Connectivity Between Salience and Default Mode Networks and Subcortical Nodes Distinguishes Between Two Classes of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease with unknown pathophysiology. Functional magnetic resonance imaging (fMRI) studies in ME/CFS have reported disparate connectivities for the brain salience (SA) network and default mode network (DMN). Materials and Methods: In this study, we acquired resting-state and task fMRI with an advanced scanner for improved subject numbers: 24 healthy controls (HC) and 42 ME/CFS patients, 18 meeting the International Consensus Criteria (ICC) and 24 meeting the Fukuda criteria. We evaluated mean functional connectivity between the SA network and DMN hubs and subcortical regions known to be involved in ME/CFS. We tested the hypothesis that ME/CFS connectivity differed from HC and the ICC and Fukuda classes are distinguished by different connectivities with HC for different pairs of SA network, DMN, or subcortical hubs. Results: During resting-state fMRI, only two connections differed from HC, both for Fukuda ME/CFS and both with an SA network hub. During task fMRI, 10 ME/CFS connections differed from HC, 5 for ICC, and 5 for Fukuda. None was common to both classes. Eight of the 10 different connections involved an SA network hub, six of the 10 were weaker in ME/CFS, and 4 were stronger. SA network connections to the hippocampus and brainstem reticular activation system (RAS) differed from and were stronger than HC. Conclusions: The SA network mediates the relative activity of the DMN and executive networks and an imbalance will have functional consequences. The RAS and hippocampus modulate cortical activation. Different regulatory connections are consistent with the impaired cognitive performance and sleep-wake cycle of ME/CFS. Different neuropathologies are involved in ICC and Fukuda classes. Impact statement Criteria for the diagnosis of the debilitating myalgic encephalitis/chronic fatigue syndrome (ME/CFS) condition have evolved over two decades. Physicians are now instructed that the recent, more stringent (ICC) questionnaire criteria define a disease that is distinct from those remaining subjects defined by the previous Fukuda criteria. This work reports the remarkable finding that functional magnetic resonance imaging connectivity can differentiate between these two classes of ME/CFS. This is the first objective medical evidence that the questionnaire-based diagnosis does indeed differentiate between two different disease states. This facilitates a clearer understanding of ME/CFS and can better direct research and therapy development.

Alteration of Cortical Volume and Thickness in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.

Myalgic Encephalomyelitis/Chronic fatigue syndrome (ME/CFS) patients suffer from neurocognitive impairment. In this study, we investigated cortical volumetric and thickness changes in ME/CFS patients and healthy controls (HC). We estimated mean surface-based cortical volume and thickness from 18 ME/CFS patients who met International Consensus Criteria (ICC) and 26 HC using FreeSurfer. Vertex-wise analysis showed significant reductions in the caudal middle frontal gyrus (p = 0.0016) and precuneus (p = 0.013) thickness in ME/CFS patients compared with HC. Region based analysis of sub-cortical volumes found that amygdala volume (p = 0.002) was significantly higher in ME/CFS patients compared with HC. We also performed interaction-with-group regressions with clinical measures to test for cortical volume and thickness correlations in ME/CFS with opposite slopes to HC (abnormal). ME/CFS cortical volume and thickness regressions with fatigue, heart-rate variability, heart rate, sleep disturbance score, respiratory rate, and cognitive performance were abnormal. Our study demonstrated different cortical volume and thickness in ME/CFS patients and showed abnormal cortical volume and thickness regressions with key symptoms of ME/CFS patients.

Volumetric differences in hippocampal subfields and associations with clinical measures in myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) patients suffer from a cognitive and memory dysfunction. Because the hippocampus plays a key role in both cognition and memory, we tested for volumetric differences in the subfields of the hippocampus in ME/CFS. We estimated hippocampal subfield volumes for 25 ME/CFS patients who met Fukuda criteria only (ME/CFSFukuda ), 18 ME/CFS patients who met the stricter ICC criteria (ME/CFSICC ), and 25 healthy controls (HC). Group comparisons with HC detected extensive differences in subfield volumes in ME/CFSICC but not in ME/CFSFukuda . ME/CFSICC patients had significantly larger volume in the left subiculum head (p < 0.001), left presubiculum head (p = 0.0020), and left fimbria (p = 0.004). Correlations of hippocampus subfield volumes with clinical measures were stronger in ME/CFSICC than in ME/CFSFukuda patients. In ME/CFSFukuda patients, we detected positive correlations between fatigue and hippocampus subfield volumes and a negative correlation between sleep disturbance score and the right CA1 body volume. In ME/CFSICC patients, we detected a strong negative relationship between fatigue and left hippocampus tail volume. Strong negative relationships were also detected between pain and SF36 physical scores and two hippocampal subfield volumes (left: GC-ML-DG head and CA4 head). Our study demonstrated that volumetric differences in hippocampal subfields have strong statistical inference for patients meeting the ME/CFSICC case definition and confirms hippocampal involvement in the cognitive and memory problems of ME/CFSICC patients.

A CNN Based Software Gradiometer for Electromagnetic Background Noise Reduction in Low Field MRI Applications.

The shielding of electromagnetic noise is critical in obtaining magnetic resonance imaging measurements in the ultra-low magnetic field regime where the intrinsic signal-to-noise ratio is very small. The traditional approach of using an enclosure for electromagnetic shielding is expensive and hinders system portability. We describe here the use of a CNN-based software gradiometer to suppress the effect of electromagnetic ambient background noise sources that inductively couple into the signal detection coils. The system involves three ambient noise monitoring coils placed at a distance from the magnetic resonance signal detector. The three coils were used to synthesize the ambient noise captured by the signal detector; a convolutional neural network approach was used. Mathematical foundations are provided to justify the noise suppression framework. The results show that as much as 20-fold noise suppression can be achieved using an optimized convolutional neural network and simultaneous ambient noise measurements. The proposed approach has the potential to replace the requirement for magnetically shielded enclosures and make ultra-low field magnetic resonance imaging truly portable.

A numerical study of pre-polarisation switching in ultra-low field magnetic resonance imaging using dynamic permanent magnet arrays.

Dynamically adjustable permanent magnet arrays have been proposed to generate switchable magnetic fields for pre-polarisation in Ultra-Low Field magnetic resonance imaging. However, the optimal switching dynamics of the pre-polarisation magnetic field as well as the energy requirements, mechanical forces and stresses during switching of the pre-polarisation field have not been evaluated. We analysed these requirements numerically and estimated the magnetic resonance signal strength and image quality for two practical switching modes in an instrument suitable for scanning the human head. Von Mises stress analysis showed that although magnetic forces were significantly higher for two specific rungs, the structural integrity of magnet rungs would not be compromised. Our simulations suggest that a significantly higher signal yield is obtained by switching off the pre-polarisation field with the angular velocity in each rung dependent on its location.

3D-Spatial encoding with permanent magnets for ultra-low field magnetic resonance imaging.

We describe with a theoretical and numerical analysis the use of small permanent magnets moving along prescribed helical paths for 3D spatial encoding and imaging without sample adjustment in ultra-low field magnetic resonance imaging (ULF-MRI). With our developed method the optimal magnet path and orientation for a given encoding magnet number and instrument architecture can be determined. As a proof-of-concept, we studied simple helical magnet paths and lengths for one and two encoding magnets to evaluate the imaging efficiency for a mechanically operated ULF-MRI instrument with permanent magnets. We demonstrate that a single encoding magnet moving around the sample in a single revolution suffices for the generation of a 3D image by back projection.

Highly Compact Artificial Memristive Neuron with Low Energy Consumption.

Neuromorphic systems aim to implement large-scale artificial neural network on hardware to ultimately realize human-level intelligence. The recent development of nonsilicon nanodevices has opened the huge potential of full memristive neural networks (FMNN), consisting of memristive neurons and synapses, for neuromorphic applications. Unlike the widely reported memristive synapses, the development of artificial neurons on memristive devices has less progress. Sophisticated neural dynamics is the major obstacle behind the lagging. Here a rich dynamics-driven artificial neuron is demonstrated, which successfully emulates partial essential neural features of neural processing, including leaky integration, automatic threshold-driven fire, and self-recovery, in a unified manner. The realization of bioplausible artificial neurons on a single device with ultralow power consumption paves the way for constructing energy-efficient large-scale FMNN and may boost the development of neuromorphic systems with high density, low power, and fast speed.