Functional Connectivity In Mild Cognitive Impairment Research Articles

Transcranial direct current stimulation and neuronal functional connectivity in MCI: role of individual factors associated to AD.

Alzheimer's disease (AD) encompasses a spectrum that may progress from mild cognitive impairment (MCI) to full dementia, characterized by amyloid-beta and tau accumulation. Transcranial direct current stimulation (tDCS) is being investigated as a therapeutic option, but its efficacy in relation to individual genetic and biological risk factors remains underexplored. To evaluate the effects of a two-week anodal tDCS regimen on the left dorsolateral prefrontal cortex, focusing on functional connectivity changes in neural networks in MCI patients resulting from various possible underlying disorders, considering individual factors associated to AD such as amyloid-beta deposition, APOE ϵ4 allele, BDNF Val66Met polymorphism, and sex. In a single-arm prospective study, 63 patients with MCI, including both amyloid-PET positive and negative cases, received 10 sessions of tDCS. We assessed intra- and inter-network functional connectivity (FC) using fMRI and analyzed interactions between tDCS effects and individual factors associated to AD. tDCS significantly enhanced intra-network FC within the Salience Network (SN) and inter-network FC between the Central Executive Network and SN, predominantly in APOE ϵ4 carriers. We also observed significant sex*tDCS interactions that benefited inter-network FC among females. Furthermore, the effects of multiple modifiers, particularly the interaction of the BDNF Val66Met polymorphism and sex, were evident, as demonstrated by increased intra-network FC of the SN in female Met non-carriers. Lastly, the effects of tDCS on FC did not differ between the group of 26 MCI patients with cerebral amyloid-beta deposition detected by flutemetamol PET and the group of 37 MCI patients without cerebral amyloid-beta deposition. The study highlights the importance of precision medicine in tDCS applications for MCI, suggesting that individual genetic and biological profiles significantly influence therapeutic outcomes. Tailoring interventions based on these profiles may optimize treatment efficacy in early stages of AD.

A novel automated deep learning approach for Alzheimer's disease classification

Alzheimer's disease is a degenerative brain illness, incurable and progressive. Globally for every two seconds, someone is affected by Alzheimer's disease. Alzheimer's disease in the elderly is difficult to diagnose due to the complexity of the brain structure. Its pixel intensity is similar and systematic distinction is necessary. Deep learning has inspired a lot of interest in recent years in tackling challenges in a variety of fields, including medical imaging. One of the drawbacks of deep learning approach is the inability to detect changes in functional connectivity in MCI (mild cognitive impairment) patients' functional brain networks. In this paper, we utilize deep features extracted from two pre-trained deep learning models to tackle this issue. The proposed models DenseNet121 and MobileNetV2 is used to perform the task of Alzheimer's disease multi-class classification. In this method, initially we increased 70 % of dataset and generated images by using CycleGAN (generative adversarial networks). We achieved 98.82% of accuracy with proposed models. It gives best results compared to existing models.

Pre vs post‐task modulation of resting state EEG functional connectivity and network topology

AbstractBackgroundRecently, we have shown a significant decrease in resting‐state EEG (rsEEG) spectral power at post‐task as compared to pre‐task cognitive engagement in older adults. Further, older adults with mild cognitive impairment (MCI) showed greater decreases in rsEEG in temporal and central cortical regions at post‐task than healthy controls (HC). Here, we present functional connectivity (FC) and network topology derived from the same pre‐ to post‐rsEEG changes.MethodWe studied a sample of community dwelling African American older participants over age 60 years, consisting of consensus‐based diagnosis for 58 HC and 41 MCI. rsEEGs were recorded before and after approximately 20 minutes of a visual motion direction discrimination task. FC between channels was assessed by the phase lag index, while minimum spanning tree (MST) was used to characterize network topology.ResultFor both HC and MCI groups, when compared to pre‐task measurements, the post‐task FC was significantly increased within the middle frontal, middle central, and left temporal regions in the lower alpha frequency band. An opposite pattern with decreased FC was found within the right parietal region in the delta, theta, lower alpha, upper alpha, and beta frequency bands. In contrast, compared to HC, the MCI group did show significantly decreased FC within the middle frontal region in the delta band, following the cognitive task. All results from network topology failed to demonstrate differences between HC and MCI. On average, both groups' post‐task functional network topology showed significant decreased eccentricity and diameter in the delta and beta bands, indicating a higher global network integration.ConclusionOur findings suggest that visual‐based cognitive engagement affects both post‐task FC and network topology similarly in both HC and MCI. For the most part, increased FC and functional topology in both groups are likely associated with after‐task effects, resulting from additional time to return to baseline, though decreased FC in MCI as compared to HC was seen within the middle frontal region in the delta. Our results demonstrate that both FC and topoloty are responsive to cognitive challenge, though frontal/executive‐driven differences in FC may be an area of future promise in distinguishing HC and MCI.

Improved functional connectivity after a 6‐month ketogenic supplementation in mild cognitive impairment

AbstractBackgroundKetones, the brain’s alternative fuel to glucose, bypass the brain glucose deficit in mild cognitive impairment (MCI). The BENEFIC trial conducted in MCI showed improved measures of cognition in multiple domains after a 6‐month ketogenic intervention [Fortier et al. 2019]. Functional connectivity in the dorsal‐attention network (DAN) deteriorates early in MCI, and prior to changes in the ventral‐attention network [Zhang et al. 2015]. We aimed to assess whether improved cognitive outcomes in the BENEFIC Trial were linked to improved brain functional connectivity.MethodParticipants in this 6‐month intervention were randomized to a placebo (n= 15) or ketogenic medium chain triglyceride (kMCT; n= 17) drink. A neurocognitive battery and brain imaging were performed pre‐ and post‐intervention. Functional connectivity was computed from resting‐state functional magnetic resonance images. Independent component analysis (FSL Melodic) was used to segment seven major resting‐state networks (DAN, ventral‐attention, frontoparietal, limbic, somatomotor, default‐mode and visual) [Yeo et al. 2011]. Regional cortical ketone (11C‐acetoacetate) and glucose (18F‐fluorodeoxyglucose) metabolic rates were also quantified using positron emission tomography (PET).ResultChanges (post ‐ pre) in DAN functional connectivity was significantly higher in the kMCT group vs placebo (P= 0.024). After correction for age, sex, education, ApoE status and intracranial volume, the significant difference between groups was still present, with a large effect size (partial h2= 0.16; P= 0.043; Figure 1). Connectivity in no other networks was significantly different between groups. Changes in attention and processing speed composite Z‐score (r= 0.42; P= 0.021) and specific tests targeting attention (Trail Making visual scanning and number sequencing conditions) were significantly associated with the increased DAN functional connectivity. Change in ketone uptake specifically in DAN cortical regions (Figure 2C) was significantly higher in the kMCT vs placebo group (P= 0.001) and was directly associated with the improved DAN functional connectivity, with a large effect size (r= 0.69; P= 0.002; Figure 3).ConclusionWe show that a 6‐month ketogenic intervention improves DAN functional connectivity in MCI, an improvement that is directly linked to increased energy (ketone) supply to the DAN. The beneficial effect of ketones on cognition in MCI may be linked to improved DAN connectivity.

Differences Changes in Cerebellar Functional Connectivity Between Mild Cognitive Impairment and Alzheimer's Disease: A Seed-Based Approach.

Background: Recent studies have discovered that functional connections are impaired among patients with Alzheimer's disease (AD), even at the preclinical stage. The cerebellum has been implicated as playing a role in cognitive processes. However, functional connectivity (FC) among cognitive sub-regions of the cerebellum in patients with AD and mild cognitive impairment (MCI) remains to be further elucidated.Objective: Our study aims to investigate the FC changes of the cerebellum among patients with AD and MCI, compared to healthy controls (HC). Additionally, we explored the role of cerebellum FC changes in the cognitive performance of all subjects.Materials: Resting-state functional magnetic resonance imaging (rs-fMRI) data from three different groups (28 AD patients, 26 MCI patients, and 30 HC) was collected. We defined cerebellar crus II and lobule IX as seed regions to assess the intragroup differences of cortico-cerebellar connectivity. Bias correlational analysis was performed to investigate the relationship between changes in FC and neuropsychological performance.Results: Compared to HC, AD patients had decreased FC within the caudate, limbic lobe, medial frontal gyrus (MFG), middle temporal gyrus, superior frontal gyrus, parietal lobe/precuneus, inferior temporal gyrus, and posterior cingulate gyrus. Interestingly, MCI patients demonstrated increased FC within inferior parietal lobe, and MFG, while they had decreased FC in the thalamus, inferior frontal gyrus, and superior frontal gyrus. Further analysis indicated that FC changes between the left crus II and the right thalamus, as well as between left lobule IX and the right parietal lobe, were both associated with cognitive decline in AD. Disrupted FC between left crus II and right thalamus, as well as between left lobule IX and right parietal lobe, was associated with attention deficit among subjects with MCI.Conclusion: These findings indicate that cortico-cerebellar FC in MCI and AD patients was significantly disrupted with different distributions, particularly in the default mode networks (DMN) and fronto-parietal networks (FPN) region. Increased activity within the fronto-parietal areas of MCI patients indicated a possible compensatory role for the cerebellum in cognitive impairment. Therefore, alterations in the cortico-cerebellar FC represent a novel approach for early diagnosis and a potential therapeutic target for early intervention.

Abnormal Anatomical Rich-Club Organization and Structural-Functional Coupling in Mild Cognitive Impairment and Alzheimer's Disease.

Emerging research indicates interruptions in the wiring organization of the brain network in Mild cognitive impairment (MCI) and Alzheimer's disease (AD). Due to the important role of rich-club organization in distinguishing abnormalities of AD patients and the close relationship between structural connectivity (SC) and functional connectivity (FC), our study examined whether changes in SC-FC coupling and the relationship with abnormal rich-club organizations during the development of diseases may contribute to the pathophysiology of AD. Structural diffusion-tensor imaging (DTI) and resting-state functional magnetic resonance imaging (fMRI) were performed in 38 normal controls (NCs), 40 MCI patients and 19 AD patients. Measures of the rich-club structure and its role in global structural–functional coupling were administered. Our study found decreased levels of feeder and local connectivity in MCI and AD patients, which were the main contributing factors to the lower efficiency of the brain structural network. Another important finding was that we have more accurately characterized the changing pattern of functional brain dynamics. The enhanced coupling between SC and FC in MCI and AD patients might be due to disruptions in optimal structural organization. More interestingly, we also found increases in the SC-FC coupling for feeder and local connections in MCI and AD patients. SC-FC coupling also showed significant differences between MCI and AD patients, mainly between the abnormal feeder connections. The connection density and coupling strength were significantly correlated with clinical metrics in patients. The present findings enhanced our understanding of the neurophysiologic mechanisms associated with MCI and AD.

Functional network topology associated with apathy in Alzheimer's disease

BackgroundApathy, a common neuropsychiatric (NPS) in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), is associated with structural and metabolic brain changes. However, functional connectivity changes across the brain in association with apathy remain unclear. In this study, graph theoretical measures of integration and segregation from resting state functional connectivity in MCI and AD patients with low depression scores, and healthy controls. MethodsIn MCI and AD patients with low depression scores, graph theoretical measures of integration and segregation were derived from resting state functional connectivity in patients, which were compared between those with apathy (NPS_A, n = 21) to those without NPS (NPS_None, n = 28) and those with NPS other than apathy (NPS_NA, n = 38). Additionally, the same measures were compared between AD patients and healthy controls (amyloid uptake below threshold levels). ResultsAltered whole brain global efficiency and reduced local efficiency were found in NPS_A compared to NPS_None and NPS_NA. In similar contrasts, apathy was associated with increased participation coefficient in the frontoparietal and cingulo-opercular template-based networks. A study-specific network definition also showed similar results. In comparison, AD patients showed higher modularity compared to controls at the whole brain level and higher participation coefficient in the ventral attention network. LimitationsThe severity and dimensions of apathy were not assessed. ConclusionsLoss of segregation in the frontoparietal and cingulo-opercular network, which are involved in the control of goal-directed behavior, was associated with apathy in MCI/AD. The results also suggest that network-level changes in AD patients may underlie specific NPS.

Altered Cerebro-Cerebellar Limbic Network in AD Spectrum: A Resting-State fMRI Study.

Recent evidence suggests that the cerebellum is related to motor and non-motor cognitive functions, and that several coupled cerebro-cerebellar networks exist, including links with the limbic network. Since several limbic structures are affected by Alzheimer pathology, even in the preclinical stages of Alzheimer’s disease (AD), we aimed to investigate the cerebral limbic network activity from the perspective of the cerebellum. Twenty patients with mild cognitive impairment (MCI), 18 patients with AD, and 26 healthy controls (HC) were recruited to acquire Resting-state functional MRI (rs-fMRI). We used seed-based approach to construct the cerebro-cerebellar limbic network. Two-sample t-tests were carried out to explore the differences of the cerebellar limbic network connectivity. The first result, a sub-scale network including the bilateral posterior part of the orbitofrontal cortex (POFC) extending to the anterior insular cortex (AIC) and left inferior parietal lobule (L-IPL), showed greater functional connectivity in MCI than in HC and less functional connectivity in AD than in MCI. The location of this sub-scale network was in accordance with components of the ventral attention network. Second, there was decreased functional connectivity to the right mid-cingulate cortex (MCC) in the AD and MCI patient groups relative to the HC group. As the cerebellum is not compromised by Alzheimer pathology in the prodromal stage of AD, this pattern indicates that the sub-scale ventral attention network may play a pivotal role in functional compensation through the coupled cerebro-cerebellar limbic network in MCI, and the cerebellum may be a key node in the modulation of social cognition.

Altered Nucleus Basalis Connectivity Predicts Treatment Response in Mild Cognitive Impairment.

PurposeTo determine whether functional connectivity (FC) mapping of nucleus basalis of Meynert (NBM) cholinergic network (hereafter, NBM FC) could provide a biomarker of central cholinergic deficits with predictive potential for response to cholinesterase inhibitor (ChEI) treatment.Materials and MethodsThe Alzheimer’s Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All participants and their representatives gave written informed consent prior to data collection. NBM FC was examined in 33 healthy control participants, 102 patients with mild cognitive impairment (MCI), and 33 patients with AD by using resting-state functional MRI data from the ADNI database. NBM FC was compared between groups before and after 6 months of ChEI treatment in MCI. Associations between baseline NBM FC and baseline cognitive performance as well as cognitive outcomes after treatment were investigated.ResultsCompared with the healthy control group, NBM FC was decreased in patients with untreated MCI and increased in patients with AD treated with ChEI (corrected P ˂ .05). Global cognition (Alzheimer’s Disease Assessment Scale-Cognitive subscale score) was associated with NBM FC (r = −0.349; P ˂ .001). NBM FC was higher 6 months after ChEI compared with before ChEI in treated MCI (corrected P ˂ .05), but did not change at 6 months in patients with untreated MCI (corrected P ˂ .05). Baseline NBM FC in MCI strongly predicted cognitive outcomes 6 months after ChEI (R2 = 0.458; P = .001).ConclusionFunctional dissociation of the nucleus basalis of Meynert from a cortical network may explain the cognitive deficits in dementia and allow for the selection of individuals who are more likely to respond to cholinesterase inhibitors at early disease stages.Published under a CC BY-NC-ND 4.0 license.Online supplemental material is available for this article.

Exercise Training and Functional Connectivity Changes in Mild Cognitive Impairment and Healthy Elders.

Effective interventions are needed to improve brain function in mild cognitive impairment (MCI), an early stage of Alzheimer's disease (AD). The posterior cingulate cortex (PCC)/precuneus is a hub of the default mode network (DMN) and is preferentially vulnerable to disruption of functional connectivity in MCI and AD. We investigated whether 12 weeks of aerobic exercise could enhance functional connectivity of the PCC/precuneus in MCI and healthy elders. Sixteen MCI and 16 healthy elders (age range = 60-88) engaged in a supervised 12-week walking exercise intervention. Functional MRI was acquired at rest; the PCC/precuneus was used as a seed for correlated brain activity maps. A linear mixed effects model revealed a significant interaction in the right parietal lobe: the MCI group showed increased connectivity while the healthy elders showed decreased connectivity. In addition, both groups showed increased connectivity with the left postcentral gyrus. Comparing pre to post intervention changes within each group, the MCI group showed increased connectivity in 10 regions spanning frontal, parietal, temporal and insular lobes, and the cerebellum. Healthy elders did not demonstrate any significant connectivity changes. The observed results show increased functional connectivity of the PCC/precuneus in individuals with MCI after 12 weeks of moderate intensity walking exercise training. The protective effects of exercise training on cognition may be realized through the enhancement of neural recruitment mechanisms, which may possibly increase cognitive reserve. Whether these effects of exercise training may delay further cognitive decline in patients diagnosed with MCI remains to be demonstrated.

Association between serotonin denervation and resting-state functional connectivity in mild cognitive impairment.

Resting-state functional connectivity alterations have been demonstrated in Alzheimer's disease (AD) and mild cognitive impairment (MCI) before the observation of AD neuropathology, but mechanisms driving these changes are not well understood. Serotonin neurodegeneration has been observed in MCI and AD and is associated with cognitive deficits and neuropsychiatric symptoms, but the role of the serotonin system in relation to brain network dysfunction has not been a major focus of investigation. The current study investigated the relationship between serotonin transporter availability (SERT; measured using positron emission tomography) and brain network functional connectivity (measured using resting-state functional MRI) in 20 participants with MCI and 21 healthy controls. Two SERT regions of interest were selected for the analysis: the Dorsal Raphe Nuclei (DRN) and the precuneus which represent the cell bodies of origin and a cortical target of projections of the serotonin system, respectively. Both regions show decreased SERT in MCI compared to controls and are the site of early AD pathology. Average resting-state functional connectivity did not differ between MCI and controls. Decreased SERT in DRN was associated with lower hippocampal resting-state connectivity in MCI participants compared to controls. Decreased SERT in the right precuneus was also associated with lower resting-state connectivity of the retrosplenial cortex to the dorsal lateral prefrontal cortex and higher resting-state connectivity of the retrosplenial cortex to the posterior cingulate and in patients with MCI but not in controls. These results suggest that a serotonergic mechanism may underlie changes in brain functional connectivity in MCI. Hum Brain Mapp 38:3391-3401, 2017. © 2017 Wiley Periodicals, Inc.

A comprehensive assessment of resting state networks: bidirectional modification of functional integrity in cerebro-cerebellar networks in dementia.

In resting state fMRI (rs-fMRI), only functional connectivity (FC) reductions in the default mode network (DMN) are normally reported as a biomarker for Alzheimer's disease (AD). In this investigation we have developed a comprehensive strategy to characterize the FC changes occurring in multiple networks and applied it in a pilot study of subjects with AD and Mild Cognitive Impairment (MCI), compared to healthy controls (HC). Resting state networks (RSNs) were studied in 14 AD (70 ± 6 years), 12 MCI (74 ± 6 years), and 16 HC (69 ± 5 years). RSN alterations were present in almost all the 15 recognized RSNs; overall, 474 voxels presented a reduced FC in MCI and 1244 in AD while 1627 voxels showed an increased FC in MCI and 1711 in AD. The RSNs were then ranked according to the magnitude and extension of FC changes (gFC), putting in evidence 6 RSNs with prominent changes: DMN, frontal cortical network (FCN), lateral visual network (LVN), basal ganglia network (BGN), cerebellar network (CBLN), and the anterior insula network (AIN). Nodes, or hubs, showing alterations common to more than one RSN were mostly localized within the prefrontal cortex and the mesial-temporal cortex. The cerebellum showed a unique behavior where voxels of decreased gFC were only found in AD while a significant gFC increase was only found in MCI. The gFC alterations showed strong correlations (p < 0.001) with psychological scores, in particular Mini-Mental State Examination (MMSE) and attention/memory tasks. In conclusion, this analysis revealed that the DMN was affected by remarkable FC increases, that FC alterations extended over several RSNs, that derangement of functional relationships between multiple areas occurred already in the early stages of dementia. These results warrant future work to verify whether these represent compensatory mechanisms that exploit a pre-existing neural reserve through plasticity, which evolve in a state of lack of connectivity between different networks with the worsening of the pathology.

Connectome-scale assessments of structural and functional connectivity in MCI

Mild cognitive impairment (MCI) has received increasing attention not only because of its potential as a precursor for Alzheimer's disease but also as a predictor of conversion to other neurodegenerative diseases. Although MCI has been defined clinically, accurate and efficient diagnosis is still challenging. Although neuroimaging techniques hold promise, compared to commonly used biomarkers including amyloid plaques, tau protein levels and brain tissue atrophy, neuroimaging biomarkers are less well validated. In this article, we propose a connectomes-scale assessment of structural and functional connectivity in MCI via two independent multimodal DTI/fMRI datasets. We first used DTI-derived structural profiles to explore and tailor the most common and consistent landmarks, then applied them in a whole-brain functional connectivity analysis. The next step fused the results from two independent datasets together and resulted in a set of functional connectomes with the most differentiation power, hence named as "connectome signatures." Our results indicate that these "connectome signatures" have significantly high MCI-vs-controls classification accuracy, at more than 95%. Interestingly, through functional meta-analysis, we found that the majority of "connectome signatures" are mainly derived from the interactions among different functional networks, for example, cognition-perception and cognition-action domains, rather than from within a single network. Our work provides support for using functional "connectome signatures" as neuroimaging biomarkers of MCI.