What Electrophysiology Tells Us About Alzheimer’s Disease::A Window into the Synchronization and Connectivity of Brain Neurons

Electrophysiology provides a real-time readout of neural functions and network capability in different brain states, on temporal (fractions of milliseconds) and spatial (micro, meso, and macro) scales unmet by other methodologies. However, current international guidelines do not endorse the use of electroencephalographic (EEG)/magnetoencephalographic (MEG) biomarkers in clinical trials performed in patients with Alzheimer’s disease (AD), despite a surge in recent validated evidence. This Position Paper of the ISTAART Electrophysiology Professional Interest Area endorses consolidated and translational electrophysiological techniques applied to both experimental animal models of AD and patients, to probe the effects of AD neuropathology (i.e., brain amyloidosis, tauopathy, and neurodegeneration) on neurophysiological mechanisms underpinning neural excitation/inhibition and neurotransmission as well as brain network dynamics, synchronization, and functional connectivity reflecting thalamocortical and cortico-cortical residual capacity. Converging evidence shows relationships between abnormalities in EEG/MEG markers and cognitive deficits in groups of AD patients at different disease stages. The supporting evidence for the application of electrophysiology in AD clinical research as well as drug discovery pathways warrants an international initiative to include the use of EEG/MEG biomarkers in the main multicentric projects planned in AD patients, to produce conclusive findings challenging the present regulatory requirements and guidelines for AD studies

Topological Biomarker of Alzheimer’s Disease

For years, it has been assumed that the cerebral accumulation of pathologic protein forms is the main trigger of Alzheimer’s disease (AD) pathology; however, recent studies revealed strong evidences that the alternations in synaptic activity precede and affect the homeostasis of amyloid-beta and tau, both of which aggregate during AD. Given that the neuropathological changes, characteristic for AD, start decades before the onset of the first symptoms, when alternations become irreversible, it is crucial to find a biomarker that can detect the preclinical signs of disease, presumably synaptic dysfunction of specific cerebral areas. Here is presented a novel, a high potential neuroimaging biomarker that can detect the postsynaptic dysfunction of specific neural substrate located in medial prefrontal cortex (mPFC) during sensory gating processing of a simple auditory stimulus. The magnetoencephalography-based localization of mPFC gating activation has the potential not only to detect symptomatic AD but also to become a predictor of cognitive decline related to the pathophysiological processes of AD, both at the individual level. The strengths of proposed biomarker lie in the simplicity of using a binary value, i.e., activated or not activated a neural generator along with its potential to follow the evolution of the pathophysiological process of disease from preclinical phase. The novel biomarker does not require estimation of uniform cutoff levels and standardization processes, the main problems of so far proposed biomarkers. Ability to individually detect AD pathology during putative preclinical and clinical stages, absolute noninvasiveness, and large effect size give this biomarker a high translation capacity and clinical potential

Reorganisation of brain networks in frontotemporal dementia and progressive supranuclear palsy.

The disruption of large-scale brain networks is increasingly recognised as a consequence of neurodegenerative dementias. We assessed adults with behavioural variant frontotemporal dementia and progressive supranuclear palsy using magnetoencephalography during an auditory oddball paradigm. Network connectivity among bilateral temporal, frontal and parietal sources was examined using dynamic causal modelling. We found evidence for a systematic change in effective connectivity in both diseases. Compared with healthy subjects, who had focal modulation of intrahemispheric frontal-temporal connections, the patient groups showed abnormally extensive and inefficient networks. The changes in connectivity were accompanied by impaired responses of the auditory cortex to unexpected deviant tones (MMNm), despite normal responses to standard stimuli. Together, these results suggest that neurodegeneration in two distinct clinical syndromes with overlapping profiles of prefrontal atrophy, causes a similar pattern of reorganisation of large-scale networks. We discuss this network reorganisation in the context of other focal brain disorders and the specific vulnerability of functional brain networks to neurodegenerative disease

Electrophysiological and information processing variability predicts memory decrements associated with normal age-related cognitive decline and Alzheimer's disease (AD)

Recent theoretical models of cognitive aging have implicated increased intra-individual variability as a critical marker of decline. The current study examined electrophysiological and information processing variability and memory performance in normal younger and older controls, and older adults with Alzheimer's disease (AD). It was hypothesized that higher levels of variability would be indicative of age-related and disease-related memory deficits. Results indicated both implicit and explicit memory deficits associated with AD. Consistent with previous research, behavioral speed and variability emerged as sensitive to age- and disease-related change. Amplitude variability of P3 event-related potentials was a unique component of electrophysiological activity and accounted for significant variance in reaction time (RT) mean and RT standard deviation, which in turn accounted for significant variance in memory function. Results are discussed in light of theoretical and applied issues in the field of cognitive aging

Exercise Training and Functional Connectivity Changes in Mild Cognitive Empairment and Healthy Elders

Background: 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. Objective: We investigated whether 12 weeks of aerobic exercise could enhance functional connectivity of the PCC/precuneus in MCI and healthy elders. Methods: 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. Results: 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. Conclusion: 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

Processing of nonverbal vocalisations in dementia

Nonverbal emotional vocalisations are fundamental communicative signals used to convey a diverse repertoire of social and emotional information. They transcend the boundaries of language and cultural specificity that hamper many neuropsychological tests, making them ideal candidates for understanding impaired socio-emotional signal processing in dementia. Symptoms related to changes in social behaviour and emotional responsiveness are poorly understood yet have significant impact on patients with dementia and those who care for them. In this thesis, I investigated processing of nonverbal emotional vocalisations in patients with Alzheimer’s disease and frontotemporal dementia (FTD), a disease spectrum encompassing three canonical syndromes characterised by marked socio-emotional and communication difficulties - behavioural variant FTD (bvFTD), semantic variant primary progressive aphasia (svPPA) and nonfluent/agrammatic variant primary progressive aphasia (nfvPPA). I demonstrated distinct profiles of impairment in identifying three salient vocalisations (laughter, crying and screaming) and the emotions they convey. All three FTD syndromes showed impairments, with the most marked deficits of emotion categorisation seen in the bvFTD group. Voxel-based morphometry was used to define critical brain substrates for processing vocalisations, identifying correlates of vocal sound processing with auditory perceptual regions (superior temporal sulcus and posterior insula) and emotion identification with limbic and medial frontal regions. The second half of this thesis focused on the more fine-grained distinction of laughter subtypes. I studied cognitive (labelling), affective (valence) and autonomic (pupillometric) processing of laughter subtypes representing dimensions of valence (mirthful versus hostile) and arousal (spontaneous versus posed). Again, FTD groups showed greatest impairment with profiles suggestive of primary perceptual deficits in nfvPPA, cognitive overgeneralisation in svPPA and disordered reward and hedonic valuation in bvFTD. Neuroanatomical correlates of explicit laughter identification included inferior frontal and cingulo-insular cortices whilst implicit processing (indexed as autonomic arousal) was particularly impaired in those conditions associated with insular compromise (nfvPPA and bvFTD). These findings demonstrate the potential of nonverbal emotional vocalisations as a probe of neural mechanisms underpinning socio-emotional dysfunction in neurodegenerative diseases

MODELING DEMENTIA RISK, COGNITIVE CHANGE, PREDICTIVE RULES IN LONGITUDINAL STUDIES

Dementia is increasing recognized as a major problem to public health worldwide. Prevention and treatment strategies are in critical need. Nowadays, research for dementia usually featured as complex longitudinal studies, which provide extensive information and also propose challenge to statistical methodology. The purpose of this dissertation research was to apply statistical methodology in the field of dementia to strengthen the understanding of dementia from three perspectives: 1) Application of statistical methodology to investigate the association between potential risk factors and incident dementia. 2) Application of statistical methodology to analyze changes over time, or trajectory, in cognitive tests and symptoms. 3) Application of statistical learning methods to predict development of dementia in the future. Prevention of Alzheimer’s disease with Vitamin E and Selenium (PREADViSE) (7547 subjects included) and Alzheimer’s disease Neuroimaging Initiative (ADNI) (591 participants included) were used in this dissertation. The first study, “Self-reported sleep apnea and dementia risk: Findings from the PREADViSE Alzheimer’s disease prevention trial ”, shows that self-reported baseline history of sleep apnea was borderline significantly associated with risk of dementia after adjustment for confounding. Stratified analysis by APOE ε4 carrier status showed that baseline history of sleep apnea was associated with significantly increased risk of dementia in APOE ε4 non-carriers. The second study, “comparison of trajectories of episodic memory for over 10 years between baseline normal and MCI ADNI subjects,” shows that estimated 30% normal subjects at baseline assigned to group 3 and 6 stay stable for over 9 years, and normal subjects at baseline assigned to Group 1 (18.18%) and Group 5 (16.67%) were more likely to develop into dementia. In contrast to groups identified for normal subjects, all trajectory groups for MCI subjects at baseline showed the tendency to decline. The third study, “comparison between neural network and logistic regression in PREADViSE trial,” demonstrates that neural network has slightly better predictive performance than logistic regression, and also it can reveal complex relationships among covariates. In third study, the effect of years of education on response variable depends on years of age, status of APOE ɛ4 allele and memory change

Deep brain stimulation in schizophrenia

Deep brain stimulation (DBS) has successfully advanced treatment options of putative therapy-resistant neuropsychiatric diseases. Building on this strong foundation more and more mental disorders in the stadium of therapy-resistance are considered as possible indications for DBS. Especially schizophrenia with its associated severe and difficult to treat symptoms is gaining attention. This attention demands critical questions regarding the assumed mechanisms of DBS and its possible influence on the supposed pathophysiology of schizophrenia. Here we synoptically compare current approaches and theories of DBS and discuss the feasibility of DBS in schizophrenia as well as the transferability from other psychiatric disorders successfully treated with DBS. For this we consider recent advances in animal models of schizophrenic symptoms, results regarding the influence of DBS on dopaminergic transmission as well as data concerning neural oscillation and synchronization. In conclusion the use of DBS for some symptoms of schizophrenia seems to be a promising approach, but the lack of a comprehensive theory of the mechanisms of DBS as well as its impact on schizophrenia might void the use of DBS in schizophrenia at this point

Role of N-methyl-D-aspartate receptors in action-based predictive coding deficits in schizophrenia

Published in final edited form as:Biol Psychiatry. 2017 March 15; 81(6): 514–524. doi:10.1016/j.biopsych.2016.06.019.BACKGROUND: Recent theoretical models of schizophrenia posit that dysfunction of the neural mechanisms subserving predictive coding contributes to symptoms and cognitive deficits, and this dysfunction is further posited to result from N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction. Previously, by examining auditory cortical responses to self-generated speech sounds, we demonstrated that predictive coding during vocalization is disrupted in schizophrenia. To test the hypothesized contribution of NMDAR hypofunction to this disruption, we examined the effects of the NMDAR antagonist, ketamine, on predictive coding during vocalization in healthy volunteers and compared them with the effects of schizophrenia. METHODS: In two separate studies, the N1 component of the event-related potential elicited by speech sounds during vocalization (talk) and passive playback (listen) were compared to assess the degree of N1 suppression during vocalization, a putative measure of auditory predictive coding. In the crossover study, 31 healthy volunteers completed two randomly ordered test days, a saline day and a ketamine day. Event-related potentials during the talk/listen task were obtained before infusion and during infusion on both days, and N1 amplitudes were compared across days. In the case-control study, N1 amplitudes from 34 schizophrenia patients and 33 healthy control volunteers were compared. RESULTS: N1 suppression to self-produced vocalizations was significantly and similarly diminished by ketamine (Cohen’s d = 1.14) and schizophrenia (Cohen’s d = .85). CONCLUSIONS: Disruption of NMDARs causes dysfunction in predictive coding during vocalization in a manner similar to the dysfunction observed in schizophrenia patients, consistent with the theorized contribution of NMDAR hypofunction to predictive coding deficits in schizophrenia.This work was supported by AstraZeneca for an investigator-initiated study (DHM) and the National Institute of Mental Health Grant Nos. R01 MH-58262 (to JMF) and T32 MH089920 (to NSK). JHK was supported by the Yale Center for Clinical Investigation Grant No. UL1RR024139 and the US National Institute on Alcohol Abuse and Alcoholism Grant No. P50AA012879. (AstraZeneca for an investigator-initiated study (DHM); R01 MH-58262 - National Institute of Mental Health; T32 MH089920 - National Institute of Mental Health; UL1RR024139 - Yale Center for Clinical Investigation; P50AA012879 - US National Institute on Alcohol Abuse and Alcoholism)Accepted manuscrip