Multimodal neuroimaging approach to variability of functional connectivity in disorders of consciousness: A PET/MRI pilot study

Behavioral assessments could not suffice to provide accurate diagnostic information in individuals with disorders of consciousness (DoC). Multimodal neuroimaging markers have been developed to support clinical assessments of these patients. Here we present findings obtained by hybrid fludeoxyglucose (FDG-)PET/MR imaging in three severely brain-injured patients, one in an unresponsive wakefulness syndrome (UWS), one in a minimally conscious state (MCS), and one patient emerged from MCS (EMCS). Repeated behavioral assessment by means of Coma Recovery Scale-Revised and neurophysiological evaluation were performed in the two weeks before and after neuroimaging acquisition, to ascertain that clinical diagnosis was stable. The three patients underwent one imaging session, during which two resting-state fMRI (rs-fMRI) blocks were run with a temporal gap of about 30 min. rs-fMRI data were analyzed with a graph theory approach applied to nine independent networks. We also analyzed the benefits of concatenating the two acquisitions for each patient or to select for each network the graph strength map with a higher ratio of fitness. Finally, as for clinical assessment, we considered the best functional connectivity pattern for each network and correlated graph strength maps to FDG uptake. Functional connectivity analysis showed several differences between the two rs-fMRI acquisitions, affecting in a different way each network and with a different variability for the three patients, as assessed by ratio of fitness. Moreover, combined PET/fMRI analysis demonstrated a higher functional/metabolic correlation for patients in EMCS and MCS compared to UWS. In conclusion, we observed for the first time, through a test-retest approach, a variability in the appearance and temporal/spatial patterns of resting-state networks in severely brain-injured patients, proposing a new method to select the most informative connectivity pattern

Francisco Varela's view on phenomenology in his cognitive interpretation

The philosophy by Husserl has always been a very interesting topic for cognitive scientists. Indeed, there is a strong analogy between the method of phenomenological reduction and the theories of mind developed by cognitive science in the last fifty years. The method of reduction is based on the concept of reality as a product of mind. Cognitive science seems to agree with this view but it is still difficult to elaborate a cognitive interpretation of the Husserl phenomenology which is philosophically correct. The best attempt is that by Francisco Varela; thanks to the philosophic teaching of Humberto Maturana, he offers us a terribly reliable and audacious interpretation of Husserl even if complex for the role which plays between two necessities: the former is to construct neurophenomenology emphasizing the philosophy of Husserl like the only conceptual architecture able to study experience directly and the latter (which) is to found the enactive paradigm for cognitive science referring to Buddhist psychology

Test-retest Reliability of Intrinsic Human Brain Default-Mode fMRI Connectivity: Slice Acquisition and Physiological Noise Correction Effects

This thesis aims at evaluating, in two separate studies, strategies for physiological noise and head motion correction in resting state brain FC-fMRI. In particular, as a general marker of noise correction performance we use the test-retest reproducibility of the DMN. The guiding hypothesis is that methods that improve reproducibility should reflect more efficient corrections and thus be preferable in longitudinal studies. The physiological denoising study evaluated longitudinal changes in a 3T harmonized multisite fMRI study of healthy elderly participants from the PharmaCog Consortium (Jovicich et al., 2016). Retrospective physiological noise correction (rPNC) methods were here implemented to investigate their influence on several DMN reliability measures within and between 13 MRI sites. Each site involved five different healthy elderly participants who were scanned twice at least a week apart (5 participants per site). fMRI data analysis was performed once without rPNC and then with WM/CSF regression, with physiological estimation by temporal ICA (PESTICA) (Beall & Lowe, 2007) and FMRIB's ICA-based Xnoiseifier (FSL-FIX) (Griffanti et al., 2014; Salimi-Khorshidi et al., 2014). These methods differ for their data-based computational approach to identify physiological noise fluctuations and need to be applied at different stages of data preprocessing. As a working hypothesis, physiological denoising was in general expected to improve DMN reliability. The head motion study evaluated longitudinal changes in the DMN connectivity from a 4T single-site study of 24 healthy young volunteers who were scanned twice within a week. Within each scanning session, RS-fMRI scans were acquired once using interleaved and then sequential slice-order acquisition methods. Furthermore, brain volumes were corrected for motion using once rigid-body volumetric and then slice-wise methods. The effects of these choices were then evaluated computing multiple DMN reliability measures and investigating single regions within the DMN to assess the existence of inter-regional effects associated with head-motion. In this case, we expected to find slice-order acquisition effects in reliability estimates under standard volumetric motion correction and no slice-order acquisition effect under 2D slice-based motion correction. Both studies used ICA to characterize the DMN using group-ICA and dual regression procedures (Beckmann et al., 2009). This methodology proved successful at defining consistent DMN connectivity metrics in longitudinal and clinical RS-fMRI studies (Zuo & Xing, 2014). Automatic DMN selection procedures and other quality assurance analyses were made to supervise ICA performance. Both studies considered several test-retest (TRT) reliability estimates (Vilagut, 2014) for some DMN connectivity measurements: absolute percent error between the sessions, intraclass correlation coefficients (ICC) between sessions and multiple sites, the Jaccard index to evaluate the degree of voxel-wise spatial pattern actiavtion overlap between sessions

Test–Retest Reproducibility of the Intrinsic Default Mode Network: Influence of Functional Magnetic Resonance Imaging Slice-Order Acquisition and Head-Motion Correction Methods

Head motion is a known challenge in resting-state functional magnetic resonance imaging studies for biasing functional connectivity (FC) among distinct anatomical regions. These persist even with small motion, limiting comparisons of groups with different head-motion characteristics. This motivates an interest in the optimization of acquisition and correction strategies to minimize motion sensitivity. In this test-retest (TRT) study of healthy young volunteers (N = 23), we investigate the effects of slice-order acquisitions (sequential or interleaved) and head-motion correction methods (volume- or slice-based) on the TRT reproducibility of intrinsic connectivity of the default mode network (DMN). We evaluated the TRT reproducibility of the entire DMN and each main node using the absolute percentage error, intraclass correlation coefficient (ICC), and the Jaccard coefficient. Regardless of slice-order acquisition, the slice-based motion correction method systematically estimated larger motion and returned significantly higher temporal signal-to-noise ratio. Although consistently extracted across all acquisition and motion correction approaches, DMN connectivity was sensitive to these choices. However, the TRT reproducibility of the whole DMN was stable and showed no sensitivity to the methods tested (absolute reproducibility ∼7%, ICC = 0.47, and Jaccard = 40%). Percentage errors and ICCs were consistent across single nodes, but the Jaccard coefficients were not. The posterior cingulate was the most reproducible node (Jaccard = 52%), whereas the anterior cingulate was the least reproducible (Jaccard = 30%). Our study suggests that the slice-order and motion correction methods evaluated offer comparable sensitivity to detect DMN connectivity changes in a longitudinal study of individuals with low head-motion characteristics, but that controlling for the consistency in acquisition and correction protocols is important in cross-sectional studies

Simultaneous resting-state FDG-PET/fMRI in Alzheimer Disease: Relationship between glucose metabolism and intrinsic activity

Simultaneously evaluating resting-state brain glucose metabolism and intrinsic functional activity has potential to impact the clinical neurosciences of Alzheimer Disease (AD). Indeed, integrating such combined information obtained in the same physiological setting may clarify how impairments in neuroenergetic and neuronal function interact and contribute to the mechanisms underlying AD. The present study used this multimodality approach to investigate, by means of a hybrid PET/MR scanner, the coupling between glucose consumption and intrinsic functional activity in 23 patients with AD-related cognitive impairment ranging from amnestic mild cognitive impairment (MCI) to mild-moderate AD (aMCI/AD), in comparison with a group of 23 healthy elderly controls. Between-group (Controls > Patients) comparisons were conducted on data from both imaging modalities using voxelwise 2-sample t-tests, corrected for partial-volume effects, head motion, age, gender and multiple tests. FDG-PET/fMRI relationships were assessed within and across subjects using Spearman partial correlations for three different resting-state fMRI (rs-fMRI) metrics sensitive to AD: fractional amplitude of low frequency fluctuations (fALFF), regional homogeneity (ReHo) and group independent component analysis with dual regression (gICA-DR). FDG and rs-fMRI metrics distinguished aMCI/AD from controls according to spatial patterns analogous to those found in stand-alone studies. Within-subject correlations were comparable across the three rs-fMRI metrics. Correlations were overall high in healthy controls (ρ = 0.80 ± 0.04), but showed a significant 17% reduction (p < 0.05) in aMCI/AD patients (ρ = 0.67 ± 0.05). Positive across-subject correlations were overall moderate (ρ = 0.33 ± 0.07) and consistent across rs-fMRI metrics. These were confined around AD-target posterior regions for metrics of functional connectivity (ReHo and gICA-DR). In contrast, FDG/fALFF correlations were distributed in the frontal gyrus, thalami and caudate nuclei. Taken together, these results support the presence of bioenergetic coupling between glucose utilization and rapid transmission of neural information in healthy ageing, which is substantially reduced in aMCI/AD, suggesting that abnormal glucose utilization is in some way linked to communication breakdown among brain regions impacted by the underlying pathological process

Test-Retest Reliability of the Default Mode Network in a Multi-Centric fMRI Study of Healthy Elderly: Effects of Data-Driven Physiological Noise Correction Techniques

International audienceUnderstanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within-site test-retest reliability and the across-site reproducibility consistency of DMN-derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue-based regression, PESTICA and FSL-FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z-scores and, albeit less markedly, the cluster-size in the DMN; in particular, FSL-FIX tended to increase the DMN z-scores compared to others. Within-site test-retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5-11% for DMN z-scores and cluster-size reliability. DMN pattern overlap was in the range 60-65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL-FIX and Tissue-based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC50.67) for the DMN z-scores relative to NPC. Overall these findings support the use of rPNC methods like tissue-based or FSL-FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. (C) 2016 Wiley Periodicals, Inc

Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study

WOS:000366646700041International audienceTo date, limited data are available regarding the inter-site consistency of test-retest reproducibility of functional connectivity measurements, in particular with regard to integrity of the Default Mode Network (DMN) in elderly participants. We implemented a harmonized resting-state fMRI protocol on 13 clinical scanners at 3.0 T using vendor-provided sequences. Each site scanned a group of 5 healthy elderly participants twice, at least a week apart. We evaluated inter-site differences and test-retest reproducibility of both temporal signal-to-noise ratio (tSNR) and functional connectivity measurements derived from: i) seed-based analysis (SBA) with seed in the posterior cingulate cortex (PCC), ii) group independent component analysis (ICA) separately for each site (site ICA), and iii) consortium ICA, with group ICA across the whole consortium. Despite protocol harmonization, significant and quantitatively important inter-site differences remained in the tSNR of resting-state fMRI data; these were plausibly driven by hardware and pulse sequence differences across scanners which could not be harmonized. Nevertheless, the tSNR test-retest reproducibility in the consortium was high (ICC = 0.81). The DMN was consistently extracted across all sites and analysis methods. While significant inter-site differences in connectivity scores were found, there were no differences in the associated test-retest error. Overall, ICA measurements were more reliable than PCC-SBA, with site ICA showing higher reproducibility than consortium ICA. Across the DMN nodes, the PCC yielded the most reliable measurements (approximate to 4% test-retest error, ICC = 0.85), the medial frontal cortex the least reliable (approximate to 12%, ICC = 0.82) and the lateral parietal cortices were in between (site ICA). Altogether these findings support usage of harmonized multisite studies of resting-state functional connectivity to characterize longitudinal effects in studies that assess disease progression and treatment response. (C) 2015 Elsevier Inc. All rights reserved