Abnormal Regional and Global Connectivity Measures in Subjective Cognitive Decline Depending on Cerebral Amyloid Status

Background: Amyloid-β accumulation was found to alter precuneus-based functional connectivity (FC) in mild cognitive impairment (MCI) and Alzheimer’s disease (AD) dementia, but its impact is less clear in subjective cognitive decline (SCD), which in combination with AD pathologic change is theorized to correspond to stage 2 of the Alzheimer’s continuum in the 2018 NIA-AA research framework. Objective: This study addresses how amyloid pathology relates to resting-state fMRI FC in SCD, especially focusing on the precuneus. Methods: From the DELCODE cohort, two groups of 24 age- and gender-matched amyloid-positive (SCDAβ+) and amyloidnegative SCD (SCDβ−) patients were selected according to visual [18F]-Florbetaben (FBB) PET readings, and studied with resting-state fMRI. Local (regional homogeneity [ReHo], fractional amplitude of low-frequency fluctuations [fALFF]) and global (degree centrality [DC], precuneus seed-based FC) measures were compared between groups. Follow-up correlation analyses probed relationships of group differences with global and precuneal amyloid load, as measured by FBB standard uptake value ratios (SUVR=⫖FBB). Results: ReHo was significantly higher (voxel-wise p < 0.01, cluster-level p < 0.05) in the bilateral precuneus for SCDAβ+patients, whereas fALFF was not altered between groups. Relatively higher precuneus-based FC with occipital areas (but no altered DC) was observed in SCDAβ+ patients. In this latter cluster, precuneus-occipital FC correlated positively with global (SCDAβ+) and precuneus SUVRFBB (both groups). Conclusion: While partial confounding influences due to a higher APOE ε4 carrier ratio among SCDAβ+ patients cannot be excluded, exploratory results indicate functional alterations in the precuneus hub region that were related to amyloid-β load, highlighting incipient pathology in stage 2 of the AD continuum

인지 노쇠에서 FDG PET과 휴지상태 fMRI를 이용한 뇌 신경 활동과 기능적 연결성 패턴의 동적 변화 연구

학위논문(박사)--서울대학교 대학원 :의과대학 의과학과,2019. 8. 이재성.Cognitive frailty is a recently defined clinical condition characterized by concurrent appearance of physical frailty and mild cognitive impairments (MCI). Literature suggests common neuropathophysiological processes underlying physical and cognitive deficits, and physical dysfunction promotes cognitive decline, eventually leading to the emergence of Alzheimers disease dementia. It remains to be discovered how neural activities and brain network reconfigurations are altered in the presence of physical frailty in MCI. In the present study, [18F]FDG PET and resting state fMRI scans were examined in 21 MCI patients without physical frailty (robust group: mean age = 74.7 ± 5.8 years) and 27 MCI with physical frailty (at-risk group: mean age = 75.5 ± 7.3 years). The first part of the study aimed to investigate changes in glucose metabolism and regional homogeneity in cognitive frailty. Regional cerebral hypometabolism was observed in right frontal cortex, anterior cingulate, and bilateral superior parietal cortex in at-risk group, and the metabolic changes in left superior parietal cortex were associated with poorer performances in handgrip strength and executive function. Brain regional homogeneity was reduced in bilateral caudate, right medial and lateral frontal cortex, right superior temporal cortex, and cerebellum, and was increased in right precuneus and cerebellum. Decreased regional homogeneity in bilateral caudate and right superior temporal cortex showed correlations with weaker grip strength, slower gait speed, and lower physical activity, and the regional changes were also linked to cognitive performances in language and visuospatial function. The results demonstrated that the metabolic and functional alterations in cognitive frailty resembled Alzheimer's disease related pattern. The second part of the study aimed to explore alterations in dynamic functional connectivity states and the temporal properties. Dynamic functional connectivity was measured using a sliding-window approach, and certain connectivity configurations (states) were estimated using k-means clustering method. Four distinguishing patterns of functional connectivity were found during the resting state scan time in our MCI cohorts. The most frequently occurring state (State 1) displayed mostly within-network connections, and the less occurring states (States 2, 3 and 4) displayed stronger between-network connections in both positive and negative fashions. The alterations in the temporal properties of dynamic states such as the number of transition, fractional windows, and mean dwell time of states did not reach the significance level, however, at-risk group appeared to have less reoccurrence of within-network State 1 and more reoccurrences of between-network States 2 and 3. Reduced reoccurrence and shorter dwell time of within-network State 1 were significantly correlated with weaker handgrip strength, and the abnormally reduced within-network State 1 may reflect reduced functional network segregation coupled with physical deficits. On the other hand, higher reoccurrence and longer dwell time of State 2, which was characterized by heightened default mode network within-connectivity and increased interactions between default mode network and sensorimotor networks were associated with poorer MMSE-K score. The overexpression of interactions between default mode and sensorimotor networks may interfere with network functional specializations, leading to poor cognitive function. Furthermore, the functional connectivity strengths between sensorimotor and cognitive networks and within cognitive control network were altered in at-risk individuals. The neuroimaging outcomes present that aberrant functional changes in frontal, temporal and parietal cortex may indicate advanced pathological process in the presence of physical frailty in MCI. The time-varying network reconfigurations indicating decreased functional segregation of brain networks may also serve as a potential biomarker in cognitive frailty.인지 노쇠는 신체적 노쇠와 경도 인지 장애가 동시에 존재하는 것이 특징적인 최근 정의된 임상적 질환이다. 기존 연구에 의하면 신체적 노쇠와 인지 기능 저하는 공통적인 신경 병리적 기전을 가지는 것으로 알려져 있다. 또한, 신체적 기능 장애는 인지 기능 감소를 촉진하고, 나아가 알츠하이머병 치매 발병까지 연결된다. 신체적 노쇠를 보이는 경도 인지 장애 환자에서의 신경 활동 변화와 동적 뇌 네트워크 재구성 변화에 대한 연구는 아직까지 보고된 바가 없으며, 본 연구 결과를 통하여 뇌 영상 데이터가 인지 노쇠의 중요한 바이오마커의 역할을 할 것으로 기대된다. 본 연구에서는 [18F]FDG PET과 rs-fMRI 뇌 영상 검사를 총 48명의 경도 인지 기능 장애 환자 (신체적 노쇠가 없는 대조군: 21명, 평균 연령 = 74.7 ± 5.8세; 신체적 노쇠가 있는 위험군: 27명, 평균 연령 = 75.5 ± 7.3세)를 대상으로 진행하였다. 본 연구의 첫번째 부분에서는 위험군에서의 뇌 영역의 포도당 대사의 변화와 regional homogeneity를 이용한 뇌 활동 변화를 조사하였다. 위험군에서는 우측 전두피질, 전대상피질, 양측 상두정소엽에서 뇌 대사 감소가 나타났고, 상두정소엽에서의 대사 변화와 악력, 집행 기능과 양의 상관 관계를 보였다. 뇌 영역의 regional homogeneity 변화는 양측 꼬리핵, 우측 내측과 가측 전두피질, 우측 상측두피질, 소뇌에서 감소하는 것으로 보였고, 꼬리핵과 상측두피질에서의 regional homogeneity 감소는 악력, 보행 속도, 신체 활동 감소 수치와 높은 상관성을 보였다. 또한, 언어 및 시공간 기능의 인지 수행 능력과 높은 상관 관계를 보이는 것을 관찰하였다. 본 연구의 두번째 부분은 위험군에서의 뇌 네트워크의 동적 기능적 연결성과 특징 변화를 살펴보았다. 동적 기능적 연결 분석은 sliding-window 방법과 k-means clustering 방법을 사용하여 뇌 네트워크 연결 구성 상태 (State)를 추정하였다. 휴지기 상태의 영상 촬영 시간 동안 총 4개의 기능적 연결성 패턴이 발견되었고, 가장 자주 발생하는 State 1은 주로 뇌 네트워크 내부 연결성을 보이고, 네트워크 간의 연결성은 약한 것이 특징으로 나타났다. 그 다음으로 자주 나타난 State 2, 3, 4는 네트워크 간의 양과 음의 연결성 모두 강하게 나타났다. State의 전환 수, fractional windows, mean dwell time과 같은 시간적 속성의 그룹 비교 결과는 유의한 수준에 도달하지 못했지만, 위험군에서 State1의 재발현이 감소되고 State 2, State 3의 발현 증가가 나타나는 것으로 확인되었다. State 1의 속성 (fractional windows, mean dwell time)이 악력 및 신체 활동량과 양의 상관 관계를 나타냈고, 반면에, 디폴트 모드 네트워크 기능 연결성 증가가 특징적이었던 State 2의 발현 증가 및 dwell time 증가는 낮은 MMSE-K 점수 저하와 상관이 있는 것을 관찰하였다. 네트워크 변화는 노화현상에서 관측되는 네트워크 기능적 분리 (functional segregation)의 감소를 나타내는 것으로 생각되며, 신체적 기능 저하가 이러한 현상을 촉진하는 것으로 보여진다. 뿐만 아니라, 위험군에서 감각운동 네트워크와 인지 기능 네트워크 간의 기능적 연결성과 인지 조절 네트워크 내부 연결성 세기에도 변화가 나타나는 것을 발견하였다. 결론으로는, 뇌 영상 분석 결과에서 인지 노쇠 위험군 환자에서 전두엽, 측두엽 그리고 두정엽에서 기능적 활동 변화가 나타나는 것을 관찰하였고, 이는 신체적 노쇠가 존재할 경우 병리학적 과정이 가속화되는 것으로 추정된다. 뇌 네트워크의 동적 기능적 연결성 분석을 통해 악력 감소와 함께 네트워크 기능적 분리 감소 현상이 두드러지는 것을 확인하였으며, 따라서, 뇌 영상 데이터가 인지 노쇠의 생체 표지자 역할을 할 수 있는 것으로 기대된다.Chapter 1. Introduction 1 1.1 Frailty and cognition 1 1.2 Purpose of the study 3 Chapter 2. Methodological Background 5 2.1 Measurement of cerebral glucose metabolism using [18F]FDG PET. 5 2.2 Measurements of brain functional activity and intrinsic network using rsfMRI 6 2.2.1 Regional homogeneity using rs-fMRI 6 2.2.2 Group independent component analysis . 7 2.3 Dynamic functional connectivity analysis 10 Chapter 3. Subjects and Methods. 13 3.1 Participants . 13 3.1.1 Criteria of participants 13 3.1.2 Neuropsychological tests 14 3.1.3 Physical frailty definition . 14 3.1.4 Acquisition of [18F]FDG PET and rs-fMR images 19 3.1.5 Statistical analysis . 19 3.2 [18F]FDG PET image analysis . 20 3.2.1 Preprocessing steps of [18F]FDG PET . 20 3.2.2 Statistical analysis . 22 3.3 Resting state functional MRI analysis 22 3.3.1 Preprocessing steps of rs-fMRI 22 3.3.2 Calculations of regional homogeneity 23 3.3.3 Statistical analysis . 23 3.4 Functional connectivity analysis using rs-fMRI. 23 3.4.1 Group independent component analysis . 23 3.4.2 Dynamic functional network connectivity analysis 24 3.4.3 Reproducibility analyses of dynamic functional connectivity states. 26 3.4.4 Graph theory-based topological analysis: network efficiency . 27 3.4.5 Statistical analysis . 28 Chapter 4. Results. 30 4.1 Demographic and clinical characteristics of robust and at-risk groups 30 4.2 Glucose metabolism using [18F]FDG PET . 32 4.2.1 Group comparison in glucose metabolism 32 4.2.2 Relationships between cerebral glucose metabolism and physical and cognitive performances. 35 4.3 Resting-state functional activity using regional homogeneity. 38 4.3.1 Group comparison in regional homogeneity. 38 4.3.2 Relationships between regional homogeneity and physical and cognitive performances 41 4.4 Dynamic functional connectivity of brain networks . 45 4.4.1 Functional connectivity networks . 45 4.4.2 Dynamic functional connectivity states. 53 4.4.3 Validation results of dynamic functional connectivity states 57 4.4.4 Temporal properties of dynamic functional connectivity states . 62 4.4.5 Relationships between dynamic functional connectivity measures and physical and cognitive performances 66 4.4.6 Functional connectivity strengths in states . 70 4.4.7 Dynamic changes of global and local network efficiency 72 Chapter 5. Discussion 75 5.1 Metabolic and functional abnormalities in cognitive frailty 75 5.2 Alterations of dynamic functional connectivity states in cognitive frailty. 79 5.3 Conclusion and limitations of the study . 84 References . 88 국문 초록. 102Docto

Effects of Transcranial Magnetic Stimulation on the Default Mode Network in Minimal Cognitive Impairment and Alzheimer's disease: An ALE meta-analysis and systematic review

openObjective: This systematic review and meta-analysis sought to comprehensively assess the efficacy of repetitive transcranial magnetic stimulation (rTMS) on the default mode network (DMN) through functional magnetic resonance imaging (fMRI) among individuals diagnosed with mild cognitive impairment (MCI) and Alzheimer's disease (AD). The primary objective was to unravel the neuroimaging mechanisms underpinning cognitive intervention. Methods: A search encompassing English articles published until July 30, 2023, was conducted across prominent databases, including PubMed, Web of Science, Embase, and Cochrane Library. The study specifically focused on randomized controlled trials utilizing resting-state fMRI to investigate the impact of rTMS within the MCI and AD populations. The analysis of fMRI data was executed using GingerALE. Results: Our meta-analysis encompassed a total of seven studies focusing on AD, collectively 116 patients in the treatment group and 90 patients in the sham group. Additionally, in MCI group comprised 34 patients in the treatment groups and 39 patients in the sham group. The combined ALE quantitative analyses on group contrasts between Alzheimer's patients and the sham group showed no significant clusters of convergence. A similar outcome was observed when conducting meta-analyses of the MCI group. The restricted pool of eligible studies may have hindered our ability to detect meaningful clusters of convergence. Conclusions: The outcomes of this meta-analysis and systematic review collectively underscore the potential effectiveness and safety of rTMS intervention in addressing the needs of patients coping with MCI and AD. These improvements could likely be attributed to the favorable modulation that rTMS imparts upon spontaneous neural activity and cognitive networks. By elucidating the intricate neural mechanisms involved, this study contributes insights into the burgeoning field of cognitive intervention strategie

Investigation of dynamic functional connectivity in cerebral small vessel disease

Tese de mestrado integrado em Engenharia Biomédica e Biofísica (Biofísica Médica e Fisiologia de Sistemas), Universidade de Lisboa, Faculdade de Ciências, 2020A doença dos pequenos vasos cerebrais ou Small Vessel Disease (SVD) é a principal causa de disfunção cognitiva em idosos e refere-se a um conjunto de processos patológicos e neurológicos que afetam os pequenos vasos do cérebro. As suas manifestações clínicas variam desde deficiências cognitivas, que podem levar a uma deterioração cognitiva progressiva e até demência, e incapacidades físicas, incluindo perda funcional em fases mais avançadas da doença. A neuroimagiologia é uma ferramenta essencial no diagnóstico e caracterização da SVD, em particular, a ressonância magnética funcional em repouso (rs-fMRI) já demonstrou potencial para fornecer biomarcadores da SVD, revelando interrupções da conectividade funcional (CF) em redes neuronais. No entanto, até o momento, apenas um estudo explorou as flutuações temporais da CF comumente observadas – a chamada conectividade funcional dinâmica (dFC). Em contraste com a CF, a dFC tem em consideração a natureza dinâmica da atividade cerebral, analisando-a em escalas de tempo mais rápidas de segundos a minutos. De facto, diversos estudos de dFC reportaram que esta abordagem pode fornecer uma maior compreensão das propriedades fundamentais das redes cerebrais e servir como um biomarcador de diversas doenças, uma vez que as alterações relacionadas com as mesmas nas propriedades dinâmicas da CF parecem ter origem neuronal. Deste modo, neste trabalho, o objetivo foi investigar a dFC medida por rs-fMRI em dois grupos de pacientes com SVD – do tipo esporádico (sSVD) e arteriopatia cerebral autossómica dominante com enfartes subcorticais e leucoencefalopatia (CADASIL) - em comparação com um grupo saudável. Para tal, a dFC foi estimada entre pares de regiões do cérebro em cada tempo de repetição, TR, com o método de Phase Coherence. Neste método, os padrões de dFC para todos os pontos de tempo foram obtidos calculando o alinhamento de fase entre cada par de regiões do cérebro, estimando a fase do sinal de cada ponto de tempo, em cada uma das 90 regiões do cérebro, com a transformada de Hilbert. De seguida, os padrões de dFC ao longo do tempo e de todos os sujeitos foram analisados utilizando o método Leading Eigenvector Dynamics Analysis (LEiDA), que considera apenas o autovetor principal de cada padrão de dFC obtido, reduzindo deste modo a dimensionalidade dos dados. Este vetor captura a orientação principal das fases do sinal sobre todas as áreas, onde cada elemento do mesmo representa a projeção da fase do sinal em cada área do cérebro no autovetor principal. Em seguida, o algoritmo k-médias foi aplicado a todos os autovetores principais de dFC para obter um número finito de estados de dFC, cada um representando um padrão dFC recorrente, para um k (número de estados) variável. Como este trabalho teve como objetivo explorar se existem estados de dFC que diferenciam pacientes SVD do grupo saudável, e não determinar o número ideal de estados de dFC, o número de estados foi variado de 2 a 20. Para cada k, examinámos as diferenças em termos de probabilidade de ocorrência, duração e perfis de transição dos estados de dFC entre o grupo de doentes e o grupo de controlos saudáveis. Adicionalmente, os estados de dFC foram correlacionados com sete redes neuronais de repouso comuns, nomeadamente a rede somatomotora, a rede de atenção ventral e dorsal, a rede visual, a rede frontoparietal, a rede límbica e a rede de modo padrão. Posteriormente, a fim de determinar se as alterações nas propriedades de dFC, encontradas neste trabalho, poderiam ser potenciais biomarcadores de declínio cognitivo causadas pela SVD, foi realizado uma análise de correlação entre as pontuações dos testes neuropsicológicos em quatro domínios relevantes (função executiva, velocidade de processamento, memória de trabalho e memória de longo prazo) e as propriedades de dFC dos pacientes. Do mesmo modo, uma análise de correlação entre os mapas probabilísticos dos tratos de substância branca mais frequentemente lesionados destes pacientes e as propriedades de dFC foi, também, realizada com o objetivo de determinar se as alterações nas propriedades de dFC, encontradas nos pacientes quando comparadas com o grupo saudável, poderiam estar correlacionadas com lesões estruturais dos mesmos. Quando comparado com o grupo de controlos saudáveis, o grupo de doentes apresentou uma probabilidade de ocorrência significativamente maior num estado de dFC fracamente conectado, composto por áreas clinicamente relevantes. Este estado compreende áreas dos lobos frontais e parietais e está significativamente associado a redes neuronais envolvidas na integração de informações sensoriais e processos específicos para o controlo da atenção, nomeadamente a rede somatomotora, a rede de atenção ventral e dorsal. Estas mesmas redes foram anteriormente identificadas, em estudos de CF, como afetadas em pacientes com SVD, mas também em indivíduos com deficiências cognitivas e com doença de Alzheimer. Além disso, estudos de dFC em doenças relacionadas com a SVD, como a demência e a doença de Alzheimer, relataram que os pacientes também apresentaram maiores probabilidades de ocorrência em estados fracamente e esparsamente conectados, com ausência de fortes conexões positivas e negativas. Em particular, o único estudo de dFC em SVD também descobriu que os pacientes com SVD tiveram mais ocorrências num estado fracamente conectado nas regiões do domínio sensório-motor, quando comparado ao grupo saudável. Deste modo, podendo indicar que mudanças dinâmicas na CF nestas áreas podem ser particularmente importantes para esta doença. É também importante ressaltar que as probabilidades de transição entre este estado fronto-parietal fracamente conectado para o estado de coerência global, fortemente conectado, foram significativamente correlacionadas com melhor desempenho no domínio cognitivo da velocidade de processamento. Estas descobertas estão de acordo com resultados anteriores de estudos de dFC em indivíduos com melhores e piores desempenhos cognitivos, onde indivíduos com melhores desempenhos cognitivos tiveram maior número de transições para este estado de coerência global. Da mesma forma, as probabilidades de transição do estado fortemente conectado para o estado fronto-parietal fracamente conectado, foram significativamente correlacionadas com um pior desempenho neste mesmo domínio cognitivo. De facto, défices na velocidade de processamento estão entre as primeiras e mais proeminentes manifestações cognitivas da SVD, com diversos estudos demonstrando associações entre o declínio na velocidade de processamento e medidas quantitativas de ressonância magnética. Assim, estudos futuros devem investigar com maior detalhe transições entre estes estados, de modo a determinar se alterações nesta propriedade de dFC podem ser biomarcadores do declínio cognitivo na SVD. Em relação à análise dos mapas probabilísticos dos tratos de substância branca mais frequentemente lesionados nestes pacientes, embora nenhuma correlação significativa tenha sido encontrada com as alterações nas propriedades da dFC encontradas neste trabalho, é interessante notar que vários estudos têm relatado associações entre estas lesões e o declínio cognitivo. O facto de a substância branca ser organizada no cérebro por tratos, conectando regiões cerebrais funcionais entre si, espera-se que danos a esses tratos levem a défices funcionais. Efetivamente, dois dos tratos frequentemente lesionados nestes pacientes, conectando regiões frontais, foram anteriormente relacionados com um pior desempenho cognitivo na velocidade de processamento em pacientes com SVD e demência. É, portanto, tentador sugerir que estes mesmo tratos frequentemente lesionados nos pacientes com SVD aqui estudados, poderiam ter alguma influência no pior desempenho no teste da velocidade de processamento encontrado neste estudo, que foi correlacionado com uma maior probabilidade de transição para o estado fracamente conectado, composto por regiões do lobo frontal e parietal. A compreensão dessa relação poderia ajudar a prever em quais das regiões do cérebro a patologia da substância branca causaria maiores défices funcionais, permitindo uma prevenção e terapia precoce. No geral, os nossos resultados fornecem um novo suporte de que a conectividade funcional dinâmica pode fornecer biomarcadores mais sensíveis da SVD e deste modo, futuras investigações deverão explorar o seu potencial para prever o declínio cognitivo relacionado com a mesma.Cerebral small vessel disease (SVD) is the leading contributor to cognitive dysfunction in the elderly and it refers to a set of pathological and neurological processes that affect the smallest vessels of the brain. Its clinical manifestations vary from cognitive impairments, which can lead to progressive cognitive deterioration and even dementia, and physical disabilities, including functional loss in more advanced stages. Neuroimaging is a crucial tool in the diagnosis and characterization of SVD; in particular, resting-state functional magnetic resonance imaging (rs-fMRI) has demonstrated potential to deliver sensitive biomarkers of SVD, by revealing disruptions in functional connectivity (FC) across brain networks. However, so far only one study has explored the commonly observed FC temporal fluctuations – so-called dynamic FC (dFC). Here we aim to further investigate dFC measured by rs-fMRI in two groups of patients with SVD – sporadic SVD (sSVD) and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) – compared with a healthy control group. For this purpose, dFC was estimated at each repetition time point, TR, using Phase Coherence between the BOLD signals in pairs of brain regions, and dFC patterns were then analysed over time and subjects using the Leading Eigenvector Dynamics Analysis (LEiDA) approach. Then, a finite number of dFC states, each representing a recurrent dFC pattern, was obtained by k-means clustering with varying k (number of clusters). For each k, we examined differences between SVD and healthy control groups in terms of the occurrence, duration and switching profiles of dFC states. Additionally, the correlations between each dFC state and seven common resting-state networks (RSNs) were computed. SVD patients showed a significant higher probability of a weakly connected dFC state, consisting of clinically relevant areas, when compared with healthy controls. This state comprises frontal and parietal areas and is significantly associated with the somatomotor, dorsal attention and ventral attention RSNs, which are involved in the integration of sensory information and specific processes for attention control. Further, the fact that the state is weakly connected agrees with the only previous study on dFC in SVD. Overall, our findings contribute with novel support that dFC may provide sensitive biomarkers of SVD and should be further explored in terms of its potential to predictive cognitive decline

Hyperconnectivity is a fundamental response to neurological disruption

In the cognitive and clinical neurosciences, the past decade has been marked by dramatic growth in a literature examining brain "connectivity" using noninvasive methods. We offer a critical review of the blood oxygen level dependent functional MRI (BOLD fMRI) literature examining neural connectivity changes in neurological disorders with focus on brain injury and dementia. The goal is to demonstrate that there are identifiable shifts in local and large-scale network connectivity that can be predicted by the degree of pathology. We anticipate that the most common network response to neurological insult is hyperconnectivity but that this response depends upon demand and resource availability

Spontaneous brain activity in healthy aging: an overview through fluctuations and regional homogeneity

Introduction: This study aims to explore whole-brain resting-state spontaneous brain activity using fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) strategies to find differences among age groups within a population ranging from middle age to older adults. Methods: The sample comprised 112 healthy persons (M = 68.80, SD = 7.99) aged 48-89 who were split into six age groups (< 60, 60-64, 65-69, 70-74, 75-79, and ≥ 80). Fractional amplitude of low-frequency fluctuation and ReHo analyses were performed and were compared among the six age groups, and the significant results commonly found across groups were correlated with the gray matter volume of the areas and the age variable. Results: Increased activity was found using fALFF in the superior temporal gyrus and inferior frontal gyrus when comparing the first group and the fifth. Regarding ReHo analysis, Group 6 showed increased ReHo in the temporal lobe (hippocampus), right and left precuneus, right caudate, and right and left thalamus depending on the age group. Moreover, significant correlations between age and fALFF and ReHo clusters, as well as with their gray matter volume were found, meaning that the higher the age, the higher the regional synchronization, the lower the fALFF activation, and the lower gray matter of the right thalamus. Conclusion: Both techniques have been shown to be valuable and usable tools for disentangling brain changes in activation in a very low interval of years in healthy aging

Physiological and pathological modulations of intrinsic brain activity assessed via resting-state fMRI

Since its inception in 1992, functional magnetic resonance imaging (fMRI) has considerably boosted our knowledge of the human brain function, primarily due to its non-invasive nature, and its relative high spatial and temporal resolution. Among the available fMRI contrasts, blood-oxygenation level-dependent (BOLD) signal plays a leading role in this field. The contrast is based on the different magnetic properties of the haemoglobin which - combined with the specific relation existing between neuronal, vascular and metabolic activity - allows to ascribe variations in the measured signal to variations in the underlying neuronal activity. During BOLD acquisitions, the comparison of different cognitive states in task-based experiment (alternating rest states to sensory or cognitive stimulations) has revealed the modular organization of the human brain function, an operation that is commonly referred to as functional brain mapping. Surprisingly, task-induced activity requires an increase in brain’s energy consumption by less than 5 percent of the underlying baseline activity. Most of the brain’s energy demand, from 60 to 80 percent, is used to sustain intrinsic, task-unrelated, neural activity (Raichle, 2006). In this light, functional brain mapping, utilizing task-based fMRI, focuses only on the tip of the iceberg, whereas most of the brain’s activity remains largely uncharted. The notion that the brain has an intrinsic or spontaneous activity is known from early electro-encephalography (EEG) measures due to Hans Berger. However, only in recent years, after the seminal work of Biswal and colleagues (Biswal et al., 1995), the study of spontaneous brain activity has overwhelmingly emerged as a primary field of research in neuroscience. In the so called resting-state condition (i.e., when the brain is not focused on the external world), Biswal reported BOLD low-frequency (< 0.1 Hz) fluctuations (LFFs) synchronized across functionally related and anatomically connected regions. Thereafter, several studies have consistently shown that specific patterns of synchronized spontaneous LFFs identify different resting-state networks, including, but not limited to, visual, motor, auditory, and attentive network. The overall picture emerging from thousands of resting-state fMRI studies depicts a never-resting brain, continuously engaged in maintaining communications within several wide-distributed networks. Such intrinsic brain activity, reflected in spontaneous BOLD LFFs, is the focus of the present thesis. The study of LFFs in spontaneous BOLD signal can reveal much about brain’s functional organization, especially considering that signal variability has been related to variability in behaviour (Fox et al., 2007). In addition, the simplicity of data acquisition – subjects just lie in the scanner refraining from falling asleep - makes the technique particularly suited for studying pathological conditions, in which subject’s cooperation might not fulfil the demands of task-based studies. Indeed, several psychiatric and neurological disorders, including degenerative dementia, have shown altered patterns of LFFs, even in the absence of observable anatomical abnormalities (Barkhof et al., 2014). Thus, how the intrinsic brain’s activity is modulated in response to different behavioural states and in response to pathological conditions can give insights into the brain functionality and into the mechanisms behind illnesses, respectively. Importantly, correct result interpretation is highly influenced by the type of metrics adopted and how they are implemented. The resting-state approach to the study of the brain’s function has required the development of more sophisticated processing and analysis techniques compared to those commonly applied in task-based fMRI. While seeking for task-responding regions in the brain is guided by information embedded in the experimental paradigm, in steady-state fMRI no a priori cue is provided. In such experiment the extraction of relevant information is based on (i) the temporal synchronization between spatially segregated elements of the brain, feature known as functional connectivity, and on (ii) the amplitude of the oscillation per se, a measure of the strength of the intrinsic brain activity. Despite such simple classification, the field of resting-state fMRI is scattered with a disparate amount of metrics, each of which highlight different facets of spontaneous LFFs. Before turning to the study of spontaneous LFF modulations, we will provide a comprehensive and optimized mathematical framework for the extraction of relevant information from resting-state data (Chapter 2). The results of this effort is an easy-to-use matlab toolbox specifically designed for the processing and analysis of steady-state fMRI data. In principle, the information coded in functional connectivity and in oscillation amplitude are unrelated. While the former assesses the degree of cooperation between segregated elements of the brain, the latter quantifies the neural workload of each single brain’s element, independently from the activity of other regions. Nonetheless, modulations in both measurements have been reported in several pathological conditions - yet in separate studies - suggesting a possible relation between them. In this context, we sought to investigate the potential coupling between the functional connectivity and the oscillation amplitude in cohort of healthy elderly and the probable modulations induced by dementia of the Alzheimer’s type (Chapter 3). Regardless of how the brain relates the two types of measures extractable from resting-state data, their disease-induced modulations are relevant per se in uncovering the illness. Indeed, Alzheimer’s disease is known to produce alterations in spontaneous brain activity, both at the synchronization and the amplitude level (Wang et al., 2007). Since the hallmark of the pathology is a profound deficit in episodic memory, much effort has been done in characterizing the alterations in spontaneous brain activity underlying such deficit. Contrarily, little is known about another commonly reported deficit, the language related impairment (Taler and Phillips, 2008). In the second part of Chapter 3 we sought to disclose the brain regions underpinning language deficits by looking at the alterations in functional connectivity of the relevant network. While the study of LFFs in pathological conditions can contribute to reveal the mechanisms behind the pathology and how it spreads into the brain, the study of spontaneous brain activity in physiological conditions can disclose the intrinsic brain functionality. In healthy subjects the resting brain has been extensively characterized and its network topology has shown to be a consistent and reliable physiological feature (Damoiseaux et al., 2006). An intriguing issue is how the brain reorganizes its patterns of spontaneous BOLD LFF while it is focusing on the external world. Indeed, the intrinsic brain activity is not an exclusive feature of the resting condition, instead it is present also on the top of the task-evoked response. In chapter 4, with peculiar experimental paradigms we separated the task-evoked response from the intrinsic brain activity during sustained cognitive stimulations. In a first experiment we sought to characterize the spatio-temporal proprieties and the dynamic of the transition from a resting to a stimulated condition. In the second part we specifically investigated how the brain reorganizes its internal functional architecture during visuospatial attention. Indeed, besides strongly affecting the processing of visual incoming stimuli, visual spatial attention also affects brain networks. Recent studies suggest that visual attention affects functional connectivity within and between the visual network and the attention network (Spadone et al., 2015), yet modulations of attention on brain networks are still poorly understood

Aberrant brain network connectivity in pre-symptomatic and manifest Huntington's disease: a systematic review

Resting-state functional magnetic resonance imaging (rs-fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic review of the literature was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs-fMRI. We included studies investigating connectivity in pre-symptomatic (pre-HD) and manifest HD gene carriers compared to healthy controls, implementing seed-based connectivity, independent component analysis, regional property and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre-HD, showing disease stage-dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior-posterior alterations, reflecting possible compensatory mechanisms. The involvement of these networks in pre-HD is still unclear. In conclusion, aberrant connectivity of the sensory-motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory-motor and executive networks exhibit hyper- and hypo-connectivity patterns following different spatiotemporal trajectories. These findings could help to implement future huntingtin-lowering interventions

Altered brain spontaneous activity in patients with cerebral small vessel disease using the amplitude of low-frequency fluctuation of different frequency bands

BackgroundPrevious studies showed that cerebral small vessel disease (cSVD) is a leading cause of cognitive decline in elderly people and the development of Alzheimer’s disease. Although brain structural changes of cSVD have been documented well, it remains unclear about the properties of brain intrinsic spontaneous activity in patients with cSVD.MethodsWe collected resting-state fMRI (rs-fMRI) and T1-weighted 3D high-resolution brain structural images from 41 cSVD patients and 32 healthy controls (HC). By estimating the amplitude of low-frequency fluctuation (ALFF) under three different frequency bands (typical band: 0.01–0.1 Hz; slow-4: 0.027–0.073 Hz; and slow-5: 0.01–0.027 Hz) in the whole-brain, we analyzed band-specific ALFF differences between the cSVD patients and controls.ResultsThe cSVD patients showed uniformly lower ALFF than the healthy controls in the typical and slow-4 bands (pFWE &lt; 0.05). In the typical band, cSVD patients showed lower ALFF involving voxels of the fusiform, hippocampus, inferior occipital cortex, middle occipital cortex, insula, inferior frontal cortex, rolandic operculum, and cerebellum compared with the controls. In the slow-4 band, cSVD patients showed lower ALFF involving voxels of the cerebellum, hippocampus, occipital, and fusiform compared with the controls. However, there is no significant between-group difference of ALFF in the slow-5 band. Moreover, we found significant “group × frequency” interactions in the left precuneus.ConclusionOur results suggested that brain intrinsic spontaneous activity of cSVD patients was abnormal and showed a frequency-specific characteristic. The ALFF in the slow-4 band may be more sensitive to detecting a malfunction in cSVD patients

Comparison of longitudinal changes in resting state functional magnetic resonance imaging between alzheimer’s and healthy controls

Resting State Functional Magnetic Resonance Imaging (rs-fMRI) is a technique that is widely used for analyzing brain function using different approaches and methods. This study involves rs-fMRI analysis of Blood Oxygenation Level Dependent (BOLD) signals acquired from Alzheimer’s disease (AD) Patients and Healthy Controls (HC). Each subject in the study had both functional and anatomical images with at least one rs-fMRI scan with their Anatomical (T1) scans. Previous rs-fMRI studies have demonstrated that AD shows differences in Amplitude of Low Frequency (\u3c0.1 Hz) Fluctuations (ALFF), and Regional Homogeneity (ReHo) measures according to HCs. The aim of the study is to investigate individual and group level differences using ReHo and mALFF related measures in a longitudinal analysis. The hypothesis is that with the age and group (AD or HC) of the subject, it is possible to separate AD and HC subjects from each other using 3 different ROIs (DMN – MT – MV), These regions are known to show abnormalities in AD patients but clinical wise never been identified as neuroimaging biomarkers. This study tries to check these ROIs to see if there are significant differences between the AD patients and HCs using 3 different features