Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.

Where sound position influences sound object representations: a 7-T fMRI study.

Evidence from human and non-human primate studies supports a dual-pathway model of audition, with partially segregated cortical networks for sound recognition and sound localisation, referred to as the What and Where processing streams. In normal subjects, these two networks overlap partially on the supra-temporal plane, suggesting that some early-stage auditory areas are involved in processing of either auditory feature alone or of both. Using high-resolution 7-T fMRI we have investigated the influence of positional information on sound object representations by comparing activation patterns to environmental sounds lateralised to the right or left ear. While unilaterally presented sounds induced bilateral activation, small clusters in specific non-primary auditory areas were significantly more activated by contra-laterally presented stimuli. Comparison of these data with histologically identified non-primary auditory areas suggests that the coding of sound objects within early-stage auditory areas lateral and posterior to primary auditory cortex AI is modulated by the position of the sound, while that within anterior areas is not.

Single Subject Finger Somatotopy Mapping at 7T.

Introduction: The primary somatosensory cortex (SI) contains Brodmann areas (BA) 1, 2, 3a, and 3b. Research in non-human primates showed that BAs 3b, 1, and 2 each contain one full representation of the hand with separate representations for each finger. This research also showed that the finger representation in BA3b has larger and clearer finger somatotopy than BA1 and 2. Although several efforts to map finger somatotopy in SI by fMRI have been made at 1.5 and 3T these studies have yielded variable results and were not able to detect single subject finger somatotopy, probably due to the limited spatial extent of the cortical areas representing a digit (close to the resolution in most fMRI experiments), complications due to acquisition of consistent maps for individual subjects (Schweizer et al 2008), or inter-individual variability in sulcal anatomy impeding group studies. Here, we used 7T fMRI to investigate finger somatotopy in SI, some of its functional characteristics, and its reproducibility. Methods: Eight right-handed male subjects were scanned on a 7T scanner (Siemens Medical, Germany) with an 8-channel Tx/Rx rf-coil (Rapid Biomedical, Germany). 1.3x1.3x1.3mm3 resolution fMRI data were acquired using a sinusoidal readout EPI sequence (Speck et al, 2008) and FOV=210mm, TE/TR=27ms/2.5s, GRAPPA=2. Each volume contained 28 transverse slices covering SI. A single EPI volume with 64 slices was acquired to aid coregistration. 1x1x1mm3 anatomical data were acquire using the MP2RAGE sequence (Marques et al, 2009; TE/TR/TI1,2/TRmprage=2.63ms/7.2ms/0.9,3.2s/5s). Subjects were positioned supine in the scanner with their right arm comfortably against the magnet bore. An experimenter was positioned at the entrance of the bore where he could easily reach and stroke successively the two distal phalanxes of each digit. The order of stroked digit was D1 (thumb)-D3-D5-D2-D4, with 20s ON, 10s OFF alternated. This sequence was repeated four times per run and two functional runs were acquired per subject. Realignment, smoothing (FWHM 2 mm), coregistration of the anatomical to the fMRI data and calculation of t-statistics were done using SPM8. An SI mask was obtained via an F-contrast (p<0.001) over all digits. Within the mask, voxels were labeled with the number of the digit demonstrating the highest t-value for that particular voxel. Results: For all subjects, areas corresponding to the five digits were identified in contralateral SI. BA3b showed the most consistent somatotopic finger representation (see an example in Fig.1). The five digits were localized in a consecutive order in the cortex, with D1 most anterior, inferior and distal and D5, most posterior, superior and medial (mean distance between centres of mass of digit representations ±stderr: 4.2±0.7mm; see Fig. 2). The analysis of average beta values within each finger representation region revealed the specificity of the somatotopic region to the tactile input for each tested finger (except digit 4 and 5). Five of these subjects also presented an orderly and consecutive representation of the five digits in BA1 and 2. Conclusions: Our data reveal that the increased BOLD sensitivity at 7T and the high spatial resolution used in this study allow consistent somatotopic mapping using human touch as a stimulus and that human SI contains at least three separate regions that contain five separate representations of all single contralateral fingers. Moreover, adjacent fingers were represented at adjacent cortical regions across the three SI regions. The spatial organization of SI as reflected in individual subject topography corresponds well with previous electrophysiological data in non-human primates. The small distance between digit representations highlights the need for the high spatial resolution available at 7T.

Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ).

Normal ageing is associated with characteristic changes in brain microstructure. Although in vivo neuroimaging captures spatial and temporal patterns of age-related changes of anatomy at the macroscopic scale, our knowledge of the underlying (patho)physiological processes at cellular and molecular levels is still limited. The aim of this study is to explore brain tissue properties in normal ageing using quantitative magnetic resonance imaging (MRI) alongside conventional morphological assessment. Using a whole-brain approach in a cohort of 26 adults, aged 18-85years, we performed voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) of diffusion tensor, magnetization transfer (MT), R1, and R2* relaxation parameters. We found age-related reductions in cortical and subcortical grey matter volume paralleled by changes in fractional anisotropy (FA), mean diffusivity (MD), MT and R2*. The latter were regionally specific depending on their differential sensitivity to microscopic tissue properties. VBQ of white matter revealed distinct anatomical patterns of age-related change in microstructure. Widespread and profound reduction in MT contrasted with local FA decreases paralleled by MD increases. R1 reductions and R2* increases were observed to a smaller extent in overlapping occipito-parietal white matter regions. We interpret our findings, based on current biophysical models, as a fingerprint of age-dependent brain atrophy and underlying microstructural changes in myelin, iron deposits and water. The VBQ approach we present allows for systematic unbiased exploration of the interaction between imaging parameters and extends current methods for detection of neurodegenerative processes in the brain. The demonstrated parameter-specific distribution patterns offer insights into age-related brain structure changes in vivo and provide essential baseline data for studying disease against a background of healthy ageing.

Regional reproducibility of calibrated BOLD functional MRI: implications for the study of cognition and plasticity.

Calibrated BOLD fMRI is a promising alternative to the classic BOLD contrast due to its reduced venous sensitivity and greater physiological specificity. The delayed adoption of this technique for cognitive studies may stem partly from a lack of information on the reproducibility of these measures in the context of cognitive tasks. In this study we have explored the applicability and reproducibility of a state-of-the-art calibrated BOLD technique using a complex functional task at 7 tesla. Reproducibility measures of BOLD, CBF, CMRO2 flow-metabolism coupling n and the calibration parameter M were compared and interpreted for three ROIs. We found an averaged intra-subject variation of CMRO2 of 8% across runs and 33% across days. BOLD (46% across runs, 36% across days), CBF (33% across runs, 46% across days) and M (41% across days) showed significantly higher intra-subject variability. Inter-subject variability was found to be high for all quantities, though CMRO2 was the most consistent across brain regions. The results of this study provide evidence that calibrated BOLD may be a viable alternative for longitudinal and cognitive MRI studies.

Disentangling in vivo the effects of iron content and atrophy on the ageing human brain.

Evidence from magnetic resonance imaging (MRI) studies shows that healthy aging is associated with profound changes in cortical and subcortical brain structures. The reliable delineation of cortex and basal ganglia using automated computational anatomy methods based on T1-weighted images remains challenging, which results in controversies in the literature. In this study we use quantitative MRI (qMRI) to gain an insight into the microstructural mechanisms underlying tissue ageing and look for potential interactions between ageing and brain tissue properties to assess their impact on automated tissue classification. To this end we acquired maps of longitudinal relaxation rate R1, effective transverse relaxation rate R2* and magnetization transfer - MT, from healthy subjects (n=96, aged 21-88 years) using a well-established multi-parameter mapping qMRI protocol. Within the framework of voxel-based quantification we find higher grey matter volume in basal ganglia, cerebellar dentate and prefrontal cortex when tissue classification is based on MT maps compared with T1 maps. These discrepancies between grey matter volume estimates can be attributed to R2* - a surrogate marker of iron concentration, and further modulation by an interaction between R2* and age, both in cortical and subcortical areas. We interpret our findings as direct evidence for the impact of ageing-related brain tissue property changes on automated tissue classification of brain structures using SPM12. Computational anatomy studies of ageing and neurodegeneration should acknowledge these effects, particularly when inferring about underlying pathophysiology from regional cortex and basal ganglia volume changes.

Towards a resolution of conflicting models of illusory contour processing in humans.

Despite myriad studies, neurophysiologic mechanisms mediating illusory contour (IC) sensitivity remain controversial. Among the competing models one favors feed-forward effects within lower-tier cortices (V1/V2). Another situates IC sensitivity first within higher-tier cortices, principally lateral-occipital cortices (LOC), with later feedback effects in V1/V2. Still others postulate that LOC are sensitive to salient regions demarcated by the inducing stimuli, whereas V1/V2 effects specifically support IC sensitivity. We resolved these discordances by using misaligned line gratings, oriented either horizontally or vertically, to induce ICs. Line orientation provides an established assay of V1/V2 modulations independently of IC presence, and gratings lack salient regions. Electrical neuroimaging analyses of visual evoked potentials (VEPs) disambiguated the relative timing and localization of IC sensitivity with respect to that for grating orientation. Millisecond-by-millisecond analyses of VEPs and distributed source estimations revealed a main effect of grating orientation beginning at 65 ms post-stimulus onset within the calcarine sulcus that was followed by a main effect of IC presence beginning at 85 ms post-stimulus onset within the LOC. There was no evidence for differential processing of ICs as a function of the orientation of the grating. These results support models wherein IC sensitivity occurs first within the LOC.

Alpha-band suppression in the visual word form area as a functional bottleneck to consciousness.

The current state of empirical investigations refers to consciousness as an all-or-none phenomenon. However, a recent theoretical account opens up this perspective by proposing a partial level (between nil and full) of conscious perception. In the well-studied case of single-word reading, short-lived exposure can trigger incomplete word-form recognition wherein letters fall short of forming a whole word in one's conscious perception thereby hindering word-meaning access and report. Hence, the processing from incomplete to complete word-form recognition straightforwardly mirrors a transition from partial to full-blown consciousness. We therefore hypothesized that this putative functional bottleneck to consciousness (i.e. the perceptual boundary between partial and full conscious perception) would emerge at a major key hub region for word-form recognition during reading, namely the left occipito-temporal junction. We applied a real-time staircase procedure and titrated subjective reports at the threshold between partial (letters) and full (whole word) conscious perception. This experimental approach allowed us to collect trials with identical physical stimulation, yet reflecting distinct perceptual experience levels. Oscillatory brain activity was monitored with magnetoencephalography and revealed that the transition from partial-to-full word-form perception was accompanied by alpha-band (7-11 Hz) power suppression in the posterior left occipito-temporal cortex. This modulation of rhythmic activity extended anteriorly towards the visual word form area (VWFA), a region whose selectivity for word-forms in perception is highly debated. The current findings provide electrophysiological evidence for a functional bottleneck to consciousness thereby empirically instantiating a recently proposed partial perspective on consciousness. Moreover, the findings provide an entirely new outlook on the functioning of the VWFA as a late bottleneck to full-blown conscious word-form perception.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders.

Auditory perceptual decision-making based on semantic categorization of environmental sounds.

Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112ms) and on a separate period at ~270ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.

Characterization of sustained BOLD activation in the rat barrel cortex and neurochemical consequences.

To date, only a couple of functional MR spectroscopy (fMRS) studies were conducted in rats. Due to the low temporal resolution of (1)H MRS techniques, prolonged stimulation paradigms are necessary for investigating the metabolic outcome in the rat brain during functional challenge. However, sustained activation of cortical areas is usually difficult to obtain due to neural adaptation. Anesthesia, habituation, high variability of the basal state metabolite concentrations as well as low concentrations of the metabolites of interest such as lactate (Lac), glucose (Glc) or γ-aminobutyric acid (GABA) and small expected changes of metabolite concentrations need to be addressed. In the present study, the rat barrel cortex was reliably and reproducibly activated through sustained trigeminal nerve (TGN) stimulation. In addition, TGN stimulation induced significant positive changes in lactate (+1.01μmol/g, p<0.008) and glutamate (+0.92μmol/g, p<0.02) and significant negative aspartate changes (-0.63μmol/g, p<0.004) using functional (1)H MRS at 9.4T in agreement with previous changes observed in human fMRS studies. Finally, for the first time, the dynamics of lactate, glucose, aspartate and glutamate concentrations during sustained somatosensory activation in rats using fMRS were assessed. These results allow demonstrating the feasibility of fMRS measurements during prolonged barrel cortex activation in rats.

A multi-center study: intra-scan and inter-scan variability of diffusion spectrum imaging.

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Comparing connectomes across subjects and populations at different scales.

Brain connectivity can be represented by a network that enables the comparison of the different patterns of structural and functional connectivity among individuals. In the literature, two levels of statistical analysis have been considered in comparing brain connectivity across groups and subjects: 1) the global comparison where a single measure that summarizes the information of each brain is used in a statistical test; 2) the local analysis where a single test is performed either for each node/connection which implies a multiplicity correction, or for each group of nodes/connections where each subset is summarized by one single test in order to reduce the number of tests to avoid a penalizing multiplicity correction. We comment on the different levels of analysis and present some methods that have been proposed at each scale. We highlight as well the possible factors that could influence the statistical results and the questions that have to be addressed in such an analysis.

Using high-resolution quantitative mapping of R1 as an index of cortical myelination

A fundamental tenet of neuroscience is that cortical functional differentiation is related to the cross-areal differences in cyto-, receptor-, and myeloarchitectonics that are observed in ex-vivo preparations. An ongoing challenge is to create noninvasive magnetic resonance (MR) imaging techniques that offer sufficient resolution, tissue contrast, accuracy and precision to allow for characterization of cortical architecture over an entire living human brain. One exciting development is the advent of fast, high-resolution quantitative mapping of basic MR parameters that reflect cortical myeloarchitecture. Here, we outline some of the theoretical and technical advances underlying this technique, particularly in terms of measuring and correcting for transmit and receive radio frequency field inhomogeneities. We also discuss new directions in analytic techniques, including higher resolution reconstructions of the cortical surface. We then discuss two recent applications of this technique. The first compares individual and group myelin maps to functional retinotopic maps in the same individuals, demonstrating a close relationship between functionally and myeloarchitectonically defined areal boundaries (as well as revealing an interesting disparity in a highly studied visual area). The second combines tonotopic and myeloarchitectonic mapping to localize primary auditory areas in individual healthy adults, using a similar strategy as combined electrophysiological and post-mortem myeloarchitectonic studies in non-human primates.

In vivo assessment of use-dependent brain plasticity--beyond the "one trick pony" imaging strategy.

This article has been written as a comment to Dr Thomas and Dr Baker's article "Teaching an adult brain new tricks: A critical review of evidence for training-dependent structural plasticity in humans". We deliberately expand on the key question about the biological substrates underlying use-dependent brain plasticity rather than reiterating the authors' main points of criticism already addressed in more general way by previous publications in the field. The focus here is on the following main issues: i) controversial brain plasticity findings in voxel-based morphometry studies are partially due to the strong dependency of the widely used T1-weighted imaging protocol on varying magnetic resonance contrast contributions; ii) novel concepts in statistical analysis allow one to directly infer topological specificity of structural brain changes associated with plasticity. We conclude that iii) voxel-based quantification of relaxometry derived parameter maps could provide a new perspective on use-dependent plasticity by characterisation of brain tissue property changes beyond the estimation of volume and cortical thickness changes. In the relevant sections we respond to the concerns raised by Dr Thomas and Dr Baker from the perspective of the proposed data acquisition and analysis strategy.