Structural Connectivity Changes Underlying Altered Working Memory Networks in Mild Cognitive Impairment: A Three-Way Image Fusion Analysis

Distinguishable features of spontaneous speech in Alzheimer's clinical syndrome and healthy controls

There is growing evidence that subtle changes in spontaneous speech may reflect early pathological changes in cognitive function. Recent work has found that lexical-semantic features of spontaneous speech predict cognitive dysfunction in individuals with mild cognitive impairment (MCI). The current study assessed whether Ostrand and Gunstad's (OG) lexical-semantic features extend to predicting cognitive status in a sample of individuals with Alzheimer's clinical syndrome (ACS) and healthy controls. Four additional (New) speech indices shown to be important in language processing research were also explored in this sample to extend prior work. Speech transcripts of the Cookie Theft Task from 81 individuals with ACS (Mage = 72.7 years, SD = 8.80, 70.4% female) and 61 healthy controls (HC) (Mage = 63.9 years, SD = 8.52, 62.3% female) from Dementia Bank were analyzed. Random forest and logistic machine learning techniques examined whether subject-level lexical-semantic features could be used to accurately discriminate those with ACS from HC. Results showed that logistic models with the New lexical-semantic features obtained good classification accuracy (78.4%), but the OG features had wider success across machine learning model types. In terms of sensitivity and specificity, the random forest model trained on the OG features was the most balanced. Findings from the current study suggest that features of spontaneous speech used to predict MCI may also distinguish between individuals with ACS and healthy controls. Future work should evaluate these lexical-semantic features in pre-clinical persons to further explore their potential to assist with early detection through speech analysis.

Aberrant Hippocampal Functional Connectivity Is Associated with Fornix White Matter Integrity in Alzheimer's Disease and Mild Cognitive Impairment

BACKGROUND

Alzheimer's disease (AD) is the most common cause of dementia in older individuals, and amnestic mild cognitive impairment (aMCI) is currently considered the prodromal stage of AD. The hippocampus and fornix interact functionally and structurally, with the fornix being the major efferent white matter tract from the hippocampus.

OBJECTIVE

The main aim of this study was to examine the impairments present in subjects with AD or aMCI and the relationship of these impairments with the microstructure of the fornix and the functional connectivity (FC) and gray matter volume of the hippocampus.

METHODS

Forty-four AD, 34 aMCI, and 41 age- and gender-matched normal controls (NCs) underwent neuropsychological assessments and multimode MRI. We chose the bilateral hippocampi as the region of interest in which gray matter alterations and FC with the whole brain were assessed and the fornix body as the region of interest in which the microstructural integrity of the white matter was observed. We also evaluated the relationship among gray matter alterations, the abnormal FC of the hippocampus and the integrity of the fornix in AD/aMCIResults:Compared to the NC group, the AD and aMCI groups demonstrated decreased gray matter volume, reduced FC between the bilateral hippocampi and several brain regions in the default mode network and control network, and damaged integrity of the fornix body (decreased fractional anisotropy and increased diffusivity). We also found that left hippocampal FC with some regions, the integrity of the fornix body, and cognition ability were significantly correlated. Therefore, our findings suggest that damage to white matter integrity may partially explain the reduced resting-state FC of the hippocampus in AD and aMCI.

CONCLUSION

AD and aMCI are diseases of disconnectivity including not only functional but also structural disconnectivity. Damage to white matter integrity may partially explain the reduced resting-state FC in AD and aMCI. These findings have significant implications for diagnostics and modeling and provide insights for understanding the disconnection syndrome in AD.

Changes in Theta but not Alpha Modulation Are Associated with Impairment in Working Memory in Alzheimer's Disease and Mild Cognitive Impairment

While several studies have found that neural oscillations play a key role in the functioning of working memory, the nature of aberrant oscillatory activity underlying working memory impairments in Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains largely unexplored. These individuals often display structural alterations in brain regions and pathways involved in working memory processes and therefore may also display altered oscillatory activity during memory activation. Electroencephalographic (EEG) activity was recorded during the N-back working memory task in three groups: AD (n = 29), MCI (n = 100), and healthy controls (HCs; n = 40). Theta (4-7 Hz) and alpha (7.5-12 Hz) modulation was measured in response to the stimulus presentation during correct and incorrect responses. This modulation represents the change in EEG activity associated with the stimulus onset and was measured as a ratio of post stimulus power to pre stimulus power. We also assessed the relationship between change in oscillatory power and working memory performance. Compared to HCs, the AD group demonstrated the lowest working memory accuracy and a smaller theta ratio for correct responses on the 2-back condition; the MCI group demonstrated a smaller theta ratio for correct responses on the 3-back condition. Finally, we observed that the theta ratio, but not the alpha ratio, was a significant predictor of working memory performance in the three groups for all conditions. Taken together, these behavioral and electrophysiological results suggest that in addition to impairments in working memory performance, modulation of theta, but not alpha power, may be impaired in MCI and AD.

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular, and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an "omics"-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical, and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer's disease. The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group "Alzheimer Precision Medicine" (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development toward breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

Frequency-Dependent Brain Regional Homogeneity Alterations in Patients with Mild Cognitive Impairment during Working Memory State Relative to Resting State

Several studies have reported working memory deficits in patients with mild cognitive impairment (MCI). However, previous studies investigating the neural mechanisms of MCI have primarily focused on brain activity alterations during working memory tasks. No study to date has compared brain network alterations in the working memory state between MCI patients and normal control (NC) subjects. Therefore, using the index of regional homogeneity (ReHo), we explored brain network impairments in MCI patients during a working memory task relative to the resting state, and identified frequency-dependent effects in separate frequency bands.Our results indicate that, in MCI patients, ReHo is altered in the posterior cingulate cortex (PCC) in the slow-3 band (0.073–0.198 Hz), and in the bottom of the right occipital lobe and part of the right cerebellum, the right thalamus, a diffusing region in the bilateral prefrontal cortex (PFC), the left and right parietal-occipital regions, and the right angular gyrus in the slow-5 band (0.01–0.027 Hz). Furthermore, in NCs, the value of ReHo in clusters belonging to the default mode network (DMN) decreased, while the value of ReHo in clusters belonging to the attentional network increased during the task state. However, this pattern was reversed in MCI patients, and was associated with decreased working memory performance. In addition, we identified altered functional connectivity of the abovementioned regions with other parts of the brain in MCI patients. This is the first study to compare frequency-dependent alterations of ReHo in MCI patients between resting and working memory states. The results provide a new perspective regarding the neural mechanisms of working memory deficits in MCI patients, and extend our knowledge of altered brain patterns in resting and task-evoked states.

Measuring Cortical Connectivity in Alzheimer's Disease as a Brain Neural Network Pathology: Toward Clinical Applications

OBJECTIVES

The objective was to review the literature on diffusion tensor imaging as well as resting-state functional magnetic resonance imaging and electroencephalography (EEG) to unveil neuroanatomical and neurophysiological substrates of Alzheimer's disease (AD) as a brain neural network pathology affecting structural and functional cortical connectivity underlying human cognition.

METHODS

We reviewed papers registered in PubMed and other scientific repositories on the use of these techniques in amnesic mild cognitive impairment (MCI) and clinically mild AD dementia patients compared to cognitively intact elderly individuals (Controls).

RESULTS

Hundreds of peer-reviewed (cross-sectional and longitudinal) papers have shown in patients with MCI and mild AD compared to Controls (1) impairment of callosal (splenium), thalamic, and anterior-posterior white matter bundles; (2) reduced correlation of resting state blood oxygen level-dependent activity across several intrinsic brain circuits including default mode and attention-related networks; and (3) abnormal power and functional coupling of resting state cortical EEG rhythms. Clinical applications of these measures are still limited.

CONCLUSIONS

Structural and functional (in vivo) cortical connectivity measures represent a reliable marker of cerebral reserve capacity and should be used to predict and monitor the evolution of AD and its relative impact on cognitive domains in pre-clinical, prodromal, and dementia stages of AD.

Speaking in Alzheimer's Disease, is That an Early Sign? Importance of Changes in Language Abilities in Alzheimer's Disease

It is known that Alzheimer’s disease (AD) influences the temporal characteristics of spontaneous speech. These phonetical changes are present even in mild AD. Based on this, the question arises whether an examination based on language analysis could help the early diagnosis of AD and if so, which language and speech characteristics can identify AD in its early stage. The purpose of this article is to summarize the relation between prodromal and manifest AD and language functions and language domains. Based on our research, we are inclined to claim that AD can be more sensitively detected with the help of a linguistic analysis than with other cognitive examinations. The temporal characteristics of spontaneous speech, such as speech tempo, number of pauses in speech, and their length are sensitive detectors of the early stage of the disease, which enables an early simple linguistic screening for AD. However, knowledge about the unique features of the language problems associated with different dementia variants still has to be improved and refined.

Structural hallmarks of amyotrophic lateral sclerosis progression revealed by probabilistic fiber tractography

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive limb and/or bulbar muscular weakness and atrophy. Although ALS-related alterations of motor and extra-motor neuronal networks have repeatedly been reported, their temporal dynamics during disease progression are not well understood. Recently, we reported a decline of motor system activity and a concurrent increase of hippocampal novelty-evoked modulations across 3 months of ALS progression. To address whether these functional changes are associated with structural ones, the current study employed probabilistic fiber tractography on diffusion tensor imaging (DTI) data using a longitudinal design. Therein, motor network integrity was assessed by DTI-based tracking of the intracranial corticospinal tract, while connectivity estimates of occipito-temporal tracts (between visual and entorhinal, perirhinal or parahippocampal cortices) served to assess structural changes that could be related to the increased novelty-evoked hippocampal activity across time described previously. Complementing these previous functional observations, the current data revealed an ALS-related decrease in corticospinal tract structural connectivity compared to controls, while in contrast, visuo-perirhinal connectivity was relatively increased in the patient group. Importantly, beyond these between-group differences, a rise in the patients' occipito-temporal tract strengths occurred across a 3-month interval, while at the same time no changes in corticospinal tract connectivity were observed. In line with previously identified functional alterations, the dynamics of these structural changes suggest that the affection of motor- and memory-related networks in ALS emerges at distinct disease stages: while motor network degeneration starts primarily during early (supposedly pre-symptomatic) phases, the hippocampal/medial temporal lobe dysfunctions arise at later stages of the disease.