Structure-function relationships in the visual system in multiple sclerosis: an MEG and OCT study

BACKGROUND: We conducted a multi-modal optical coherence tomography (OCT) and magnetoencephalography (MEG) study to test whether there is a relationship between retinal layer integrity and electrophysiological activity and connectivity (FC) in the visual network influenced by optic neuritis (ON) in patients with multiple sclerosis (MS). METHODS: One hundred and two MS patients were included in this MEG/OCT study. Retinal OCT data were collected from the optic discs, macular region, and segmented. Neuronal activity and FC in the visual cortex was estimated from source-reconstructed resting-state MEG data by computing relative power and the phase lag index (PLI). Generalized estimating equations (GEE) were used to account for intereye within-patient dependencies. RESULTS: There was a significant relationship for both relative power and FC in the visual cortex with retinal layer thicknesses. The findings were influenced by the presence of MSON, particularly for connectivity in the alpha bands and the outer macular layers. In the absence of MSON, this relationship was dominated by the lower frequency bands (theta, delta) and inner and outer retinal layers. CONCLUSION: These results suggest that visual cortex FC more than activity alters in the presence of MSON, which may guide the understanding of FC plasticity effects following MSON

Timing of retinal neuronal and axonal loss in MS: a longitudinal OCT study

The objective of the study was to investigate the timing of central nervous system tissue atrophy in MS by evaluating longitudinal retinal volume changes in a broadly representative cohort with disease duration across the entire arc of disease. In this longitudinal study, 135 patients with MS and 16 healthy reference subjects underwent spectral-domain optical coherence tomography (OCT) at baseline and 2 years later. Following OCT quality control, automated segmentation of the peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell–inner plexiform layer (mGCIPL) and macular inner nuclear layer (mINL) was performed. Generalized estimation equations were used to analyze longitudinal changes and associations with disease duration and clinical measures. Participants had a median disease duration at baseline of 16.4 years (range 0.1–45.4). Nearly half (44 %) of the MS patients had previously experienced MS-related optic neuritis (MSON) more than 6 months prior. The MS patients demonstrated a significant decrease over 2 years of the pRNFL (−1.1 µm, 95 % CI 1.4–0.7, p < 0.001) and mGCIPL (−1.1 µm, 95 % CI −1.4 to −0.8, p < 0.001). This thinning was most pronounced early in the course of disease. These findings were irrespective of previous episodes of MSON. No consistent pattern of change was observed for the mINL (−0.03 µm, 95 % CI −0.2 to 0.2, p = 0.795). This longitudinal study demonstrated that injury of the innermost retinal layers is found in MS and that this damage occurs most rapidly during the early stages of disease. The attenuation of atrophy with longer disease duration is suggestive of a plateau effect. These findings emphasize the importance of early intervention to prevent such injury

Disruption in structural–functional network repertoire and time-resolved subcortical fronto-temporoparietal connectivity in disorders of consciousness

Understanding recovery of consciousness and elucidating its underlying mechanism is believed to be crucial in the field of basic neuroscience and medicine. Ideas such as the global neuronal workspace (GNW) and the mesocircuit theory hypothesize that failure of recovery in conscious states coincide with loss of connectivity between subcortical and frontoparietal areas, a loss of the repertoire of functional networks states and metastable brain activation. We adopted a time-resolved functional connectivity framework to explore these ideas and assessed the repertoire of functional network states as a potential marker of consciousness and its potential ability to tell apart patients in the unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). In addition, the prediction of these functional network states by underlying hidden spatial patterns in the anatomical network, that is so-called eigenmodes, was supplemented as potential markers. By analysing time-resolved functional connectivity from functional MRI data, we demonstrated a reduction of metastability and functional network repertoire in UWS compared to MCS patients. This was expressed in terms of diminished dwell times and loss of nonstationarity in the default mode network and subcortical fronto-temporoparietal network in UWS compared to MCS patients. We further demonstrated that these findings co-occurred with a loss of dynamic interplay between structural eigenmodes and emerging time-resolved functional connectivity in UWS. These results are, amongst others, in support of the GNW theory and the mesocircuit hypothesis, underpinning the role of time-resolved thalamo-cortical connections and metastability in the recovery of consciousness

Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions

Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typically measured using haemodynamic signals) and electrophysiology has been explored using functional Magnetic Resonance Imaging (fMRI) and magnetoencephalography (MEG). Significant progress has been made, with similar spatial structure observable in both modalities. However, there is a pressing need to understand this relationship beyond simple visual similarity of RSN patterns. Here, we introduce a mathematical model to predict fMRI-based RSNs using MEG. Our unique model, based upon a multivariate Taylor series, incorporates both phase and amplitude based MEG connectivity metrics, as well as linear and non-linear interactions within and between neural oscillations measured in multiple frequency bands. We show that including non-linear interactions, multiple frequency bands and cross-frequency terms significantly improves fMRI network prediction. This shows that fMRI connectivity is not only the result of direct electrophysiological connections, but is also driven by the overlap of connectivity profiles between separate regions. Our results indicate that a complete understanding of the electrophysiological basis of RSNs goes beyond simple frequency-specific analysis, and further exploration of non-linear and cross-frequency interactions will shed new light on distributed network connectivity, and its perturbation in pathology

Screen-detected breast cancers have a lower mitotic activity index

We know that screening for breast cancer leads to detection of smaller tumours with less lymph node metastases. Could it be possible that the decrease in mortality after screening is not only caused by this earlier stage, but also by a different mitotic activity index (MAI) of the tumours that are detected by screening? Is MAI a prognostic factor for recurrence-free survival? A retrospective study was carried out of 387 patients with breast cancer, treated at the University Hospital Nijmegen between January 1992 and September 1997. Ninety patients had screen-detected breast cancer, 297 patients had breast cancers detected outside the screening programme. The MAI, other prognostic factors and recurrence-free survival were determined. In non-screen-detected tumours the MAI is twice as high as in screen-detected tumours, even after correction for age took place. The MAI correlated well with other tumour characteristics. The MAI in itself is a prognostic factor for recurrence-free survival. Favourable outcome in screen detected breast cancer is not entirely caused by detecting cancer in early stages: quantitative features such as the MAI indicate a less malignant character of screen detected breast cancer. The MAI is an independent prognostic factor for recurrence-free survival. © 2000 Cancer Research Campaig

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations

There is an increasing awareness of the advantages of multi-modal neuroimaging. Networks obtained from different modalities are usually treated in isolation, which is however contradictory to accumulating evidence that these networks show non-trivial interdependencies. Even networks obtained from a single modality, such as frequency-band specific functional networks measured from magnetoencephalography (MEG) are often treated independently. Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation for group comparison. We analyse how well-known biases for single layer networks, such as effects of group differences in link density and/or average connectivity, influence multilayer networks, and we compare four schemes that aim to correct for such biases: the minimum spanning tree (MST), effective graph resistance cost minimisation, efficiency cost optimisation (ECO) and a normalisation scheme based on singular value decomposition (SVD). These schemes can be applied to the layers independently or to the multilayer network as a whole. For correction applied to whole multilayer networks, only the SVD showed sufficient bias correction. For correction applied to individual layers, three schemes (ECO, MST, SVD) could correct for biases. By using generative models as well as empirical MEG and functional magnetic resonance imaging (fMRI) data, we further demonstrated that all schemes were sensitive to identify network topology when the original networks were perturbed. In conclusion, uncorrected multilayer network analysis leads to biases. These biases may differ between centres and studies and could consequently lead to unreproducible results in a similar manner as for single layer networks. We therefore recommend using correction schemes prior to multilayer network analysis for group comparisons

The OSCAR-IB Consensus Criteria for Retinal OCT Quality Assessment

Retinal optical coherence tomography (OCT) is an imaging biomarker for neurodegeneration in multiple sclerosis (MS). In order to become validated as an outcome measure in multicenter studies, reliable quality control (QC) criteria with high inter-rater agreement are required

Comparison of inpatient vs. outpatient anterior cervical discectomy and fusion: a retrospective case series

<p>Abstract</p> <p>Background</p> <p>Spinal surgery is increasingly being done in the outpatient setting. We reviewed our experience with inpatient and outpatient single-level anterior cervical discectomy and fusion with plating (ACDF+P).</p> <p>Methods</p> <p>All patients undergoing single-level anterior cervical discectomy and fusion with plating between August 2005 and May 2007 by two surgeons (RPB or JAF) were retrospectively reviewed. All patients underwent anterior cervical microdiscectomy, arthrodesis using structural allograft, and titanium plating. A planned change from doing ACDF+P on an inpatient basis to doing ACDF+P on an outpatient basis was instituted at the midpoint of the study. There were no other changes in technique, patient selection, instrumentation, facility, or other factors. All procedures were done in full-service hospitals accommodating outpatient and inpatient care.</p> <p>Results</p> <p>64 patients underwent ACDF+P as inpatients, while 45 underwent ACDF+P as outpatients. When outpatient surgery was planned, 17 patients were treated as inpatients due to medical comorbidities (14), older age (1), and patient preference (2). At a mean follow-up of 62.4 days, 90 patients had an excellent outcome, 19 patients had a good outcome, and no patients had a fair or poor outcome. There was no significant difference in outcome between inpatients and outpatients. There were 4 complications, all occurring in inpatients: a hematoma one week post-operatively requiring drainage, a cerebrospinal fluid leak treated with lumbar drainage, syncope of unknown etiology, and moderate dysphagia.</p> <p>Conclusion</p> <p>In this series, outpatient ACDF+P was safe and was not associated with a significant difference in outcome compared with inpatient ACDF+P.</p

A novel brain partition highlights the modular skeleton shared by structure and function

Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.Work supported by Ikerbasque: The Basque Foundation for Science, Euskampus at UPV/EHU, Gobierno Vasco (Saiotek SAIO13-PE13BF001) and Junta de Andalucía (P09-FQM-4682) to JMC; Ikerbasque Visiting Professor to SS; Junta de Andalucía (P09-FQM-4682) and Spanish Ministry of Economy and Competitiveness (FIS2013-43201-P) to MAM; the European Union’s Seventh Framework Programme (ICT-FET FP7/2007-2013, FET Young Explorers scheme) under grant agreement n. 284772 BRAIN BOW (www.brainbowproject.eu) and by the Joint Italy—Israel Laboratory on Neuroscience to PB. For results validation (figure S8), data were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University