Novelty-Related fMRI Responses of Precuneus and Medial Temporal Regions in Individuals at Risk for Alzheimer Disease

Deep linear matrix approximate reconstruction with integrated BOLD signal denoising reveals reproducible hierarchical brain connectivity networks from multiband multi-echo fMRI

The hierarchical modular functional structure in the human brain has not been adequately depicted by conventional functional magnetic resonance imaging (fMRI) acquisition techniques and traditional functional connectivity reconstruction methods. Fortunately, rapid advancements in fMRI scanning techniques and deep learning methods open a novel frontier to map the spatial hierarchy within Brain Connectivity Networks (BCNs). The novel multiband multi-echo (MBME) fMRI technique has increased spatiotemporal resolution and peak functional sensitivity, while the advanced deep linear model (multilayer-stacked) named DEep Linear Matrix Approximate Reconstruction (DELMAR) enables the identification of hierarchical features without extensive hyperparameter tuning. We incorporate a multi-echo blood oxygenation level-dependent (BOLD) signal and DELMAR for denoising in its first layer, thereby eliminating the need for a separate multi-echo independent component analysis (ME-ICA) denoising step. Our results demonstrate that the DELMAR/Denoising/Mapping strategy produces more accurate and reproducible hierarchical BCNs than traditional ME-ICA denoising followed by DELMAR. Additionally, we showcase that MBME fMRI outperforms multiband (MB) fMRI in terms of hierarchical BCN mapping accuracy and precision. These reproducible spatial hierarchies in BCNs have significant potential for developing improved fMRI diagnostic and prognostic biomarkers of functional connectivity across a wide range of neurological and psychiatric disorders.

Whole-brain functional connectivity predicts regional tau PET in preclinical Alzheimer's disease

Preclinical Alzheimer's disease (AD), characterized by the abnormal accumulation of amyloid prior to cognitive symptoms, presents a critical opportunity for early intervention. Past work has described functional connectivity changes in preclinical disease, yet the interplay between AD pathology and the functional connectome during this window remains unexplored. We applied connectome-based predictive modeling to investigate the ability of resting-state whole-brain functional connectivity to predict tau (18F-flortaucipir) and amyloid (18F-florbetapir) PET binding in a preclinical AD cohort (A4, n =342, age 65-85). Separate predictive models were developed for each of 14 regions, and model performance was assessed using a Spearman's correlation between predicted and observed PET binding standard uptake value ratios. We assessed the validity of significant models by applying them to an external dataset, and visualized the underlying connectivity that was positively and negatively correlated to posterior cingulate tau binding, the most successful model. We found that whole brain functional connectivity predicts regional tau PET, outperforming amyloid PET models. The best performing tau models were for regions affected in Braak stage IV-V regions (posterior cingulate, precuneus, lateral occipital cortex, middle temporal, inferior temporal, and Bank STS), while models for regions of earlier tau pathology (entorhinal, parahippocampal, fusiform, and amygdala) performed poorly. Importantly, tau models generalized to a symptomatic AD cohort (ADNI; amyloid positive, n = 211, age 55-90), in tau-elevated but not tau-negative individuals. For the posterior cingulate A4 tau model, the most successful model, the predictive edges positively correlated with posterior cingulate tau predominantly came from nodes within temporal, limbic, and cerebellar regions. The most predictive edges negatively associated to tau were from nodes of heteromodal association areas, particularly within the prefrontal and parietal cortices. These findings reveal that whole-brain functional connectivity predicts tau PET in preclinical AD and generalizes to a clinical dataset specifically in individuals with abnormal tau PET, highlighting the relevance of the functional connectome for the early detection and monitoring of AD pathology.

Precuneus Activity during Retrieval Is Positively Associated with Amyloid Burden in Cognitively Normal Older APOE4 Carriers

The precuneus is a site of early amyloid-beta (Aβ) accumulation. Previous cross-sectional studies reported increased precuneus fMRI activity in older adults with mild cognitive deficits or elevated Aβ. However, longitudinal studies in early Alzheimer's disease (AD) are lacking and the relationship to the Apolipoprotein-E (APOE) genotype is unclear. Investigating the PREVENT-AD dataset, we assessed how baseline and longitudinal precuneus activity during successful memory retrieval relates to future Aβ and tau burden and change in memory performance. We further studied the moderation by APOE4 genotype. We included 165 older adults (age, 62.8 ± 4.4 years; 113 female; 66 APOE4 carriers) who were cognitively normal at baseline with a family history of AD. All participants performed task-fMRI at baseline and underwent 18F-flortaucipir-PET and 18F-NAV4694-Aβ-PET on average 5 years later. We found that higher baseline activity and greater longitudinal increase in precuneus activity were associated with higher Aβ burden in APOE4 carriers but not noncarriers. We observed no effects of precuneus activity on tau burden. Finally, APOE4 noncarriers with low baseline precuneus activity exhibited better longitudinal performance in an independent memory test compared with (1) noncarriers with higher baseline activity and (2) APOE4 carriers. Our findings suggest that higher task-related precuneus activity during memory retrieval at baseline and over time are associated with greater Aβ burden in cognitively normal APOE4 carriers. Our results further indicate that the absence of "hyperactivation" and the absence of the APOE4 allele is related with better future cognitive outcomes in cognitively normal older adults at risk for AD.

Environmental enrichment is associated with favorable memory-related functional brain activity patterns in older adults

Background

In humans, environmental enrichment (EE), as measured by the engagement in a variety of leisure activities, has been associated with larger hippocampal structure and better memory function. The present cross-sectional study assessed whether EE during early life (13-30 years) and midlife (30-65 years) is associated with better preserved memory-related brain activity patterns in older age.

Methods

In total, 372 cognitively unimpaired older adults (aged ≥60 years old) of the DZNE-Longitudinal Study on Cognitive Impairment and Dementia (DELCODE; DRKS00007966) were investigated. EE was operationalized using items of the Lifetime of Experiences Questionnaire (LEQ), which measures the self-reported participation in a variety of leisure activities in early life and midlife. The preservation of memory-related functional brain activity was assessed using single-value scores, which relate older adults' brain activity patterns in the temporo-parieto-occipital memory network to those of young adults during visual memory encoding (FADE and SAME scores).

Results

EE during early life and midlife was significantly associated with higher SAME scores during novelty processing (n = 372, β = 0.13, p = 0.011). Thus, older participants with higher EE showed greater similarity of functional brain activity patterns during novelty processing with young adults. This positive association was observed most strongly in participants with subjective cognitive decline (SCD, n = 199, β = 0.20, p = 0.006).

Conclusion

More frequent participation in a variety of leisure activities in early life and midlife is associated with more successful aging of functional brain activity patterns in the memory network of older adults, including participants at increased risk for dementia. Longitudinal studies are needed to clarify whether higher EE during life could help preserve memory network function in later life.

Cognitive reserve against Alzheimer's pathology is linked to brain activity during memory formation

The cognitive reserve (CR) hypothesis posits that individuals can differ in how their brain function is disrupted by pathology associated with aging and neurodegeneration. Here, we test this hypothesis in the continuum from cognitively normal to at-risk stages for Alzheimer's Disease (AD) to AD dementia using longitudinal data from 490 participants of the DELCODE multicentric observational study. Brain function is measured using task fMRI of visual memory encoding. Using a multivariate moderation analysis, we identify a CR-related activity pattern underlying successful memory encoding that moderates the detrimental effect of AD pathological load on cognitive performance. CR is mainly represented by a more pronounced expression of the task-active network encompassing deactivation of the default mode network (DMN) and activation of inferior temporal regions including the fusiform gyrus. We devise personalized fMRI-based CR scores that moderate the impact of AD pathology on cognitive performance and are positively associated with years of education. Furthermore, higher CR scores attenuate the effect of AD pathology on cognitive decline over time. Our findings primarily provide evidence for the maintenance of core cognitive circuits including the DMN as the neural basis of CR. Individual brain activity levels of these areas during memory encoding have prognostic value for future cognitive decline.

Comparative efficacy of intermittent theta burst stimulation and high-frequency repetitive transcranial magnetic stimulation in amnestic mild cognitive impairment patients

Intermittent theta burst stimulation, a derivative of repetitive transcranial magnetic stimulation, has been applied to improve cognitive deficits. However, its efficacy and mechanisms in enhancing cognitive function in patients with amnestic mild cognitive impairment compared with traditional repetitive transcranial magnetic stimulation paradigms remain unclear. This study recruited 48 amnestic mild cognitive impairment patients, assigning them to intermittent theta burst stimulation, repetitive transcranial magnetic stimulation, and sham groups (5 times/wk for 4 wk). Neuropsychological assessments and functional magnetic resonance imaging data were collected pre- and post-treatment. Regarding efficacy, both angular gyrus intermittent theta burst stimulation and repetitive transcranial magnetic stimulation significantly improved general cognitive function and memory compared to the sham group, with no significant difference between the 2 treatment groups. Mechanistically, significant changes in brain activity within the temporoparietal network were observed in both the intermittent theta burst stimulation and repetitive transcranial magnetic stimulation groups, and these changes correlated with improvements in general cognitive and memory functions. Additionally, intermittent theta burst stimulation showed stronger modulation of functional connectivity between the hippocampus, parahippocampal gyrus, and temporal regions compared to repetitive transcranial magnetic stimulation. The intermittent theta burst stimulation and repetitive transcranial magnetic stimulation can improve cognitive function in amnestic mild cognitive impairment patients, but intermittent theta burst stimulation may offer higher efficiency. Intermittent theta burst stimulation and repetitive transcranial magnetic stimulation likely enhance cognitive function, especially memory function, by modulating the temporoparietal network.

Single-value brain activity scores reflect both severity and risk across the Alzheimer's continuum

Single-value scores reflecting the deviation from (FADE score) or similarity with (SAME score) prototypical novelty-related and memory-related functional MRI activation patterns in young adults have been proposed as imaging biomarkers of healthy neurocognitive ageing. Here, we tested the utility of these scores as potential diagnostic and prognostic markers in Alzheimer's disease (AD) and risk states like mild cognitive impairment (MCI) or subjective cognitive decline (SCD). To this end, we analysed subsequent memory functional MRI data from individuals with SCD, MCI and AD dementia as well as healthy controls and first-degree relatives of AD dementia patients (AD-rel) who participated in the multi-centre DELCODE study (n = 468). Based on the individual participants' whole-brain functional MRI novelty and subsequent memory responses, we calculated the FADE and SAME scores and assessed their association with AD risk stage, neuropsychological test scores, CSF amyloid positivity and APOE genotype. Memory-based FADE and SAME scores showed a considerably larger deviation from a reference sample of young adults in the MCI and AD dementia groups compared to healthy controls, SCD and AD-rel. In addition, novelty-based scores significantly differed between the MCI and AD dementia groups. Across the entire sample, single-value scores correlated with neuropsychological test performance. The novelty-based SAME score further differed between Aβ-positive and Aβ-negative individuals in SCD and AD-rel, and between ApoE ɛ4 carriers and non-carriers in AD-rel. Hence, FADE and SAME scores are associated with both cognitive performance and individual risk factors for AD. Their potential utility as diagnostic and prognostic biomarkers warrants further exploration, particularly in individuals with SCD and healthy relatives of AD dementia patients.

Synergistic association of Aβ and tau pathology with cortical neurophysiology and cognitive decline in asymptomatic older adults

Animal and computational models of Alzheimer's disease (AD) indicate that early amyloid-β (Aβ) deposits drive neurons into a hyperactive regime, and that subsequent tau depositions manifest an opposite, suppressive effect as behavioral deficits emerge. Here we report analogous changes in macroscopic oscillatory neurophysiology in the human brain. We used positron emission tomography and task-free magnetoencephalography to test the effects of Aβ and tau deposition on cortical neurophysiology in 104 cognitively unimpaired older adults with a family history of sporadic AD. In these asymptomatic individuals, we found that Aβ depositions colocalize with accelerated neurophysiological activity. In those also presenting medial-temporal tau pathology, linear mixed effects of Aβ and tau depositions indicate a shift toward slower neurophysiological activity, which was also linked to cognitive decline. We conclude that early Aβ and tau depositions relate synergistically to human cortical neurophysiology and subsequent cognitive decline. Our findings provide insight into the multifaceted neurophysiological mechanisms engaged in the preclinical phases of AD.

Cerebral hyperactivation across the Alzheimer's disease pathological cascade

Neuronal dysfunction in specific brain regions or across distributed brain networks is a known feature of Alzheimer's disease. An often reported finding in the early stage of the disease is the presence of increased functional MRI (fMRI) blood oxygenation level-dependent signal under task conditions relative to cognitively normal controls, a phenomenon known as 'hyperactivation'. However, research in the past decades yielded complex, sometimes conflicting results. The magnitude and topology of fMRI hyperactivation patterns have been found to vary across the preclinical and clinical spectrum of Alzheimer's disease, including concomitant 'hypoactivation' in some cases. These incongruences are likely due to a range of factors, including the disease stage at which the cohort is examined, the brain areas or networks studied and the fMRI paradigm utilized to evoke these functional abnormalities. Additionally, a perennial question pertains to the nature of hyperactivation in the context of Alzheimer's disease. Some propose it reflects compensatory mechanisms to sustain cognitive performance, while others suggest it is linked to the pathological disruption of a highly regulated homeostatic cycle that contributes to, or even drives, disease progression. Providing a coherent narrative for these empirical and conceptual discrepancies is paramount to develop disease models, understand the synergy between hyperactivation and the Alzheimer's disease pathological cascade and tailor effective interventions. We first provide a comprehensive overview of functional brain changes spanning the course from normal ageing to the clinical spectrum of Alzheimer's disease. We then highlight evidence supporting a close relationship between fMRI hyperactivation and in vivo markers of Alzheimer's pathology. We primarily focus on task-based fMRI studies in humans, but also consider studies using different functional imaging techniques and animal models. We then discuss the potential mechanisms underlying hyperactivation in the context of Alzheimer's disease and provide a testable framework bridging hyperactivation, ageing, cognition and the Alzheimer's disease pathological cascade. We conclude with a discussion of future challenges and opportunities to advance our understanding of the fundamental disease mechanisms of Alzheimer's disease, and the promising development of therapeutic interventions incorporating or aimed at hyperactivation and large-scale functional systems.

fMRI-based Alzheimer's disease detection via functional connectivity analysis: a systematic review

Alzheimer's disease is a common brain disorder affecting many people worldwide. It is the primary cause of dementia and memory loss. The early diagnosis of Alzheimer's disease is essential to provide timely care to AD patients and prevent the development of symptoms of this disease. Various non-invasive techniques can be utilized to diagnose Alzheimer's in its early stages. These techniques include functional magnetic resonance imaging, electroencephalography, positron emission tomography, and diffusion tensor imaging. They are mainly used to explore functional and structural connectivity of human brains. Functional connectivity is essential for understanding the co-activation of certain brain regions co-activation. This systematic review scrutinizes various works of Alzheimer's disease detection by analyzing the learning from functional connectivity of fMRI datasets that were published between 2018 and 2024. This work investigates the whole learning pipeline including data analysis, standard preprocessing phases of fMRI, feature computation, extraction and selection, and the various machine learning and deep learning algorithms that are used to predict the occurrence of Alzheimer's disease. Ultimately, the paper analyzed results on AD and highlighted future research directions in medical imaging. There is a need for an efficient and accurate way to detect AD to overcome the problems faced by patients in the early stages.

Functional locus coeruleus imaging to investigate an ageing noradrenergic system

The locus coeruleus (LC), our main source of norepinephrine (NE) in the brain, declines with age and is a potential epicentre of protein pathologies in neurodegenerative diseases (ND). In vivo measurements of LC integrity and function are potentially important biomarkers for healthy ageing and early ND onset. In the present study, high-resolution functional MRI (fMRI), a reversal reinforcement learning task, and dedicated post-processing approaches were used to visualise age differences in LC function (N = 50). Increased LC responses were observed during emotionally and task-related salient events, with subsequent accelerations and decelerations in reaction times, respectively, indicating context-specific adaptive engagement of the LC. Moreover, older adults exhibited increased LC activation compared to younger adults, indicating possible compensatory overactivation of a structurally declining LC in ageing. Our study shows that assessment of LC function is a promising biomarker of cognitive aging.

Examining the relationship between brain activation and proxies of disease severity using quantile regression in individuals at risk of Alzheimer's disease

Previous studies have reported a pattern of hyperactivation in the pre-dementia phase of Alzheimer's disease (AD), followed by hypoactivation in later stages of the disease. This pattern was modeled as an inverse U-shape function between activation and markers of disease severity. In this study, we used quantile regression to model the association between task-related brain activation in AD signature regions and three markers of disease severity (hippocampal volume, cortical thickness, and associative memory). This approach offers distinct advantages over standard regression models as it analyzes the relationship between brain activation and disease severity across various levels of brain activation. Participants were 54 older adults with subjective cognitive decline+ (SCD+) or mild cognitive impairment (MCI) from the CIMA-Q cohort. The analysis revealed an inverse U-shape quadratic function depicting the relationship between disease severity markers and the activation of the left superior parietal region, while a linear relationship was observed for activation of the hippocampal and temporal regions. Quantile differences were observed for temporal and parietal activation, with more pronounced effects observed in the higher quantiles of activation. When comparing quantiles, we found that higher quantile of activation featured a greater number of individuals with SCD+ compared to mild cognitive impairment (MCI). Results are globally consistent with the presence of an inverse-U shape function of activation in relation to disease severity. They study also underscores the utility of employing quantile regression modeling as the modeling approach revealed the presence of non-homogeneous effects across various quantiles.

Alterations in hippocampus-centered morphological features and function of the progression from normal cognition to mild cognitive impairment

Mild cognitive impairment (MCI) is a significant precursor to dementia, highlighting the critical need for early identification of individuals at high risk of MCI to prevent cognitive decline. The study aimed to investigate the changes in brain structure and function before the onset of MCI. This study enrolled 19 older adults with progressive normal cognition (pNC) to MCI and 19 older adults with stable normal cognition (sNC). The gray matter (GM) volume and functional connectivity (FC) were estimated via magnetic resonance imaging during their normal cognition state 3 years prior. Additionally, spatial associations between FC maps and neurochemical profiles were examined using JuSpace. Compared to the sNC group, the pNC group showed decreased volume in the left hippocampus and left amygdala. The significantly positive correlation was observed between the GM volume of the left hippocampus and the MMSE scores after 3 years in pNC group. Besides, it showed that the pNC group had increased FC between the left hippocampus and the anterior-posterior cingulate gyrus, which was significantly correlated with the spatial distribution of dopamine D2 and noradrenaline transporter. Taken together, the study identified the abnormal brain characteristics before the onset of MCI, which might provide insight into clinical research.

Amyloid induced hyperexcitability in default mode network drives medial temporal hyperactivity and early tau accumulation

In early Alzheimer's disease (AD) β-amyloid (Aβ) deposits throughout association cortex and tau appears in the entorhinal cortex (EC). Why these initially appear in disparate locations is not understood. Using task-based fMRI and multimodal PET imaging, we assess the impact of local AD pathology on network-to-network interactions. We show that AD pathologies flip interactions between the default mode network (DMN) and the medial temporal lobe (MTL) from inhibitory to excitatory. The DMN is hyperexcited with increasing levels of Aβ, which drives hyperexcitability within the MTL and this directed hyperexcitation of the MTL by the DMN predicts the rate of tau accumulation within the EC. Our results support a model whereby Aβ induces disruptions to local excitatory-inhibitory balance in the DMN, driving hyperexcitability in the MTL, leading to tau accumulation. We propose that Aβ-induced disruptions to excitatory-inhibitory balance is a candidate causal route between Aβ and remote EC-tau accumulation.

Convergent Multimodal Imaging Abnormalities in the Dorsal Precuneus in Subjective Cognitive Decline

Background

A range of imaging modalities have reported Alzheimer's disease-related abnormalities in individuals experiencing subjective cognitive decline (SCD). However, there has been no consistent local abnormality identified across multiple neuroimaging modalities for SCD.

Objective

We aimed to investigate the convergent local alterations in amyloid-β (Aβ) deposition, glucose metabolism, and resting-state functional MRI (RS-fMRI) metrics in SCD.

Methods

Fifty SCD patients (66.4±5.7 years old, 19 men [38%]) and 15 normal controls (NC) (66.3±4.4 years old, 5 men [33.3%]) were scanned with both [18F]-florbetapir PET and [18F]-fluorodeoxyglucose PET, as well as simultaneous RS-fMRI from February 2018 to November 2018. Voxel-wise metrics were retrospectively analyzed, including Aβ deposition, glucose metabolism, amplitude of low frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality(DC).

Results

The SCD group showed increased Aβ deposition and glucose metabolism (p < 0.05, corrected), as well as decreased ALFF, ReHo, and DC (p < 0.05, uncorrected) in the left dorsal precuneus (dPCu). Furthermore, the dPCu illustrated negative resting-state functional connectivity with the default mode network. Regarding global Aβ deposition positivity, the Aβ deposition in the left dPCu showed a gradient change, i.e., Aβ positive SCD > Aβ negative SCD > Aβ negative NC. Additionally, both Aβ positive SCD and Aβ negative SCD showed increased glucose metabolism and decreased RS-fMRI metrics in the dPCu.

Conclusions

The dorsal precuneus, an area implicated in early AD, shows convergent neuroimaging alterations in SCD, and might be more related to other cognitive functions (e.g., unfocused attention) than episodic memory.

Altered Neuronal Activity Patterns of the Prefrontal Cortex in Alzheimer's Disease After Transcranial Alternating Current Stimulation: A Resting-State fMRI Study

Background

Transcranial alternating current stimulation (tACS) could improve cognition in patients with Alzheimer's disease (AD). However, the effects of tACS on brain activity remain unclear.

Objective

The purpose is to investigate the change in regional neuronal activity after tACS in AD patients employing resting-state functional magnetic resonance imaging (rs-fMRI).

Methods

A total of 46 patients with mild AD were enrolled. Each patient received 30 one-hour sessions of real or sham tACS for three weeks (clinical trial: NCT03920826). The fractional amplitude of low-frequency fluctuations (fALFF) and the regional homogeneity (ReHo) measured by rs-fMRI were calculated to evaluate the regional brain activity.

Results

Compared to baseline, AD patients in the real group exhibited increased fALFF in the left middle frontal gyrus-orbital part and right inferior frontal gyrus-orbital part, as well as increased ReHo in the left precentral gyrus and right middle frontal gyrus at the end of intervention. At the 3-month follow-up, fALFF increased in the left superior parietal lobule and right inferior temporal gyrus, as well as ReHo, in the left middle frontal gyrus and right superior medial frontal gyrus. A higher fALFF in the right lingual gyrus and ReHo in the right parahippocampal gyrus were observed in the response group than in the nonresponse group.

Conclusions

The findings demonstrated the beneficial effects of tACS on the neuronal activity of the prefrontal cortex and even more extensive regions and provided a neuroimaging biomarker of treatment response in AD patients.

Associations Between Hyperactive Neuropsychiatric Symptoms and Brain Morphology in Mild Cognitive Impairment and Alzheimer's Disease

BACKGROUND

Hyperactive neuropsychiatric symptoms (NPS) (i.e., agitation, disinhibition, and irritability) are among the most challenging symptoms to manage in Alzheimer's disease (AD). However, their underlying brain correlates have been poorly studied.

OBJECTIVE

We aimed to investigate the associations between the total score of hyperactive NPS and brain structures in participants with AD, mild cognitive impairment (MCI), and cognitively normal older adults (CN).

METHODS

Neuropsychiatric and 3T MRI data from 216 AD, 564 MCI, and 660 CN participants were extracted from the Alzheimer's Disease Neuroimaging Initiative database. To define NPS and brain structures' associations, we fitted a general linear model (GLM) in two ways: 1) an overall GLM including all three groups (AD, MCI, CN) and 2) three pair-wise GLMs (AD versus MCI, MCI versus CN, AD versus CN). The cortical changes as a function of NPS total score were investigated using multiple regression analyses.

RESULTS

Results from the overall GLM include associations between 1) agitation and the right parietal supramarginal surface area in the MCI-CN contrast, 2) disinhibition and the cortical thickness of the right frontal pars opercularis and temporal inferior in the AD-MCI contrast, and 3) irritability and the right frontal pars opercularis, frontal superior, and temporal superior volumes in the MCI-CN contrast.

CONCLUSIONS

Our study shows that each hyperactive NPS is associated with distinct brain regions in AD, MCI, and CN (groups with different levels of cognitive performance). This suggests that each NPS is associated with a unique signature of brain morphology, including variations in volume, thickness, or area.

Correlation Between the Fractional Amplitude of Low-Frequency Fluctuation and Cognitive Defects in Alzheimer's Disease

Background

The fractional amplitude of low-frequency fluctuations (fALFFs) can detect spontaneous brain activity. However, the association between abnormal brain activity and cognitive function, amyloid protein (Aβ), and emotion in Alzheimer's disease (AD) patients remains unclear.

Objective

This study aimed to survey alterations in fALFF in different frequency bands and the relationship between abnormal brain activity, depressive mood, and cognitive function to determine the potential mechanism of AD.

Methods

We enrolled 34 AD patients and 32 healthy controls (HC). All the participants underwent resting-state magnetic resonance imaging, and slow-4 and slow-5 fALFF values were measured. Subsequently, the study determined the correlation of abnormal brain activity with mood and cognitive function scores.

Results

AD patients revealed altered mfALFF values in the slow-5 and slow-4 bands. In the slow-4 band, the altered mfALFF regions were the right cerebellar crus I, right inferior frontal orbital gyrus (IFOG), right supramarginal gyrus, right precuneus, angular gyrus, and left middle cingulate gyrus. Elevated mfALFF values in the right IFOG were negatively associated with Montreal Cognitive Assessment scores, Boston Naming Test, and Aβ1-42 levels. The mfALFF value of the AD group was lower than the HC group in the slow-5 band, primarily within the right inferior parietal lobule and right precuneus.

Conclusions

Altered mfALFF values in AD patients are linked with cognitive dysfunction. Compared with HCs, Aβ1-42 levels in AD patients are related to abnormal IFOG activity. Therefore, mfALFF could be a potential biomarker of AD.

Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment

Mild cognitive impairment (MCI) is a potential therapeutic window in the prevention of dementia; however, automated detection of early cognitive deterioration is an unresolved issue. The aim of our study was to compare various classification approaches to differentiate MCI patients from healthy controls, based on rs-fMRI data, using machine learning (ML) algorithms. Own dataset (from two centers) and ADNI database were used during the analysis. Three fMRI parameters were applied in five feature selection algorithms: local correlation, intrinsic connectivity, and fractional amplitude of low frequency fluctuations. Support vector machine (SVM) and random forest (RF) methods were applied for classification. We achieved a relatively wide range of 78-87% accuracy for the various feature selection methods with SVM combining the three rs-fMRI parameters. In the ADNI datasets case we can also see even 90% accuracy scores. RF provided a more harmonized result among the feature selection algorithms in both datasets with 80-84% accuracy for our local and 74-82% for the ADNI database. Despite some lower performance metrics of some algorithms, most of the results were positive and could be seen in two unrelated datasets which increase the validity of our methods. Our results highlight the potential of ML-based fMRI applications for automated diagnostic techniques to recognize MCI patients.

High burdens of phosphorylated tau protein and distinct precuneus atrophy in sporadic early-onset Alzheimer's disease

Early-onset Alzheimer's disease (EOAD) is a rare devastating subclassification of Alzheimer's disease (AD). EOAD affects individuals <65 years old, and accounts for 5%-10% of all AD cases. Previous studies on EOAD primarily focused on familial forms, whereas research on sporadic EOAD (sEOAD), which represents 85%-90% of EOAD cases, is limited. In this prospective cohort study, participants were recruited between 2018 and 2023 and included patients with sEOAD (n = 110), late-onset AD (LOAD, n = 89), young controls (YC, n = 50), and older controls (OC, n = 25). All AD patients fulfilled the diagnostic criteria based on biomarker evidence. Familial EOAD patients or non-AD dementia patients were excluded. Single molecule array technology was used to measure fluid biomarkers, including cerebrospinal fluid (CSF) and plasma amyloid beta (Aβ) 40, Aβ42, phosphorylated tau (P-tau) 181, total tau (T-tau), serum neurofilament light chain and glial fibrillary acidic protein (GFAP). Patients with sEOAD exhibited more severe executive function impairment and bilateral precuneus atrophy (P < 0.05, family-wise error corrected) than patients with LOAD. Patients with sEOAD showed elevated CSF and plasma P-tau181 levels (154.0 ± 81.2 pg/mL, P = 0.002; and 6.1 ± 2.3 pg/mL, P = 0.046). Moreover, precuneus atrophy was significantly correlated with serum GFAP levels in sEOAD (P < 0.001). Serum GFAP levels (area under the curve (AUC) = 96.0%, cutoff value = 154.3 pg/mL) displayed excellent diagnostic value in distinguishing sEOAD patients from the control group. These preliminary findings highlight the crucial role of tau protein phosphorylation in the pathogenesis and progression of sEOAD.

rTMS regulates homotopic functional connectivity in the SCD and MCI patients

OBJECTIVE

Impaired interhemispheric connectivity and corpus callosum atrophy have been linked to cognitive impairment in Alzheimer's disease (AD). Existing evidence indicates that repetitive transcranial magnetic stimulation (rTMS) targeting the bilateral precuneus may enhance cognitive function in AD. This study aims to investigate the effects of precuneus rTMS on cognitive function, as well as alterations in interhemispheric functional connectivity (FC) and its structural basis in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

METHODS

A total of 14 patients with SCD and 16 patients with MCI were enrolled in this study and received 10 Hz rTMS intervention on the bilateral precuneus for 2 weeks. Neurocognitive scales, structural and functional magnetic resonance imaging were collected at enrollment and after the rTMS intervention. Interhemispheric FC was assessed using mirror homotopic functional connectivity (VMHC), while the structural equation modeling (SEM) was employed to analyze the relationship between corpus callosum volume, interhemispheric connectivity, and cognitive function after rTMS intervention.

RESULTS

The precuneus rTMS not only enhanced episodic memory in SCD, but also improved multiple cognitive domains in MCI. Post-rTMS intervention, decreased VMHC values in the lingual cortex, middle occipital gyrus, putamen, and fusiform gyrus were observed in SCD, and an increased VMHC value in the postcentral gyrus along with reduced VMHC value in the cerebellum and putamen in MCI. After intervention, more brain regions show decreased FC in SCD and MCI patients, suggesting that precuneus rTMS may protect cerebral cortical plasticity by reducing excessive functional compensation, and thus improve cognitive function. The SEM indicated that the corpus callosum serves as the structural foundation for rTMS regulation of interhemispheric FC to further improve cognitive function.

CONCLUSION

10 Hz rTMS in the bilateral precuneus could be a promising strategy to improve cognitive function in patients with SCD and MCI. Our study implies that improvements in cognition brought about by precuneus rTMS may result from the remodeling of interhemispheric FC, with the corpus callosum possibly acting as the anatomical basis for functional modulation.

Inhibitory temporo-parietal effective connectivity is associated with explicit memory performance in older adults

Successful explicit memory encoding is associated with inferior temporal activations and medial parietal deactivations, which are attenuated in aging. Here we used dynamic causal modeling (DCM) of functional magnetic resonance imaging data to elucidate effective connectivity patterns between hippocampus, parahippocampal place area (PPA), and precuneus during encoding of novel visual scenes. In 117 young adults, DCM revealed pronounced activating input from the PPA to the hippocampus and inhibitory connectivity from the PPA to the precuneus during novelty processing, with both being enhanced during successful encoding. This pattern could be replicated in two cohorts (N = 141 and 148) of young and older adults. In both cohorts, older adults selectively exhibited attenuated inhibitory PPA-precuneus connectivity, which correlated negatively with memory performance. Our results provide insight into the network dynamics underlying explicit memory encoding and suggest that age-related differences in memory-related network activity are, at least partly, attributable to altered temporo-parietal neocortical connectivity.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

The functional role of the precuneus

Recent advancements in computational approaches and neuroimaging techniques have refined our understanding of the precuneus. While previously believed to be largely a visual processing region, the importance of the precuneus in complex cognitive functions has been previously less familiar due to a lack of focal lesions in this deeply seated region, but also a poor understanding of its true underlying anatomy. Fortunately, recent studies have revealed significant information on the structural and functional connectivity of this region, and this data has provided a more detailed mechanistic understanding of the importance of the precuneus in healthy and pathologic states. Through improved resting-state functional MRI analyses, it has become clear that the function of the precuneus can be better understood based on its functional association with large scale brain networks. Dual default mode network systems have been well explained in recent years in supporting episodic memory and theory of mind; however, a novel 'para-cingulate' network, which is a subnetwork of the larger central executive network, with likely significant roles in self-referential processes and related psychiatric symptoms is introduced here and requires further clarification. Importantly, detailed anatomic studies on the precuneus structural connectivity inside and beyond the cingulate cortex has demonstrated the presence of large structural white matter connections, which provide an additional layer of meaning to the structural-functional significance of this region and its association with large scale brain networks. Together, the structural-functional connectivity of the precuneus has provided central elements which can model various neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease and depression.

The relationship between resting-state amplitude fluctuations and memory-related deactivations of the default mode network in young and older adults

The default mode network (DMN) typically exhibits deactivations during demanding tasks compared to periods of relative rest. In functional magnetic resonance imaging (fMRI) studies of episodic memory encoding, increased activity in DMN regions even predicts later forgetting in young healthy adults. This association is attenuated in older adults and, in some instances, increased DMN activity even predicts remembering rather than forgetting. It is yet unclear whether this phenomenon is due to a compensatory mechanism, such as self-referential or schema-dependent encoding, or whether it reflects overall reduced DMN activity modulation in older age. We approached this question by systematically comparing DMN activity during successful encoding and tonic, task-independent, DMN activity at rest in a sample of 106 young (18-35 years) and 111 older (60-80 years) healthy participants. Using voxel-wise multimodal analyses, we assessed the age-dependent relationship between DMN resting-state amplitude (mean percent amplitude of fluctuation, mPerAF) and DMN fMRI signals related to successful memory encoding, as well as their modulation by age-related hippocampal volume loss, while controlling for regional grey matter volume. Older adults showed lower resting-state DMN amplitudes and lower task-related deactivations. However, a negative relationship between resting-state mPerAF and subsequent memory effect within the precuneus was observed only in young, but not older adults. Hippocampal volumes showed no relationship with the DMN subsequent memory effect or mPerAF. Lastly, older adults with higher mPerAF in the DMN at rest tend to show higher memory performance, pointing towards the importance of a maintained ability to modulate DMN activity in old age.

Brain microvascular disease and functional network connectivity-a call for a stage-based approach

This scientific commentary refers to 'Functional connectivity in older adults-the effect of cerebral small vessel disease' by Drenth et al. (https://doi.org/10.1093/braincomms/fcad126).

Functional gradients of the medial parietal cortex in a healthy cohort with family history of sporadic Alzheimer's disease

BACKGROUND

The medial parietal cortex is an early site of pathological protein deposition in Alzheimer's disease (AD). Previous studies have identified different subregions within this area; however, these subregions are often heterogeneous and disregard individual differences or subtle pathological alterations in the underlying functional architecture. To address this limitation, here we measured the continuous connectivity gradients of the medial parietal cortex and assessed their relationship with cerebrospinal fluid (CSF) biomarkers, ApoE ε4 carriership and memory in asymptomatic individuals at risk to develop AD.

METHODS

Two hundred sixty-three cognitively normal participants with a family history of sporadic AD who underwent resting-state and task-based functional MRI using encoding and retrieval tasks were included from the PREVENT-AD cohort. A novel method for characterizing spatially continuous patterns of functional connectivity was applied to estimate functional gradients in the medial parietal cortex during the resting-state and task-based conditions. This resulted in a set of nine parameters that described the appearance of the gradient across different spatial directions. We performed correlation analyses to assess whether these parameters were associated with CSF biomarkers of phosphorylated tau181 (p-tau), total tau (t-tau), and amyloid-ß1-42 (Aß). Then, we compared the spatial parameters between ApoE ε4 carriers and noncarriers, and evaluated the relationship between these parameters and memory.

RESULTS

Alterations involving the superior part of the medial parietal cortex, which was connected to regions of the default mode network, were associated with higher p-tau, t-tau levels as well as lower Aß/p-tau levels during the resting-state condition (p < 0.01). Similar alterations were found in ApoE ε4 carriers compared to non-carriers (p < 0.003). In contrast, lower immediate memory scores were associated with changes in the middle part of the medial parietal cortex, which was connected to inferior temporal and posterior parietal regions, during the encoding task (p = 0.001). No results were found when using conventional connectivity measures.

CONCLUSIONS

Functional alterations in the medial parietal gradients are associated with CSF AD biomarkers, ApoE ε4 carriership, and lower memory in an asymptomatic cohort with a family history of sporadic AD, suggesting that functional gradients are sensitive to subtle changes associated with early AD stages.

Single‐value scores of memory‐related brain activity reflect dissociable neuropsychological and anatomical signatures of neurocognitive aging

Memory-related functional magnetic resonance imaging (fMRI) activations show age-related differences across multiple brain regions that can be captured in summary statistics like single-value scores. Recently, we described two single-value scores reflecting deviations from prototypical whole-brain fMRI activity of young adults during novelty processing and successful encoding. Here, we investigate the brain-behavior associations of these scores with age-related neurocognitive changes in 153 healthy middle-aged and older adults. All scores were associated with episodic recall performance. The memory network scores, but not the novelty network scores, additionally correlated with medial temporal gray matter and other neuropsychological measures including flexibility. Our results thus suggest that novelty-network-based fMRI scores show high brain-behavior associations with episodic memory and that encoding-network-based fMRI scores additionally capture individual differences in other aging-related functions. More generally, our results suggest that single-value scores of memory-related fMRI provide a comprehensive measure of individual differences in network dysfunction that may contribute to age-related cognitive decline.

Spatial memory deficits in Alzheimer's disease and their connection to cognitive maps' formation by place cells and grid cells

Whenever we navigate through different contexts, we build a cognitive map: an internal representation of the territory. Spatial navigation is a complex skill that involves multiple types of information processing and integration. Place cells and grid cells, collectively with other hippocampal and medial entorhinal cortex neurons (MEC), form a neural network whose activity is critical for the representation of self-position and orientation along with spatial memory retrieval. Furthermore, this activity generates new representations adapting to changes in the environment. Though there is a normal decline in spatial memory related to aging, this is dramatically increased in pathological conditions such as Alzheimer's disease (AD). AD is a multi-factorial neurodegenerative disorder affecting mainly the hippocampus-entorhinal cortex (HP-EC) circuit. Consequently, the initial stages of the disease have disorientation and wandering behavior as two of its hallmarks. Recent electrophysiological studies have linked spatial memory deficits to difficulties in spatial information encoding. Here we will discuss map impairment and remapping disruption in the HP-EC network, as a possible circuit mechanism involved in the spatial memory and navigation deficits observed in AD, pointing out the benefits of virtual reality as a tool for early diagnosis and rehabilitation.

Structural and Functional MRI Data Differentially Predict Chronological Age and Behavioral Memory Performance

Human cognitive abilities decline with increasing chronological age, with decreased explicit memory performance being most strongly affected. However, some older adults show "successful aging," that is, relatively preserved cognitive ability in old age. One explanation for this could be higher brain-structural integrity in these individuals. Alternatively, the brain might recruit existing resources more efficiently or employ compensatory cognitive strategies. Here, we approached this question by testing multiple candidate variables from structural and functional neuroimaging for their ability to predict chronological age and memory performance, respectively. Prediction was performed using support vector machine (SVM) classification and regression across and within two samples of young (N = 106) and older (N = 153) adults. The candidate variables were (1) behavioral response frequencies in an episodic memory test; (2) recently described functional magnetic resonance imaging (fMRI) scores reflecting preservation of functional memory networks; (3) whole-brain fMRI contrasts for novelty processing and subsequent memory; (4) resting-state fMRI maps quantifying voxel-wise signal fluctuation; and (5) gray matter volume estimated from structural MRIs. While age group could be reliably decoded from all variables, chronological age within young and older subjects was best predicted from gray matter volume. In contrast, memory performance was best predicted from task-based fMRI contrasts and particularly single-value fMRI scores, whereas gray matter volume has no predictive power with respect to memory performance in healthy adults. Our results suggest that superior memory performance in healthy older adults is better explained by efficient recruitment of memory networks rather than by preserved brain structure.