Reliability measures of functional magnetic resonance imaging in a longitudinal evaluation of mild cognitive impairment

Gamma neuromodulation improves episodic memory and its associated network in amnestic mild cognitive impairment: a pilot study

Amnestic mild cognitive impairment (aMCI) is a predementia stage of Alzheimer's disease associated with dysfunctional episodic memory and limited treatment options. We aimed to characterize feasibility, clinical, and biomarker effects of noninvasive neurostimulation for aMCI. 13 individuals with aMCI received eight 60-minute sessions of 40-Hz (gamma) transcranial alternating current stimulation (tACS) targeting regions related to episodic memory processing. Feasibility, episodic memory, and plasma Alzheimer's disease biomarkers were assessed. Neuroplastic changes were characterized by resting-state functional connectivity (RSFC) and neuronal excitatory/inhibitory balance. Gamma tACS was feasible and aMCI participants demonstrated improvement in multiple metrics of episodic memory, but no changes in biomarkers. Improvements in episodic memory were most pronounced in participants who had the highest modeled tACS-induced electric fields and exhibited the greatest changes in RSFC. Increased RSFC was also associated with greater hippocampal excitability and higher baseline white matter integrity. This study highlights initial feasibility and the potential of gamma tACS to rescue episodic memory in an aMCI population by modulating connectivity and excitability within an episodic memory network.

Moxibustion modulates working memory in patients with amnestic mild cognitive impairment: a functional magnetic resonance imaging study

OBJECTIVE

To investigate the correlation between changes in brain activity associated with working memory and assessment scales of memory scores in amnestic mild cognitive impairment (aMCI) before and after moxibustion therapy.

METHODS

aMCI patients were randomized into the moxibustion treatment (MT) group and the placebo moxibustion (PM) group. Each group received either moxibustion therapy or a placebo moxibustion for eight weeks. Neuropsychological performance and functional brain responses to a working memory task were assessed at baseline and at the end of treatment. Memory function was evaluated individually by the Rivermead behavioral memory test (RBMT), and working memory was assessed by the N-back task.

RESULTS

Compared with the PM group, RBMT score changes were significant ( < 0.05). In the MT group, the accuracy of the N-back texts increased compared with those before the intervention. After moxibustion intervention, the right insula, postcentral gyrus, precentral gyrus, superior temporal gyrus, thalamus, lingual gyrus, calcarine sulcus, posterior cingulate gyrus, middle frontal gyrus and anterior frontal gyrus were significantly activated (= 0.01, Cluster-level Family-Wise Error = 0.05). Pearson correlation analysis showed that the insula, lingual gyrus and posterior cingulate gyrus were associated with changes in N-back score. Spearman correlation analysis showed that the postcentral gyrus, superior temporal gyrus, thalamus, lingual gyrus, and posterior cingulate gyrus were correlated with RBMT score changes.

CONCLUSION

Moxibustion treatment improved memory in aMCI patients and was associated with the activation of the brain region of the insula, lingual gyrus, posterior cingulate gyrus, postcentral gyrus, superior temporal gyrus, and thalamus, which may be an important mechanism by which moxibustion improves the memory function.

Brain Reactions to Opening and Closing the Eyes: Salivary Cortisol and Functional Connectivity

This study empirically assessed the strength and duration of short-term effects induced by brain reactions to closing/opening the eyes on a few well-known resting-state networks. We also examined the association between these reactions and subjects’ cortisol levels. A total of 55 young adults underwent 8-min resting-state fMRI (rs-fMRI) scans under 4-min eyes-closed and 4-min eyes-open conditions. Saliva samples were collected from 25 of the 55 subjects before and after the fMRI sessions and assayed for cortisol levels. Our empirical results indicate that when the subjects were relaxed with their eyes closed, the effect of opening the eyes on conventional resting-state networks (e.g., default-mode, frontal-parietal, and saliency networks) lasted for roughly 60-s, during which we observed a short-term increase in activity in rs-fMRI time courses. Moreover, brain reactions to opening the eyes had a pronounced effect on time courses in the temporo-parietal lobes and limbic structures, both of which presented a prolonged decrease in activity. After controlling for demographic factors, we observed a significantly positive correlation between pre-scan cortisol levels and connectivity in the limbic structures under both conditions. Under the eyes-closed condition, the temporo-parietal lobes presented significant connectivity to limbic structures and a significantly positive correlation with pre-scan cortisol levels. Future research on rs-fMRI could consider the eyes-closed condition when probing resting-state connectivity and its neuroendocrine correlates, such as cortisol levels. It also appears that abrupt instructions to open the eyes while the subject is resting quietly with eyes closed could be used to probe brain reactivity to aversive stimuli in the ventral hippocampus and other limbic structures.

Reliability and stability challenges in ABCD task fMRI data

Trait stability of measures is an essential requirement for individual differences research. Functional MRI has been increasingly used in studies that rely on the assumption of trait stability, such as attempts to relate task related brain activation to individual differences in behavior and psychopathology. However, recent research using adult samples has questioned the trait stability of task-fMRI measures, as assessed by test-retest correlations. To date, little is known about trait stability of task fMRI in children. Here, we examined within-session reliability and long-term stability of individual differences in task-fMRI measures using fMRI measures of brain activation provided by the adolescent brain cognitive development (ABCD) Study Release v4.0 as an individual's average regional activity, using its tasks focused on reward processing, response inhibition, and working memory. We also evaluated the effects of factors potentially affecting reliability and stability. Reliability and stability (quantified as the ratio of non-scanner related stable variance to all variances) was poor in virtually all brain regions, with an average value of 0.088 and 0.072 for short term (within-session) reliability and long-term (between-session) stability, respectively, in regions of interest (ROIs) historically-recruited by the tasks. Only one reliability or stability value in ROIs exceeded the 'poor' cut-off of 0.4, and in fact rarely exceeded 0.2 (only 4.9%). Motion had a pronounced effect on estimated reliability/stability, with the lowest motion quartile of participants having a mean reliability/stability 2.5 times higher (albeit still 'poor') than the highest motion quartile. Poor reliability and stability of task-fMRI, particularly in children, diminishes potential utility of fMRI data due to a drastic reduction of effect sizes and, consequently, statistical power for the detection of brain-behavior associations. This essential issue urgently needs to be addressed through optimization of task design, scanning parameters, data acquisition protocols, preprocessing pipelines, and data denoising methods.

Longitudinal fMRI task reveals neural plasticity in default mode network with disrupted executive-default coupling and selective attention after traumatic brain injury

Executive dysfunctions are common in individuals with Traumatic Brain Injury (TBI). However, change in functional neural coupling of default and executive networks in the post-acute phase (≥ 1 month after injury) patients over time has yet to be understood. During a 5-week observation period, we examined changes in the goal-oriented executive function networks in 20 TBI participants, using a face/scene matching 1-back fMRI task (Chen et al. 2011). We conducted multivariate pattern analysis to assess working memory and visual selective attention, followed by a repeat-measures ANOVA to examine longitudinal changes, with a cluster FDR at p = .001. Results showed that task accuracy significantly improved after follow-up. Significantly increased activity patterns over time were observed in the right dorsolateral prefrontal cortex and right insula. Decreased activity patterns were seen in the left posterior cingulate cortex (PCC), bilateral precuneus, right inferior occipital gyrus and right temporo-occipital junction. Improvement in task accuracy correlated with decreased activity patterns in the PCC (r = -0.478, p = 0.031) and temporo-occipital junction (r = -0.592, p = 0.006), which were interpreted as neural plastic changes. However, we did not observe the default mode network (DMN)-executive network decoupling during task performance that is found in other studies. These results suggest that fMRI of attentional task performance could serve as a potential biomarker for neural plasticity of selective attention in TBI patients in the post-acute phase.

Reliability of single-subject neural activation patterns in speech production tasks

Speech neuroimaging research targeting individual speakers could help elucidate differences that may be crucial to understanding speech disorders. However, this research necessitates reliable brain activation across multiple speech production sessions. In the present study, we evaluated the reliability of speech-related brain activity measured by functional magnetic resonance imaging data from twenty neuro-typical subjects who participated in two experiments involving reading aloud simple speech stimuli. Using traditional methods like the Dice and intraclass correlation coefficients, we found that most individuals displayed moderate to high reliability. We also found that a novel machine-learning subject classifier could identify these individuals by their speech activation patterns with 97% accuracy from among a dataset of seventy-five subjects. These results suggest that single-subject speech research would yield valid results and that investigations into the reliability of speech activation in people with speech disorders are warranted.

Non-classical behavior of the default mode network regions during an information processing task

The default mode network (DMN) efficient deactivation and suppressed functional connectivity (FC) during goal-directed tasks, which require attentional resources, have been considered essential to healthy brain cognition. However, recent studies have shown that DMN regions do not always show the expected behavior. Then, we aimed to investigate the functional activation and connectivity of DMN nodes in young, healthy controls during a goal-directed task. We used an adaptation of the symbol digit modalities test (SDMT) to evaluate the information processing speed (IPS). Twenty-four subjects (10 women, age: 29 ± 7 years) underwent two functional Magnetic Resonance Imaging experiments: one during resting-state and one during a block-designed SDMT paradigm. We superimposed the templates of the DMN on the group activation map and observed the reorganization of the network. For the posterior cingulate cortex (PCC) node of the DMN, which is spatially extensive, comprising the precuneus (dorsal portion) and the posterior cingulate gyrus (PCG, ventral portion), the extent of each region was different between conditions, suggesting different functional roles for them. Therefore, for the functional connectivity (FC) analysis, we split the DMN-PCC region into two regions: left precuneus (BA 7) and PCG. The left precuneus (BA 7) was positively correlated with the left lingual gyrus (BA 17), a task-positive region, and negatively associated with the DMN nodes when comparing task performance with the resting-state condition. The other DMN regions presented the classical antagonistic role during the attentional task. In conclusion, we found that the activation and functional connectivity of the DMN is, in general, suppressed during the information processing. However, the left precuneus BA 7 presented a context-dependent modulatory behavior, working as a transient in-between hub connecting the DMN to task-positive areas. Such findings support studies that show increased activation and excitatory functional connectivity of DMN portions during goal-directed tasks. Moreover, our results may contribute to defining more precise functional correlates of IPS deficits in a wide range of clinical and neurological diseases.

Functional connectivity of the retrosplenial cortex in rats with ischemic stroke is improved by electroacupuncture

BACKGROUND

The aim of this study was to investigate the central mechanism underlying the putative beneficial effects of electroacupuncture (EA) on learning and memory ability of rats with ischemic stroke-induced cognitive deficits by resting-state functional magnetic resonance imaging (fMRI).

METHODS

A rat model of middle cerebral artery occlusion (MCAO)-induced cognitive deficit (MICD) was established. Rats were randomly assigned into a sham-operated control group (SC group, n = 12), untreated MICD model group (MICD group, n = 12), and MICD group receiving EA treatment at GV20 and GV24 (MICD + EA group, n = 12).

RESULTS

Compared to the MICD group, rats in the MICD + EA group receiving EA at GV20 and GV24 exhibited significantly shortened escape latency times and crossed the position of the platform a significantly increased number of times during the Morris water maze test on the 14th day after EA, which suggested EA could significantly improve spatial learning and memory ability. Furthermore, compared to the MICD group, functional connectivity of the left retrosplenial cortex (RSC) with the left hippocampus, left RSC, right RSC, left cingulate gyrus, right cingulate gyrus, right tegmentum of midbrain, and right visual cortex was increased in the MICD + EA group; the MICD group showed decreased functional connectivity of the left RSC with the left hippocampus, right hippocampus, left RSC, right RSC, right amygdaloid body, left visual cortex, and right visual cortex.

CONCLUSION

These findings suggest that EA at GV20 and GV24 might improve the learning and memory ability of MICD rats by increasing the functional connectivity between the RSC and hippocampus, cingulate gyrus and midbrain, which is encouraging for the potential treatment for cognitive impairment secondary to ischemia stroke.

Test-retest reliability in an fMRI study of naming in dementia

fMRI has been used as an outcome measure in dementia treatment studies, with many previous studies comparing only single pre- and post-treatment fMRI scans to determine treatment-induced neural changes, while utilizing single subject experimental designs. The purpose of the current study was to evaluate fMRI test-retest reliability in dementia patients and typical older adults using noun and verb confrontation naming to evaluate the validity of using a single pre/post-treatment scan comparison. Seven individuals with dementia and 9 control participants were tested three times over two months using the same fMRI procedures. Differences in individual and group level activation patterns were observed that varied across time. Additionally, the extent of variability fluctuated across individuals, groups, and the grammatical category of target words. Our findings suggested that one time fMRI scanning may inadequately represent an individual's typical brain activation pattern, particularly an individual with dementia. Thus, multiple imaging baselines are recommended.

Intraclass correlation: Improved modeling approaches and applications for neuroimaging

Intraclass correlation (ICC) is a reliability metric that gauges similarity when, for example, entities are measured under similar, or even the same, well-controlled conditions, which in MRI applications include runs/sessions, twins, parent/child, scanners, sites, and so on. The popular definitions and interpretations of ICC are usually framed statistically under the conventional ANOVA platform. Here, we provide a comprehensive overview of ICC analysis in its prior usage in neuroimaging, and we show that the standard ANOVA framework is often limited, rigid, and inflexible in modeling capabilities. These intrinsic limitations motivate several improvements. Specifically, we start with the conventional ICC model under the ANOVA platform, and extend it along two dimensions: first, fixing the failure in ICC estimation when negative values occur under degenerative circumstance, and second, incorporating precision information of effect estimates into the ICC model. These endeavors lead to four modeling strategies: linear mixed-effects (LME), regularized mixed-effects (RME), multilevel mixed-effects (MME), and regularized multilevel mixed-effects (RMME). Compared to ANOVA, each of these four models directly provides estimates for fixed effects and their statistical significances, in addition to the ICC estimate. These new modeling approaches can also accommodate missing data and fixed effects for confounding variables. More importantly, we show that the MME and RMME approaches offer more accurate characterization and decomposition among the variance components, leading to more robust ICC computation. Based on these theoretical considerations and model performance comparisons with a real experimental dataset, we offer the following general-purpose recommendations. First, ICC estimation through MME or RMME is preferable when precision information (i.e., weights that more accurately allocate the variances in the data) is available for the effect estimate; when precision information is unavailable, ICC estimation through LME or the RME is the preferred option. Second, even though the absolute agreement version, ICC(2,1), is presently more popular in the field, the consistency version, ICC(3,1), is a practical and informative choice for whole-brain ICC analysis that achieves a well-balanced compromise when all potential fixed effects are accounted for. Third, approaches for clear, meaningful, and useful result reporting in ICC analysis are discussed. All models, ICC formulations, and related statistical testing methods have been implemented in an open source program 3dICC, which is publicly available as part of the AFNI suite. Even though our work here focuses on the whole-brain level, the modeling strategy and recommendations can be equivalently applied to other situations such as voxel, region, and network levels.

Changes in Hemodynamic Response Patterns in Motor Cortices Measured by Task-Based Functional Magnetic Resonance Imaging in Patients With Moyamoya Disease

OBJECTIVE

We aimed to study the value of blood oxygen level-dependent functional magnetic resonance imaging (BOLD-fMRI) in assessing cerebral hemodynamic changes for moyamoya disease (MMD).

METHODS

We recruited 15 healthy volunteers, 15 patients with MMD without dyskinesia, and 30 patients with MMD who experienced paroxysmal limb dyskinesia. The BOLD-fMRI scans were obtained during grasping motions of the left or right hand. Hemodynamic response curves in the primary motor cortices were generated. Six response parameters including negative response time (Tnr), maximum signal intensity of negative response, time to peak, maximum peak arrival time, maximum signal intensity of positive response, and positive response time were measured.

RESULTS

The hemodynamic response curve in the primary motor cortices of MMD patients showed extended Tnr, prolonged positive response time, and delayed time to peak than those of the controls. The response curve showed longer Tnr and maximum peak arrival time in the primary motor cortices on the affected side of the dyskinesia group.

CONCLUSIONS

Blood oxygen level-dependent fMRI is an effective technique to assess hemodynamic changes in patients with MMD.

Tracking sentence comprehension: Test-retest reliability in people with aphasia and unimpaired adults

PURPOSE

Visual-world eyetracking is increasingly used to investigate online language processing in normal and language impaired listeners. Tracking changes in eye movements over time also may be useful for indexing language recovery in those with language impairments. Therefore, it is critical to determine the test-retest reliability of results obtained using this method.

METHODS

Unimpaired young adults and people with aphasia took part in two eyetracking sessions spaced about one week apart. In each session, participants completed a sentence-picture matching task in which they listened to active and passive sentences (e.g., The [N1+Auxwoman was] [Vvisiting/visited] [NP/PP2(by) the man]) and selected between two pictures with reversed thematic roles. We used intraclass correlations (ICCs) to examine the test-retest reliability of response measures (accuracy, reaction time (RT)) and online eye movements (i.e., the likelihood of fixating the target picture in each region of the sentence) in each participant group.

RESULTS

In the unimpaired adults, accuracy was at ceiling (thus ICCs were not computed), with moderate ICCs for RT (i.e., 0.4 - 0.58) for passive sentences and low (<0.4) for actives. In individuals with aphasia, test-retest reliability was strong (0.590.75) for RT for both sentence types. Similarly, for the unimpaired listeners, reliability of eye movements was moderate for passive sentences (NP/PP2 region) and low in all regions for active sentences. But, for the aphasic participant group, eye movement reliability was excellent for passive sentences (in the first second after sentence end) and strong for active sentences (V and NP/PP2 regions).

CONCLUSION

Results indicated moderate-to-low reliability for unimpaired listeners; however, reliable eye movement patterns were detected for processes specific to passive sentences (e.g., thematic reanalysis). In contrast, individuals with aphasia exhibited strong and stable performance across sentence types in response measures and online eye movements. These findings indicate that visual-world eyetracking provides a reliable measure of online sentence comprehension, and thus may be useful for investigating sentence processing changes over time.

Brain imaging of neurovascular dysfunction in Alzheimer's disease

Neurovascular dysfunction, including blood-brain barrier (BBB) breakdown and cerebral blood flow (CBF) dysregulation and reduction, are increasingly recognized to contribute to Alzheimer's disease (AD). The spatial and temporal relationships between different pathophysiological events during preclinical stages of AD, including cerebrovascular dysfunction and pathology, amyloid and tau pathology, and brain structural and functional changes remain, however, still unclear. Recent advances in neuroimaging techniques, i.e., magnetic resonance imaging (MRI) and positron emission tomography (PET), offer new possibilities to understand how the human brain works in health and disease. This includes methods to detect subtle regional changes in the cerebrovascular system integrity. Here, we focus on the neurovascular imaging techniques to evaluate regional BBB permeability (dynamic contrast-enhanced MRI), regional CBF changes (arterial spin labeling- and functional-MRI), vascular pathology (structural MRI), and cerebral metabolism (PET) in the living human brain, and examine how they can inform about neurovascular dysfunction and vascular pathophysiology in dementia and AD. Altogether, these neuroimaging approaches will continue to elucidate the spatio-temporal progression of vascular and neurodegenerative processes in dementia and AD and how they relate to each other.

Longitudinal development of frontoparietal activity during feedback learning: Contributions of age, performance, working memory and cortical thickness

•

We performed a longitudinal study on feedback learning (N = 208, age 8–27 years).

•

We tested linear and nonlinear patterns in frontoparietal activity during learning.

•

DLPFC and parietal cortex showed a late-adolescent peak in activity.

•

SMA showed a linear increase, and ACC a linear decrease in brain activity with age.

•

Performance predicted DLPFC and parietal activity, thickness predicted SMA activity.

Feedback learning is a crucial skill for cognitive flexibility that continues to develop into adolescence, and is linked to neural activity within a frontoparietal network. Although it is well conceptualized that activity in the frontoparietal network changes during development, there is surprisingly little consensus about the direction of change. Using a longitudinal design (N = 208, 8–27 years, two measurements in two years), we investigated developmental trajectories in frontoparietal activity during feedback learning. Our first aim was to test for linear and nonlinear developmental trajectories in dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), supplementary motor area (SMA) and anterior cingulate cortex (ACC). Second, we tested which factors (task performance, working memory, cortical thickness) explained additional variance in time-related changes in activity besides age. Developmental patterns for activity in DLPFC and SPC were best characterized by a quadratic age function leveling off/peaking in late adolescence. There was a linear increase in SMA and a linear decrease with age in ACC activity. In addition to age, task performance explained variance in DLPFC and SPC activity, whereas cortical thickness explained variance in SMA activity. Together, these findings provide a novel perspective of linear and nonlinear developmental changes in the frontoparietal network during feedback learning.

Psychobiological operationalization of RDoC constructs: Methodological and conceptual opportunities and challenges

NIMH's Research Domain Criteria (RDoC) project seeks to advance the diagnosis, prevention, and treatment of mental disorders by promoting psychobiological research on dimensional constructs that might cut across traditional diagnostic boundaries (Kozak & Cuthbert, ). At the core of this approach is the notion that these dimensional constructs can be assessed across different units of analysis (e.g., genes, physiology, behavior), enriching the constructs and providing more complete explanations of clinical problems. While the conceptual aspects of RDoC have been discussed in several prior papers, its methodological aspects have received comparatively less attention. For example, how to integrate data from different units of analysis has been relatively unclear. Here, we discuss one means of psychobiologically operationalizing RDoC constructs across different units of analysis (the psychoneurometric approach; Yancey et al., ), highlighting ways in which this approach might be refined in future iterations. We conclude that there is much to be learned from this technique; however, greater attention to scale-development methods and to psychometrics will likely benefit this and other methodological approaches to combining measurements across multiple units of analysis.

Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art

In the last 15 years, many articles have studied brain connectivity in Mild Cognitive Impairment patients with fMRI techniques, seemingly using different connectivity statistical models in each investigation to identify complex connectivity structures so as to recognize typical behavior in this type of patient. This diversity in statistical approaches may cause problems in results comparison. This paper seeks to describe how researchers approached the study of brain connectivity in MCI patients using fMRI techniques from 2002 to 2014. The focus is on the statistical analysis proposed by each research group in reference to the limitations and possibilities of those techniques to identify some recommendations to improve the study of functional connectivity. The included articles came from a search of Web of Science and PsycINFO using the following keywords: f MRI, MCI, and functional connectivity. Eighty-one papers were found, but two of them were discarded because of the lack of statistical analysis. Accordingly, 79 articles were included in this review. We summarized some parts of the articles, including the goal of every investigation, the cognitive paradigm and methods used, brain regions involved, use of ROI analysis and statistical analysis, emphasizing on the connectivity estimation model used in each investigation. The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found. Additionally, the study of brain connectivity in this type of population is not providing, at the moment, any significant information or results related to clinical aspects relevant for prediction and treatment. We propose to follow guidelines for publishing fMRI data that would be a good solution to the problem of study replication. The latter aspect could be important for future publications because a higher homogeneity would benefit the comparison between publications and the generalization of results.

Test-retest reliability of graph metrics of resting state MRI functional brain networks: A review

The employment of graph theory to analyze spontaneous fluctuations in resting state BOLD fMRI data has become a dominant theme in brain imaging studies and neuroscience. Analysis of resting state functional brain networks based on graph theory has proven to be a powerful tool to quantitatively characterize functional architecture of the brain and it has provided a new platform to explore the overall structure of local and global functional connectivity in the brain. Due to its increased use and possible expansion to clinical use, it is essential that the reliability of such a technique is very strongly assessed. In this review, we explore the outcome of recent studies in network reliability which apply graph theory to analyze connectome resting state networks. Therefore, we investigate which preprocessing steps may affect reproducibility the most. In order to investigate network reliability, we compared the test-retest (TRT) reliability of functional data of published neuroimaging studies with different preprocessing steps. In particular we tested influence of global signal regression, correlation metric choice, binary versus weighted link definition, frequency band selection and length of time-series. Statistical analysis shows that only frequency band selection and length of time-series seem to affect TRT reliability. Our results highlight the importance of the choice of the preprocessing steps to achieve more reproducible measurements.

Bringing memory fMRI to the clinic: comparison of seven memory fMRI protocols in temporal lobe epilepsy

fMRI is increasingly implemented in the clinic to assess memory function. There are multiple approaches to memory fMRI, but limited data on advantages and reliability of different methods. Here, we compared effect size, activation lateralisation, and between‐sessions reliability of seven memory fMRI protocols: Hometown Walking (block design), Scene encoding (block design and event‐related design), Picture encoding (block and event‐related), and Word encoding (block and event‐related). All protocols were performed on three occasions in 16 patients with temporal lobe epilepsy (TLE). Group T‐maps showed activity bilaterally in medial temporal lobe for all protocols. Using ANOVA, there was an interaction between hemisphere and seizure‐onset lateralisation (P = 0.009) and between hemisphere, protocol and seizure‐onset lateralisation (P = 0.002), showing that the distribution of memory‐related activity between left and right temporal lobes differed between protocols and between patients with left‐onset and right‐onset seizures. Using voxelwise intraclass Correlation Coefficient, between‐sessions reliability was best for Hometown and Scenes (block and event). The between‐sessions spatial overlap of activated voxels was also greatest for Hometown and Scenes. Lateralisation of activity between hemispheres was most reliable for Scenes (block and event) and Words (event). Using receiver operating characteristic analysis to explore the ability of each fMRI protocol to classify patients as left‐onset or right‐onset TLE, only the Words (event) protocol achieved a significantly above‐chance classification of patients at all three sessions. We conclude that Words (event) protocol shows the best combination of between‐sessions reliability of the distribution of activity between hemispheres and reliable ability to distinguish between left‐onset and right‐onset patients. Hum Brain Mapp 36:1595–1608, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Attempted and successful compensation in preclinical and early manifest neurodegeneration - a review of task FMRI studies

Several models of neural compensation in healthy aging have been suggested to explain brain activity that aids to sustain cognitive function. Applying recently suggested criteria of "attempted" and "successful" compensation, we reviewed existing literature on compensatory mechanisms in preclinical Huntington's disease (HD) and amnestic mild cognitive impairment (aMCI). Both disorders constitute early stages of neurodegeneration ideal for examining compensatory mechanisms and developing targeted interventions. We strived to clarify whether compensation criteria derived from healthy aging populations can be applied to early neurodegeneration. To concentrate on the close coupling of cognitive performance and brain activity, we exclusively addressed task fMRI studies. First, we found evidence for parallels in compensatory mechanisms between healthy aging and neurodegenerative disease. Several studies fulfilled criteria of attempted compensation, while reports of successful compensation were largely absent, which made it difficult to conclude on. Second, comparing working memory studies in preclinical HD and aMCI, we identified similar compensatory patterns across neurodegenerative disorders in lateral and medial prefrontal cortex. Such patterns included an inverted U-shaped relationship of neurodegeneration and compensatory activity spanning from preclinical to manifest disease. Due to the lack of studies systematically targeting all criteria of compensation, we propose an exemplary study design, including the manipulation of compensating brain areas by brain stimulation. Furthermore, we delineate the benefits of targeted interventions by non-invasive brain stimulation, as well as of unspecific interventions such as physical activity or cognitive training. Unambiguously detecting compensation in early neurodegenerative disease will help tailor interventions aiming at sustained overall functioning and delayed clinical disease onset.