Posts Tagged functional magnetic resonance imaging

[Editorial] Functional brain mapping of epilepsy networks: methods and applications – Neuroscience

This multidisciplinary research topic is a collection of contemporary advances in neuroimaging applied to mapping functional brain networks in epilepsy. With technology such as simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) now more readily available, it is possible to non-invasively map epileptiform activity throughout the entire brain at millimetre resolution. This research topic includes original research studies, technical notes and reviews of the field. Due to the multidisciplinary nature of the domain, the topic spans two journals: Frontiers in Neurology (Section: Epilepsy) and Frontiers in Neuroscience (Section: Brain Imaging Methods).
In this editorial we consider the outcomes of the multidisciplinary work presented in the topic. With the benefit of time elapsed since the original papers were published, we can see that the works are making a substantial impact in the field. At the time of writing, this topic had well over 27,000 full-paper downloads (including over 18,000 for the 15 papers in the Epilepsy section, and over 9,000 for the 8 papers in the Brain Imaging Methods section). Several papers in the topic have climbed the tier in Frontiers and received an associated invited commentary, demonstrating there is substantial interest in this research area.
Reviews
The topic’s review papers set the scene for the original research papers and synthesise contemporary thinking in epilepsy research and neuroimaging methods. We see that Epilepsy, whether of a “generalised” or “focal” origin, is increasingly recognised as a disorder of large-scale brain networks. At one level it is self-evident that otherwise healthy functional networks are recruited during epileptic activity, as this is what generates patient perceptions of their epileptic aura. For example, the epileptic aura of mesial temporal lobe epilepsy can include an intense sensation of familiarity (déjà vu) associated with involvement of the hippocampus, and unpleasant olfactory auras which may reflect involvement of adjacent olfactory cortex. As seizures spread more widely throughout the brain, presumably along pre-existing neural pathways, patients lose control of certain functions; for example, their motor system in the case of generalised convulsions, or aspects of awareness in seizures that remain localised to non-motor brain regions. Yet these functions return when the seizure abates, implying involved brain regions are also responsible for normal brain function. What has been less clear, and difficult to investigate until the advent of functional neuroimaging, is precisely which brain networks are involved (especially in ‘generalised’ epilepsy syndromes), and the extent to which functional networks are perturbed during seizures, inter-ictal activity, and at other times.
Functional imaging evidence of brain abnormalities in temporal lobe epilepsy is explored in (Caciagli et al., 2014), including evidence of dysfunction in limbic and other specific brain networks, as well as global changes in network topography derived from resting-state fMRI. Archer et al systematically review the functional neuroimaging of a particularly severe epilepsy phenotype, Lennox-Gastaut Syndrome (LGS), illustrating well how different forms of brain pathology can manifest in a similar clinical phenotype, simply by the nature of the healthy networks that the underlying pathology perturbs (Archer et al., 2014). Similarly, the mechanisms of absence seizure generation are reviewed by (Carney and Jackson, 2014), revealing that it too has a signature pattern of large-scale functional brain network perturbation. The ability to make such observations has considerable clinical significance, as highlighted in the review by (Pittau et al., 2014).
The tantalising proposition that there may be a common treatment target for all focal epilepsy phenotypes is also explored in a review of the piriform cortex by (Vaughan and Jackson, 2014). The piriform cortex was first implicated as a common brain region associated with spread of interictal discharges in focal epilepsy in an experiment that analysed the spatially normalised functional imaging data of a heterogeneous group of focal epilepsy patients (Laufs et al., 2011). This finding, since replicated (Flanagan et al., 2014), led Vaughan & Jackson to explore in detail what is known of the piriform cortex. Their findings reveal the piriform has several features that likely predispose it to involvement in focal epilepsy, and features that also explain many of the peculiar symptoms experienced by patients, from olfactory auras to the characteristic nose-wiping that many patients perform postictally. This work points to the need for future studies to determine whether the piriform might be an effective target for deep brain stimulation or other targeted therapy to prevent the spread of epileptiform activity.
Original research
Temporal lobe epilepsy is investigated in several papers in this topic. One of these studies also introduces a new exploratory method, Shared and specific independent component analysis (SSICA), that builds upon independent component analysis to perform between-group network comparison (Maneshi et al., 2014). In application to mesial temporal lobe epilepsy (MTLE) and healthy controls, three distinct reliable networks were revealed: two that exhibited increased activity in patients (a network including hippocampus and amygdala bilaterally, and a network including postcentral gyri and temporal poles), and a network identified as specific to healthy controls (i.e. effectively decreased in patients, consisting of bilateral precuneus, anterior cingulate, thalamus, and parahippocampal gyrus). These finding give mechanistic clues to the cognitive impairments often reported in patients with MTLE. Further clues are revealed in a study of the dynamics of fMRI and its functional connectivity (Laufs et al., 2014). Compared to healthy controls, temporal variance of fMRI was seen to be most increased in the hippocampi of TLE patients, and variance of functional connectivity to this region was increased mainly in the precuneus, the supplementary and sensorimotor, and the frontal cortices. More severe disruption of connectivity in these networks during seizures may explain patients’ cognitive dysfunction (Laufs et al., 2014). Yang and colleagues also show that it may be possible to use fMRI functional connectivity to lateralise TLE (Yang et al., 2015), which could be a useful clinical tool.
Mechanistic explanations of symptomatology beyond the seizure onset zone can also be revealed with conventional nuclear medicine techniques such as 18F-FDG-PET. This is demonstrated in a study of Occipital Lobe Epilepsy by Wong and colleagues, who observed that patients with automatisms have metabolic changes extending from the epileptogenic occipital lobe into the ipsilateral temporal lobe, whereas in patients without automatisms the 18F-FDG-PET was abnormal only in the occipital lobe (Wong et al., 2014).
The clinical significance of the ability to non-invasively study functional brain networks extends to understanding the impact of surgery on brain networks. This Frontiers research topic includes an investigation by Doucet and colleagues revealing that temporal lobe epilepsy and surgery selectively alter the dorsal, rather than the ventral, default-mode network (Doucet et al., 2014).
Another approach to better understand the mechanisms of seizure onset and broader symptomatology is computational modelling. It can track aspects of neurophysiology than cannot be readily measured: for example effective connectivity and mean membrane potential dynamics are shown by (Freestone et al., 2014) to be estimable using model inversion. In a proof-of-principle experiment with simulated data, they demonstrate that by tailoring the model to subject-specific data, it may be possible for the framework to identify a seizure onset site and the mechanism for seizure initiation and termination. Also in this topic, Petkov and colleagues utilise a computational model of the transition into seizure dynamics to explore how conditions favourable for seizures relate to changes in functional networks. They find that networks with higher mean node degree are more prone to generating seizure dynamics in the model, thus providing a mathematical mechanistic explanation for increasing node degree causing increased ictogenicity (Petkov et al., 2014).
Seizure prediction is an area of considerable research, and in this topic Cook and colleagues reveal intriguing characteristics in the long-term temporal pattern of seizure onset. They confirmed that human inter-seizure intervals follow a power law, and they found evidence of long-range dependence. Specifically, the dynamics that led to the generation of a seizure in most patients appeared to be affected by events that took place much earlier (as little as 30 minutes prior and up to 40 days prior in some patients) (Cook et al., 2014). The authors rightly note that this information could be valuable for individually-tuned seizure prediction algorithms.
Several methodological papers in this Frontiers Topic prove there remains considerable potential to improve neuroimaging methods as applied to the study of epilepsy. For example, (Mullinger et al., 2014) reveal the critical importance of the accuracy of physical models if one is to optimise lead positioning in functional MRI with simultaneous EEG. Confirming with computer modelling and phantom measurements that lead positioning can have a substantial effect on the amplitude of the MRI gradient artefact present on the EEG, they optimised the positions in a novel cap design. However, whilst this substantially reduced gradient artefact amplitude on the phantom, it made things worse when used on human subjects. Thus, improvement is required in model accuracy if one is to make accurate predictions for the human context.
Reduction of artefact, particularly cardioballistic and non-periodic motion artefact, remains a challenge for off-the-shelf MRI-compatible EEG systems. However, for over a decade, the Jackson group in Melbourne has dealt well with this issue using insulated carbon-fibre artefact detectors, physically but not electrically attached to the scalp (Masterton et al., 2007). In the present topic, they provide detailed instructions for building such detectors and interfacing them with a commercially available MRI-compatible EEG system (Abbott et al., 2015). This team also previously developed event-related ICA (eICA), to map fMRI activity associated with inter-ictal events observed on EEG (Masterton et al., 2013b). The method is capable of distinguishing separate sub-networks characterised by differences in spatio-temporal response (Masterton et al., 2013a). The eICA approach frees one from assumptions regarding the shape of the time-course of the neuronal and haemodynamic response associated with inter-ictal activity (which can vary according to spike type, can vary from conventional models and may include pre-spike activity (Masterton et al., 2010); issues explored further in the present topic by (Faizo et al., 2014) and (Jacobs et al., 2014)). However, the effectiveness of eICA can be affected by fMRI noise or artefact. In the present topic we see that application of a fully automated de-noising algorithm (SOCK) is now recommended, as it can substantially improve the quality of eICA results (Bhaganagarapu et al., 2014).
The ability to detect activity associated with inter-ictal events can also be improved with faster image acquisition. Magnetic Resonance Encephalography (MREG) is a particularly fast fMRI acquisition method (TR=100ms) that achieves its speed using an under-sampled k-space trajectory (Assländer et al., 2013; Zahneisen et al., 2012). This has now been applied in conjunction with simultaneous EEG, to reveal that the negative fMRI response in the default-mode network is larger in temporal compared to extra-temporal epileptic spikes (Jacobs et al., 2014).
The default mode network and its relationship to epileptiform activity is also examined in several other papers in this topic. In a pilot fMRI connectivity study of Genetic Generalised Epilepsy and Temporal Lobe Epilepsy patients, (Lopes et al., 2014) observed that intrinsic connectivity in portions of the default mode network appears to increase several seconds prior to the onset of inter-ictal discharges. The authors suggest that the default mode network connectivity may facilitate IED generation. This is plausible, although causality is difficult to establish and it is possible that something else drives both the connectivity and EEG changes (Abbott, 2015).
Complicating matters further is the question of what connectivity means. There are many ways in which connectivity can be assessed. Jones and colleagues have discovered that some of these do not necessarily correlate well with each other. They examined connectivity between measurements made with intracranial electrodes, connectivity assessed using simultaneous BOLD fMRI and intracranial electrode stimulation, connectivity between low-frequency voxel measures of fMRI activity, and a diffusion MRI measure of connectivity – an integrated diffusivity measure along a connecting pathway (Jones et al., 2014). They found only mild correlation between these four measures, implying they assess quite different features of brain networks. More research in this domain would therefore be valuable.
Whatever the measure of connectivity utilised, most evidence of alterations in connectivity in epilepsy has been obtained from comparison of a group of patients with a group of healthy controls. However, a new method called Detection of Abnormal Networks in Individuals (DANI) is now proposed by (Dansereau et al., 2014). This method is designed to detect the organisation of brain activity in stable networks, which the authors call modularity. The conventional definition of modularity refers to the degree to which networks can be segregated into distinct communities, usually estimated by maximising within-group nodal links, and minimising between group links (Girvan and Newman, 2002; Rubinov and Sporns, 2010). Dansereau take a novel approach to this concept, instead evaluating the stability of each resting state network across replications of a bootstrapped clustering method (Bellec et al., 2010). In the DANI approach, the degree to which an individual’s functional connectivity modular pattern deviates from a population of controls is quantified. Whilst application of the method to epilepsy patients is preliminary, significant changes were reported likely related to the epileptogenic focus in 5 of the 6 selected focal epilepsy patients studied. In several patients, modularity changes in regions distant from the focus were also observed, adding further evidence that the pervasive network effects of focal epilepsy can extend well beyond the seizure onset zone.
When it comes to application of EEG-fMRI to detect the seizure onset zone, there is typically a trade-off between specificity and sensitivity, with the added complication that activity or network changes may also occur in brain regions other than the ictal onset zone. The distant activity may be due to activity propagation from the onset zone, pervasive changes in functional networks creating a ‘permissive state’, or in some cases might be the brain’s attempt to prevent seizures. Specificity and sensitivity of EEG-fMRI to detect the ictal onset zone is explored by (Tousseyn et al., 2014). They determined how rates of true and false positives and negatives varied with voxel height and cluster size thresholds, both for the full statistical parametric map, and for the single cluster that contained the voxel of maximum statistical significance. The latter conferred the advantage of reducing positives remote from the seizure onset zone. As a result, it appeared to be more robust to variations in statistical threshold than analysis of the entire map. One needs to be cautious however, given the small numbers of patients studied, and the fact that the “optimal” settings were determined using receiver operator characteristic curves of the same study data. It remains to be seen how well this might generalise to a different study.
Perhaps the greatest potential for future advancement in EEG-fMRI is in methods to make the most of the all the information captured by each modality. This is highlighted by the work of Deligianni et al, demonstrating with a novel analysis framework the potential to obtain more information on the human functional connectome by utilising EEG and fMRI together (Abbott, 2016; Deligianni et al., 2014).
We hope that you enjoy this collection of papers providing a broad snapshot of advances in brain mapping methods and application to better understand epilepsy.

via Frontiers | Editorial: Functional brain mapping of epilepsy networks: methods and applications | Neuroscience

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[Abstract] Impact of transcranial direct current stimulation on structural plasticity of the somatosensory system

Significance Recently, it has been shown that repeated anodal transcranial direct current stimulation (tDCS) applied to the somatosensory system induces functionalchanges at its site of application in the primary somatosensory cortex and therefore at an early stage of information processing (Hilgenstock, Weiss, Huonker, & Witte, ). The present study complements this finding by showing that tDCS also affects the somatosensory system on a structural level, however, at a late stage of decision making, probably at the stage of decision readout. Thus, tDCS seems capable of inducing changes at all levels of the somatosensory processing hierarchy.

Abstract

While there is a growing body of evidence regarding the behavioral and neurofunctional changes in response to the longitudinal delivery of transcranial direct current stimulation (tDCS), there is limited evidence regarding its structural effects. Therefore, the present study was intended to investigate the effect of repeatedly applied anodal tDCS over the primary somatosensory cortex on the gray matter (GM) and white matter (WM) compartment of the brain. Structural tDCS effects were, moreover, related to effects evidenced by functional imaging and behavioral assessment. tDCS was applied over the course of 5 days in 25 subjects with concomitant assessment of tactile acuity of the right and left index finger as well as imaging at baseline, after the last delivery of tDCS and at follow‐up 4 weeks thereafter. Irrespective of the stimulation condition (anodal vs. sham), voxel‐based morphometry revealed a behaviorally relevant decrease of GM in the precuneus co‐localized with a functional change of its activity. Moreover, there was a decrease in GM of the bilateral lingual gyrus and the right cerebellum. Diffusion tensor imaging analysis showed an increase of fractional anisotropy exclusively in the tDCSanodal condition in the left frontal cortex affecting the final stretch of a somatosensory decision making network comprising the middle and superior frontal gyrus as well as regions adjacent to the genu of the corpus callosum. Thus, this is the first study in humans to identify structural plasticity in the GM compartment and tDCS‐specific changes in the WM compartment in response to somatosensory learning.

 

via Impact of transcranial direct current stimulation on structural plasticity of the somatosensory system – Hirtz – 2018 – Journal of Neuroscience Research – Wiley Online Library

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[ARTICLE] Impact of transcranial direct current stimulation on structural plasticity of the somatosensory system – Full Text

Abstract

While there is a growing body of evidence regarding the behavioral and neurofunctional changes in response to the longitudinal delivery of transcranial direct current stimulation (tDCS), there is limited evidence regarding its structural effects. Therefore, the present study was intended to investigate the effect of repeatedly applied anodal tDCS over the primary somatosensory cortex on the gray matter (GM) and white matter (WM) compartment of the brain. Structural tDCS effects were, moreover, related to effects evidenced by functional imaging and behavioral assessment. tDCS was applied over the course of 5 days in 25 subjects with concomitant assessment of tactile acuity of the right and left index finger as well as imaging at baseline, after the last delivery of tDCS and at follow‐up 4 weeks thereafter. Irrespective of the stimulation condition (anodal vs. sham), voxel‐based morphometry revealed a behaviorally relevant decrease of GM in the precuneus co‐localized with a functional change of its activity. Moreover, there was a decrease in GM of the bilateral lingual gyrus and the right cerebellum. Diffusion tensor imaging analysis showed an increase of fractional anisotropy exclusively in the tDCSanodal condition in the left frontal cortex affecting the final stretch of a somatosensory decision making network comprising the middle and superior frontal gyrus as well as regions adjacent to the genu of the corpus callosum. Thus, this is the first study in humans to identify structural plasticity in the GM compartment and tDCS‐specific changes in the WM compartment in response to somatosensory learning.

1 INTRODUCTION

Recently, we reported effects of repeatedly applied anodal transcranial direct current stimulation (tDCS) on tactile acuity learning of the dominant (right) index finger (IF) and concomitant neural changes as investigated by functional magnetic resonance imaging (fMRI) (Hilgenstock, Weiss, Huonker, & Witte, 2016). Relying on the same study, this article focuses on the structural underpinnings of these findings as investigated by voxel‐based morphometry (VBM) and diffusion tensor imaging (DTI).

tDCS is the application of a weak current exerting local effects on membrane potential (Bindman, 1965; Purpura & McMurtry, 1965) and neurotransmitter release (e.g., Clark, Coffman, Trumbo, & Gasparovic, 2011; Hone‐Blanchet, Edden, & Fecteau, 2016) as well as global effects on network functioning (e.g., Bachtiar, Near, Johansen‐Berg, & Stagg, 2015; Kim, Stephenson, Morris, & Jackson, 2014; Polania, Nitsche, & Paulus, 2011; Polania, Paulus, & Nitsche, 2012). Therefore, tDCS has widely been applied to study cognition, motor, and somatosensory functioning (e.g., Das, Holland, Frens, & Donchin, 2016; Stagg & Nitsche, 2011) but also to explore its beneficial potential in pathological states (e.g., Allman et al., 2016; Lindenberg, Renga, Zhu, Nair, & Schlaug, 2010; Lindenberg, Zhu, & Schlaug, 2012; Mori et al., 2013). With regard to the somatosensory system, anodal tDCS induces short‐term (e.g., Fujimoto, Yamaguchi, Otaka, Kondo, & Tanaka, 2014; Fujimoto et al., 2016; Ragert, Vandermeeren, Camus, & Cohen, 2008) as well as long‐term (Hilgenstock et al., 2016) effects on tactile acuity. After 5 days of anodal tDCS delivery, there was a profound and bilateral improvement of tactile acuity that persisted for at least 4 weeks. These improvements in tactile acuity were accompanied by changes in brain metabolism interpreted to indicate a more effective recruitment of neural machinery to process somatosensory information (Hilgenstock et al., 2016). Yet, despite the widespread application of tDCS and insights into changes in brain metabolism and connectivity, structural changes in the gray matter (GM) and white matter (WM) compartment of the brain in response to its repeated application have hardly been investigated.

Recently, Allman et al. (2016) were the first to show the capability of tDCS to induce structural changes in the GM compartment of the brain in response to repeatedly applied tDCS in stroke patients undergoing a course of 9 days of tDCS delivery with concomitant daily motor training. To the best of the authors’ knowledge, no study has investigated changes in GM in the somatosensory system in response to somatosensory training or the delivery of tDCS. Studies in the blind, however, indicate changes in GM focusing on the visual system. For example, Modi, Bhattacharya, Singh, Tripathi, and Khushu (2012) observed GM decreases in the lingual gyrus (primary visual cortex), the precuneus, the cerebellum, especially lobule VIIIa and intraparietal areas as well as an GM increase in the middle frontal gyrus (BA 6). Likewise, Voss, Pike, and Zatorre (2014) observed a significantly lower GM density in parts of the visual system and adjacent regions (pre‐/cuneus) in late blinded opposed to sighted individuals.

Changes in the WM compartment of the brain have primarily been investigated by studying fractional anisotropy (FA) (Zheng & Schlaug, 2015) that indicates organizational and directional changes in the diffusivity of water molecules in the WM compartment (Basser, 1995). Lindenberg, Nachtigall, Meinzer, Sieg, and Flöel (2013) could show that effects of tDCS on motor performance in stroke patients depended on the integrity of transcallosal and corticospinal fibers as characterized by FA (Lindenberg et al., 20122013). Moreover, Zheng and Schlaug (2015) were the first to provide evidence of a behaviorally relevant increase in FA of the so‐called alternate motor fibers (cortico‐rubro‐spinal and cortico‐reticulo‐spinal fibers) in response to repeated anodal tDCS in stroke patients. While there is no study investigating FA changes in the somatosensory domain in response to tDCS, Debowska et al. (2016) revealed changes after training of Braille reading in sighted individuals affecting the primary and secondary somatosensory system, the visual system, and the middle and superior frontal gyrus. In the blind, there is a decrease in WM in the visual system (BA 17, 18) and an increase in the superior frontal gyrus (Modi et al., 2012).

Thus, this article was intended to provide insight into where changes in tactile (acuity) perception emerge both in the GM and WM compartment of the brain (sham stimulation) and how these changes are modified by the repeated delivery of anodal tDCS. Moreover, we were interested in how somatosensory learning (sham stimulation) and its modification by anodal tDCS are implemented by combining findings from the analysis of VBM and DTI data with our previously reported findings from the analysis of fMRI and behavioral data (Hilgenstock et al., 2016). To this end, the analysis of fMRI data will be extended. Given the current state of research, we hypothesized that somatosensory learning and the repeated delivery of anodal tDCS will affect the visual system and its adjacent brain regions as well as prefrontal areas, especially the middle and superior frontal gyrus. There are only a few reports of sex‐specific tDCS‐induced effects (e.g., Chaieb, Antal, & Paulus, 2008; Fumagalli et al., 2010; Kuo, Paulus, & Nitsche, 2006). Yet, to also investigate the possibility of sex‐specific effects of tDCS in the somatosensory domain, we conducted additional exploratory analyses.[…]

 

Continue —> Impact of transcranial direct current stimulation on structural plasticity of the somatosensory system – Hirtz – 2018 – Journal of Neuroscience Research – Wiley Online Library

Figure 2 
(a) Significant decrease of gray matter (GM) density (red) and increase of the BOLD response (green) over the course of study projected on the MNI152 template provided by FSL, family‐wise error‐corrected on a cluster‐level at p < .05. (b) Changes in the BOLD response (green) over the course of the study and changes in relative GM volume (red) relative to baseline at the fifth day of the study (T2) and at follow‐up 4 weeks thereafter (T3) separately plotted for the sham (dark green/dark red) and anodal (light green/light red) condition (Mean ± SEM). (c) Pearson correlation between changes in relative GM volume at T3 relative to T1 and the GOT threshold (millimeter) of the right and left IF. Regression line and 95% confidence interval [Color figure can be viewed at wileyonlinelibrary.com]

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[Abstract] Neuroimaging in epilepsy

Purpose of review Epilepsy neuroimaging is important for detecting the seizure onset zone, predicting and preventing deficits from surgery and illuminating mechanisms of epileptogenesis. An aspiration is to integrate imaging and genetic biomarkers to enable personalized epilepsy treatments.

Recent findings The ability to detect lesions, particularly focal cortical dysplasia and hippocampal sclerosis, is increased using ultra high-field imaging and postprocessing techniques such as automated volumetry, T2 relaxometry, voxel-based morphometry and surface-based techniques. Statistical analysis of PET and single photon emission computer tomography (STATISCOM) are superior to qualitative analysis alone in identifying focal abnormalities in MRI-negative patients. These methods have also been used to study mechanisms of epileptogenesis and pharmacoresistance.

Recent language fMRI studies aim to localize, and also lateralize language functions. Memory fMRI has been recommended to lateralize mnemonic function and predict outcome after surgery in temporal lobe epilepsy.

Summary Combinations of structural, functional and post-processing methods have been used in multimodal and machine learning models to improve the identification of the seizure onset zone and increase understanding of mechanisms underlying structural and functional aberrations in epilepsy.

via Neuroimaging in epilepsy : Current Opinion in Neurology

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[Abstract+References] Action, observation or imitation of virtual hand movement affect differently regions of the mirror neuron system and the default mode network

Abstract

Virtual reality (VR)-based paradigms use visual stimuli that can modulate visuo-motor networks leading to the stimulation of brain circuits. The aims of this study were to compare the changes in blood-oxygenation level dependent (BOLD) signal when watching and imitating moving real (RH) and virtual hands (VH) in 11 healthy participants (HP). No differences were found between the observation of RH or VH making this VR-based experiment a promising tool for rehabilitation protocols. VH-imitation involved more the ventral premotor cortex (vPMC) as part of the mirror neuron system (MNS) compared to execution and VH-observation conditions. The dorsal-anterior Precuneus (da-Pcu) as part of the Precuneus/posterior Cingulate Cortex (Pcu/pCC) complex, a key node of the Default Mode Network (DMN), was also less deactivated and therefore more involved. These results may reflect the dual visuo-motor roles for the vPMC and the implication of the da-Pcu in the reallocation of attentional and neural resources for bimodal task management. The ventral Pcu/pCC was deactivated regardless of the condition confirming its role in self-reference processes. Imitation of VH stimuli can then modulate the activation of specific areas including those belonging to the MNS and the DMN.

 

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[ARTICLE] Leap Motion-based virtual reality training for improving motor functional recovery of upper limbs and neural reorganization in subacute stroke patients – Full Text

 

Abstract

Virtual reality is nowadays used to facilitate motor recovery in stroke patients. Most virtual reality studies have involved chronic stroke patients; however, brain plasticity remains good in acute and subacute patients. Most virtual reality systems are only applicable to the proximal upper limbs (arms) because of the limitations of their capture systems. Nevertheless, the functional recovery of an affected hand is most difficult in the case of hemiparesis rehabilitation after a stroke. The recently developed Leap Motion controller can track the fine movements of both hands and fingers. Therefore, the present study explored the effects of a Leap Motion-based virtual reality system on subacute stroke. Twenty-six subacute stroke patients were assigned to an experimental group that received virtual reality training along with conventional occupational rehabilitation, and a control group that only received conventional rehabilitation. The Wolf motor function test (WMFT) was used to assess the motor function of the affected upper limb; functional magnetic resonance imaging was used to measure the cortical activation. After four weeks of treatment, the motor functions of the affected upper limbs were significantly improved in all the patients, with the improvement in the experimental group being significantly better than in the control group. The action performance time in the WMFT significantly decreased in the experimental group. Furthermore, the activation intensity and the laterality index of the contralateral primary sensorimotor cortex increased in both the experimental and control groups. These results confirmed that Leap Motion-based virtual reality training was a promising and feasible supplementary rehabilitation intervention, could facilitate the recovery of motor functions in subacute stroke patients. The study has been registered in the Chinese Clinical Trial Registry (registration number: ChiCTR-OCH-12002238).

Introduction

Chronic conditions such as stroke are becoming more prevalent as the world’s population ages (Christensen et al., 2009). Although the number of fatalities caused by stroke has fallen in most countries, stroke is still a leading cause of acquired adult hemiparesis (Langhorne et al., 2009; Liu and Duan, 2017). Up to 85% of patients who survive a stroke experience hemiparesis, resulting in impaired movement of an arm and hand (Nakayama et al., 1994). Among them, a large proportion (46% to 95%) remain symptomatic six months after experiencing an ischemic stroke (Kong et al., 2011). The loss of upper limb function adversely affects the quality of life and impedes the normal use of other body parts. The motor function recovery of the upper limbs is more difficult than that of the lower extremities (Kwakkel et al., 1996; Nichols-Larsen et al., 2005; Día and Gutiérrez, 2013). Functional motor recovery in the affected upper extremities in patients with hemiparesis is the primary goal of physical therapists (Page et al., 2001). Evidence suggests that repetitive, task-oriented training of the paretic upper extremity is beneficial (Barreca et al., 2003; Wolf et al., 2006). Rehabilitation intervention is a critical part of the recovery and studies have reported that intensive repeated practice is likely necessary to modify the neural organization and favor the recovery of the functional upper limb motor skills of stroke survivors (Brunnstrom, 1966; Kopp et al., 1999; Taub et al., 1999; Wolf et al., 2006; Nudo, 2011). Meta-analyses of clinical trials have indicated that longer sessions of practice promote better outcomes in the case of impairments, thus improving the daily activities of people after a stroke (Nudo, 2011; Veerbeek et al., 2014; Sehatzadeh, 2015; French et al., 2016). However, the execution of these conventional rehabilitation techniques is tedious, resource-intensive, and often requires the transportation of patients to specialized facilities (Jutai and Teasell, 2003; Teasell et al., 2009).

Virtual reality training is becoming a promising technology that can promote motor recovery by providing high-intensity, repetitive, and task-orientated training with computer programs simulating three-dimensional situations in which patients play by moving their body parts (Saposnik et al., 2010, 2011; Kim et al., 2011; Laver et al., 2015; Tsoupikova et al., 2015). The gaming industry has developed a variety of virtual reality systems for both home and clinical applications (Saposnik et al., 2010; Bao et al., 2013; Orihuela-Espina et al., 2013; Gatica-Rojas and Méndez-Rebolledo, 2014). The most difficult task related to hemiparesis rehabilitation after a stroke is the functional recovery of the affected hand (Carey et al., 2002). To facilitate the functional recovery of a paretic hand along with that of the proximal upper extremity, an ideal virtual reality system should be able to track hand position and motion, which is not a feature of most existing virtual reality systems (Jang et al., 2005; Merians et al., 2009). The leap motion controller developed by Leap Motion (https://www.leapmotion.com) provides a means of capturing and tracking the fine movements of the hand and fingers, while controlling a virtual environment requiring hand-arm coordination as part of the practicing of virtual tasks (Iosa et al., 2015; Smeragliuolo et al., 2016).

Most virtual reality studies have often only involved patients who have experienced chronic stroke (Piron et al., 2003; Yavuzer et al., 2008; Saposnik et al., 2010; da Silva Cameirao et al., 2011). For patients in the chronic stage, who had missed the window of opportunity present at the acute and subacute stages (in which the brain plasticity peaks), rehabilitation-therapy-induced neuroplasticity can only be effective within a relatively narrow range (Chen et al., 2002). No motor function recovery of the hands, six months after the onset of a stroke, indicates a poor prognosis for hand function (Duncan et al., 1992).

We hypothesized that Leap Motion-based virtual reality training would facilitate motor functional recovery of the affected upper limb, as well as neural reorganization in subacute stroke patients. Functional magnetic resonance imaging (fMRI), also called blood oxygenation level-dependent fMRI (BOLD-fMRI), is widely used as a non-invasive, convenient, and economical method to examine cerebral function (Ogawa et al., 1990; Iosa et al., 2015; Yu et al., 2016). In the present study, we evaluated the brain function reorganization by fMRI, as well as the motor function recovery of the affected upper limb in patients with subacute stroke using Leap Motion-based virtual reality training.[…]

Continue —>  Leap Motion-based virtual reality training for improving motor functional recovery of upper limbs and neural reorganization in subacute stroke patients Wang Zr, Wang P, Xing L, Mei Lp, Zhao J, Zhang T – Neural Regen Res

Figure 1: Leap Motion-based virtual reality system and training games.
(A, B) Leap Motion-based virtual reality system; (C) petal-picking game; (D) piano-playing game; (E) robot-assembling game; (F) object-catching with balance board game; (G) firefly game; (H) bee-batting game.

 

 

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[Abstract+References] Cortical and functional responses to an early protocol of sensory re-education of the hand using audio–tactile interaction.

Early sensory re-education techniques are important strategies associated with cortical hand area preservation. The aim of this study was to investigate early cortical responses, sensory function outcomes and disability in patients treated with an early protocol of sensory re-education of the hand using an audio-tactile interaction device with a sensor glove model.

After surgical repair of median and/or ulnar nerves, participants received either early sensory re-education twice a week with the sensor glove during three months or no specific sensory training. Both groups underwent standard rehabilitation. Patients were assessed at one, three and six months after surgery on training-related cortical responses by functional magnetic resonance imaging, sensory thresholds, discriminative touch and disability using the Disabilities of the Arm, Shoulder and Hand patient-reported questionnaire.

At six-months, there were no statistically significant differences in sensory function between groups. During functional magnetic resonance imaging, trained patients presented complex cortical responses to auditory stimulation indicating an effective connectivity between the cortical hand map and associative areas.

Training with the sensor glove model seems to provide some type of early cortical audio-tactile interaction in patients with sensory impairment at the hand after nerve injury. Although no differences were observed between groups related to sensory function and disability at the intermediate phase of peripheral reinnervation, this study suggests that an early sensory intervention by sensory substitution could be an option to enhance the response on cortical reorganization after nerve repair in the hand. Longer follow-up and an adequately powered trial is needed to confirm our findings.

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via Cortical and functional responses to an early protocol of sensory re-education of the hand using audio–tactile interactionHand Therapy – Raquel Metzker Mendes, Carlo Rondinoni, Marisa de Cássia Registro Fonseca, Rafael Inácio Barbosa, Carlos Ernesto Garrido Salmón, Cláudio Henrique Barbieri, Nilton Mazzer, 2017

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[ARTICLE] Fatigue and Cognitive Fatigability in Mild Traumatic Brain Injury are Correlated with Altered Neural Activity during Vigilance Test Performance – Full Text

Introduction: Fatigue is the most frequently reported persistent symptom following a mild traumatic brain injury (mTBI), but the explanations for the persisting fatigue symptoms in mTBI remain controversial. In this study, we investigated the change of cerebral blood flow during the performance of a psychomotor vigilance task (PVT) by using pseudo-continuous arterial spin labeling (PCASL) MRI technique to better understand the relationship between fatigability and brain activity in mTBI.

Material and methods: Ten patients (mean age: 37.5 ± 11.2 years) with persistent complaints of fatigue after mTBI and 10 healthy controls (mean age 36.9 ± 11.0 years) were studied. Both groups completed a 20-min long PVT inside a clinical MRI scanner during simultaneous measurements of reaction time and regional cerebral blood flow (rCBF) with PCASL technique. Cognitive fatigability and neural activity during PVT were analyzed by dividing the performance and rCBF data into quintiles in addition to the assessment of self-rated fatigue before and after the PVT.

Results: The patients showed significant fatigability during the PVT while the controls had a stable performance. The variability in performance was also significantly higher among the patients, indicating monitoring difficulty. A three-way ANOVA, modeling of the rCBF data demonstrated that there was a significant interaction effect between the subject group and performance time during PVT in a mainly frontal/thalamic network, indicating that the pattern of rCBF change for the mTBI patients differed significantly from that of healthy controls. In the mTBI patients, fatigability at the end of the PVT was related to increased rCBF in the right middle frontal gyrus, while self-rated fatigue was related to increased rCBF in left medial frontal and anterior cingulate gyri and decreases of rCBF in a frontal/thalamic network during this period.

Discussion: This study demonstrates that PCASL is a useful technique to investigate neural correlates of fatigability and fatigue in mTBI patients. Patients suffering from fatigue after mTBI used different brain networks compared to healthy controls during a vigilance task and in mTBI, there was a distinction between rCBF changes related to fatigability vs. perceived fatigue. Whether networks for fatigability and self-rated fatigue are different, needs to be investigated in future studies.

Introduction

Fatigue is a frequently reported symptom after mild traumatic brain injury (mTBI) (13) and a major reason why patients fail to return to work (4). The subjective experience of fatigue may be concomitant with physiological fatigue or with deteriorating performance, but may also be a sole complaint (56). Research on the relationship between underlying neural correlates to fatigue in mTBI, and possible performance decrements is complicated by the fact that fatigue is still not a well-defined concept. It is multidimensional in its nature, involving both physiological and psychological components (79) and, therefore, a single explanatory mechanism is unlikely (310).

Kluger and coworkers (11) suggested distinguishing the self-rated fatigue measures from objective measures of fatigue by labeling the later as fatigability. Such distinction might encourage among others more focused correlational studies; such as fatigue in relation to the neural activity. Measuring performance during sustained cognitive process provides a method to evaluate fatigue/fatigability objectively (1214). For example, sustained attention during vigilance performance is a demanding cognitive task and performance induced fatigability has been demonstrated as increased error rate and reaction time (15). Our group has also found fatigability in mTBI on a higher order attention demanding task (16).

More recently, we studied the behavioral correlates of changes in resting-state functional connectivity before and after performing a 20-min psychomotor vigilance task (PVT) for mTBI patients with persistent post-concussion fatigue (17). Taking advantage of a quantitative data-driven analysis approach developed by us, we were able to demonstrate that there was a significant linear correlation between the self-rated fatigue and functional connectivity in the thalamus and middle frontal cortex. Furthermore, we found that the 20 min PVT was sufficiently sensitive to invoke significant mental fatigue and specific functional connectivity changes in mTBI patients. These findings indicate that resting-state functional MRI (fMRI) measurements before and after a 20 min PVT may serve as a useful method for objective assessment of fatigue level in the neural attention system. However, these measurements neither provide any information about the dynamic change of the neural activities in the involved functional networks during the performance of PVT nor can they answer whether other neural systems mediate the observed functional connectivity change in the attention network.

Arterial spin labeling (ASL) MRI technique has recently been used to examine the cerebral blood flow (CBF) in patients with amnestic mild cognitive impairment and cognitively normal healthy controls both at rest and during the active performance of a memory task (18). As compared to rest, CBF measurement during the task performance showed increased group difference between patients and healthy controls indicating that CBF measures during a cognitive task may increase the discriminatory ability and the sensitivity to detect subtle functional changes in neurological diseases. In another ASL MRI study, Lim et al. (19) investigated the neural correlates of cognitive fatigue effects in a group of healthy volunteers during a 20-min PVT (19). They observed progressively slower reaction times and significantly increased mental fatigue ratings after the task and reported that such persistent cognitive fatigue effect was significantly correlated with regional cerebral blood flow (rCBF) decline in the right fronto-parietal attention network in addition to the basal ganglia and sensorimotor cortices. They also found that the rCBF at rest in the thalamus and right middle frontal gyrus before the PVT task was predictive of subjects’ subsequent performance decline. Based on these findings, they claimed that the rCBF at rest in the attention network might be a useful indicator of performance potential and a marker of the level of fatigue in neural attention system. However, it remains to be clarified how the relationship between the neural activity in mTBI patients and their fatigability is dynamically influenced by the performance of a difficult cognitive task.

Pseudo-Continuous Arterial Spin Labeling (PCASL) can provide quantitative rCBF measurements with whole-brain coverage and high signal-to-noise ratio. Furthermore, it is non-invasive and repetitive experiments can be carried out. It has been shown that fMRI experiments based on PCASL perfusion measurements may have higher sensitivity than experimental designs based on blood oxygenation level-dependent (BOLD) fMRI, particularly when studying slow neural activity changes within a subject (2022) and useful as a biomarker of brain function (18). To shed light on the questions discussed above, in this study we used PCASL MRI technique to measure the rCBF changes during a 20 min PVT in a group of mTBI patients with chronic fatigue and matched healthy control subjects. The aims of the present study are the following: (1) evaluate the PVT induced fatigability over time by dividing the performance data (error rate and reaction time) into quintiles to verify if the change of fatigability for mTBI patients follows the same pattern as that for healthy controls; (2) estimate the dynamic change of neural activity during PVT in terms of rCBF measurements in each quintile to reveal brain activities significantly associated with the change of fatigability. (3) Voxel-wise assessment of the rCBF values pre- and post-PVT to detect brain activity associated with changes in self-rated fatigue level. […]

Continue —> Frontiers | Fatigue and Cognitive Fatigability in Mild Traumatic Brain Injury are Correlated with Altered Neural Activity during Vigilance Test Performance | Neurology

Figure 4. Summary of the F-score results from the three-way ANOVA modeling of the regional cerebral blood flow data acquired during a 20-min psychomotor vigilance task (PVT) performance to illustrate the brain regions of statistically significant differences (family-wise error rate, p ≤ 0.05) in neural activity associated with the two fixed factors (the PVT performance time and subject group) and their interaction. (A) The effect of PVT performance time; (B) the interaction effect between the PVT performance time and subject groups. The color bar indicates the F-score of the three-way ANOVA results.

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[ARTICLE] Functional Magnetic Resonance Imaging of Cognitive Control following Traumatic Brain Injury

Novel and non-routine tasks often require information processing and behavior to adapt from moment to moment depending on task requirements and current performance. This ability to adapt is an executive function that is referred to as cognitive control. Patients with moderate-to-severe traumatic brain injury (TBI) have been reported to exhibit impairments in cognitive control and functional magnetic resonance imaging (fMRI) has provided evidence for TBI-related alterations in brain activation using various fMRI cognitive control paradigms. There is some support for greater and more extensive cognitive control-related brain activation in patients with moderate-to-severe TBI, relative to comparison subjects without TBI. In addition, some studies have reported a correlation between these activation increases and measures of injury severity. Explanations that have been proposed for increased activation within structures that are thought to be directly involved in cognitive control, as well as the extension of this over-activation into other brain structures, have included compensatory mechanisms, increased demand upon normal processes required to maintain adequate performance, less efficient utilization of neural resources, and greater vulnerability to cognitive fatigue. Recent findings are also consistent with the possibility that activation increases within some structures, such as the posterior cingulate gyrus, may reflect a failure to deactivate components of the default mode network (DMN) and that some cognitive control impairment may result from ineffective coordination between the DMN and components of the salience network. Functional neuroimaging studies examining cognitive control-related activation following mild TBI (mTBI) have yielded more variable results, with reports of increases, decreases, and no significant change. These discrepancies may reflect differences among the various mTBI samples under study, recovery of function in some patients, different task characteristics, and the presence of comorbid conditions such as depression and posttraumatic stress disorder that also alter brain activation. There may be mTBI populations with activation changes that overlap with those found following more severe injuries, including symptomatic mTBI patients and those with acute injuries, but future research to address such dysfunction will require well-defined samples with adequate controls for injury characteristics, comorbid disorders, and severity of post-concussive symptoms.

Traumatic brain injury (TBI) is a neurological insult of major public health significance with over 1.7 million new injuries each year among Americans under the age of 35 (1). Numerous studies, most of which have been conducted with moderate-to-severe TBI due to blunt head trauma, have reported findings consistent with a mixed and highly heterogeneous neuropathology that may include multifocal or diffuse axonal injury, as well contusions and other focal lesions (2). Additional injury may occur as a result of edema, herniation, hemorrhage, ischemia, inflammation, and excitotoxic processes (2, 3). Structures and connections of the frontal and limbic regions have been said to be especially vulnerable to these various pathological processes (3, 4). Executive functions are highly dependent on the integrity of this neural substrate, and it is not surprising that such functions, including cognitive control, are often impaired following TBI (57).

Cognitive control allows for flexibility in human thought and behavior and may be defined as the ability to pursue task-related goals in the presence of conditions that include conflicting information or interference, prepotent response alternatives, or the need to interrupt or switch an ongoing activity (810). A common factor in all of these situations is the top-down direction, or biasing, of cognition and this is necessary for information processing and behavior to adapt from moment to moment depending on task requirements and performance (8, 11, 12). Cognitive control relies upon the active maintenance of neural activity associated with the internal representation of goals and task-related rules or contingencies (1113). However, it is a complex construct that likely includes multiple component processes, some of these processes overlap with those of other executive functions (e.g., working memory), and it contributes to performance on various high level cognitive tasks, including those representing domains such as attention, memory, and language (810, 14).

Although prefrontally guided top-down direction is critical for cognitive control and other executive functions, the prefrontal cortex (PFC) is only one of several structures that contribute to cognitive control (15). Another important structure is the anterior cingulate cortex, which is thought to monitor performance and internal bodily states associated with task-related reward conditions, to determine whether task performance is adequate, and to signal to the dorsolateral PFC when mental effort or top-down direction needs to be increased (11, 1517). Some anterior cingulate functions, including the detection of states associated with reward and expected outcomes, likely depend on distant connections with structures such as the insula (17). These various structures may be vulnerable to disconnection associated with diffuse axonal injury and other TBI-related neuropathology (1820).

Functional magnetic resonance imaging (fMRI) provides an indirect measure of neural activity and has the potential to reveal changes in brain function associated with neuropathology, including alterations following TBI (21, 22). One powerful application of this method is the use of fMRI paradigms to examine brain activation during cognitive tasks (22), including those which place a demand upon executive functions such as cognitive control. This type of research has the potential to reveal relationships between specific cognitive impairments and dysfunction within the underlying neural substrate, to provide a neuroimaging marker that may contribute to differential diagnosis, and to lead to the development of methods to track changes in brain activity associated with recovery and treatment (23). Cognitive control is a high level function that is critical for the completion of many complex and non-routine tasks (8, 11). Despite the importance of this topic and the incredible potential offered by fMRI research, only a few studies have examined changes in cognitive control-related activation following TBI, and these have often suffered from various methodological limitations. The purpose of this article is to provide an overview of that existing research, to discuss findings that contribute to our understanding of how cognitive control may be impaired following TBI, and to provide some suggestions to improve future research and increase its relevance.

Although fMRI research has also investigated working memory and other executive functions following TBI (24, 25), the current review will focus on cognitive control by examining fMRI studies that have specifically addressed the top-down direction of cognition and related cognitive control processes (e.g., performance monitoring). This research has employed fMRI paradigms adapted from common clinical measures of cognitive control, such as the Stoop Test (26), as well as experimental procedures developed specifically for the purpose of acquiring fMRI data [e.g., Ref. (27)]. Studies using paradigms that assess other functions, such as working memory or attention, are also included within this review if they had incorporated procedures to investigate top-down control [e.g., Ref. (28)]. Some had utilized a block design approach [e.g., Ref. (29)], whereas others had employed event-related fMRI [e.g., Ref. (30)]. A major feature of block design fMRI paradigms is that this method combines images acquired across an entire block of trials, which then prevents the separation of images acquired within a block to examine activation relative to different types of stimuli or responses (31). Event-related designs have the advantage of allowing the examination of images at the trial level, including the ability to isolate correct or incorrect responses, but these designs typically have less statistical power (31). It is also possible to capitalize upon some of the advantages of both approaches by employing a mixed design (32). […]

Continue —> Frontiers | Functional Magnetic Resonance Imaging of Cognitive Control following Traumatic Brain Injury | Neurology

Figure 3. Integrity of the white matter tract connecting the right anterior insula with the pre-supplementary motor area and the dorsal anterior cingulate cortex (rAI-preSMA/dACC) predicts default mode network deactivation during the stop-signal task. (A) Coronal view of the rAI-preSMA/dACC tract (blue) overlaid on the activation map for the contrast comparing correct stop trials with correct go trials (StC > Go) in traumatic brain injury (TBI) patients (orange). (B) Fractional anistropy (FA) of the rAI-preSMA/dACC tracts in TBI patients plotted against the percent signal change within a precuneus/posterior cingulate gyrus (Precu/PCC) region of interest on correct stop trials relative to go trials. FA measures are normalized and are corrected for age and whole-brain FA. (C) Sagittal view of brain regions with a negative correlation between activation for the StC > Go contrast and FA within the rAI-preSMA/dACC tract. Activation is superimposed on the Montreal Neurological Institute 152 T1 template (R = right side of image) [reused with permission from Ref. (18)].

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[OPINION ARTICLE] Can Functional Magnetic Resonance Imaging Generate Valid Clinical Neuroimaging Reports? – Full Text

imageRoland Beisteiner* Study Group Clinical fMRI, High Field MR Center, Department of Neurology, Medical University of Vienna, Vienna, Austria

A highly critical issue for applied neuroimaging in neurology—and particularly for functional neuroimaging—concerns the question of validity of the final clinical result. Within a clinical context, the question of “validity” often equals the question of “instantaneous repeatability,” because clinical functional neuroimaging is done within a specific pathophysiological framework. Here, not only every brain is different but also every pathology is different, and most importantly, individual pathological brains may rapidly change in short time.

Within the brain mapping community, the problem of validity and repeatability of functional neuroimaging results has recently become a major issue. In 2016, the Committee on Best Practice in Data Analysis and Sharing from the Organization for Human Brain Mapping (OHBM) created recommendations for replicable research in neuroimaging, focused on magnetic resonance imaging and functional magnetic resonance imaging (fMRI). Here, “replication” is defined as “Independent researchers use independent data and … methods to arrive at the same original conclusion.” “Repeatability” is defined as repeated investigations performed “with the same method on identical test/measurement items in the same test or measuring facility by the same operator using the same equipment within short intervals of time” (ISO 3534-2:2006 3.3.5). An intermediate position between replication and repeatability is defined for “reproducibility”: repeated investigations performed “with the same method on identical test/measurement items in different test or measurement facilities with different operators using different equipment” (ISO 3534-2:2006 3.3.10). Further definitions vary depending on the focus, be it the “measurement stability,” the “analytical stability,” or the “generalizability” over subjects, labs, methods, or populations.

The whole discussion was recently fueled by an PNAS article published by Eklund et al. (1), which claims that certain results achieved with widely used fMRI software packages may generate false-positive results, i.e., show brain activation where is none. More specifically, when looking at activation clusters defined by the software as being significant (clusterwise inference), the probability of a false-positive brain activation is not 5% but up to 70%. This was true for group as well as single subject data (2). The reason lies in an “imperfect” model assumption about the distribution of the spatial autocorrelation of functional signals over the brain. A squared exponential distribution was assumed but found not to be correct for the empirical data. This article received heavy attention and discussion in scientific and public media and a major Austrian newspaper titled “Doubts about thousands of brain research studies.” A recent PubMed analysis indicates already 69 publications citing the Eklund work. Critical comments by Cox et al. (3)—with focusing on the AFNI software results—criticize the authors for “their emphasis on reporting the single worst result from thousands of simulation cases,” which “greatly exaggerated the scale of the problem.” Other groups extended the work. With regard to the fact that “replicability of individual studies is an acknowledged limitation,” Eickhoff et al. (4) suggest that “Coordinate-based meta-analysis offers a practical solution to this limitation.” They claim that meta-analyses allow “filtering and consolidating the enormous corpus of functional and structural neuroimaging results” but also describe “errors in multiple-comparison corrections” in GingerALE, a software package for coordinate-based meta-analysis. One of their goals is to “exemplify and promote an open approach to error management.” More generally and probably also triggered by the Eklund paper, Nissen et al. (5) discuss the current situation that “Science is facing a ‘replication crisis’.” They focus on the publicability of negative results and model “the community’s confidence in a claim as a Markov process with successive published results shifting the degree of belief.” Important findings are, that “unless a sufficient fraction of negative results are published, false claims frequently can become canonized as fact” and “Should negative results become easier to publish … true and false claims would be more readily distinguished.”

As a consequence of this discussion, public skepticism about the validity of clinical functional neuroimaging arose. At first sight, this seems to be really bad news for clinicians. However, at closer inspection, it turns out that particularly the clinical neuroimaging community has already long been aware of the problems with standard (“black box”) analyses of functional data recorded from compromised patients with largely variable pathological brains. Quite evidently, methodological assumptions as developed for healthy subjects and implemented in standard software packages may not always be valid for distorted and physiologically altered brains. There are specific problems for clinical populations and particularly for defining the functional status of an individual brain (as opposed to a “group brain” in group studies). With task-based fMRI—the most important clinical application—the major problems may be categorized in “patient problems” and “methodological problems.”

Critical patient problems concern:

  • – Patient compliance may change quickly and considerably.
  • – The patient may “change” from 1 day to the other (altered vigilance, effects of pathology and medication, mood changes—depression, exhaustion).
  • – The clinical state may “change” considerably from patient to patient (despite all having the same diagnosis). This is primarily due to location and extent of brain pathology and compliance capabilities.

Critical methodological problems concern:

  • – Selection of clinically adequate experimental paradigms (note paresis, neglect, aphasia).
  • – Performance control (particularly important in compromised patients).
  • – Restriction of head motion (in patients artifacts may be very large).
  • – Clarification of the signal source (microvascular versus remote large vessel effects).
  • – Large variability of the contrast to noise ratio from run to run.
  • – Errors with inter-image registration of brains with large pathologies.
  • – Effects of data smoothing, definition of adequate functional regions of interest, and definition of essential brain activations.
  • – Difficult data interpretation requires specific clinical fMRI expertise and independent validation of the local hardware and software performance (preferably with electrocortical stimulation).

All these problems have to be recognized and specific solutions have to be developed depending on the question at hand—generation of an individual functional diagnosis or performance of a clinical group study. To discuss such problems and define solutions, clinical functional neuroimagers have already assembled early (Austrian Society for fMRI,1 American Society of Functional Neuroradiology2) and just recently the Alpine Chapter from the OHBM3 was established with a dedicated focus on applied neuroimaging. Starting in the 1990s (6), this community published a considerable number of clinical methodological investigations focused on the improvement of individual patient results and including studies on replication, repeatability, and reproducibility [compare (7)]. Early examples comprise investigations on fMRI signal sources (8), clinical paradigms (9), reduction of head motion artifacts (10), and fMRI validation studies (11, 12). Of course the primary goal of this clinical research is improvement of the validity of the final clinical result. One of the suggested clinical procedures focuses particularly on instantaneous replicability as a measure of validity [Risk Map Technique (1315); see Figure 1] with successful long-term clinical use. This procedure was developed for presurgical fMRI and minimizes methodological assumptions to stay as close to the original data as possible. This is done by avoiding data smoothing and normalization procedures and minimization of head motion artifacts by helmet fixation (avoiding artifacts instead of correcting them). It is interesting to note that in the Eklund et al. (1) analysis it was also the method with minimal assumptions (a non-parametric permutation), which was the only one that achieved correct (nominal) results. The two general ideas of the risk map technique are (a) to use voxel replicability as a criterion for functionally most important voxels (extracting activation foci = voxels with largest risk for a functional deficit when lesioned) and (b) to consider regional variability of brain conditions (e.g., close to tumor) by variation of the hemodynamic response functions (step function/HRF/variable onset latencies) and thresholds. The technique consists only of few steps, which can easily be realized by in house programming: (i) Record up to 20 short runs of the same task type to allow checking of repeatability. (ii) Define a reference function (e.g., step function with a latency of 1 TR). (iii) Calculate Pearson correlation r for every voxel and every run. (iv) Color code voxels according to their reliability at a given correlation threshold (e.g., r > 0.5): yellow voxels >75%, orange voxels >50%, red voxels >25% of runs need to be active. (v) Repeat (i)–(iv) with different reference functions (to our experience, a classical HRF and two step functions with different latencies are sufficient to evaluate most patients) and at different correlation thresholds (e.g., r > 0.2 to r > 0.9). The clinical fMRI expert performs a comprehensive evaluation of all functional maps with consideration of patient pathology, patient performance, and the distribution and level of artifacts [compare descriptions in Ref. (13, 15)]. The final clinical result is illustrated in Figure 1, and a typical interpretation would be: most reliable activation of the Wernicke area is found with a step function of 1 TR latency and shown at Pearson correlation r > 0.5. It is important to note that risk maps extract the most active voxel(s) within a given brain area and judgment of a “true” activation extent is not possible. However, due to the underlying neurophysiological principles [gradients of functional representations (16)], it is questionable whether “true” activation extents of fMRI activations can be defined with any technique.

 

Figure 1. Example for a missing language activation (Wernicke activity, white arrow) with a “black box” standard analysis (right, SPM12 applying motion regression and smoothing, voxelwise inference FWE <0.05, standard k = 25) using an overt language design [described in Ref. (17)]. Wernicke activity is detectable with the clinical risk map analysis (left) based on activation replicability (yellow = most reliabel voxels). Patient with left temporoparietal tumor.

The importance to check individual patient data from various perspectives instead of relying on a “standard statistical significance value,” which may not correctly reflect the individual patients signal situation, has also been stressed by other authors [e.g., Ref. (18)]. Of course, clinical fMRI—as all other applied neuroimaging techniques—requires clinical fMRI expertise and particularly pathophysiological expertise to be able to conceptualize where to find what, depending on the pathologies of the given brain. One should be aware that full automatization is currently not possible neither for a comparatively simple analysis of a chest X-ray nor for applied neuroimaging. In a clinical context, error estimations still need to be supported by the fMRI expert and cannot be done by an algorithm alone. As a consequence, the international community started early with offering dedicated clinical methodological courses (compare http://oegfmrt.org or http://ohbmbrainmappingblog.com/blog/archives/12-2016). Meanwhile, there are enough methodological studies that enable an experienced clinical fMRI expert to safely judge the possibilities and limitations for a valid functional report in a given patient with his/her specific pathologies and compliance situation. Of course, this also requires adequate consideration of the local hard- and software. Therefore and particularly when considering the various validation studies, neither for patients nor for doctors there is a need to raise “doubts about clinical fMRI studies” but instead good reason to “keep calm and scan on.”4

Author Contributions

The author confirms being the sole contributor of this work and approved it for publication.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The methodological developments have been supported by the Austrian Science Fund (KLI455, KLI453, P23611) and Cluster Grants of the Medical University of Vienna and the University of Vienna, Austria.

Footnotes

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Source: Frontiers | Can Functional Magnetic Resonance Imaging Generate Valid Clinical Neuroimaging Reports? | Neurology

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