Brain Gray Matter MRI Morphometry for Neuroprognostication After Cardiac Arrest.

OBJECTIVES: We hypothesize that the combined use of MRI cortical thickness measurement and subcortical gray matter volumetry could provide an early and accurate in vivo assessment of the structural impact of cardiac arrest and therefore could be used for long-term neuroprognostication in this setting. DESIGN: Prospective cohort study. SETTING: Five Intensive Critical Care Units affiliated to the University in Toulouse (France), Paris (France), Clermont-Ferrand (France), Liège (Belgium), and Monza (Italy). PATIENTS: High-resolution anatomical T1-weighted images were acquired in 126 anoxic coma patients ("learning" sample) 16 ± 8 days after cardiac arrest and 70 matched controls. An additional sample of 18 anoxic coma patients, recruited in Toulouse, was used to test predictive model generalization ("test" sample). All patients were followed up 1 year after cardiac arrest. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Cortical thickness was computed on the whole cortical ribbon, and deep gray matter volumetry was performed after automatic segmentation. Brain morphometric data were employed to create multivariate predictive models using learning machine techniques. Patients displayed significantly extensive cortical and subcortical brain volumes atrophy compared with controls. The accuracy of a predictive classifier, encompassing cortical and subcortical components, has a significant discriminative power (learning area under the curve = 0.87; test area under the curve = 0.96). The anatomical regions which volume changes were significantly related to patient's outcome were frontal cortex, posterior cingulate cortex, thalamus, putamen, pallidum, caudate, hippocampus, and brain stem. CONCLUSIONS: These findings are consistent with the hypothesis of pathologic disruption of a striatopallidal-thalamo-cortical mesocircuit induced by cardiac arrest and pave the way for the use of combined brain quantitative morphometry in this setting.

Validation of a model of itch induction for brain positron emission tomography studies using histamine iontophoresis.

Skin-brain signalling in itch reactions has been demonstrated with neuroimaging techniques showing specific brain activation. With positron emission tomography (PET), the itch model used must be adapted to technical and practical constraints. The technique of itch induction by histamine iontophoresis enables modulation of the sensation via the electrical charge applied. This itch model was validated on normal forearm skin of 56 subjects, with itch visual analogue scores peaking to approximately 1.0 cm after 3-4 min, falling to 0.2 cm at 15 min, with no influence of sex, zone, or order. Subsequently, the model was used in a PET study on 14 male volunteers, comparing histamine with physiological saline (control). The results show that the brain is able to discriminate these two conditions, with activated areas similar to those described previously, with, in addition, the anterior cingulate cortex and the insula being positively correlated with the intensity of the sensation.

Testing for the dual-route cascade reading model in the brain: an fMRI effective connectivity account of an efficient reading style.

Neuropsychological data about the forms of acquired reading impairment provide a strong basis for the theoretical framework of the dual-route cascade (DRC) model which is predictive of reading performance. However, lesions are often extensive and heterogeneous, thus making it difficult to establish precise functional anatomical correlates. Here, we provide a connective neural account in the aim of accommodating the main principles of the DRC framework and to make predictions on reading skill. We located prominent reading areas using fMRI and applied structural equation modeling to pinpoint distinct neural pathways. Functionality of regions together with neural network dissociations between words and pseudowords corroborate the existing neuroanatomical view on the DRC and provide a novel outlook on the sub-regions involved. In a similar vein, congruent (or incongruent) reliance of pathways, that is reliance on the word (or pseudoword) pathway during word reading and on the pseudoword (or word) pathway during pseudoword reading predicted good (or poor) reading performance as assessed by out-of-magnet reading tests. Finally, inter-individual analysis unraveled an efficient reading style mirroring pathway reliance as a function of the fingerprint of the stimulus to be read, suggesting an optimal pattern of cerebral information trafficking which leads to high reading performance.

Early diagnosis of Alzheimer's disease using cortical thickness: impact of cognitive reserve.

Brain atrophy measured by magnetic resonance structural imaging has been proposed as a surrogate marker for the early diagnosis of Alzheimer's disease. Studies on large samples are still required to determine its practical interest at the individual level, especially with regards to the capacity of anatomical magnetic resonance imaging to disentangle the confounding role of the cognitive reserve in the early diagnosis of Alzheimer's disease. One hundred and thirty healthy controls, 122 subjects with mild cognitive impairment of the amnestic type and 130 Alzheimer's disease patients were included from the ADNI database and followed up for 24 months. After 24 months, 72 amnestic mild cognitive impairment had converted to Alzheimer's disease (referred to as progressive mild cognitive impairment, as opposed to stable mild cognitive impairment). For each subject, cortical thickness was measured on the baseline magnetic resonance imaging volume. The resulting cortical thickness map was parcellated into 22 regions and a normalized thickness index was computed using the subset of regions (right medial temporal, left lateral temporal, right posterior cingulate) that optimally distinguished stable mild cognitive impairment from progressive mild cognitive impairment. We tested the ability of baseline normalized thickness index to predict evolution from amnestic mild cognitive impairment to Alzheimer's disease and compared it to the predictive values of the main cognitive scores at baseline. In addition, we studied the relationship between the normalized thickness index, the education level and the timeline of conversion to Alzheimer's disease. Normalized thickness index at baseline differed significantly among all the four diagnosis groups (P < 0.001) and correctly distinguished Alzheimer's disease patients from healthy controls with an 85% cross-validated accuracy. Normalized thickness index also correctly predicted evolution to Alzheimer's disease for 76% of amnestic mild cognitive impairment subjects after cross-validation, thus showing an advantage over cognitive scores (range 63-72%). Moreover, progressive mild cognitive impairment subjects, who converted later than 1 year after baseline, showed a significantly higher education level than those who converted earlier than 1 year after baseline. Using a normalized thickness index-based criterion may help with early diagnosis of Alzheimer's disease at the individual level, especially for highly educated subjects, up to 24 months before clinical criteria for Alzheimer's disease diagnosis are met.

Piecemeal recruitment of left-lateralized brain areas during reading: a spatio-functional account.

Neuroimaging studies of reading converge to suggest that linguistically elementary stimuli are confined to the activation of bilateral posterior regions, whereas linguistically complex stimuli additionally recruit left hemispheric anterior regions, raising the hypotheses of a gradual bilateral-to-left and a posterior-to-anterior recruitment of reading related areas. Here, we tested these two hypotheses by contrasting a repertoire of eight categories of stimuli ranging from simple orthographic-like characters to words and pseudowords in a single experiment, and by measuring BOLD signal changes and connectivity while 16 fluent readers passively viewed the stimuli. Our results confirm the existence of a bilateral-to-left and posterior-to-anterior recruitment of reading related areas, straightforwardly resulting from the increase in stimuli's linguistic processing load, which reflects reading processes: visual analysis, orthographic encoding and phonological decoding. Connectivity analyses strengthened the validity of these observations and additionally revealed an enhancement of the left parieto-frontal information trafficking for higher linguistic processing. Our findings clearly establish the notion of a gradual spatio-functional recruitment of reading areas and demonstrate, to the best of our knowledge, the first evidence of a robust and staged link between the level of linguistic processing, the spatial distribution of brain activity and its information trafficking.

Cortical imaging on a head template: a simulation study using a resistor mesh model (RMM).

The T1 head template model used in Statistical Parametric Mapping Version 2000 (SPM2), was segmented into five layers (scalp, skull, CSF, grey and white matter) and implemented in 2 mm voxels. We designed a resistor mesh model (RMM), based on the finite volume method (FVM) to simulate the electrical properties of this head model along the three axes for each voxel. Then, we introduced four dipoles of high eccentricity (about 0.8) in this RMM, separately and simultaneously, to compute the potentials for two sets of conductivities. We used the direct cortical imaging technique (CIT) to recover the simulated dipoles, using 60 or 107 electrodes and with or without addition of Gaussian white noise (GWN). The use of realistic conductivities gave better CIT results than standard conductivities, lowering the blurring effect on scalp potentials and displaying more accurate position areas when CIT was applied to single dipoles. Simultaneous dipoles were less accurately localized, but good qualitative and stable quantitative results were obtained up to 5% noise level for 107 electrodes and up to 10% noise level for 60 electrodes, showing that a compromise must be found to optimize both the number of electrodes and the noise level. With the RMM defined in 2 mm voxels, the standard 128-electrode cap and 5% noise appears to be the upper limit providing reliable source positions when direct CIT is used. The admittance matrix defining the RMM is easy to modify so as to adapt to different conductivities. The next step will be the adaptation of individual real head T2 images to the RMM template and the introduction of anisotropy using diffusion imaging (DI).

Stimulus complexity and prospective timing: clues for a parallel process model of time perception.

Whereas many studies have considered the role of attention in prospective timing, fewer have established relations between movement complexity and prospective timing. The present study aims at assessing to what extent motion complexity interferes with prospective timing and at delineating a neuropsychophysical plausible model. We have thus designed a visual paradigm presenting stimuli in sequential pairs (reference comparison interval). Stimuli are motionless or moving according to different complexities, and stimulus complexities are intermixed within each pair. To prevent a possible attention-sharing effect, no concurrent task was required. Our study suggests that movement complexity is a key component of duration perception, and that the relative judgement of durations depends on spatio-temporal features of stimuli. In particular, it shows that movement complexity can bias subjects' perception and performance, and that subjects detect that comparison intervals are longer than reference before their end. In the discussion, we advocate that the classical internal clock model cannot easily account for our results. Consequently, we propose a model for time perception, based on a parallel processing between comparison interval perception and the reconstruction of the reference duration.