The association between posterior resting-state EEG alpha rhythms and functional MRI connectivity in older adults with subjective memory complaint.

Resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms are dominant in posterior cortical areas in healthy adults and are abnormal in subjective memory complaint (SMC) persons with Alzheimer's disease amyloidosis. This exploratory study in 161 SMC participants tested the relationships between those rhythms and seed-based resting-state functional magnetic resonance imaging (rs-fMRI) connectivity between thalamus and visual cortical networks as a function of brain amyloid burden, revealed by positron emission tomography and cognitive reserve, measured by educational attainment. The SMC participants were divided into 4 groups according to 2 factors: Education (Edu+ and Edu-) and Amyloid burden (Amy+ and Amy-). There was a statistical interaction (p < 0.05) between the two factors, and the subgroup analysis using estimated marginal means showed a positive association between the mentioned rs-fMRI connectivity and the posterior rsEEG alpha rhythms in the SMC participants with low brain amyloidosis and high CR (Amy-/Edu+). These results suggest that in SMC persons, early Alzheimer's disease amyloidosis may contrast the beneficial effects of cognitive reserve on neurophysiological oscillatory mechanisms at alpha frequencies and connectivity between the thalamus and visual cortical networks.

Theta Band-Power Shapes Amyloid-Driven Longitudinal EEG Changes in Elderly Subjective Memory Complainers At-Risk for Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) includes progressive symptoms spread along a continuum of preclinical and clinical stages. Although numerous studies uncovered the neuro-cognitive changes of AD, very little is known on the natural history of brain lesions and modifications of brain networks in elderly cognitively-healthy memory complainers at risk of AD for carrying pathophysiological biomarkers (amyloidopathy and tauopathy). OBJECTIVE: We analyzed resting-state electroencephalography (EEG) of 318 cognitively-healthy subjective memory complainers from the INSIGHT-preAD cohort at the time of their first visit (M0) and two-years later (M24). METHODS: Using 18F-florbetapir PET-scanner, subjects were stratified between amyloid negative (A-; n = 230) and positive (A+; n = 88) groups. Differences between A+ and A- were estimated at source-level in each band-power of the EEG spectrum. RESULTS: At M0, we found an increase of theta power in the mid-frontal cortex in A+ compared to A-. No significant association was found between mid-frontal theta and the individuals' cognitive performance. At M24, theta power increased in A+ relative to A- individuals in the posterior cingulate cortex and the pre-cuneus. Alpha band revealed a peculiar decremental trend in posterior brain regions in the A+ relative to the A- group only at M24. Theta power increase over the mid-frontal and mid-posterior cortices suggests an hypoactivation of the default-mode network in the A+ individuals and a non-linear longitudinal progression at M24. CONCLUSION: We provide the first source-level longitudinal evidence on the impact of brain amyloidosis on the EEG dynamics of a large-scale, monocentric cohort of elderly individuals at-risk for AD.

Resting-state posterior alpha rhythms are abnormal in subjective memory complaint seniors with preclinical Alzheimer's neuropathology and high education level: the INSIGHT-preAD study.

Cognitive reserve is present in Alzheimer's disease (AD) seniors with high education attainment making them clinically resilient to extended brain neuropathology and neurodegeneration. Here, we tested whether subjective memory complaint (SMC) seniors with AD neuropathology and high education attainment of the prospective INSIGHT-preAD cohort (Paris) may present abnormal eyes-closed resting state posterior electroencephalographic rhythms around individual alpha frequency peak, typically altered in AD patients. The SMC participants negative to amyloid PET AD markers (SMCneg) with high (over low-moderate) education level showed higher posterior alpha 2 power density (possibly "neuroprotective"). Furthermore, amyloid PET-positive SMC (SMCpos) participants with high (over low-moderate) education level showed higher temporal alpha 3 power density (possibly "neuroprotective") and lower posterior alpha 2 power density (possibly "compensatory"). This effect may reflect cognitive reserve as no differences in brain gray-white matter, and cognitive functions were observed between these SMCpos/SMCneg subgroups. Preclinical Alzheimer's neuropathology may interact with education attainment and neurophysiological mechanisms generating cortical alpha rhythms around individual alpha frequency peak (i.e., alpha 2 and 3) in quiet wakefulness.

Relationships between objectives sleep parameters and brain amyloid load in subjects at risk for Alzheimer's disease: the INSIGHT-preAD Study.

STUDY OBJECTIVES: Sleep changes have been associated with increased risks of developing cognitive disturbances and Alzheimer's disease (AD). A bidirectional relation is underlined between amyloid-beta (Aß) and sleep disruptions. The sleep profile in participants at risk to develop AD is not fully deciphered. We aim to investigate sleep-wake changes with objective sleep measurements in elderly participants without cognitive impairment depending on their brain amyloid status, positive (Aß+) or negative (Aß-) based on standard absorption ratios (SUVr) positron emission tomography-florbetapir imaging. METHODS: Sixty-eight participants without cognitive impairment who have accepted to be involved in the sleep ancillary study from the InveStIGation of Alzheimer's Predictors in Subjective Memory Complainers (INSIGHT-pre AD) cohort, aiming to record sleep profile based on the analyses of an ambulatory accelerometer-based assessment (seven consecutive 24-hour periods). Neuropsychological tests were performed and sleep parameters have been individualized by actigraph. Participants also underwent a magnetic resonance imaging scan to assess their hippocampal volume. Based on SUVr PET-florbetapir imaging, two groups Aß+ and Aß- were compared. RESULTS: Participants were divided into two groups: Aß+ (n = 24) and Aß- (n = 44). Except for the SUVr, the two subgroups were comparable. When looking to sleep parameters, increased sleep latency, sleep fragmentation (wake after sleep onset [WASO] score and awakenings) and worst sleep efficiency were associated with cortical brain amyloid load. CONCLUSION: Actigraphic sleep parameters were associated with cortical brain amyloid load in participants at risk to develop AD. The detection of sleep abnormalities in those participants may be of interest to propose some preventive strategies.

Which Episodic Memory Performance is Associated with Alzheimer's Disease Biomarkers in Elderly Cognitive Complainers? Evidence from a Longitudinal Observational Study with Four Episodic Memory Tests (Insight-PreAD).

BACKGROUND: Alzheimer's disease (AD) pathology is found in the brain years before symptoms are usually detected. An episodic memory (EM) decline is considered to be the specific cognitive sign indicating a transition from the preclinical to the prodromal stage of AD. However, there is still no consensus on the most sensitive tool to detect it. OBJECTIVE: The goal of our study was to determine which EM measures, among three clinically used EM tests and one research EM test, would be optimal to use for detection of early decline in elderly cognitive complainers. METHODS: 318 healthy elderly participants with subjective cognitive complaint were followed for two years. We applied generalized linear mixed models to investigate the effect of baseline brain amyloid and metabolism on the longitudinal evolution of four EM tests. RESULTS: Our findings show that participants performed significantly worse in two out of four EM tests (i.e., the Memory Binding Test and the Delayed Matched Sample test 48 items) as their level of brain amyloid load increased. However, we did not find an association between EM measures and brain metabolism. An interaction of the two biomarkers was associated with the number of intrusions in the Memory Binding Test over two years. CONCLUSION: As most clinical trials in AD are now including patients at its early clinical stage, the precise delineation of the transition phase between the preclinical and prodromal stages of the disease is of crucial importance. Our study indicates that challenging EM tests and intrusions are valuable tools to identify this critical transition.

EEG evidence of compensatory mechanisms in preclinical Alzheimer's disease.

Early biomarkers are needed to identify individuals at high risk of preclinical Alzheimer's disease and to better understand the pathophysiological processes of disease progression. Preclinical Alzheimer's disease EEG changes would be non-invasive and cheap screening tools and could also help to predict future progression to clinical Alzheimer's disease. However, the impact of amyloid-ß deposition and neurodegeneration on EEG biomarkers needs to be elucidated. We included participants from the INSIGHT-preAD cohort, which is an ongoing single-centre multimodal observational study that was designed to identify risk factors and markers of progression to clinical Alzheimer's disease in 318 cognitively normal individuals aged 70-85 years with a subjective memory complaint. We divided the subjects into four groups, according to their amyloid status (based on 18F-florbetapir PET) and neurodegeneration status (evidenced by 18F-fluorodeoxyglucose PET brain metabolism in Alzheimer's disease signature regions). The first group was amyloid-positive and neurodegeneration-positive, which corresponds to stage 2 of preclinical Alzheimer's disease. The second group was amyloid-positive and neurodegeneration-negative, which corresponds to stage 1 of preclinical Alzheimer's disease. The third group was amyloid-negative and neurodegeneration-positive, which corresponds to 'suspected non-Alzheimer's pathophysiology'. The last group was the control group, defined by amyloid-negative and neurodegeneration-negative subjects. We analysed 314 baseline 256-channel high-density eyes closed 1-min resting state EEG recordings. EEG biomarkers included spectral measures, algorithmic complexity and functional connectivity assessed with a novel information-theoretic measure, weighted symbolic mutual information. The most prominent effects of neurodegeneration on EEG metrics were localized in frontocentral regions with an increase in high frequency oscillations (higher beta and gamma power) and a decrease in low frequency oscillations (lower delta power), higher spectral entropy, higher complexity and increased functional connectivity measured by weighted symbolic mutual information in theta band. Neurodegeneration was associated with a widespread increase of median spectral frequency. We found a non-linear relationship between amyloid burden and EEG metrics in neurodegeneration-positive subjects, either following a U-shape curve for delta power or an inverted U-shape curve for the other metrics, meaning that EEG patterns are modulated differently depending on the degree of amyloid burden. This finding suggests initial compensatory mechanisms that are overwhelmed for the highest amyloid load. Together, these results indicate that EEG metrics are useful biomarkers for the preclinical stage of Alzheimer's disease.

Cognitive and neuroimaging features and brain ß-amyloidosis in individuals at risk of Alzheimer's disease (INSIGHT-preAD): a longitudinal observational study.

BACKGROUND: Improved understanding is needed of risk factors and markers of disease progression in preclinical Alzheimer's disease. We assessed associations between brain ß-amyloidosis and various cognitive and neuroimaging parameters with progression of cognitive decline in individuals with preclinical Alzheimer's disease. METHODS: The INSIGHT-preAD is an ongoing single-centre observational study at the Salpêtrière Hospital, Paris, France. Eligible participants were age 70-85 years with subjective memory complaints but unimpaired cognition and memory (Mini-Mental State Examination [MMSE] score ≥27, Clinical Dementia Rating score 0, and Free and Cued Selective Reminding Test [FCSRT] total recall score ≥41). We stratified participants by brain amyloid ß deposition on 18F-florbetapir PET (positive or negative) at baseline. All patients underwent baseline assessments of demographic, cognitive, and psychobehavioural, characteristics, APOE ε4 allele carrier status, brain structure and function on MRI, brain glucose-metabolism on 18F-fluorodeoxyglucose (18F-FDG) PET, and event-related potentials on electroencephalograms (EEGs). Actigraphy and CSF investigations were optional. Participants were followed up with clinical, cognitive, and psychobehavioural assessments every 6 months, neuropsychological assessments, EEG, and actigraphy every 12 months, and MRI, and 18F-FDG and 18F-florbetapir PET every 24 months. We assessed associations of amyloid ß deposition status with test outcomes at baseline and 24 months, and with clinical status at 30 months. Progression to prodromal Alzheimer's disease was defined as an amnestic syndrome of the hippocampal type. FINDINGS: From May 25, 2013, to Jan 20, 2015, we enrolled 318 participants with a mean age of 76·0 years (SD 3·5). The mean baseline MMSE score was 28·67 (SD 0·96), and the mean level of education was high (score >6 [SD 2] on a scale of 1-8, where 1=infant school and 8=higher education). 88 (28%) of 318 participants showed amyloid ß deposition and the remainder did not. The amyloid ß subgroups did not differ for any psychobehavioural, cognitive, actigraphy, and structural and functional neuroimaging results after adjustment for age, sex, and level of education More participants positive for amyloid ß deposition had the APOE ε4 allele (33 [38%] vs 29 [13%], p<0·0001). Amyloid ß1-42 concentration in CSF significantly correlated with mean 18F-florbetapir uptake at baseline (r=-0·62, p<0·0001) and the ratio of amyloid ß1-42 to amyloid ß1-40 (r=-0·61, p<0·0001), and identified amyloid ß deposition status with high accuracy (mean area under the curve values 0·89, 95% CI 0·80-0·98 and 0·84, 0·72-0·96, respectively). No difference was seen in MMSE (28·3 [SD 2·0] vs 28·9 [1·2], p=0·16) and Clinical Dementia Rating scores (0·06 [0·2] vs 0·05 [0·3]; p=0·79) at 30 months (n=274) between participants positive or negative for amyloid ß. Four participants (all positive for amyloid ß deposition at baseline) progressed to prodromal Alzheimer's disease. They were older than other participants positive for amyloid ß deposition at baseline (mean 80·2 years [SD 4·1] vs 76·8 years [SD 3·4]) and had greater 18F-florbetapir uptake at baseline (mean standard uptake value ratio 1·46 [SD 0·16] vs 1·02 [SD 0·20]), and more were carriers of the APOE ε4 allele (three [75%] of four vs 33 [39%] of 83). They also had mild executive dysfunction at baseline (mean FCSRT free recall score 21·25 [SD 2·75] vs 29·08 [5·44] and Frontal Assessment Battery total score 13·25 [1·50] vs 16·05 [1·68]). INTERPRETATION: Brain ß-amyloidosis alone did not predict progression to prodromal Alzheimer's disease within 30 months. Longer follow-up is needed to establish whether this finding remains consistent. FUNDING: Institut Hospitalo-Universitaire and Institut du Cerveau et de la Moelle Epinière (IHU-A-ICM), Ministry of Research, Fondation Plan Alzheimer, Pfizer, and Avid.

Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults.

The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer's disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects (n = 318, mean age 76.1 ± 3.5, 64% female, 28% amyloid positive). Degree, clustering, path length and small world properties were computed. Global and regional amyloid load was determined using [18F]-Florbetapir PET. Associations between standardized uptake value ratio (SUVr) values and network measures were examined using linear regression models. We found that higher global SUVr was associated with lower clustering (ß = -0.12, p < 0.05), and small world values (ß = -0.16, p < 0.01). Associations were most prominent in orbito- and dorsolateral frontal and parieto-occipital regions. Local SUVr values showed less anatomical variability and did not convey additional information beyond global amyloid burden. In conclusion, we found that in cognitively normal elderly subjects, increased global amyloid pathology is associated with alterations in gray matter networks that are indicative of incipient network breakdown towards AD dementia.

No association of cortical amyloid load and EEG connectivity in older people with subjective memory complaints.

Changes in functional connectivity of cortical networks have been observed in resting-state EEG studies in healthy aging as well as preclinical and clinical stages of AD. Little information, however, exists on associations between EEG connectivity and cortical amyloid load in people with subjective memory complaints. Here, we determined the association of global cortical amyloid load, as measured by florbetapir-PET, with functional connectivity based on the phase-lag index of resting state EEG data for alpha and beta frequency bands in 318 cognitively normal individuals aged 70-85 years with subjective memory complaints from the INSIGHT-preAD cohort. Within the entire group we did not find any significant associations between global amyloid load and phase-lag index in any frequency band. Assessing exclusively the subgroup of amyloid-positive participants, we found enhancement of functional connectivity with higher global amyloid load in the alpha and a reduction in the beta frequency bands. In the amyloid-negative participants, higher amyloid load was associated with lower connectivity in the low alpha band. However, these correlations failed to reach significance after controlling for multiple comparisons. The absence of a strong amyloid effect on functional connectivity may represent a selection effect, where individuals remain in the cognitively normal group only if amyloid accumulation does not impair cortical functional connectivity.

Evaluation of amyloid status in a cohort of elderly individuals with memory complaints: validation of the method of quantification and determination of positivity thresholds.

OBJECTIVE: Our aim is to validate the process steps implemented by the French CATI platform to assess amyloid status, obtained from 18F-Florbetapir PET scans, in a cohort of 318 cognitively normal subjects participating in the INSIGHT-preAD study. Our objective was to develop a method with partial volume effect correction (PVEC) on untransformed PET images, using an automated pipeline ("RACHEL") adapted to large series of patients and including quality checks of results. METHODS: We compared RACHEL using different options (with and without PVEC, different sets of regions of interest), to two other methods validated in the literature, referred as the "AVID" and "CAEN" methods. A standard uptake value ratio (SUVR) was obtained with the different methods for participants to another French study, IMAP, including 26 normal elderly controls (NEC), 11 patients with mild cognitive impairment (MCI) and 16 patients with Alzheimer's disease (AD). We determined two cutoffs for RACHEL method by linear correlation with the other methods and applied them to the INSIGHT-preAD subjects. RESULTS: RACHEL including PVEC and a combination of the whole cerebellum and the pons as a reference region allowed the best discrimination between NEC and AD participants. A strong linear correlation was found between RACHEL and the other two methods and yielded the two cutoffs of 0.79 and 0.88. According to the more conservative threshold, 19.8% of the INSIGHT-preAD subjects would be considered amyloid positive, and 27.7% according to the more liberal threshold. CONCLUSIONS: With our method, we clearly discriminated between NEC with negative amyloid status and patients with clinical AD. Using a linear correlation with other validated cutoffs, we could infer our own positivity thresholds and apply them to an independent population. This method might be useful to the community, especially when the optimal cutoff could not be obtained from a population of healthy young adults or from correlation with post-mortem results.

Preclinical Alzheimer's disease: A systematic review of the cohorts underlying the concept.

Preclinical Alzheimer's disease (AD) is a relatively recent concept describing an entity characterized by the presence of a pathophysiological biomarker signature characteristic for AD in the absence of specific clinical symptoms. There is rising interest in the scientific community to define such an early target population mainly because of failures of all recent clinical trials despite evidence of biological effects on brain amyloidosis for some compounds. A conceptual framework has recently been proposed for this preclinical phase of AD. However, few data exist on this silent stage of AD. We performed a systematic review to investigate how the concept is defined across studies. The review highlights the substantial heterogeneity concerning the three main determinants of preclinical AD: "normal cognition," "cognitive decline," and "AD pathophysiological signature." We emphasize the need for a harmonized nomenclature of the preclinical AD concept and standardized population-based and case-control studies using unified operationalized criteria.

Preclinical Alzheimer's disease: Definition, natural history, and diagnostic criteria.

During the past decade, a conceptual shift occurred in the field of Alzheimer's disease (AD) considering the disease as a continuum. Thanks to evolving biomarker research and substantial discoveries, it is now possible to identify the disease even at the preclinical stage before the occurrence of the first clinical symptoms. This preclinical stage of AD has become a major research focus as the field postulates that early intervention may offer the best chance of therapeutic success. To date, very little evidence is established on this "silent" stage of the disease. A clarification is needed about the definitions and lexicon, the limits, the natural history, the markers of progression, and the ethical consequence of detecting the disease at this asymptomatic stage. This article is aimed at addressing all the different issues by providing for each of them an updated review of the literature and evidence, with practical recommendations.

Predictors of cognitive decline and treatment response in a clinical trial on suspected prodromal Alzheimer's disease.

UNLABELLED: We determined the value of hippocampus (Hp) and basal forebrain (BF) volumes for predicting cognitive decline and treatment response in a double-blind, randomized, placebo-controlled phase 4 trial at 28 academic centers (France) in patients with amnestic mild cognitive impairment (MCI) receiving Donepezil 10 mg daily or placebo over 12 months, and 6 months open label follow-up. Outcome measures were the rates of global and domain specific cognitive decline as non-primary efficacy endpoint. The intention-to-treat (ITT) sample analyzed comprised 215 cases. Baseline Hp volume was a significant predictor of rates of change in global cognitive function in linear mixed effects models. This effect was independent of treatment. BF volume was not associated with rates of global or domain specific cognitive decline. Rates of delayed free recall decline were higher in MCI cases treated with donepezil compared to placebo. Only Hp, but not BF volume was a useful predictor of cognitive decline in suspected prodromal AD patients. Both Hp and BF volumes were poor predictors of treatment response, questioning previous approaches on predicting treatment response without placebo control. TRIAL REGISTRATION: clinicalTrials.gov Identifier NCT00403520.

Mechanical stress related to brain atrophy in Alzheimer's disease.

INTRODUCTION: The effects related to endogenous mechanical energy in Alzheimer's disease (AD) pathology have been widely overlooked. With the support of available data from literature and mathematical arguments, we hypothesize that brain atrophy in AD could be co-driven by the cumulative impact of the pressure within brain tissues. METHODS: Brain volumetric and physical data in AD and normal aging (NA) were extracted from the literature. Average brain shrinkage and axial deformations were evaluated mathematically. Mechanical stress equivalents related to brain shrinkage were calculated using a conservation law derived from fluid and solid mechanics. RESULTS: Pressure equivalents of 5.92 and 3.43 mm Hg were estimated in AD and in NA, respectively. DISCUSSION: The calculated increments of brain mechanical stress in AD, which could be impacted by marked dampening of arterial pulse waves, may point to the need to expand the focus on the mechanical processes underpinning pathologic aging of the brain.

Prediction of Alzheimer's Disease Dementia: Data from the GuidAge Prevention Trial.

In therapeutic trials, it is crucial to identify Alzheimer's disease (AD) at its prodromal stage. We assessed the accuracy of the free and cued selective reminding test (FCSRT) compared to other cognitive tests to predict AD dementia in subjects with subjective cognitive decline or mild cognitive impairment. Subjects from the placebo group of the GuidAge trial over 70 years old and without clinical signs of dementia at baseline who completed the 5-year follow-up free of dementia (n = 840) or developed AD dementia (n = 73) were included in our study. Among all the tests, the sum of the 3 free recall of the FCSRT (FCSRT-FR) and the sum of free and cued recall (FCSRT-TR) yielded the best results to predict AD dementia occurrence (all p values <0.05 for comparison of FCSRT-FR ROC and MMSE, CDRsb, and CVF ROCs). FCSRT-FR had an area under the ROC curve of 0.799 (95% CI 0.738-0.85) and the optimal cut-off was 20 (se 68.06% , sp 81.43% , PPV 23.90% , NPV 96,75%). Concerning FCSRT-TR, the AUC was 0.776 and the optimal cut-off was 42 (se 62.5% , sp 82.26% , PPV 23.20% and NPV 96.24%). This study sets the framework for implementing the FCSRT in clinical and therapeutic trials for efficient subject selection.

Evolving Evidence for the Value of Neuroimaging Methods and Biological Markers in Subjects Categorized with Subjective Cognitive Decline.

There is evolving evidence that individuals categorized with subjective cognitive decline (SCD) are potentially at higher risk for developing objective and progressive cognitive impairment compared to cognitively healthy individuals without apparent subjective complaints. Interestingly, SCD, during advancing preclinical Alzheimer's disease (AD), may denote very early, subtle cognitive decline that cannot be identified using established standardized tests of cognitive performance. The substantial heterogeneity of existing SCD-related research data has led the Subjective Cognitive Decline Initiative (SCD-I) to accomplish an international consensus on the definition of a conceptual research framework on SCD in preclinical AD. In the area of biological markers, the cerebrospinal fluid signature of AD has been reported to be more prevalent in subjects with SCD compared to healthy controls; moreover, there is a pronounced atrophy, as demonstrated by magnetic resonance imaging, and an increased hypometabolism, as revealed by positron emission tomography, in characteristic brain regions affected by AD. In addition, SCD individuals carrying an apolipoprotein ɛ4 allele are more likely to display AD-phenotypic alterations. The urgent requirement to detect and diagnose AD as early as possible has led to the critical examination of the diagnostic power of biological markers, neurophysiology, and neuroimaging methods for AD-related risk and clinical progression in individuals defined with SCD. Observational studies on the predictive value of SCD for developing AD may potentially be of practical value, and an evidence-based, validated, qualified, and fully operationalized concept may inform clinical diagnostic practice and guide earlier designs in future therapy trials.

Bimodal BCI using simultaneously NIRS and EEG.

Although noninvasive brain-computer interfaces (BCI) based on electroencephalographic (EEG) signals have been studied increasingly over the recent decades, their performance is still limited in two important aspects. First, the difficulty of performing a reliable detection of BCI commands increases when EEG epoch length decreases, which makes high information transfer rates difficult to achieve. Second, the BCI system often misclassifies the EEG signals as commands, although the subject is not performing any task. In order to circumvent these limitations, the hemodynamic fluctuations in the brain during stimulation with steady-state visual evoked potentials (SSVEP) were measured using near-infrared spectroscopy (NIRS) simultaneously with EEG. BCI commands were estimated based on responses to a flickering checkerboard (ON-period). Furthermore, an "idle" command was generated from the signal recorded by the NIRS system when the checkerboard was not flickering (OFF-period). The joint use of EEG and NIRS was shown to improve the SSVEP classification. For 13 subjects, the relative improvement in error rates obtained by using the NIRS signal, for nine classes including the "idle" mode, ranged from 85% to 53 %, when the epoch length increase from 3 to 12 s. These results were obtained from only one EEG and one NIRS channel. The proposed bimodal NIRS-EEG approach, including detection of the idle mode, may make current BCI systems faster and more reliable.

Perspective on future role of biological markers in clinical therapy trials of Alzheimer's disease: a long-range point of view beyond 2020.

Recent advances in understanding the molecular mechanisms underlying various paths toward the pathogenesis of Alzheimer's disease (AD) has begun to provide new insight for interventions to modify disease progression. The evolving knowledge gained from multidisciplinary basic research has begun to identify new concepts for treatments and distinct classes of therapeutic targets; as well as putative disease-modifying compounds that are now being tested in clinical trials. There is a mounting consensus that such disease modifying compounds and/or interventions are more likely to be effectively administered as early as possible in the cascade of pathogenic processes preceding and underlying the clinical expression of AD. The budding sentiment is that "treatments" need to be applied before various molecular mechanisms converge into an irreversible pathway leading to morphological, metabolic and functional alterations that characterize the pathophysiology of AD. In light of this, biological indicators of pathophysiological mechanisms are desired to chart and detect AD throughout the asymptomatic early molecular stages into the prodromal and early dementia phase. A major conceptual development in the clinical AD research field was the recent proposal of new diagnostic criteria, which specifically incorporate the use of biomarkers as defining criteria for preclinical stages of AD. This paradigm shift in AD definition, conceptualization, operationalization, detection and diagnosis represents novel fundamental opportunities for the modification of interventional trial designs. This perspective summarizes not only present knowledge regarding biological markers but also unresolved questions on the status of surrogate indicators for detection of the disease in asymptomatic people and diagnosis of AD.

Emotional faces boost up steady-state visual responses for brain-computer interface.

Steady-state visual evoked potentials (SSVEPs) can be used successfully for brain-computer interfaces (BCI) with multiple commands and high information transfer rates. In this study, we investigated a novel affective SSVEP paradigm using flickering video clips of emotional human faces, and evaluated their performance in an 8-command BCI controlling a robotic arm in near real-time. Single-trial affective SSVEP responses, estimated using a new phase-locking value variability and a wavelet energy variability measures, were significantly enhanced compared with blurred-face flicker and standard checkerboards. For multicommand SSVEP-based BCI, affective face-flicker boosted up the information transfer rates from 50 to 64 bits/min, while reducing user fatigue and enhancing visual attention and reliability. In the 5-12 Hz flicker frequency range, the strongest affective SSVEP responses were obtained at 10 Hz. These findings suggest new directions for SSVEP-based neural applications, including affective BCI and enhanced steady-state clinical probes.

Optimization of SSVEP brain responses with application to eight-command Brain-Computer Interface.

This study pursues the optimization of the brain responses to small reversing patterns in a Steady-State Visual Evoked Potentials (SSVEP) paradigm, which could be used to maximize the efficiency of applications such as Brain-Computer Interfaces (BCI). We investigated the SSVEP frequency response for 32 frequencies (5-84 Hz), and the time dynamics of the brain response at 8, 14 and 28 Hz, to aid the definition of the optimal neurophysiological parameters and to outline the onset-delay and other limitations of SSVEP stimuli in applications such as our previously described four-command BCI system. Our results showed that the 5.6-15.3 Hz pattern reversal stimulation evoked the strongest responses, peaking at 12 Hz, and exhibiting weaker local maxima at 28 and 42 Hz. After stimulation onset, the long-term SSVEP response was highly non-stationary and the dynamics, including the first peak, was frequency-dependent. The evaluation of the performance of a frequency-optimized eight-command BCI system with dynamic neurofeedback showed a mean success rate of 98%, and a time delay of 3.4s. Robust BCI performance was achieved by all subjects even when using numerous small patterns clustered very close to each other and moving rapidly in 2D space. These results emphasize the need for SSVEP applications to optimize not only the analysis algorithms but also the stimuli in order to maximize the brain responses they rely on.