Multi-influential genetic interactions alter behaviour and cognition through six main biological cascades in Down syndrome mouse models.

Down syndrome (DS) is the most common genetic form of intellectual disability caused by the presence of an additional copy of human chromosome 21 (Hsa21). To provide novel insights into genotype-phenotype correlations, we used standardized behavioural tests, magnetic resonance imaging and hippocampal gene expression to screen several DS mouse models for the mouse chromosome 16 region homologous to Hsa21. First, we unravelled several genetic interactions between different regions of chromosome 16 and how they contribute significantly to altering the outcome of the phenotypes in brain cognition, function and structure. Then, in-depth analysis of misregulated expressed genes involved in synaptic dysfunction highlighted six biological cascades centred around DYRK1A, GSK3ß, NPY, SNARE, RHOA and NPAS4. Finally, we provide a novel vision of the existing altered gene-gene crosstalk and molecular mechanisms targeting specific hubs in DS models that should become central to better understanding of DS and improving the development of therapies.

Brain network remodelling reflects tau-related pathology prior to memory deficits in Thy-Tau22 mice.

In Alzheimer's disease, the tauopathy is known as a major mechanism responsible for the development of cognitive deficits. Early biomarkers of such affectations for diagnosis/stratification are crucial in Alzheimer's disease research, and brain connectome studies increasingly show their potential establishing pathology fingerprints at the network level. In this context, we conducted an in vivo multimodal MRI study on young Thy-Tau22 transgenic mice expressing tauopathy, performing resting state functional MRI and structural brain imaging to identify early connectome signatures of the pathology, relating with histological and behavioural investigations. In the prodromal phase of tauopathy, before the emergence of cognitive impairments, Thy-Tau22 mice displayed selective modifications of brain functional connectivity involving three main centres: hippocampus (HIP), amygdala (AMG) and the isocortical areas, notably the somatosensory (SS) cortex. Each of these regions showed differential histopathological profiles. Disrupted ventral HIP-AMG functional pathway and altered dynamic functional connectivity were consistent with high pathological tau deposition and astrogliosis in both hippocampus and amygdala, and significant microglial reactivity in amygdalar nuclei. These patterns were concurrent with widespread functional hyperconnectivity of memory-related circuits of dorsal hippocampus-encompassing dorsal HIP-SS communication-in the absence of significant cortical histopathological markers. These findings suggest the coexistence of two intermingled mechanisms of response at the functional connectome level in the early phases of pathology: a maladaptive and a likely compensatory response. Captured in the connectivity patterns, such first responses to pathology could further be used in translational investigations as a lead towards an early biomarker of tauopathy as well as new targets for future treatments.

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination.

Myelin imaging in the central nervous system is essential for monitoring pathologies involving white matter alterations. Various quantitative MRI protocols relying on the modeling of the interactions of water protons with myelinated tissues have shown sensitivities in case of myelin disruption. Some extracted model parameters are more sensitive to demyelination, such as the bound pool fraction (f) in quantitative magnetization transfer imaging (qMTI), the radial diffusivity in diffusion tensor imaging (DTI), and the myelin water fraction (MWF) in myelin water imaging (MWI). A 3D ultrashort echo time (UTE) sequence within an appropriate water suppression condition (Diff-UTE) is also considered for the direct visualization of the myelin semi-solid matrix (Diff-UTE normalized signal; rSPF). In this paper, we aimed at assessing the sensitivities and correlations of the parameters mentioned above to an immuno-histological study of the myelin basic protein (MBP) in a murine model of demyelination at 7 T. We demonstrated a high sensitivity of the MRI metrics to demyelination, and strong Spearman correlations in the corpus callosum between histology, macromolecular proton fraction (ρ>0.87) and Diff-UTE signal (ρ>0.76), but moderate ones with radial diffusivity and MWF (|ρ|<0.70).

A diffusion-based method for long-T2 suppression in steady state sequences: Validation and application for 3D-UTE imaging.

PURPOSE: To introduce a novel method for long-T2 signal physical suppression in steady-state based on configuration states combination and modulation using diffusion weighting. Its efficiency in yielding a high contrast in short-T2 structures using an ultrashort echo time acquisition module (Diff-UTE) is compared to the adiabatically prepared Inversion-Recovery-UTE sequence (IR-UTE). THEORY AND METHODS: Using a rectangular-pulse prepared 3D-UTE sequence, the possibility of long-T2 component signal cancellation through diffusion effects is addressed, and the condition met for sets of sequence parameters. Simultaneously, the short-T2 component signal is maximized using a Bloch equation-based optimization process. The method is evaluated from simulations, and experiments are conducted on a phantom composed of short and long-T2 components, as well as on an ex vivo mouse head. RESULTS: Within equal scan times, the proposed method allowed for an efficient long-T2 signal suppression, and expectedly yielded a higher signal to noise ratio in short-T2 structures compared to the IR-UTE technique, although an intrinsic short-T2 signal loss is expected through the preparation module. CONCLUSION: The Diff-UTE method represents an interesting alternative to the IR-UTE technique. Diffusion weighting allowing for a long-T2 suppression results in a less penalizing method to generate a high and selective contrast in short-T2 components. Magn Reson Med 80:548-559, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Functional Disconnectivity during Inter-Task Resting State in Dementia with Lewy Bodies.

AIMS: Limited research has been done on the functional connectivity in visuoperceptual regions in dementia with Lewy bodies (DLB) patients. This study aimed to investigate the functional connectivity differences between a task condition and an inter-task resting state condition within a visuoperceptual paradigm, in DLB patients compared with Alzheimer disease (AD) patients and healthy elderly control subjects. METHODS: Twenty-six DLB, 29 AD, and 22 healthy subjects underwent a detailed clinical and neuropsychological examination along with a functional MRI during the different conditions of a visuoperceptual paradigm. Functional images were analyzed using group-level spatial independent component analysis and seed-based connectivity analyses. RESULTS: While the DLB patients scored well and did not differ from the control and AD groups in terms of functional activity and connectivity during the task conditions, they showed decreased functional connectivity in visuoperceptual regions during the resting state condition, along with a temporal impairment of the default-mode network activity. Functional connectivity disturbances were also found within two attentional-executive networks and between these networks and visuoperceptual regions. CONCLUSION: We found a specific functional profile in the switching between task and resting state conditions in DLB patients. This result could help better characterize functional impairments in DLB and their contribution to several core symptoms of this pathology such as visual hallucinations and cognitive fluctuations.

Which is the most appropriate strategy for conducting multivariate voxel-based group studies on diffusion tensors?

There is a real need in the neuroscience community for efficient tools to compare Diffusion Tensor Magnetic Resonance Imaging across cohorts of subjects. Most studies focus on the comparison of scalar images such as fractional anisotropy or mean diffusivity. Although different statistical frameworks have been proposed to compare the whole diffusion tensor information, they are still seldom used in neuroimaging studies. In this paper, we investigate on both simulated and real data whether there is a real added value of considering the whole tensor information for conducting voxel-based group studies. Then, we compare two statistical tests dedicated to tensor, namely the Cramér test and a tensor-based extension of the General Linear Model (GLM), the latter presenting the advantage to account for covariates. We also evaluate the impact of different metrics (Euclidean, Log-Euclidean and affine-invariant Riemannian metrics) for estimating the GLM parameters. Finally, we address the problem of interpreting the change detection maps obtained by tensor-based methods by proposing a way to characterize each of the detected clusters according to several scalar indices. Our study suggests that if there is no prior assumption about the nature of the expected changes, it is really preferable to use tensor-based rather than scalar-based statistical analysis. The Cramér test can advantageously be used when no confounding variable hampers the group comparison, otherwise the GLM should be considered. Finally, the different metrics show similar performance in the real scenario, with a significant computational overhead for the Riemannian framework.

Ischaemic strokes with reversible vasoconstriction and without thunderclap headache: a variant of the reversible cerebral vasoconstriction syndrome?

BACKGROUND: Reversible vasoconstriction (RV) may cause ischaemic stroke (IS) in the absence of any other defined stroke aetiology. The three objectives of our study were to evaluate the frequency of RV in a prospective series of young IS patients, to describe the detailed clinical-radiological features in the patients with RV and IS, and to compare these characteristics with those of reversible cerebral vasoconstriction syndrome (RCVS). METHODS: We identified between October 2005 and December 2010, 159 consecutive young patients (<45 years) hospitalized for an acute IS confirmed by cerebral magnetic resonance imaging. An extensive diagnostic work-up was performed including toxicological urinary screening for cannabis, cocaine and amphetamines, and the usual biological, cardiac and vascular investigations for an IS in the young. We specifically studied patients with IS and RV, which was defined as multifocal intracranial arterial stenoses confirmed by intracranial arterial imaging that resolved within 3-6 months. RESULTS: Out of 159 patients with IS, 21 (13%, 12 males, 9 females; mean age 32 years) had multifocal cerebral arterial stenoses that were fully reversible at 3-6 months, and no other cause for stroke. IS were located on posterior territory in 71% of cases, and vasoconstriction predominated on posterior cerebral and superior cerebellar arteries. Precipitating factors of IS and RV were the use of cannabis resin (n = 14), nasal decongestants (n = 2) and triptan (n = 1). Most cases (74%) had unusual severe headache, but none had thunderclap headache. None of 21 cases had reversible posterior leukoencephalopathy, cortical subarachnoid or intracerebral haemorrhage. CONCLUSION: RV was the sole identified cause of IS in 13% of our cohort. These young patients with IS and RV may have a variant of RCVS, related to an increased susceptibility to vasoactive agents in some individuals. RV in our patients differs from the classical characteristics of RCVS by the absence of thunderclap headache, reversible brain oedema and subarachnoid or intracranial haemorrhage. Intracranial arteries should be looked for, by appropriate vascular imaging, in young patients with IS at the acute stage and during the follow-up period.

High frequency of intracranial arterial stenosis and cannabis use in ischaemic stroke in the young.

BACKGROUND: Leading aetiologies of ischaemic stroke in young adults are cervico-cerebral arterial dissections and cardio-embolism, but the causes remain undetermined in a considerable proportion of cases. In a few reports, intracranial arterial stenosis has been suggested to be a potential cause of ischaemic stroke in young adults. The aim of our work was to evaluate the frequency, characteristics and risk factors of intracranial arterial stenosis in a prospective series of young ischaemic stroke patients. METHODS: The study was based on a prospective consecutive hospital-based series of 159 patients aged 18-45 years who were admitted to our unit for an acute ischaemic stroke from October 2005 to December 2010. A structured questionnaire was used in order to assess common vascular risk factors such as hypertension, diabetes, hypercholesterolemia, use of tobacco, alcohol and illicit drugs, migraine, and, in women, oral contraceptive use. A systematic screening was performed, including the following: brain magnetic resonance imaging or, if not feasible, brain computed tomography scan, carotid and vertebral Duplex scanning and trans-cranial Doppler sonography, 3D time-of-flight magnetic resonance cerebral angiography or cerebral computed tomography angiography. Long-duration electrocardiography, trans-thoracic and trans-oesophageal echocardiography were performed and laboratory blood investigations were extensive. Urine samples were screened for cannabinoids, cocaine, amphetamine and methylene-dioxy-methamphetamine. When this initial work-up was inconclusive, trans-femoral intra-arterial selective digital subtraction angiography with reconstructed 3D images was performed. RESULTS: In this series, 49 patients (31%) had intracranial arterial stenosis. Other defined causes were found in 91 patients (57%), including cardio-embolism in 32 (20%), cervical dissection in 23 (14%), extracranial atherosclerosis in 7 (4%), haematological disorders in 7 (4%), small vessel disease in 1, and isolated patent foramen ovale in 21 (13%); in 19 patients (12%), ischaemic stroke was related to an undetermined aetiology. Comparing risk factors between patients with intracranial arterial stenosis and those with other definite causes showed that there were only two significant differences: a lower age and a higher frequency of vasoactive substances (especially cannabis) in patients with intracranial arterial stenosis. All intracranial arterial stenosis in patients who used vasoactive substances were located in several intracranial vessels. CONCLUSIONS: Intracranial arterial stenosis may be an important mechanism of stroke in young patients and it should be systematically investigated using vascular imaging. Strong questioning about illicit drug consumption (including cannabis) or vasoactive medication use should also be performed. It should be emphasized for health prevention in young adults that cannabis use might be associated with critical consequences such as stroke.

Longitudinal change detection in diffusion MRI using multivariate statistical testing on tensors.

This paper presents a longitudinal change detection framework for detecting relevant modifications in diffusion MRI, with application to neuromyelitis optica (NMO) and multiple sclerosis (MS). The core problem is to identify image regions that are significantly different between two scans. The proposed method is based on multivariate statistical testing which was initially introduced for tensor population comparison. We use this method in the context of longitudinal change detection by considering several strategies to build sets of tensors characterizing the variability of each voxel. These strategies make use of the variability existing in the diffusion weighted images (thanks to a bootstrap procedure), or in the spatial neighborhood of the considered voxel, or a combination of both. Results on synthetic evolutions and on real data are presented. Interestingly, experiments on NMO patients highlight the ability of the proposed approach to detect changes in the normal-appearing white matter (according to conventional MRI) that are related with physical status outcome. Experiments on MS patients highlight the ability of the proposed approach to detect changes in evolving and non-evolving lesions (according to conventional MRI). These findings might open promising prospects for the follow-up of NMO and MS pathologies.

SPECT assessment of brain activation induced by caffeine: no effect on areas involved in dependence.

Caffeine is not considered addictive, and in animals it does not trigger metabolic increases or dopamine release in brain areas involved in reinforcement and reward. Our objective was to measure caffeine effects on cerebral perfusion in humans using single photon emission computed tomography with a specific focus on areas of reinforcement and reward. Two groups of nonsmoking subjects were studied, one with a low (8 subjects) and one with a high (6 subjects) daily coffee consumption. The subjects ingested 3 mg/kg caffeine or placebo in a raspberry-tasting drink, and scans were performed 45 min after ingestion. A control group of 12 healthy volunteers receiving no drink was also studied. Caffeine consumption led to a generalized, statistically nonsignificant perfusion decrease of 6% to 8%, comparable in low and high consumers. Compared with controls, low consumers displayed neuronal activation bilaterally in inferior frontal gyrus-anterior insular cortex and uncus, left internal parietal cortex, right lingual gyrus, and cerebellum. In high consumers, brain activation occurred bilaterally only in hypothalamus. Thus, on a background of widespread low-amplitude perfusion decrease, caffeine activates a few regions mainly involved in the control of vigilance, anxiety, and cardiovascular regulation, but does not affect areas involved in reinforcing and reward.

A mouse model of MSU-induced acute inflammation in vivo suggests imiquimod-dependent targeting of Il-1ß as relevant therapy for gout patients.

Rationale: The role of Monosodium Urate (MSU) crystals in gout pathophysiology is well described, as is the major impact of IL-1ß in the inflammatory reaction that constitutes the hallmark of the disease. However, despite the discovery of the NLRP3 inflammasome and its role as a Pattern Recognition Receptor linking the detection of a danger signal (MSU) to IL-1ß secretion in vitro, the precise mechanisms leading to joint inflammation in gout patients are still poorly understood. Methods: Acute urate crystal inflammation was obtained by subcutaneous injections of MSU crystals in mice. Symptoms were followed by scoring, cytokine quantification by ELISA and western blot, gene expression by RT-qPCR and RNAseq; Magnetic Resonance Imaging was also used to assess inflammation. Results: We provide an extensive clinical, biological and molecular characterization of an acute uratic inflammation mouse model which accurately mimics human gout. We report the efficacy of topical imiquimod treatment and its impact on Interferon-dependent down modulation of Il-1ß gene expression in this experimental model. Conclusion: Our work reveals several key features of MSU-dependent inflammation and identifies novel therapeutic opportunities for gout patients.

Accurate inversion of 3-D transformation fields.

This correspondence addresses the inversion of 3-D transformation fields, which is a problem that typically arises in image warping problems. A topology preserving parametric B-spline-based representation of the deformation field is considered. Topology preservation ensures that the transformation is a one-to-one mapping and consequently that it is invertible. Inverting such transformation fields amounts to solving a system of nonlinear equations. To tackle this problem, we rely on interval analysis techniques. The proposed algorithm yields a solution whose accuracy is user-controlled. This method may be extended to any dense transformation field and also to deformations defined on a grid of points, by considering a projection in the space of topology preserving B-spline-based deformation fields. The performance of the algorithm is illustrated on transformation fields coming from intersubject brain registration.

Brain perfusion in dementia with Lewy bodies and Alzheimer's disease: an arterial spin labeling MRI study on prodromal and mild dementia stages.

BACKGROUND: We aimed to describe specific changes in brain perfusion in patients with dementia with Lewy bodies (DLB) at both the prodromal (also called mild cognitive impairment) and mild dementia stages, relative to patients with Alzheimer's disease (AD) and controls. METHODS: Altogether, 96 participants in five groups (prodromal DLB, prodromal AD, DLB with mild dementia, AD with mild dementia, and healthy elderly controls) took part in an arterial spin labeling MRI study. Three analyses were performed: a global perfusion value comparison, a voxel-wise analysis of both absolute and relative perfusion, and a linear discriminant analysis. These were used to assess the global decrease in perfusion, regional changes, and the sensitivity and specificity of these changes. RESULTS: Patterns of perfusion in DLB differed from AD and controls in both the prodromal stage and dementia, DLB having more deficits in frontal, insular, and temporal cortices whereas AD showed reduced perfusion in parietal and parietotemporal cortices. Decreases but also increases of perfusion in DLB relative to controls were observed in both absolute and relative measurements. All these regional changes of perfusion classified DLB patients with respect to either healthy controls or AD with sensitivity from 87 to 100 % and specificity from 90 to 96 % depending on the stage of the disease. CONCLUSIONS: Our results are consistent with previous studies. We extend the scope of those studies by integrating prodromal DLB patients and by describing both hypo- and hyperperfusion in DLB. While decreases in perfusion may relate to functional impairments, increases might suggest a functional compensation of some brain areas.

Identifying Dynamic Functional Connectivity Changes in Dementia with Lewy Bodies Based on Product Hidden Markov Models.

Exploring time-varying connectivity networks in neurodegenerative disorders is a recent field of research in functional MRI. Dementia with Lewy bodies (DLB) represents 20% of the neurodegenerative forms of dementia. Fluctuations of cognition and vigilance are the key symptoms of DLB. To date, no dynamic functional connectivity (DFC) investigations of this disorder have been performed. In this paper, we refer to the concept of connectivity state as a piecewise stationary configuration of functional connectivity between brain networks. From this concept, we propose a new method for group-level as well as for subject-level studies to compare and characterize connectivity state changes between a set of resting-state networks (RSNs). Dynamic Bayesian networks, statistical and graph theory-based models, enable one to learn dependencies between interacting state-based processes. Product hidden Markov models (PHMM), an instance of dynamic Bayesian networks, are introduced here to capture both statistical and temporal aspects of DFC of a set of RSNs. This analysis was based on sliding-window cross-correlations between seven RSNs extracted from a group independent component analysis performed on 20 healthy elderly subjects and 16 patients with DLB. Statistical models of DFC differed in patients compared to healthy subjects for the occipito-parieto-frontal network, the medial occipital network and the right fronto-parietal network. In addition, pairwise comparisons of DFC of RSNs revealed a decrease of dependency between these two visual networks (occipito-parieto-frontal and medial occipital networks) and the right fronto-parietal control network. The analysis of DFC state changes thus pointed out networks related to the cognitive functions that are known to be impaired in DLB: visual processing as well as attentional and executive functions. Besides this context, product HMM applied to RSNs cross-correlations offers a promising new approach to investigate structural and temporal aspects of brain DFC.

Cockayne syndrome: a diffusion tensor imaging and volumetric study.

OBJECTIVE: Cockayne syndrome (CS) is a rare disorder characterized by severe brain atrophy, white matter (WM) hypomyelination and basal ganglia calcifications. This study aimed to quantify atrophy and WM abnormalities using diffusion tensor imaging (DTI) and volumetric analysis, to evaluate possible differences between CS subtypes and to determine whether DTI findings may correspond to a hypomyelinating disorder. METHODS: 14 patients with CS and 14 controls underwent brain MRI including DTI and a volumetric three-dimensional T1 weighted sequence. DTI analysis was made through regions of interest within the whole brain to obtain fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values and in the left centrum semiovale to obtain DTI eigenvalues. The Student's t-test was used to compare patients and controls, and CS subtypes. Given the small number of patients with CS, they were pooled into two groups: moderate (CS1/CS3) and severe (CS2/cerebro-oculo-facio-skeletal syndrome). RESULTS: Total brain volume in CS was reduced by 57%, predominantly in the infratentorial area (68%) (p < 0.001). Total brain volume reduction was greater in the severe group, but there was no difference in the degree of infratentorial atrophy in the two groups (p = 0.7). Mean FA values were lower, whereas ADC was higher in most of the WM in patients with CS (p < 0.05). ADC in the splenium of the corpus callosum and the posterior limb of the internal capsule and FA in the cerebral peduncles were significantly different between the two groups (p < 0.05). Mean ADC values corresponded to a hypomyelinating disorder. All DTI eigenvalues were higher in patients with CS, mainly for transverse diffusivity (+51%) (p < 0.001). CONCLUSION: DTI and volumetric analysis provide quantitative information for the characterization of CS and may be particularly useful for evaluating therapeutic intervention. Advances in knowledge: DTI combined with volumetric analysis provides additional information useful for not only the characterization of CS and distinction of clinical subtypes but also monitoring of therapeutic interventions.

Cognitive and affective theory of mind in dementia with Lewy bodies and Alzheimer's disease.

BACKGROUND: Theory of mind (ToM) refers to the ability to attribute mental states, thoughts (cognitive component) or feelings (affective component) to others. This function has been studied in many neurodegenerative diseases; however, to our knowledge, no studies investigating ToM in dementia with Lewy bodies (DLB) have been published. The aim of our study was to assess ToM in patients with DLB and to search for neural correlates of potential deficits. METHODS: Thirty-three patients with DLB (DLB group) and 15 patients with Alzheimer's disease (AD group), all in the early stage of the disease, as well as 16 healthy elderly control subjects (HC group), were included in the study. After a global cognitive assessment, we used the Faux Pas Recognition (FPR) test, the Reading the Mind in the Eyes (RME) test and Ekman's Facial Emotion Recognition test to assess cognitive and affective components of ToM. Patients underwent cerebral 3-T magnetic resonance imaging, and atrophy of grey matter was analysed using voxel-based morphometry. We performed a one-sample t test to investigate the correlation between each ToM score and grey matter volume and a two-sample t test to compare patients with DLB impaired with those non-impaired for each test. RESULTS: The DLB group performed significantly worse than the HC group on the FPR test (P = 0.033) and the RME test (P = 0.015). There was no significant difference between the AD group and the HC group or between the DLB group and the AD group. Some brain regions were associated with ToM impairments. The prefrontal cortex, with the inferior frontal cortex and the orbitofrontal cortex, was the main region, but we also found correlations with the temporoparietal junction, the precuneus, the fusiform gyrus and the insula. CONCLUSIONS: This study is the first one to show early impairments of ToM in DLB. The two cognitive and affective components both appear to be affected in this disease. Among patients with ToM difficulties, we found atrophy in brain regions classically involved in ToM, which reinforces the neuronal network of ToM. Further studies are now needed to better understand the neural basis of such impairment.

Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models.

In this paper, a novel functional magnetic resonance imaging (fMRI) brain mapping method is presented within the statistical modeling framework of hidden semi-Markov event sequence models (HSMESMs). Neural activation detection is formulated at the voxel level in terms of time coupling between the sequence of hemodynamic response onsets (HROs) observed in the fMRI signal, and an HSMESM of the hidden sequence of task-induced neural activations. The sequence of HRO events is derived from a continuous wavelet transform (CWT) of the fMRI signal. The brain activation HSMESM is built from the timing information of the input stimulation protocol. The rich mathematical framework of HSMESMs makes these models an effective and versatile approach for fMRI data analysis. Solving for the HSMESM Evaluation and Learning problems enables the model to automatically detect neural activation embedded in a given set of fMRI signals, without requiring any template basis function or prior shape assumption for the fMRI response. Solving for the HSMESM Decoding problem allows to enrich brain mapping with activation lag mapping, activation mode visualizing, and hemodynamic response function analysis. Activation detection results obtained on synthetic and real epoch-related fMRI data demonstrate the superiority of the HSMESM mapping method with respect to a real application case of the statistical parametric mapping (SPM) approach. In addition, the HSMESM mapping method appears clearly insensitive to timing variations of the hemodynamic response, and exhibits low sensitivity to fluctuations of its shape.

Hidden Markov event sequence models: toward unsupervised functional MRI brain mapping.

RATIONALE AND OBJECTIVES: Most methods used in functional MRI (fMRI) brain mapping require restrictive assumptions about the shape and timing of the fMRI signal in activated voxels. Consequently, fMRI data may be partially and misleadingly characterized, leading to suboptimal or invalid inference. To limit these assumptions and to capture the broad range of possible activation patterns, a novel statistical fMRI brain mapping method is proposed. It relies on hidden semi-Markov event sequence models (HSMESMs), a special class of hidden Markov models (HMMs) dedicated to the modeling and analysis of event-based random processes. MATERIALS AND METHODS: Activation detection is formulated in terms of time coupling between (1) the observed sequence of hemodynamic response onset (HRO) events detected in the voxel's fMRI signal and (2) the "hidden" sequence of task-induced neural activation onset (NAO) events underlying the HROs. Both event sequences are modeled within a single HSMESM. The resulting brain activation model is trained to automatically detect neural activity embedded in the input fMRI data set under analysis. The data sets considered in this article are threefold: synthetic epoch-related, real epoch-related (auditory lexical processing task), and real event-related (oddball detection task) fMRI data sets. RESULTS: Synthetic data: Activation detection results demonstrate the superiority of the HSMESM mapping method with respect to a standard implementation of the statistical parametric mapping (SPM) approach. They are also very close, sometimes equivalent, to those obtained with an "ideal" implementation of SPM in which the activation patterns synthesized are reused for analysis. The HSMESM method appears clearly insensitive to timing variations of the hemodynamic response and exhibits low sensitivity to fluctuations of its shape (unsustained activation during task). Real epoch-related data: HSMESM activation detection results compete with those obtained with SPM, without requiring any prior definition of the expected activation patterns thanks to the unsupervised character of the HSMESM mapping approach. Along with activation maps, the method offers a wide range of additional fMRI analysis functionalities, including activation lag mapping, activation mode visualization, and hemodynamic response function analysis. Real event-related data: Activation detection results confirm and validate the overall strategy that consists in focusing the analysis on the transients, time-localized events that are the HROs. CONCLUSION: All the experiments performed on synthetic and real fMRI data demonstrate the relevance of HSMESMs in fMRI brain mapping. In particular, the statistical character of these models, along with their learning and generalizing abilities are of particular interest when dealing with strong variabilities of the active fMRI signal across time, space, experiments, and subjects.

3-D deformable image registration: a topology preservation scheme based on hierarchical deformation models and interval analysis optimization.

This paper deals with topology preservation in three-dimensional (3-D) deformable image registration. This work is a nontrivial extension of, which addresses the case of two-dimensional (2-D) topology preserving mappings. In both cases, the deformation map is modeled as a hierarchical displacement field, decomposed on a multiresolution B-spline basis. Topology preservation is enforced by controlling the Jacobian of the transformation. Finding the optimal displacement parameters amounts to solving a constrained optimization problem: The residual energy between the target image and the deformed source image is minimized under constraints on the Jacobian. Unlike the 2-D case, in which simple linear constraints are derived, the 3-D B-spline-based deformable mapping yields a difficult (until now, unsolved) optimization problem. In this paper, we tackle the problem by resorting to interval analysis optimization techniques. Care is taken to keep the computational burden as low as possible. Results on multipatient 3-D MRI registration illustrate the ability of the method to preserve topology on the continuous image domain.