Looking for Neuroimaging Markers in Frontotemporal Lobar Degeneration Clinical Trials: A Multi-Voxel Pattern Analysis Study in Granulin Disease

Narcissistic Personality Disorder as Prodromal Feature of Early-Onset, GRN-Positive bvFTD: A Case Report

Background

Behavioral variant frontotemporal dementia (bvFTD) typically involves subtle changes in personality that can delay a timely diagnosis.

Objective

Here, we report the case of a patient diagnosed of GRN-positive bvFTD at the age of 52 presenting with a 7-year history of narcissistic personality disorder, accordingly to DSM-5 criteria.

Methods

The patient was referred to neurological and neuropsychological examination. She underwent 3 Tesla magnetic resonance imaging (MRI) and genetic studies.

Results

The neuropsychological examination revealed profound deficits in all cognitive domains and 3T brain MRI showed marked fronto-temporal atrophy. A mutation in the GRN gene further confirmed the diagnosis.

Conclusions

The present case documents an unusual onset of bvFTD and highlights the problematic nature of the differential diagnosis between prodromal psychiatric features of the disease and primary psychiatric disorders. Early recognition and diagnosis of bvFTD can lead to appropriate management and support for patients and their families. This case highlights the importance of considering neurodegenerative diseases, such as bvFTD, in the differential diagnosis of psychiatric disorders, especially when exacerbations of behavioral traits manifest in adults.

Early neurotransmitters changes in prodromal frontotemporal dementia: A GENFI study

BACKGROUND

Neurotransmitters deficits in Frontotemporal Dementia (FTD) are still poorly understood. Better knowledge of neurotransmitters impairment, especially in prodromal disease stages, might tailor symptomatic treatment approaches.

METHODS

In the present study, we applied JuSpace toolbox, which allowed for cross-modal correlation of Magnetic Resonance Imaging (MRI)-based measures with nuclear imaging derived estimates covering various neurotransmitter systems including dopaminergic, serotonergic, noradrenergic, GABAergic and glutamatergic neurotransmission. We included 392 mutation carriers (157 GRN, 164 C9orf72, 71 MAPT), together with 276 non-carrier cognitively healthy controls (HC). We tested if the spatial patterns of grey matter volume (GMV) alterations in mutation carriers (relative to HC) are correlated with specific neurotransmitter systems in prodromal (CDR® plus NACC FTLD = 0.5) and in symptomatic (CDR® plus NACC FTLD≥1) FTD.

RESULTS

In prodromal stages of C9orf72 disease, voxel-based brain changes were significantly associated with spatial distribution of dopamine and acetylcholine pathways; in prodromal MAPT disease with dopamine and serotonin pathways, while in prodromal GRN disease no significant findings were reported (p < 0.05, Family Wise Error corrected). In symptomatic FTD, a widespread involvement of dopamine, serotonin, glutamate and acetylcholine pathways across all genetic subtypes was found. Social cognition scores, loss of empathy and poor response to emotional cues were found to correlate with the strength of GMV colocalization of dopamine and serotonin pathways (all p < 0.01).

CONCLUSIONS

This study, indirectly assessing neurotransmitter deficits in monogenic FTD, provides novel insight into disease mechanisms and might suggest potential therapeutic targets to counteract disease-related symptoms.

Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference

Characterizing a particular neurodegenerative condition against others possible diseases remains a challenge along clinical, biomarker, and neuroscientific levels. This is the particular case of frontotemporal dementia (FTD) variants, where their specific characterization requires high levels of expertise and multidisciplinary teams to subtly distinguish among similar physiopathological processes. Here, we used a computational approach of multimodal brain networks to address simultaneous multiclass classification of 298 subjects (one group against all others), including five FTD variants: behavioral variant FTD, corticobasal syndrome, nonfluent variant primary progressive aphasia, progressive supranuclear palsy, and semantic variant primary progressive aphasia, with healthy controls. Fourteen machine learning classifiers were trained with functional and structural connectivity metrics calculated through different methods. Due to the large number of variables, dimensionality was reduced, employing statistical comparisons and progressive elimination to assess feature stability under nested cross-validation. The machine learning performance was measured through the area under the receiver operating characteristic curves, reaching 0.81 on average, with a standard deviation of 0.09. Furthermore, the contributions of demographic and cognitive data were also assessed via multifeatured classifiers. An accurate simultaneous multiclass classification of each FTD variant against other variants and controls was obtained based on the selection of an optimum set of features. The classifiers incorporating the brain's network and cognitive assessment increased performance metrics. Multimodal classifiers evidenced specific variants' compromise, across modalities and methods through feature importance analysis. If replicated and validated, this approach may help to support clinical decision tools aimed to detect specific affectations in the context of overlapping diseases.

Choice of Voxel-based Morphometry processing pipeline drives variability in the location of neuroanatomical brain markers

Fundamental and clinical neuroscience has benefited tremendously from the development of automated computational analyses. In excess of 600 human neuroimaging papers using Voxel-based Morphometry (VBM) are now published every year and a number of different automated processing pipelines are used, although it remains to be systematically assessed whether they come up with the same answers. Here we examined variability between four commonly used VBM pipelines in two large brain structural datasets. Spatial similarity and between-pipeline reproducibility of the processed gray matter brain maps were generally low between pipelines. Examination of sex-differences and age-related changes revealed considerable differences between the pipelines in terms of the specific regions identified. Machine learning-based multivariate analyses allowed accurate predictions of sex and age, however accuracy differed between pipelines. Our findings suggest that the choice of pipeline alone leads to considerable variability in brain structural markers which poses a serious challenge for reproducibility and interpretation.

Four common processing pipelines tested on two Voxel-based Morphometry (VBM) datasets yield considerable variations in results, raising issues on the interpretability and robustness of VBM results.

Pre-symptomatic radiological changes in frontotemporal dementia: propagation characteristics, predictive value and implications for clinical trials

Computational imaging and quantitative biomarkers offer invaluable insights in the pre-symptomatic phase of neurodegenerative conditions several years before clinical manifestation. In recent years, there has been a focused effort to characterize pre-symptomatic cerebral changes in familial frontotemporal dementias using computational imaging. Accordingly, a systematic literature review was conducted of original articles investigating pre-symptomatic imaging changes in frontotemporal dementia focusing on study design, imaging modalities, data interpretation, control cohorts and key findings. The review is limited to the most common genotypes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) genotypes. Sixty-eight studies were identified with a median sample size of 15 (3-141) per genotype. Only a minority of studies were longitudinal (28%; 19/68) with a median follow-up of 2 (1-8) years. MRI (97%; 66/68) was the most common imaging modality, and primarily grey matter analyses were conducted (75%; 19/68). Some studies used multimodal analyses 44% (30/68). Genotype-associated imaging signatures are presented, innovative study designs are highlighted, common methodological shortcomings are discussed and lessons for future studies are outlined. Emerging academic observations have potential clinical implications for expediting the diagnosis, tracking disease progression and optimising the timing of pharmaceutical trials.

Data-driven staging of genetic frontotemporal dementia using multi-modal MRI

Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high‐dimensional large‐scale population datasets to obtain individual scores of disease stage. We used cross‐sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting‐state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI‐obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre‐dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data‐driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.

The role of disrupted functional connectivity in aphasia

Language is one of the most complex and specialized higher cognitive processes. Brain damage to the distributed, primarily left-lateralized language network can result in aphasia, a neurologic disorder characterized by receptive and/or expressive deficits in spoken and/or written language. Most often, aphasia is the consequence of stroke-termed poststroke aphasia (PSA)-yet, aphasia can also manifest due to neurodegenerative disease, specifically, a disorder called primary progressive aphasia (PPA). In recent years, functional connectivity neuroimaging studies have provided emerging evidence supporting theories regarding the relationships between language impairments, structural brain damage, and functional network properties in these two disorders. This chapter reviews the current evidence for the "network phenotype of stroke injury" hypothesis (Siegel et al., 2016) as it pertains to PSA and the "network degeneration hypothesis" (Seeley et al., 2009) as it pertains to PPA. Methodologic considerations for functional connectivity studies, limitations of the current functional connectivity literature in aphasia, and future directions are also discussed.

Deficient neurotransmitter systems and synaptic function in frontotemporal lobar degeneration-Insights into disease mechanisms and current therapeutic approaches

Frontotemporal lobar degeneration (FTLD) comprises a heterogenous group of fatal neurodegenerative diseases and, to date, no validated diagnostic or prognostic biomarkers or effective disease-modifying therapies exist for the different clinical or genetic subtypes of FTLD. Current treatment strategies rely on the off-label use of medications for symptomatic treatment. Changes in several neurotransmitter systems including the glutamatergic, GABAergic, dopaminergic, and serotonergic systems have been reported in FTLD spectrum disease patients. Many FTLD-related clinical and neuropsychiatric symptoms such as aggressive and compulsive behaviour, agitation, as well as altered eating habits and hyperorality can be explained by disturbances in these neurotransmitter systems, suggesting that their targeting might possibly offer new therapeutic options for treating patients with FTLD. This review summarizes the present knowledge on neurotransmitter system deficits and synaptic dysfunction in model systems and patients harbouring the most common genetic causes of FTLD, the hexanucleotide repeat expansion in C9orf72 and mutations in the granulin (GRN) and microtubule-associated protein tau (MAPT) genes. We also describe the current pharmacological treatment options for FLTD that target different neurotransmitter systems.

Conceptual framework for the definition of preclinical and prodromal frontotemporal dementia

The presymptomatic stages of frontotemporal dementia (FTD) are still poorly defined and encompass a long accrual of progressive biological (preclinical) and then clinical (prodromal) changes, antedating the onset of dementia. The heterogeneity of clinical presentations and the different neuropathological phenotypes have prevented a prior clear description of either preclinical or prodromal FTD. Recent advances in therapeutic approaches, at least in monogenic disease, demand a proper definition of these predementia stages. It has become clear that a consensus lexicon is needed to comprehensively describe the stages that anticipate dementia. The goal of the present work is to review existing literature on the preclinical and prodromal phases of FTD, providing recommendations to address the unmet questions, therefore laying out a strategy for operationalizing and better characterizing these presymptomatic disease stages.

Altered Spontaneous Brain Activity in Subjects With Different Cognitive States of Biologically Defined Alzheimer's Disease: A Surface-Based Functional Brain Imaging Study

Background: Before the apparent cognitive decline, subjects on the course of Alzheimer's disease (AD) can have significantly altered spontaneous brain activity, which could be potentially used for early diagnosis. As previous studies investigating local brain activity may suffer from the problem of cortical signal aliasing during volume-based analysis, we aimed to investigate the cortical functional alterations in the AD continuum using a surface-based approach. Methods: Based on biomarker profile "A/T," we included 11 healthy controls (HC, A-T-), 22 preclinical AD (CU, A+T+), 33 prodromal AD (MCI, A+T+), and 20 AD with dementia (d-AD, A+T+) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The amplitude of low-frequency fluctuation (ALFF) method was used to evaluate the changes of spontaneous brain activity, which was performed in the classic frequency band (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) band, and slow-5 (0.01-0.027 Hz) band. Results: Under classic frequency band and slow-4 band, analysis of covariance (ANCOVA) showed that there were significant differences of standardized ALFF (zALFF) in the left posterior cingulate cortex (PCC) among the four groups. The post-hoc analyses showed that under the classic frequency band, the AD group had significantly decreased zALFF compared with the other three groups, and the cognitively unimpaired (CU) group had decreased zALFF compared with the healthy control (HC) group. Under the slow-4 band, more group differences were detected (HC > CU/MCI > d-AD). The accuracy of classifying CU, mild cognitive impairment (MCI), and AD from HC by left PCC activity under the slow-4 band were 0.774, 0.744, and 0.920, respectively. Moreover, the zALFF values of the left PCC had significant correlations with cerebrospinal fluid (CSF) biomarkers and neuropsychological tests. Conclusions: Spontaneous brain activity in the left PCC may decrease in preclinical AD when cognitive functions were relatively normal. The combination of a surfaced-based approach and specific frequency band analysis may increase sensitivity for the identification of preclinical AD subjects.

The presymptomatic phase of amyotrophic lateral sclerosis: are we merely scratching the surface?

Presymptomatic studies in ALS have consistently captured considerable disease burden long before symptom manifestation and contributed important academic insights. With the emergence of genotype-specific therapies, however, there is a pressing need to address practical objectives such as the estimation of age of symptom onset, phenotypic prediction, informing the optimal timing of pharmacological intervention, and identifying a core panel of biomarkers which may detect response to therapy. Existing presymptomatic studies in ALS have adopted striking different study designs, relied on a variety of control groups, used divergent imaging and electrophysiology methods, and focused on different genotypes and demographic groups. We have performed a systematic review of existing presymptomatic studies in ALS to identify common themes, stereotyped shortcomings, and key learning points for future studies. Existing presymptomatic studies in ALS often suffer from sample size limitations, lack of disease controls and rarely follow their cohort until symptom manifestation. As the characterisation of presymptomatic processes in ALS serves a multitude of academic and clinical purposes, the careful review of existing studies offers important lessons for future initiatives.

Neuroimaging in genetic frontotemporal dementia and amyotrophic lateral sclerosis

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) have a strong clinical, genetic and pathological overlap. This review focuses on the current understanding of structural, functional and molecular neuroimaging signatures of genetic FTD and ALS. We overview quantitative neuroimaging studies on the most common genes associated with FTD (MAPT, GRN), ALS (SOD1), and both (C9orf72), and summarize visual observations of images reported in the rarer genes (CHMP2B, TARDBP, FUS, OPTN, VCP, UBQLN2, SQSTM1, TREM2, CHCHD10, TBK1).

Trajectory of lobar atrophy in asymptomatic and symptomatic GRN mutation carriers: a longitudinal MRI study

Loss-of-function mutations in the progranulin gene (GRN) are one of the major causes of familial frontotemporal lobar degeneration. Our objective was to determine the rates and trajectories of lobar cortical atrophy from longitudinal structural magnetic resonance imaging in both asymptomatic and symptomatic GRN mutation carriers. Individuals in this study were from the ADRC and LEFFTDS studies at the Mayo Clinic. We identified 13 GRN mutation carriers (8 asymptomatic, 5 symptomatic) and noncarriers (n = 10) who had at least 2 serial T1-weighted structural magnetic resonance images and were followed annually with a median of 3 years (range 1.0-9.8 years). Longitudinal changes in lobar cortical volume were analyzed using the tensor-based morphometry with symmetric normalization (TBM-SyN) algorithm. Linear mixed-effect models were used to model cortical volume change over time among 3 groups. The annual rates of frontal (p < 0.05) and parietal (p < 0.01) lobe cortical atrophy were higher in asymptomatic GRN mutation carriers than noncarriers. The symptomatic GRN mutation carriers also had increased rates of atrophy in the frontal (p < 0.01) and parietal lobe (p < 0.01) cortices than noncarriers. In addition, greater rates of cortical atrophy were observed in the temporal lobe cortices of symptomatic GRN mutation carriers than noncarriers (p < 0.001). We found that a decline in frontal and parietal lobar cortical volume occurs in asymptomatic GRN mutation carriers and continues in the symptomatic GRN mutation carriers, whereas an increased rate of temporal lobe cortical atrophy is observed only in symptomatic GRN mutation carriers. This sequential pattern of cortical involvement in GRN mutation carriers has important implications for using imaging biomarkers of neurodegeneration as an outcome measure in potential treatment trials involving GRN mutation carriers.

Functional Connectivity in Neurodegenerative Disorders: Alzheimer's Disease and Frontotemporal Dementia

Neurodegenerative disorders are a growing cause of morbidity and mortality worldwide. Onset is typically insidious and clinical symptoms of behavioral change, memory loss, or cognitive dysfunction may not be evident early in the disease process. Efforts have been made to discover biomarkers that allow for earlier diagnosis of neurodegenerative disorders, to initiate treatment that may slow the course of clinical deterioration. Neuronal dysfunction occurs earlier than clinical symptoms manifest. Thus, assessment of neuronal function using functional brain imaging has been examined as a potential biomarker. While most early studies used task-functional magnetic resonance imaging (fMRI), with the more recent technique of resting-state fMRI, "intrinsic" relationships between brain regions or brain networks have been studied in greater detail in neurodegenerative disorders. In Alzheimer's disease, the most common neurodegenerative disorder, and frontotemporal dementia, another of the common dementias, specific brain networks may be particularly susceptible to dysfunction. In this review, we highlight the major findings of functional connectivity assessed by resting state fMRI in Alzheimer's disease and frontotemporal dementia.

Characterization of Cerebellar Atrophy and Resting State Functional Connectivity Patterns in Sporadic Adult-Onset Ataxia of Unknown Etiology (SAOA)

Sporadic adult-onset ataxia of unknown etiology (SAOA) is a non-genetic neurodegenerative disorder of the cerebellum of unknown cause which manifests with progressive ataxia without severe autonomic failure. Although SAOA is associated with cerebellar degeneration, little is known about the specific cerebellar atrophy pattern in SAOA. Thirty-seven SAOA patients and 49 healthy controls (HCs) were included at two centers. We investigated the structural and functional characteristics of SAOA brains using voxel-based morphometry (VBM) and resting-state functional imaging (rs-fMRI). In order to examine the functional consequence of structural cerebellar alterations, the amplitude of low-frequency fluctuation (ALFF) and degree centrality (DC) were analyzed, and then assessed their relation with disease severity, disease duration, and age of onset within these regions. Group differences were investigated using two-sample t tests, controlling for age, gender, site, and the total intracranial volume. The VBM analysis revealed a significant, mostly bilateral reduction of local gray matter (GM) volume in lobules I-V, V, VI, IX, X, and vermis VIII a/b in SAOA patients, compared with HCs. The GM volume loss in these regions was significantly associated with disease severity, disease duration, and age of onset. The disease-related atrophy regions did not show any functional alternations compared with HCs but were functionally characterized by high ALFF and poor DC compared with intact cerebellar regions. Our data revealed volume reduction in SAOA in cerebellar regions that are known to be involved in motor and somatosensory processing, corresponding with the clinical phenotype of SAOA. Our data suggest that the atrophy occurs in those cerebellar regions which are characterized by high ALFF and poor DC. Further studies have to show if these findings are specific for SAOA, and if they can be used to predict disease progression.

Imaging Biomarkers for Neurodegeneration in Presymptomatic Familial Frontotemporal Lobar Degeneration

Frontotemporal lobar degeneration (FTLD) is a neurodegenerative disorder characterized by behavioral changes, language abnormality, as well as executive function deficits and motor impairment. In about 30-50% of FTLD patients, an autosomal dominant pattern of inheritance was found with major mutations in the MAPT, GRN, and the C9orf72 repeat expansion. These mutations could lead to neurodegenerative pathology years before clinical symptoms onset. With potential disease-modifying treatments that are under development, non-invasive biomarkers that help determine the early brain changes in presymptomatic FTLD patients will be critical for tracking disease progression and enrolling the right participants into the clinical trials at the right time during the disease course. In recent years, there is increasing evidence that a number of imaging biomarkers show the abnormalities during the presymptomatic stage. Imaging biomarkers of presymptomatic familial FTLD may provide insight into the underlying neurodegenerative process years before symptom onset. Structural magnetic resonance imaging (MRI) has demonstrated cortical degeneration with a mutation-specific neurodegeneration pattern years before onset of clinical symptoms in presymptomatic familial FTLD mutation carriers. In addition, diffusion tensor imaging (DTI) has shown the loss of white matter microstructural integrity in the presymptomatic stage of familial FTLD. Furthermore, proton magnetic resonance spectroscopy (¹H MRS), which provides a non-invasive measurement of brain biochemistry, has identified early neurochemical abnormalities in presymptomatic MAPT mutation carriers. Positron emission tomography (PET) imaging with [¹⁸F]-fluorodeoxyglucose (FDG) has demonstrated the glucose hypometabolism in the presymptomatic stage of familial FTLD. Also, a novel PET ligand, ¹⁸F-AV-1451, has been used in this group to evaluate tau deposition in the brain. Promising imaging biomarkers for presymptomatic familial FTLD have been identified and assessed for specificity and sensitivity for accurate prediction of symptom onset and tracking disease progression during the presymptomatic stage when clinical measures are not useful. Furthermore, identifying imaging biomarkers for the presymptomatic stage is important for the design of disease-modifying trials. We review the recent progress in imaging biomarkers of the presymptomatic phase of familial FTLD and discuss the imaging techniques and analysis methods, with a focus on the potential implication of these imaging techniques and their utility in specific mutation types.

Predementia Brain Changes in Progranulin Mutation: A Systematic Review of Neuroimaging Evidence

BACKGROUND

Mutations in the progranulin (GRN) gene are a major cause of familial frontotemporal dementia. They result in a loss of progranulin levels and in GRN-related brain degenerative changes that unfold over years if not decades. The aim of our review was to summarize the evidence on emerging functional and structural brain abnormalities in carriers of GRN mutations.

SUMMARY

We performed a systematic search for studies that used at least one modality (structural MRI, fMRI, fluorodeoxyglucose positron emission tomography, diffusion tensor imaging) to compare mutation carriers to non-carrier controls. Our search produced 13 studies published between 2008 and 2017, the majority cross-sectional, with carrier sample sizes ranging from 5 to 65. Key Messages: The aggregate findings suggest that (1) measurable brain changes are detectable in at least some mutation carriers 20-25 years prior to disease onset; (2) functional/metabolic changes progress more consistently over time than structural changes; (3) the topographic pattern is anterior to posterior, not always asymmetric, and maps onto known functional networks.

Brain structural alterations are distributed following functional, anatomic and genetic connectivity

The pathological brain is characterized by distributed morphological or structural alterations in the grey matter, which tend to follow identifiable network-like patterns. We analysed the patterns formed by these alterations (increased and decreased grey matter values detected with the voxel-based morphometry technique) conducting an extensive transdiagnostic search of voxel-based morphometry studies in a large variety of brain disorders. We devised an innovative method to construct the networks formed by the structurally co-altered brain areas, which can be considered as pathological structural co-alteration patterns, and to compare these patterns with three associated types of connectivity profiles (functional, anatomical, and genetic). Our study provides transdiagnostical evidence that structural co-alterations are influenced by connectivity constraints rather than being randomly distributed. Analyses show that although all the three types of connectivity taken together can account for and predict with good statistical accuracy, the shape and temporal development of the co-alteration patterns, functional connectivity offers the better account of the structural co-alteration, followed by anatomic and genetic connectivity. These results shed new light on the possible mechanisms at the root of neuropathological processes and open exciting prospects in the quest for a better understanding of brain disorders.

Thalamo-cortical network hyperconnectivity in preclinical progranulin mutation carriers

Mutations in progranulin (GRN) cause heterogeneous clinical syndromes, including behavioral variant frontotemporal dementia (bvFTD), primary progressive aphasia (PPA), corticobasal syndrome (CBS) and Alzheimer-type dementia (AD-type dementia). Human studies have shown that presymptomatic GRN carriers feature reduced connectivity in the salience network, a system targeted in bvFTD. Mice with homozygous deletion of GRN, in contrast, show thalamo-cortical hypersynchrony due to aberrant pruning of inhibitory synapses onto thalamo-cortical projection neurons. No studies have systematically explored the intrinsic connectivity networks (ICNs) targeted by the four GRN-associated clinical syndromes, or have forged clear links between human and mouse model findings. We compared 17 preclinical GRN carriers (14 “presymptomatic” clinically normal and three “prodromal” with mild cognitive symptoms) to healthy controls to assess for differences in cognitive testing and gray matter volume. Using task-free fMRI, we assessed connectivity in the salience network, a non-fluent variant primary progressive aphasia network (nfvPPA), the perirolandic network (CBS), and the default mode network (AD-type dementia). GRN carriers and controls showed similar performance on cognitive testing. Although carriers showed little evidence of brain atrophy, markedly enhanced connectivity emerged in all four networks, and thalamo-cortical hyperconnectivity stood out as a unifying feature. Voxelwise assessment of whole brain degree centrality, an unbiased graph theoretical connectivity metric, confirmed thalamic hyperconnectivity. These results show that human GRN disease and the prevailing GRN mouse model share a thalamo-cortical network hypersynchrony phenotype. Longitudinal studies will determine whether this network physiology represents a compensatory response as carriers approach symptom onset, or an early and sustained preclinical manifestation of lifelong progranulin haploinsufficiency.

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Preclinical GRN mutation carriers feature marked hyperconnectivity in four task-free fMRI intrinsic connectivity networks.

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Thalamocortical hyperconnectivity was a unifying feature across all four networks.

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Human GRN disease and the prevailing GRN mouse model share a thalamo-cortical network hypersynchrony phenotype.

The inner fluctuations of the brain in presymptomatic Frontotemporal Dementia: The chronnectome fingerprint

Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD. In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort. We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted. Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials.

Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker?

Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.

Biological, Neuroimaging, and Neurophysiological Markers in Frontotemporal Dementia: Three Faces of the Same Coin

Frontotemporal dementia (FTD) is a heterogeneous clinical, genetic, and neuropathological disorder. Clinical diagnosis and prediction of neuropathological substrates are hampered by heterogeneous pictures. Diagnostic markers are key in clinical trials to differentiate FTD from other neurodegenerative dementias. In the same view, identifying the neuropathological hallmarks of the disease is key in light of future disease-modifying treatments. The aim of the present review is to unravel the progress in biomarker discovery, discussing the potential applications of available biological, imaging, and neurophysiological markers.

Basic Emotions in Human Neuroscience: Neuroimaging and Beyond

The existence of so-called ‘basic emotions’ and their defining attributes represents a long lasting and yet unsettled issue in psychology. Recently, neuroimaging evidence, especially related to the advent of neuroimaging meta-analytic methods, has revitalized this debate in the endeavor of systems and human neuroscience. The core theme focuses on the existence of unique neural bases that are specific and characteristic for each instance of basic emotion. Here we review this evidence, outlining contradictory findings, strengths and limits of different approaches. Constructionism dismisses the existence of dedicated neural structures for basic emotions, considering that the assumption of a one-to-one relationship between neural structures and their functions is central to basic emotion theories. While these critiques are useful to pinpoint current limitations of basic emotions theories, we argue that they do not always appear equally generative in fostering new testable accounts on how the brain relates to affective functions. We then consider evidence beyond PET and fMRI, including results concerning the relation between basic emotions and awareness and data from neuropsychology on patients with focal brain damage. Evidence from lesion studies are indeed particularly informative, as they are able to bring correlational evidence typical of neuroimaging studies to causation, thereby characterizing which brain structures are necessary for, rather than simply related to, basic emotion processing. These other studies shed light on attributes often ascribed to basic emotions, such as automaticity of perception, quick onset, and brief duration. Overall, we consider that evidence in favor of the neurobiological underpinnings of basic emotions outweighs dismissive approaches. In fact, the concept of basic emotions can still be fruitful, if updated to current neurobiological knowledge that overcomes traditional one-to-one localization of functions in the brain. In particular, we propose that the structure-function relationship between brain and emotions is better described in terms of pluripotentiality, which refers to the fact that one neural structure can fulfill multiple functions, depending on the functional network and pattern of co-activations displayed at any given moment.

Imaging and fluid biomarkers in frontotemporal dementia

Frontotemporal dementia (FTD), the second most common type of presenile dementia, is a heterogeneous neurodegenerative disease characterized by progressive behavioural and/or language problems, and includes a range of clinical, genetic and pathological subtypes. The diagnostic process is hampered by this heterogeneity, and correct diagnosis is becoming increasingly important to enable future clinical trials of disease-modifying treatments. Reliable biomarkers will enable us to better discriminate between FTD and other forms of dementia and to predict disease progression in the clinical setting. Given that different underlying pathologies probably require specific pharmacological interventions, robust biomarkers are essential for the selection of patients with specific FTD subtypes. This Review emphasizes the increasing availability and potential applications of structural and functional imaging biomarkers, and cerebrospinal fluid and blood fluid biomarkers in sporadic and genetic FTD. The relevance of new MRI modalities - such as voxel-based morphometry, diffusion tensor imaging and arterial spin labelling - in the early stages of FTD is discussed, together with the ability of these modalities to classify FTD subtypes. We highlight promising new fluid biomarkers for staging and monitoring of FTD, and underline the importance of large, multicentre studies of individuals with presymptomatic FTD. Harmonization in the collection and analysis of data across different centres is crucial for the implementation of new biomarkers in clinical practice, and will become a great challenge in the next few years.

A comparison of stimulus presentation methods in temporal discrimination testing

The temporal discrimination threshold (TDT) is the shortest time interval at which an individual detects two stimuli to be asynchronous (normal  =  30-50 ms). It has been shown to be abnormal in patients with disorders affecting the basal ganglia including adult onset idiopathic focal dystonia (AOIFD). Up to 97% of patients have an abnormal TDT with age- and sex-related penetrance in unaffected relatives, demonstrating an autosomal dominant inheritance pattern. These findings support the use of the TDT as a pre-clinical biomarker for AOIFD. The usual stimulus presentation method involves the presentation of progressively asynchronous stimuli; when three sequential stimuli are reported asynchronous is taken as a participant's TDT. To investigate the robustness of the 'staircase' method of presentation, we introduced a method of randomised presentation order to explore any potential 'learning effect' that may be associated with this existing method. The aim of this study was to investigate differences in temporal discrimination using two methods of stimulus presentation. Thirty healthy volunteers were recruited to the study (mean age 33.73  ±  3.4 years). Visual and tactile TDT testing using a staircase and randomised method of presentation order was carried out in a single session. There was a strong relationship between the staircase and random method for TDT values. This observed consistency between testing methods suggests that the existing experimental approach is a robust method of recording an individual's TDT. In addition, our newly devised randomised paradigm is a reproducible and more efficient method for data acquisition in the clinic setting. However, the two presentation methods yield different absolute TDT results and either of the two methods should be used uniformly in all participants in any one particular study.

A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community.