the performance of plasma neurofilament light (NfL) and phosphorylated tau 181 (p-tau181) to inform about cerebral Alzheimer's disease (AD) pathology and predict clinical progression in a memory clinic setting.

Methods: Plasma NfL and p-tau181, along with established cerebrospinal fluid (CSF) biomarkers of AD pathology, were measured in participants with normal cognition (CN) and memory clinic patients with cognitive impairment (mild cognitive impairment and dementia, CI). Clinical and neuropsychological assessments were performed at inclusion and follow-up visits at 18 and 36 months. Multivariate analysis assessed associations of plasma NfL and p-tau181 levels with AD, single CSF biomarkers, hippocampal volume, and clinical measures of disease progression.

Results: Plasma NfL levels were higher in CN participants with an AD CSF profile (defined by a CSF p-tau181/Aβ > 0.0779) as compared with CN non-AD, while p-tau181 plasma levels were higher in CI patients with AD. Plasma NfL levels correlated with CSF tau and p-tau181 in CN, and with CSF tau in CI patients. Plasma p-tau181 correlated with CSF p-tau181 in CN and with CSF tau, p-tau181, Aβ, and Aβ/Aβ in CI participants. Compared with a reference model, adding plasma p-tau181 improved the prediction of AD in CI patients while adding NfL did not. Adding p-tau181, but not NfL levels, to a reference model improved prediction of cognitive decline in CI participants.

Conclusion: Plasma NfL indicates neurodegeneration while plasma p-tau181 levels can serve as a biomarker of cerebral AD pathology and cognitive decline. Their predictive performance depends on the presence of cognitive impairment.
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http://dx.doi.org/10.1186/s13195-021-00805-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7995778PMC
March 2021

Periinfarct rewiring supports recovery after primary motor cortex stroke.

J Cereb Blood Flow Metab 2021 Mar 24:271678X211002968. Epub 2021 Mar 24.

Stroke Research Group, Department of Clinical Neurosciences, University Hospital and Faculty of Medicine, Geneva, Switzerland.

After stroke restricted to the primary motor cortex (M1), it is uncertain whether network reorganization associated with recovery involves the periinfarct or more remote regions. We studied 16 patients with focal M1 stroke and hand paresis. Motor function and resting-state MRI functional connectivity (FC) were assessed at three time points: acute (<10 days), early subacute (3 weeks), and late subacute (3 months). FC correlates of recovery were investigated at three spatial scales, (i) ipsilesional non-infarcted M1, (ii) core motor network (M1, premotor cortex (PMC), supplementary motor area (SMA), and primary somatosensory cortex), and (iii) extended motor network including all regions structurally connected to the upper limb representation of M1. Hand dexterity was impaired only in the acute phase ( = 0.036). At a small spatial scale, clinical recovery was more frequently associated with connections involving ipsilesional non-infarcted M1 (Odds Ratio = 6.29; 0.036). At a larger scale, recovery correlated with increased FC strength in the core network compared to the extended motor network (rho = 0.71; = 0.006). These results suggest that FC changes associated with motor improvement involve the perilesional M1 and do not extend beyond the core motor network. Core motor regions, and more specifically ipsilesional non-infarcted M1, could hence become primary targets for restorative therapies.
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http://dx.doi.org/10.1177/0271678X211002968DOI Listing
March 2021

To buy or not to buy-evaluating commercial AI solutions in radiology (the ECLAIR guidelines).

Eur Radiol 2021 Mar 5. Epub 2021 Mar 5.

Department of Radiology, Lausanne University Hospital and University of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.

Artificial intelligence (AI) has made impressive progress over the past few years, including many applications in medical imaging. Numerous commercial solutions based on AI techniques are now available for sale, forcing radiology practices to learn how to properly assess these tools. While several guidelines describing good practices for conducting and reporting AI-based research in medicine and radiology have been published, fewer efforts have focused on recommendations addressing the key questions to consider when critically assessing AI solutions before purchase. Commercial AI solutions are typically complicated software products, for the evaluation of which many factors are to be considered. In this work, authors from academia and industry have joined efforts to propose a practical framework that will help stakeholders evaluate commercial AI solutions in radiology (the ECLAIR guidelines) and reach an informed decision. Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services. KEY POINTS: • Numerous commercial solutions based on artificial intelligence techniques are now available for sale, and radiology practices have to learn how to properly assess these tools. • We propose a framework focusing on practical points to consider when assessing an AI solution in medical imaging, allowing all stakeholders to conduct relevant discussions with manufacturers and reach an informed decision as to whether to purchase an AI commercial solution for imaging applications. • Topics to consider in the evaluation include the relevance of the solution from the point of view of each stakeholder, issues regarding performance and validation, usability and integration, regulatory and legal aspects, and financial and support services.
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http://dx.doi.org/10.1007/s00330-020-07684-xDOI Listing
March 2021

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis.

NMR Biomed 2020 05 3;33(5):e4283. Epub 2020 Mar 3.

Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.

The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a deep learning-based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS-positive (CVS ) and 448 CVS-negative (CVS ) lesions. A 3D convolutional neural network ("CVSnet") was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS /CVS lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion-wise and subject-wise and compared with a state-of-the-art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion-wise median balanced accuracy of 81%, and subject-wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was ~ 600-fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion-wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.
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http://dx.doi.org/10.1002/nbm.4283DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754184PMC
May 2020

Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends.

Semin Musculoskelet Radiol 2019 Jun 4;23(3):304-311. Epub 2019 Jun 4.

Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland, Lausanne, Switzerland.

Artificial intelligence (AI) has gained major attention with a rapid increase in the number of published articles, mostly recently. This review provides a general understanding of how AI can or will be useful to the musculoskeletal radiologist. After a brief technical background on AI, machine learning, and deep learning, we illustrate, through examples from the musculoskeletal literature, potential AI applications in the various steps of the radiologist's workflow, from managing the request to communication of results. The implementation of AI solutions does not go without challenges and limitations. These are also discussed, as well as the trends and perspectives.
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http://dx.doi.org/10.1055/s-0039-1684024DOI Listing
June 2019

Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder.

Sci Transl Med 2019 04;11(486)

Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA 94304, USA.

A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.
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http://dx.doi.org/10.1126/scitranslmed.aal3236DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980337PMC
April 2019

Identifying motor functional neurological disorder using resting-state functional connectivity.

Neuroimage Clin 2018 12;17:163-168. Epub 2017 Oct 12.

Department of Clinical Neuroscience, Geneva University Hospital, Rue Gabrielle-Perret-Gentil 4, 1211 Geneva, Switzerland; Department of Neuroscience, University of Geneva, Campus Biotech, Chemin des Mines 9, 1202 Geneva, Switzerland; Neurology University Clinic, InselSpital, Department of Clinical Neuroscience, 3010 Bern, Switzerland. Electronic address:

Background: Motor functional neurological disorder (mFND) is a clinical diagnosis with reliable features; however, patients are reluctant to accept the diagnosis and physicians themselves bear doubts on potential misdiagnoses. The identification of a positive biomarker could help limiting unnecessary costs of multiple referrals and investigations, thus promoting early diagnosis and allowing early engagement in appropriate therapy.

Objectives: To test whether resting-state (RS) functional magnetic resonance imaging could discriminate patients suffering from mFND from healthy controls.

Methods: We classified 23 mFND patients and 25 age- and gender-matched healthy controls based on whole-brain RS functional connectivity (FC) data, using a support vector machine classifier and the standard Automated Anatomic Labeling (AAL) atlas, as well as two additional atlases for validation.

Results: Accuracy, specificity and sensitivity were over 68% (p = 0.004) to discriminate between mFND patients and controls, with consistent findings between the three tested atlases. The most discriminative connections comprised the right caudate, amygdala, prefrontal and sensorimotor regions. Post-hoc seed connectivity analyses showed that these regions were hyperconnected in patients compared to controls.

Conclusions: The good accuracy to discriminate patients from controls suggests that RS FC could be used as a biomarker with high diagnostic value in future clinical practice to identify mFND patients at the individual level.
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http://dx.doi.org/10.1016/j.nicl.2017.10.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651543PMC
June 2018

Differences in Social Decision-Making between Proposers and Responders during the Ultimatum Game: An EEG Study.

Front Integr Neurosci 2017 11;11:13. Epub 2017 Jul 11.

Laboratory for Psychiatric Neuroscience and Psychotherapy, Department of Medicine, Faculty of Science, University of FribourgFribourg, Switzerland.

The Ultimatum Game (UG) is a typical paradigm to investigate social decision-making. Although the behavior of humans in this task is already well established, the underlying brain processes remain poorly understood. Previous investigations using event-related potentials (ERPs) revealed three major components related to cognitive processes in participants engaged in the responder condition, the early ERP component P2, the feedback-related negativity (FRN) and a late positive wave (late positive component, LPC). However, the comparison of the ERP waveforms between the responder and proposer conditions has never been studied. Therefore, to investigate condition-related electrophysiological changes, we applied the UG paradigm and compared parameters of the P2, LPC and FRN components in twenty healthy participants. For the responder condition, we found a significantly decreased amplitude and delayed latency for the P2 component, whereas the mean amplitudes of the LPC and FRN increased compared to the proposer condition. Additionally, the proposer condition elicited an early component consisting of a negative deflection around 190 ms, in the upward slope of the P2, probably as a result of early conflict-related processing. Using independent component analysis (ICA), we extracted one functional component time-locked to this deflection, and with source reconstruction (LAURA) we found the anterior cingulate cortex (ACC) as one of the underlying sources. Overall, our findings indicate that intensity and time-course of neuronal systems engaged in the decision-making processes diverge between both UG conditions, suggesting differential cognitive processes. Understanding the electrophysiological bases of decision-making and social interactions in controls could be useful to further detect which steps are impaired in psychiatric patients in their ability to attribute mental states (such as beliefs, intents, or desires) to oneself and others. This ability is called mentalizing (also known as theory of mind).
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http://dx.doi.org/10.3389/fnint.2017.00013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5504150PMC
July 2017

Integration and segregation of large-scale brain networks during short-term task automatization.

Nat Commun 2016 11 3;7:13217. Epub 2016 Nov 3.

Department of Psychology, Technische Universität Dresden, Dresden 01069, Germany.

The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.
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http://dx.doi.org/10.1038/ncomms13217DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5097148PMC
November 2016

Large-scale functional network reorganization in 22q11.2 deletion syndrome revealed by modularity analysis.

Cortex 2016 09 20;82:86-99. Epub 2016 Jun 20.

Office Médico-Pédagogique Research Unit, Department of Psychiatry, University of Geneva School of Medicine, Geneva 8, Switzerland; Department of Genetic Medicine and Development, University of Geneva School of Medicine, Geneva, Switzerland.

The 22q11.2 deletion syndrome (22q11DS) is associated with cognitive impairments and a 41% risk of developing schizophrenia. While several studies performed on patients with 22q11DS showed the presence of abnormal functional connectivity in this syndrome, how these alterations affect large-scale network organization is still unknown. Here we performed a network modularity analysis on whole-brain functional connectomes derived from the resting-state fMRI of 40 patients with 22q11DS and 41 healthy control participants, aged between 9 and 30 years old. We then split the sample at 18 years old to obtain two age subgroups and repeated the modularity analyses. We found alterations of modular communities affecting the visuo-spatial network and the anterior cingulate cortex (ACC) in both age groups. These results corroborate previous structural and functional studies in 22q11DS that showed early impairment of visuo-spatial processing regions. Furthermore, as ACC has been linked to the development of psychotic symptoms in 22q11DS, the early impairment of its functional connectivity provide further support that ACC alterations may provide potential biomarkers for an increased risk of schizophrenia. Finally, we found an abnormal modularity partition of the dorsolateral prefrontal cortex (DLPFC) only in adults with 22q11DS, suggesting the presence of an abnormal development of functional network communities during adolescence in 22q11DS.
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http://dx.doi.org/10.1016/j.cortex.2016.06.004DOI Listing
September 2016

Quantitative and Qualitative Analysis of Transient Fetal Compartments during Prenatal Human Brain Development.

Front Neuroanat 2016 24;10:11. Epub 2016 Feb 24.

Department of Developmental Neuroscience, Croatian Institute for Brain Research, School of Medicine, University of Zagreb Zagreb, Croatia.

The cerebral wall of the human fetal brain is composed of transient cellular compartments, which show characteristic spatiotemporal relationships with intensity of major neurogenic events (cell proliferation, migration, axonal growth, dendritic differentiation, synaptogenesis, cell death, and myelination). The aim of the present study was to obtain new quantitative data describing volume, surface area, and thickness of transient compartments in the human fetal cerebrum. Forty-four postmortem fetal brains aged 13-40 postconceptional weeks (PCW) were included in this study. High-resolution T1 weighted MR images were acquired on 19 fetal brain hemispheres. MR images were processed using in-house software (MNI-ACE toolbox). Delineation of fetal compartments was performed semi-automatically by co-registration of MRI with histological sections of the same brains, or with the age-matched brains from Zagreb Neuroembryological Collection. Growth trajectories of transient fetal compartments were reconstructed. The composition of telencephalic wall was quantitatively assessed. Between 13 and 25 PCW, when the intensity of neuronal proliferation decreases drastically, the relative volume of proliferative (ventricular and subventricular) compartments showed pronounced decline. In contrast, synapse- and extracellular matrix-rich subplate compartment continued to grow during the first two trimesters, occupying up to 45% of telencephalon and reaching its maximum volume and thickness around 30 PCW. This developmental maximum coincides with a period of intensive growth of long cortico-cortical fibers, which enter and wait in subplate before approaching the cortical plate. Although we did not find significant age related changes in mean thickness of the cortical plate, the volume, gyrification index, and surface area of the cortical plate continued to exponentially grow during the last phases of prenatal development. This cortical expansion coincides developmentally with the transformation of embryonic cortical columns, dendritic differentiation, and ingrowth of axons. These results provide a quantitative description of transient human fetal brain compartments observable with MRI. Moreover, they will improve understanding of structural-functional relationships during brain development, will enable correlation between in vitro/in vivo imaging and fine structural histological studies, and will serve as a reference for study of perinatal brain injuries.
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http://dx.doi.org/10.3389/fnana.2016.00011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4764715PMC
March 2016

BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.

Science 2015 Jun 11;348(6240):1241-4. Epub 2015 Jun 11.

Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK. Medical Research Council (MRC) Social, Genetic and Developmental Psychiatry (SGDP) Centre, London, UK.

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function.
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http://dx.doi.org/10.1126/science.1255905DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4829082PMC
June 2015

Multicontrast connectometry: a new tool to assess cerebellum alterations in early relapsing-remitting multiple sclerosis.

Hum Brain Mapp 2015 Apr 24;36(4):1609-19. Epub 2014 Nov 24.

Advanced Clinical Imaging Technology, Siemens Healthcare IM BM PI & Department of Radiology, Centre Hospitalier Universitaire Vaudois and University of Lausanne (CHUV), Lausanne, Switzerland; Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne, Switzerland.

Background: Cerebellar pathology occurs in late multiple sclerosis (MS) but little is known about cerebellar changes during early disease stages. In this study, we propose a new multicontrast "connectometry" approach to assess the structural and functional integrity of cerebellar networks and connectivity in early MS.

Methods: We used diffusion spectrum and resting-state functional MRI (rs-fMRI) to establish the structural and functional cerebellar connectomes in 28 early relapsing-remitting MS patients and 16 healthy controls (HC). We performed multicontrast "connectometry" by quantifying multiple MRI parameters along the structural tracts (generalized fractional anisotropy-GFA, T1/T2 relaxation times and magnetization transfer ratio) and functional connectivity measures. Subsequently, we assessed multivariate differences in local connections and network properties between MS and HC subjects; finally, we correlated detected alterations with lesion load, disease duration, and clinical scores.

Results: In MS patients, a subset of structural connections showed quantitative MRI changes suggesting loss of axonal microstructure and integrity (increased T1 and decreased GFA, P < 0.05). These alterations highly correlated with motor, memory and attention in patients, but were independent of cerebellar lesion load and disease duration. Neither network organization nor rs-fMRI abnormalities were observed at this early stage.

Conclusion: Multicontrast cerebellar connectometry revealed subtle cerebellar alterations in MS patients, which were independent of conventional disease markers and highly correlated with patient function. Future work should assess the prognostic value of the observed damage.
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http://dx.doi.org/10.1002/hbm.22698DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6869568PMC
April 2015

Graph analysis of functional brain networks: practical issues in translational neuroscience.

Philos Trans R Soc Lond B Biol Sci 2014 Oct;369(1653)

Univ. Grenoble Alpes, GIPSA-Lab, F-38000 Grenoble, France CNRS, GIPSA-Lab, F-38000 Grenoble, France.

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes.
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http://dx.doi.org/10.1098/rstb.2013.0521DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4150298PMC
October 2014

Neural Correlate of Anterograde Amnesia in Wernicke-Korsakoff Syndrome.

Brain Topogr 2015 Sep 23;28(5):760-770. Epub 2014 Aug 23.

Laboratory of Cognitive Neurorehabilitation, Department of Clinical Neurosciences and Dermatology, Medical Faculty, University Hospitals of Geneva, Geneva, Switzerland.

The neural correlate of anterograde amnesia in Wernicke-Korsakoff syndrome (WKS) is still debated. While the capacity to learn new information has been associated with integrity of the medial temporal lobe (MTL), previous studies indicated that the WKS is associated with diencephalic lesions, mainly in the mammillary bodies and anterior or dorsomedial thalamic nuclei. The present study tested the hypothesis that amnesia in WKS is associated with a disrupted neural circuit between diencephalic and hippocampal structures. High-density evoked potentials were recorded in four severely amnesic patients with chronic WKS, in five patients with chronic alcoholism without WKS, and in ten age matched controls. Participants performed a continuous recognition task of pictures previously shown to induce a left medial temporal lobe dependent positive potential between 250 and 350 ms. In addition, the integrity of the fornix was assessed using diffusion tensor imaging (DTI). WKS, but not alcoholic patients without WKS, showed absence of the early, left MTL dependent positive potential following immediate picture repetitions. DTI indicated disruption of the fornix, which connects diencephalic and hippocampal structures. The findings support an interpretation of anterograde amnesia in WKS as a consequence of a disconnection between diencephalic and MTL structures with deficient contribution of the MTL to rapid consolidation.
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http://dx.doi.org/10.1007/s10548-014-0391-5DOI Listing
September 2015

Altered cerebrovascular reactivity velocity in mild cognitive impairment and Alzheimer's disease.

Neurobiol Aging 2015 Jan 24;36(1):33-41. Epub 2014 Jul 24.

Service neuro-diagnostique et neuro-interventionnel DISIM, Hôpitaux Universitaires de Genève, Genève, Switzerland. Electronic address:

Interindividual variation in neurovascular reserve and its relationship with cognitive performance is not well understood in imaging in neurodegeneration. We assessed the neurovascular reserve in amnestic mild cognitive impairment (aMCI) and Alzheimer's dementia (AD). Twenty-eight healthy controls (HC), 15 aMCI, and 20 AD patients underwent blood oxygen level-dependent imaging for 9 minutes, breathing alternatively air and 7% carbon dioxide mixture. The data were parcellated into 88 anatomic regions, and carbon dioxide regressors accounting for different washin and washout velocities were fitted to regional average blood oxygen level-dependent signals. Velocity of cerebrovascular reactivity (CVR) was analyzed and correlated with cognitive scores. aMCI and AD patients had significantly slower response than HC (mean time to reach 90% of peak: HC 33 seconds, aMCI and AD 59 seconds). CVR velocity correlated with Mini Mental State Examination in 35 of 88 brain regions (p = 0.019, corrected for multiple comparisons), including 10 regions of the default-mode network, an effect modulated by age. This easily applicable protocol yielded a practical assessment of CVR in cognitive decline.
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http://dx.doi.org/10.1016/j.neurobiolaging.2014.07.020DOI Listing
January 2015

Head motion parameters in fMRI differ between patients with mild cognitive impairment and Alzheimer disease versus elderly control subjects.

Brain Topogr 2014 Nov 6;27(6):801-7. Epub 2014 Mar 6.

Service Neuro-diagnostique et Neuro-interventionnel, Department of Imaging and Medical Informatics, University Hospitals of Geneva, Rue Gabrielle Perret-Gentil 4, 1211, Geneva 14, Switzerland,

Motion artifacts are a well-known and frequent limitation during neuroimaging workup of cognitive decline. While head motion typically deteriorates image quality, we test the hypothesis that head motion differs systematically between healthy controls (HC), amnestic mild cognitive impairment (aMCI) and Alzheimer disease (AD) and consequently might contain diagnostic information. This prospective study was approved by the local ethics committee and includes 28 HC (age 71.0 ± 6.9 years, 18 females), 15 aMCI (age 67.7 ± 10.9 years, 9 females) and 20 AD (age 73.4 ± 6.8 years, 10 females). Functional magnetic resonance imaging (fMRI) at 3T included a 9 min echo-planar imaging sequence with 180 repetitions. Cumulative average head rotation and translation was estimated based on standard fMRI preprocessing and compared between groups using receiver operating characteristic statistics. Global cumulative head rotation discriminated aMCI from controls [p < 0.01, area under curve (AUC) 0.74] and AD from controls (p < 0.01, AUC 0.73). The ratio of rotation z versus y discriminated AD from controls (p < 0.05, AUC 0.71) and AD from aMCI (p < 0.05, AUC of 0.75). Head motion systematically differs between aMCI/AD and controls. Since motion is not random but convoluted with diagnosis, the higher amount of motion in aMCI and AD as compared to controls might be a potential confounding factor for fMRI group comparisons. Additionally, head motion not only deteriorates image quality, yet also contains useful discriminatory information and is available for free as a "side product" of fMRI data preprocessing.
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http://dx.doi.org/10.1007/s10548-014-0358-6DOI Listing
November 2014

Identifying 22q11.2 deletion syndrome and psychosis using resting-state connectivity patterns.

Brain Topogr 2014 Nov 22;27(6):808-21. Epub 2014 Feb 22.

Office Médico-Pédagogique Research Unit, Department of Psychiatry, University of Geneva School of Medicine, 1 rue David Dufour, CP 50, 1211, Geneva 8, Switzerland,

The clinical picture associated with 22q11.2 deletion syndrome (22q11DS) includes mild mental retardation and an increased risk of schizophrenia. While the clinical phenotype has been related to structural brain network alterations, there is only scarce information about functional connectivity in 22q11DS. However, such studies could lead to a better comprehension of the disease and reveal potential biomarkers for psychosis. A connectivity decoding approach was used to discriminate between 42 patients with 22q11DS and 41 controls using resting-state connectivity. The same method was then applied within the 22q11DS group to identify brain connectivity patterns specifically related to the presence of psychotic symptoms. An accuracy of 84 % was achieved in differentiating patients with 22q11DS from controls. The discriminative connections were widespread, but predominantly located in the bilateral frontal and right temporal lobes, and were significantly correlated to IQ. An 88 % accuracy was obtained for identification of existing psychotic symptoms within the patients group. The regions containing most discriminative connections included the anterior cingulate cortex (ACC), the left superior temporal and the right inferior frontal gyri. Functional connectivity alterations in 22q11DS affect mostly frontal and right temporal lobes and are related to the syndrome's mild mental retardation. These results also provide evidence that resting-state connectivity can potentially become a biomarker for psychosis and that ACC plays an important role in the development of psychotic symptoms.
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http://dx.doi.org/10.1007/s10548-014-0356-8DOI Listing
November 2014

Principal components of functional connectivity: a new approach to study dynamic brain connectivity during rest.

Neuroimage 2013 Dec 18;83:937-50. Epub 2013 Jul 18.

Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.

Functional connectivity (FC) as measured by correlation between fMRI BOLD time courses of distinct brain regions has revealed meaningful organization of spontaneous fluctuations in the resting brain. However, an increasing amount of evidence points to non-stationarity of FC; i.e., FC dynamically changes over time reflecting additional and rich information about brain organization, but representing new challenges for analysis and interpretation. Here, we propose a data-driven approach based on principal component analysis (PCA) to reveal hidden patterns of coherent FC dynamics across multiple subjects. We demonstrate the feasibility and relevance of this new approach by examining the differences in dynamic FC between 13 healthy control subjects and 15 minimally disabled relapse-remitting multiple sclerosis patients. We estimated whole-brain dynamic FC of regionally-averaged BOLD activity using sliding time windows. We then used PCA to identify FC patterns, termed "eigenconnectivities", that reflect meaningful patterns in FC fluctuations. We then assessed the contributions of these patterns to the dynamic FC at any given time point and identified a network of connections centered on the default-mode network with altered contribution in patients. Our results complement traditional stationary analyses, and reveal novel insights into brain connectivity dynamics and their modulation in a neurodegenerative disease.
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http://dx.doi.org/10.1016/j.neuroimage.2013.07.019DOI Listing
December 2013

Pulsatile blood flow in human bone assessed by laser-Doppler flowmetry and the interpretation of photoplethysmographic signals.

Physiol Meas 2013 Mar 26;34(3):N25-40. Epub 2013 Feb 26.

Département de Neurosciences Fondamentales, University of Geneva, Geneva, Switzerland.

Human bone blood flow, mean blood speed and the number of moving red blood cells were assessed (in arbitrary units), as a function of time, during one cardiac cycle. The measurements were obtained non-invasively on five volunteers by laser-Doppler flowmetry at large interoptode spacing. The investigated bones included: patella, clavicle, tibial diaphysis and tibial malleolus. As hypothesized, we found that in all bones the number of moving cells remains constant during cardiac cycles. Therefore, we concluded that the pulsatile nature of blood flow must be completely determined by the mean blood speed and not by changes in blood volume (vessels dilation). Based on these results, it is finally demonstrated using a mathematical model (derived from the radiative transport theory) that photoplethysmographic (PPG) pulsations observed by others in the literature, cannot be generated by oscillations in blood oxygen saturation, which is physiologically linked to blood speed. In fact, possible oxygen saturation changes during pulsations decrease the amplitude of PPG pulsations due to specific features of the PPG light source. It is shown that a variation in blood oxygen saturation of 3% may induce a negative change of ∼1% in the PPG signal. It is concluded that PPG pulsations are determined by periodic 'positive' changes of the reduced scattering coefficient of the tissue and/or the absorption coefficient at constant blood volume. No explicit experimental PPG measurements have been performed. As a by-product of this study, an estimation of the arterial pulse wave velocity obtained from the analysis of the blood flow pulsations give a value of 7.8 m s(-1) (95% confidence interval of the sample mean distribution: [6.7, 9.5] m s(-1)), which is perfectly compatible with data in the literature. We hope that this note will contribute to a better understanding of PPG signals and to further develop the domain of the vascular physiology of human bone.
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http://dx.doi.org/10.1088/0967-3334/34/3/N25DOI Listing
March 2013

Altered cortical and subcortical local coherence in obstructive sleep apnea: a functional magnetic resonance imaging study.

J Sleep Res 2013 Jun 21;22(3):337-47. Epub 2012 Nov 21.

Department of Neurological and Sensorial Sciences, University of Siena, Viale Bracci 2, Siena, Italy.

Obstructive sleep apnea (OSA) syndrome is the most common sleep-related breathing disorder, characterized by excessive snoring and repetitive apneas and arousals, which leads to fragmented sleep and, most importantly, to intermittent nocturnal hypoxaemia during apneas. Considering previous studies about morphovolumetric alterations in sleep apnea, in this study we aimed to investigate for the first time the functional connectivity profile of OSA patients and age-gender-matched healthy controls, using resting-state functional magnetic resonance imaging (fMRI). Twenty severe OSA patients (mean age 43.2 ± 8 years; mean apnea-hypopnea index, 36.3 h(-1) ) and 20 non-apneic age-gender-body mass index (BMI)-matched controls underwent fMRI and polysomnographic (PSG) registration, as well as mood and sleepiness evaluation. Cerebro-cerebellar regional homogeneity (ReHo) values were calculated from fMRI acquisition, in order to identify pathology-related alterations in the local coherence of low-frequency signal (<0.1 Hz). Multivariate pattern classification was also performed using ReHo values as features. We found a significant pattern of cortical and subcortical abnormal local connectivity in OSA patients, suggesting an overall rearrangement of hemispheric connectivity balance, with a decrease of local coherence observed in right temporal, parietal and frontal lobe regions. Moreover, an increase in bilateral thalamic and somatosensory/motor cortices coherence have been found, a finding due possibly to an aberrant adaptation to incomplete sleep-wake transitions during nocturnal apneic episodes, induced by repetitive choke sensation and physical efforts attempting to restore breathing. Different hemispheric roles into sleep processes and a possible thalamus key role in OSA neurophysiopathology are intriguing issues that future studies should attempt to clarify.
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http://dx.doi.org/10.1111/jsr.12006DOI Listing
June 2013

Attention-related potentials allow for a highly accurate discrimination of mild cognitive impairment subtypes.

Neurodegener Dis 2013 7;12(2):59-70. Epub 2012 Sep 7.

Clinical Neurophysiology and Neuroimaging Unit, Division of Neuropsychiatry, Department of Psychiatry, University Hospitals of Geneva, Chene-Bourg, Switzerland.

The three most frequent forms of mild cognitive impairment (MCI) are single-domain amnestic MCI (sd-aMCI), single-domain dysexecutive MCI (sd-dMCI) and multiple-domain amnestic MCI (md-aMCI). Brain imaging differences among single domain subgroups of MCI were recently reported supporting the idea that electroencephalography (EEG) functional hallmarks can be used to differentiate these subgroups. We performed event-related potential (ERP) measures and independent component analysis in 18 sd-aMCI, 13 sd-dMCI and 35 md-aMCI cases during the successful performance of the Attentional Network Test. Sensitivity and specificity analyses of ERP for the discrimination of MCI subgroups were also made. In center-cue and spatial-cue warning stimuli, contingent negative variation (CNV) was elicited in all MCI subgroups. Two independent components (ICA1 and 2) were superimposed in the time range on the CNV. The ICA2 was strongly reduced in sd-dMCI compared to sd-aMCI and md-aMCI (4.3 vs. 7.5% and 10.9% of the CNV component). The parietal P300 ERP latency increased significantly in sd-dMCI compared to md-aMCI and sd-aMCI for both congruent and incongruent conditions. This latency for incongruent targets allowed for a highly accurate separation of sd-dMCI from both sd-aMCI and md-aMCI with correct classification rates of 90 and 81%, respectively. This EEG parameter alone performed much better than neuropsychological testing in distinguishing sd-dMCI from md-aMCI. Our data reveal qualitative changes in the composition of the neural generators of CNV in sd-dMCI. In addition, they document an increased latency of the executive P300 component that may represent a highly accurate hallmark for the discrimination of this MCI subgroup in routine clinical settings.
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http://dx.doi.org/10.1159/000338815DOI Listing
January 2014

Haemodynamic responses to temperature changes of human skeletal muscle studied by laser-Doppler flowmetry.

Physiol Meas 2012 Jul 27;33(7):1181-97. Epub 2012 Jun 27.

Département de Neurosciences Fondamentales, University of Geneva, Geneva, Switzerland.

Using a small, but very instructive experiment, it is demonstrated that laser-Doppler flowmetry (LDF) at large interoptode spacing represents a unique tool for new investigations of thermoregulatory processes modulating the blood flow of small muscle masses in humans. It is shown on five healthy subjects that steady-state values of blood flow (perfusion) in the thenar eminence muscle group depend in a complex manner on both the local intramuscular temperature and local skin temperature, while the values of blood flow parameters measured during physiological transients, such as the post-ischaemic hyperhaemic response, depend only on the intramuscular temperature. In addition, it is shown that the so-called biological zero (i.e. remaining LDF signal during arterial occlusion) is influenced not only as expected by the intramuscular temperature, but also by the skin temperature. The proposed results reveal that the skeletal muscle has unique thermoregulatory characteristics compared, for example, to human skin. These and other observations represent new findings and we hope that they will serve as a stimulus for the creation of new experimental protocols leading to better understanding of blood flow regulation.
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http://dx.doi.org/10.1088/0967-3334/33/7/1181DOI Listing
July 2012

Classifying minimally disabled multiple sclerosis patients from resting state functional connectivity.

Neuroimage 2012 Sep 5;62(3):2021-33. Epub 2012 Jun 5.

Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.

Multiple sclerosis (MS), a variable and diffuse disease affecting white and gray matter, is known to cause functional connectivity anomalies in patients. However, related studies published to-date are post hoc; our hypothesis was that such alterations could discriminate between patients and healthy controls in a predictive setting, laying the groundwork for imaging-based prognosis. Using functional magnetic resonance imaging resting state data of 22 minimally disabled MS patients and 14 controls, we developed a predictive model of connectivity alterations in MS: a whole-brain connectivity matrix was built for each subject from the slow oscillations (<0.11 Hz) of region-averaged time series, and a pattern recognition technique was used to learn a discriminant function indicating which particular functional connections are most affected by disease. Classification performance using strict cross-validation yielded a sensitivity of 82% (above chance at p<0.005) and specificity of 86% (p<0.01) to distinguish between MS patients and controls. The most discriminative connectivity changes were found in subcortical and temporal regions, and contralateral connections were more discriminative than ipsilateral connections. The pattern of decreased discriminative connections can be summarized post hoc in an index that correlates positively (ρ=0.61) with white matter lesion load, possibly indicating functional reorganisation to cope with increasing lesion load. These results are consistent with a subtle but widespread impact of lesions in white matter and in gray matter structures serving as high-level integrative hubs. These findings suggest that predictive models of resting state fMRI can reveal specific anomalies due to MS with high sensitivity and specificity, potentially leading to new non-invasive markers.
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http://dx.doi.org/10.1016/j.neuroimage.2012.05.078DOI Listing
September 2012

Event-related potentials and changes of brain rhythm oscillations during working memory activation in patients with first-episode psychosis.

J Psychiatry Neurosci 2012 Feb;37(2):95-105

Department of Psychiatry, Geneva University Hospitals and University of Geneva, Switzerland.

Background: Earlier contributions have documented significant changes in sensory, attention-related endogenous event-related potential (ERP) components and θ band oscillatory responses during working memory activation in patients with schizophrenia. In patients with first-episode psychosis, such studies are still scarce and mostly focused on auditory sensory processing. The present study aimed to explore whether subtle deficits of cortical activation are present in these patients before the decline of working memory performance.

Methods: We assessed exogenous and endogenous ERPs and frontal θ event-related synchronization (ERS) in patients with first-episode psychosis and healthy controls who successfully performed an adapted 2-back working memory task, including 2 visual n-backworking memory tasks as well as oddball detection and passive fixation tasks.

Results: We included 15 patients with first-episode psychosis and 18 controls in this study. Compared with controls, patients with first-episode psychosis displayed increased latencies of early visual ERPs and phasic θ ERS culmination peak in all conditions. However, they also showed a rapid recruitment of working memory-related neural generators, even in pure attention tasks, as indicated by the decreased N200 latency and increased amplitude of sustained θ ERS in detection compared with controls.

Limitations: Owing to the limited sample size, no distinction was made between patients with first-episode psychosis with positive and negative symptoms. Although we controlled for the global load of neuroleptics, medication effect cannot be totally ruled out.

Conclusion: The present findings support the concept of a blunted electroencephalographic response in patients with first-episode psychosis who recruit the maximum neural generators in simple attention conditions without being able to modulate their brain activation with increased complexity of working memory tasks.
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http://dx.doi.org/10.1503/jpn.110033DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3297068PMC
February 2012

Decoding brain states from fMRI connectivity graphs.

Neuroimage 2011 May 9;56(2):616-26. Epub 2010 Jun 9.

Medical Image Processing Laboratory, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

Functional connectivity analysis of fMRI data can reveal synchronised activity between anatomically distinct brain regions. Here, we extract the characteristic connectivity signatures of different brain states to perform classification, allowing us to decode the different states based on the functional connectivity patterns. Our approach is based on polythetic decision trees, which combine powerful discriminative ability with interpretability of results. We also propose to use ensemble of classifiers within specific frequency subbands, and show that they bring systematic improvement in classification accuracy. Exploiting multi-band classification of connectivity graphs is also proposed, and we explain theoretical reasons why the technique could bring further improvement in classification performance. The choice of decision trees as classifier is shown to provide a practical way to identify a subset of connections that distinguishes best between the conditions, permitting the extraction of very compact representations for differences between brain states, which we call discriminative graphs. Our experimental results based on strict train/test separation at all stages of processing show that the method is applicable to inter-subject brain decoding with relatively low error rates for the task considered.
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http://dx.doi.org/10.1016/j.neuroimage.2010.05.081DOI Listing
May 2011

Bayesian networks and information theory for audio-visual perception modeling.

Biol Cybern 2010 Sep 26;103(3):213-26. Epub 2010 May 26.

Institute of Movement Sciences, CNRS & Université de la Méditerranée, Marseille, France.

Thanks to their different senses, human observers acquire multiple information coming from their environment. Complex cross-modal interactions occur during this perceptual process. This article proposes a framework to analyze and model these interactions through a rigorous and systematic data-driven process. This requires considering the general relationships between the physical events or factors involved in the process, not only in quantitative terms, but also in term of the influence of one factor on another. We use tools from information theory and probabilistic reasoning to derive relationships between the random variables of interest, where the central notion is that of conditional independence. Using mutual information analysis to guide the model elicitation process, a probabilistic causal model encoded as a Bayesian network is obtained. We exemplify the method by using data collected in an audio-visual localization task for human subjects, and we show that it yields a well-motivated model with good predictive ability. The model elicitation process offers new prospects for the investigation of the cognitive mechanisms of multisensory perception.
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http://dx.doi.org/10.1007/s00422-010-0392-8DOI Listing
September 2010

The multiscenario multienvironment BioSecure Multimodal Database (BMDB).

IEEE Trans Pattern Anal Mach Intell 2010 Jun;32(6):1097-111

Universidad Autonoma de Madrid, Madrid.

A new multimodal biometric database designed and acquired within the framework of the European BioSecure Network of Excellence is presented. It is comprised of more than 600 individuals acquired simultaneously in three scenarios: 1) over the Internet, 2) in an office environment with desktop PC, and 3) in indoor/outdoor environments with mobile portable hardware. The three scenarios include a common part of audio/video data. Also, signature and fingerprint data have been acquired both with desktop PC and mobile portable hardware. Additionally, hand and iris data were acquired in the second scenario using desktop PC. Acquisition has been conducted by 11 European institutions. Additional features of the BioSecure Multimodal Database (BMDB) are: two acquisition sessions, several sensors in certain modalities, balanced gender and age distributions, multimodal realistic scenarios with simple and quick tasks per modality, cross-European diversity, availability of demographic data, and compatibility with other multimodal databases. The novel acquisition conditions of the BMDB allow us to perform new challenging research and evaluation of either monomodal or multimodal biometric systems, as in the recent BioSecure Multimodal Evaluation campaign. A description of this campaign including baseline results of individual modalities from the new database is also given. The database is expected to be available for research purposes through the BioSecure Association during 2008.
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http://dx.doi.org/10.1109/TPAMI.2009.76DOI Listing
June 2010

Multimodal biometrics for identity documents (MBioID).

Forensic Sci Int 2007 Apr 4;167(2-3):154-9. Epub 2006 Aug 4.

Institut de Police Scientifique, Ecole des Sciences Criminelles, Université de Lausanne, Switzerland.

The MBioID initiative has been set up to address the following germane question: What and how biometric technologies could be deployed in identity documents in the foreseeable future? This research effort proposes to look at current and future practices and systems of establishing and using biometric identity documents (IDs) and evaluate their effectiveness in large-scale developments. The first objective of the MBioID project is to present a review document establishing the current state-of-the-art related to the use of multimodal biometrics in an IDs application. This research report gives the main definitions, properties and the framework of use related to biometrics, an overview of the main standards developed in the biometric industry and standardisation organisations to ensure interoperability, as well as some of the legal framework and the issues associated to biometrics such as privacy and personal data protection. The state-of-the-art in terms of technological development is also summarised for a range of single biometric modalities (2D and 3D face, fingerprint, iris, on-line signature and speech), chosen according to ICAO recommendations and availabilities, and for various multimodal approaches. This paper gives a summary of the main elements of that report. The second objective of the MBioID project is to propose relevant acquisition and evaluation protocols for a large-scale deployment of biometric IDs. Combined with the protocols, a multimodal database will be acquired in a realistic way, in order to be as close as possible to a real biometric IDs deployment. In this paper, the issues and solutions related to the acquisition setup are briefly presented.
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http://dx.doi.org/10.1016/j.forsciint.2006.06.037DOI Listing
April 2007