Brain source localization of MMN and P300 ERPs in mild cognitive impairment and Alzheimer's disease: a high-density EEG approach

P300 Latency with Memory Performance: A Promising Biomarker for Preclinical Stages of Alzheimer's Disease

Detecting and tracking the preclinical stages of Alzheimer's disease (AD) is now of particular interest due to the aging of the world's population. AD is the most common cause of dementia, affecting the daily lives of those afflicted. Approaches in development can accelerate the evaluation of the preclinical stages of AD and facilitate early treatment and the prevention of symptom progression. Shifts in P300 amplitude and latency, together with neuropsychological assessments, could serve as biomarkers in the early screening of declines in cognitive abilities. In this study, we investigated the ability of the P300 indices evoked during a visual oddball task to differentiate pre-clinically diagnosed participants from normal healthy adults (HCs). Two preclinical stages, named asymptomatic AD (AAD) and prodromal AD (PAD), were included in this study, and a total of 79 subjects participated, including 35 HCs, 22 AAD patients, and 22 PAD patients. A mixed-design ANOVA test was performed to compare the P300 indices among groups during the processing of the target and non-target stimuli. Additionally, the correlation between these neurophysiological variables and the neuropsychological tests was evaluated. Our results revealed that neither the peak amplitude nor latency of P300 can distinguish AAD from HCs. Conversely, the peak latency of P300 can be used as a biomarker to differentiate PAD from AAD and HCs. The correlation results revealed a significant relationship between the peak latency of P300 and memory domain tasks, showing that less time-demanding neuropsychological assessments can be used. In summary, our findings showed that a combination of P300 latency and memory-requiring tasks can be used as an efficient biomarker to differentiate individuals with AAD from HCs.

The characteristics of auditorial event-related potential under propofol sedation associated with preoperative cognitive performance in glioma patients

Background

Glioma patients often experience neurocognitive deficits, particularly mild cognitive impairment (MCI), which affects their perioperative safety. The use of auditory event-related potentials (AERPs) might be a promising method for reflecting perioperative cognitive function in patients, even under unresponsive sedation. In this study, we aimed to investigate the relationships between the AERP under sedation and preoperative cognitive performance in glioma patients.

Methods

Patients with primary supratentorial gliomas who were scheduled for elective craniotomy under general anesthesia were included in this prospective observational study. The patients were categorized into MCI and non-MCI groups based on their preoperative Montreal Cognitive Assessment (MoCA) scores. AERP characteristics, including mismatch negativity (MMN), P300, and event-related spectral perturbation (ERSP) in the theta bands, were analyzed under different propofol-induced sedation conditions. Differences in these parameters between groups and their relationships with preoperative cognitive performance were subsequently investigated.

Results

Twenty-nine eligible patients were included in the analysis. Compared to that in the non-MCI group, the average amplitude of the MMN component evoked by the novel stimulus significantly decreased during the recovery period in the MCI group (-3.895 ± 1.961 μV vs. -1.617 ± 1.831 μV, p = 0.003). Theta-ERSPs also differed between the two groups under standard (0.021 ± 0.658 μV2/Hz vs. 0.515 ± 0.622 μV2/Hz, p = 0.048) and novel (0.212 ± 0.584 μV2/Hz vs. 0.823 ± 0.931 μV2/Hz, p = 0.041) stimulation conditions under light sedation. After correcting for age, education level, site of lesion, WHO pathological grade and combined symptomatic epilepsy as confounders, the frontal theta-ERSP induced by standard and novel stimuli under light sedation was inversely related to the preoperative MoCA score (standard stimuli: β = -0.491, p = 0.011; novel stimuli: β = -0.594, p = 0.007), as was the average MMN amplitude induced by novel stimuli during the recovery period (β = -0.356, p = 0.035).

Conclusion

The AERP neural response characteristics of glioma patients during propofol sedation were associated with preoperative cognitive performance, which might be a potential neurophysiological indicator for monitoring perioperative cognitive function, especially theta-ERSP.

Exploring easily accessible neurophysiological biomarkers for predicting Alzheimer's disease progression: a systematic review

Alzheimer disease (AD) remains a significant global health concern. The progression from preclinical stages to overt dementia has become a crucial point of interest for researchers. This paper reviews the potential of neurophysiological biomarkers in predicting AD progression, based on a systematic literature search following PRISMA guidelines, including 55 studies. EEG-based techniques have been predominantly employed, whereas TMS studies are less common. Among the investigated neurophysiological measures, spectral power measurements and event-related potentials-based measures, including P300 and N200 latencies, have emerged as the most consistent and reliable biomarkers for predicting the likelihood of conversion to AD. In addition, TMS-based indices of cortical excitability and synaptic plasticity have also shown potential in assessing the risk of conversion to AD. However, concerns persist regarding the methodological discrepancies among studies, the accuracy of these neurophysiological measures in comparison to established AD biomarkers, and their immediate clinical applicability. Further research is needed to validate the predictive capabilities of EEG and TMS measures. Advancements in this area could lead to cost-effective, reliable biomarkers, enhancing diagnostic processes and deepening our understanding of AD pathophysiology.

Neurophysiological markers of early cognitive decline in older adults: a mini-review of electroencephalography studies for precursors of dementia

The early detection of cognitive decline in older adults is crucial for preventing dementia. This mini-review focuses on electroencephalography (EEG) markers of early dementia-related precursors, including subjective cognitive decline, subjective memory complaints, and cognitive frailty. We present recent findings from EEG analyses identifying high dementia risk in older adults, with an emphasis on conditions that precede mild cognitive impairment. We also cover event-related potentials, quantitative EEG markers, microstate analysis, and functional connectivity approaches. Moreover, we discuss the potential of these neurophysiological markers for the early detection of cognitive decline as well as their correlations with related biomarkers. The integration of EEG data with advanced artificial intelligence technologies also shows promise for predicting the trajectory of cognitive decline in neurodegenerative disorders. Although challenges remain in its standardization and clinical application, EEG-based approaches offer non-invasive, cost-effective methods for identifying individuals at risk of dementia, which may enable earlier interventions and personalized treatment strategies.

Transient changes in mismatch negativity after two sessions of electroconvulsive therapy for atypical psychosis: A case report

Background

Cognitive abnormalities associated with electroconvulsive therapy (ECT) are limited to the first few days after treatment. Mismatch negativity (MMN) is an event-related potential that reflects an automatic auditory change detection process under nonattention conditions and cognitive function in psychotic disorders and may be trait- or state-dependent. This study aimed to report the changes in MMN and cognitive function after two ECT treatments in a female patient who underwent maintenance ECT for atypical psychosis.

Case Presentation

A 67-year-old Japanese woman with atypical psychosis was admitted to our hospital for the maintenance of ECT. She received two ECT treatments. We measured her duration-MMN (MMN-D) at baseline, the day after two ECT treatments, and approximately 40 days after the two ECT treatments. After the two ECT treatments, the peak latency of the MMN on the following day was delayed compared with that before the first ECT treatment. Forty days after the two ECT treatments, the peak latency reverted to the baseline. The Brief Assessment of Cognition in Schizophrenia scores measured at the same time point also showed a similar temporary decrease in scores.

Conclusion

Peak latency prolongation in MMN-D may reflect transient cognitive abnormalities after ECT. MMN can be useful to evaluate cognitive dysfunction, one of the adverse events of ECT. However, future studies are needed to examine the reproducibility and to examine the results in diseases other than atypical psychosis.

Human brain imaging with high-density electroencephalography: Techniques and applications

Electroencephalography (EEG) is a technique for non-invasively measuring neuronal activity in the human brain using electrodes placed on the participant's scalp. With the advancement of digital technologies, EEG analysis has evolved over time from the qualitative analysis of amplitude and frequency modulations to a comprehensive analysis of the complex spatiotemporal characteristics of the recorded signals. EEG is now considered a powerful tool for measuring neural processes in the same time frame in which they happen (i.e. the subsecond range). However, it is commonly argued that EEG suffers from low spatial resolution, which makes it difficult to localize the generators of EEG activity accurately and reliably. Today, the availability of high-density EEG (hdEEG) systems, combined with methods for incorporating information on head anatomy and sophisticated source-localization algorithms, has transformed EEG into an important neuroimaging tool. hdEEG offers researchers and clinicians a rich and varied range of applications. It can be used not only for investigating neural correlates in motor and cognitive neuroscience experiments, but also for clinical diagnosis, particularly in the detection of epilepsy and the characterization of neural impairments in a wide range of neurological disorders. Notably, the integration of hdEEG systems with other physiological recordings, such as kinematic and/or electromyography data, might be especially beneficial to better understand the neuromuscular mechanisms associated with deconditioning in ageing and neuromotor disorders, by mapping the neurokinematic and neuromuscular connectivity patterns directly in the brain.

The accuracy of different mismatch negativity amplitude representations in predicting the levels of consciousness in patients with disorders of consciousness

Introduction

The mismatch negativity (MMN) index has been used to evaluate consciousness levels in patients with disorders of consciousness (DoC). Indeed, MMN has been validated for the diagnosis of vegetative state/unresponsive wakefulness syndrome (VS/UWS) and minimally conscious state (MCS). In this study, we evaluated the accuracy of different MMN amplitude representations in predicting levels of consciousness.

Methods

Task-state electroencephalography (EEG) data were obtained from 67 patients with DoC (35 VS and 32 MCS). We performed a microstate analysis of the task-state EEG and used four different representations (the peak amplitude of MMN at electrode Fz (Peak), the average amplitude within a time window -25- 25 ms entered on the latency of peak MMN component (Avg for peak ± 25 ms), the average amplitude of averaged difference wave for 100-250 ms (Avg for 100-250 ms), and the average amplitude difference between the standard stimulus ("S") and the deviant stimulus ("D") at the time corresponding to Microstate 1 (MS1) (Avg for MS1) of the MMN amplitude to predict the levels of consciousness.

Results

The results showed that among the four microstates clustered, MS1 showed statistical significance in terms of time proportion during the 100-250 ms period. Our results confirmed the activation patterns of MMN through functional connectivity analysis. Among the four MMN amplitude representations, the microstate-based representation showed the highest accuracy in distinguishing different levels of consciousness in patients with DoC (AUC = 0.89).

Conclusion

We discovered a prediction model based on microstate calculation of MMN amplitude can accurately distinguish between MCS and VS states. And the functional connection of the MS1 is consistent with the activation mode of MMN.

Prefrontal event-related potential markers in association with mild cognitive impairment

Background

Alzheimer's disease (AD) is among the leading contributors of dementia globally with approximately 60-70% of its cases. Current research is focused on the mild cognitive impairment (MCI), which is associated with cognitive decline but does not disrupt routine activities. Event-related potential (ERP) research is essential in screening patients with MCI. Low-density channel electroencephalography (EEG) is frequently used due to its convenience, portability, and affordability, making it suitable for resource-constrained environments. Despite extensive research on neural biomarkers for cognitive impairment, there is a considerable gap in understanding the effects on early stages of cognitive processes, particularly when combining physiological and cognitive markers using portable devices. The present study aimed to examine cognitive shortfalls and behavioral changes in patients with MCI using prefrontal selective attention ERP recorded from a prefrontal two-channel EEG device.

Methods

We assessed cognitive decline using the Mini-Mental State Examination (MMSE) and the Seoul Neuropsychological Screening Battery (SNSB). We administered auditory selective attention tasks to 598 elderly participants, including those with MCI (160) and cognitively normal (CN) individuals (407). We conducted statistical analyses such as independent t-tests, Pearson's correlations, and univariate and multiple logistic regression analyses to assess group differences and associations between neuropsychological tests, ERP measures, behavioral measures, and MCI prevalence.

Results

Our findings revealed that patients with MCI demonstrated slower information-processing abilities, and exhibited poorer task execution, characterized by reduced accuracy, increased errors, and higher variability in response time, compared to CN adults. Multiple logistic regression analyses confirmed the association between some ERP and behavioral measures with MCI prevalence, independent of demographic and neuropsychological factors. A relationship was observed between neuropsychological scores, ERP, and behavioral measures.

Discussion

The slower information processing abilities, and poor task execution in the MCI group compared to the CN individuals suggests flawed neurological changes and reduced attentional maintenance during cognitive processing, respectively. Hence, the utilization of portable EEG devices to capture prefrontal selective attention ERPs, in combination with behavioral assessments, holds promise for the identification of mild cognitive deficits and neural alterations in individuals with MCI. This approach could potentially augment the traditional neuropsychological tests during clinical screening for MCI.

Activation of the brain during motor imagination task with auditory stimulation

Introduction

Auditory stimulation is one of the most important influence factors in the cognitive process. It is an important guiding role in cognitive motor process. However, previous studies on auditory stimuli mainly focused on the cognitive effects of auditory stimuli on the cortex, while the role of auditory stimuli in motor imagery tasks is still unclear.

Methods

In order to explore the role of auditory stimuli in motor imagery tasks, we studied the EEG power spectrum distribution characteristics, frontal parietal mismatch negative (MMN) wave characteristics, and the Inter trial phase locking consistency (ITPC) characteristics of the prefrontal cognitive cortex and parietal motor cortex. In this study, 18 subjects were hired to complete the motor imagery tasks, induced by auditory stimuli of task related verbs and task independent nouns.

Results

EEG power spectrum analysis showed that the activity of the contralateral motor cortex was significantly increased under the stimulation of verbs, and the amplitude of mismatch negative wave was also significantly increased. ITPC is mainly concentrated in μ, α, and γ bands in the process of motor imagery task guided by the auditory stimulus of verbs, while it is mainly concentrated in the β band under the nouns stimulation. This difference may be due to the impact of auditory cognitive process on motor imagery.

Discussion

We speculate that there may be a more complex mechanism for the effect of auditory stimulation on the inter test phase lock consistency. When the stimulus sound has the corresponding meaning to the motor action, the parietal motor cortex may be more affected by the cognitive prefrontal cortex, thus changing its normal response mode. This mode change is due to the joint action of motor imagination, cognitive and auditory stimuli. This study provides new insight into the neural mechanism of motor imagery task guided by auditory stimuli, and provides more information on the activity characteristics of the brain network in motor imagery task by cognitive auditory stimulation.

Auditory Event-Related Potentials in Older Adults with Subjective Memory Complaints

BACKGROUND

Auditory event-related potentials (AERPs) have been suggested as possible biomarkers for the early diagnosis of Alzheimer's disease (AD). However, no study has investigated AERP measures in individuals with subjective memory complaints (SMCs), who have been suggested to be at a pre-clinical stage of AD.

OBJECTIVE

This study investigated whether AERPs in older adults with SMC can be used to objectively identify those at high risk of developing AD.

METHODS

AERPs were measured in older adults. Presence of SMC was determined using the Memory Assessment Clinics Questionnaire (MAC-Q). Hearing thresholds using pure-tone audiometry, neuropsychological data, levels of amyloid-β burden and Apolipoprotein E (APOE)ɛ genotype were also obtained A classic two-tone discrimination (oddball) paradigm was used to elicit AERPs (i.e., P50, N100, P200, N200, and P300).

RESULTS

Sixty-two individuals (14 male, mean age 71.9±5.2 years) participated in this study, of which, 43 (11 male, mean age 72.4±5.5 years) were SMC and 19 (3 male, mean age 70.8±4.3 years) were non-SMC (controls). P50 latency was weakly but significantly correlated with MAC-Q scores. In addition, P50 latencies were significantly longer in Aβ+ individuals compared to Aβ- individuals.

CONCLUSION

Results suggest that P50 latencies may be a useful tool to identify individuals at higher risk (i.e., participants with high Aβ burden) of developing measurable cognitive decline. Further longitudinal and cross-sectional studies in a larger cohort on SMC individuals are warranted to determine if AERP measures could be of significance for the detection of pre-clinical AD.

Differentiation of Subjective Cognitive Decline, Mild Cognitive Impairment, and Dementia Using qEEG/ERP-Based Cognitive Testing and Volumetric MRI in an Outpatient Specialty Memory Clinic

BACKGROUND

Distinguishing between subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia in a scalable, accessible way is important to promote earlier detection and intervention.

OBJECTIVE

We investigated diagnostic categorization using an FDA-cleared quantitative electroencephalographic/event-related potential (qEEG/ERP)-based cognitive testing system (eVox® by Evoke Neuroscience) combined with an automated volumetric magnetic resonance imaging (vMRI) tool (Neuroreader® by Brainreader).

METHODS

Patients who self-presented with memory complaints were assigned to a diagnostic category by dementia specialists based on clinical history, neurologic exam, neuropsychological testing, and laboratory results. In addition, qEEG/ERP (n = 161) and quantitative vMRI (n = 111) data were obtained. A multinomial logistic regression model was used to determine significant predictors of cognitive diagnostic category (SCD, MCI, or dementia) using all available qEEG/ERP features and MRI volumes as the independent variables and controlling for demographic variables. Area under the Receiver Operating Characteristic curve (AUC) was used to evaluate the diagnostic accuracy of the prediction models.

RESULTS

The qEEG/ERP measures of Reaction Time, Commission Errors, and P300b Amplitude were significant predictors (AUC = 0.79) of cognitive category. Diagnostic accuracy increased when volumetric MRI measures, specifically left temporal lobe volume, were added to the model (AUC = 0.87).

CONCLUSION

This study demonstrates the potential of a primarily physiological diagnostic model for differentiating SCD, MCI, and dementia using qEEG/ERP-based cognitive testing, especially when combined with volumetric brain MRI. The accessibility of qEEG/ERP and vMRI means that these tools can be used as adjuncts to clinical assessments to help increase the diagnostic certainty of SCD, MCI, and dementia.

Understanding the Relationship Between Age-Related Hearing Loss and Alzheimer’s Disease: A Narrative Review

Evidence suggests that hearing loss (HL), even at mild levels, increases the long-term risk of cognitive decline and incident dementia. Hearing loss is one of the modifiable risk factors for dementia, with approximately 4 million of the 50 million cases of dementia worldwide possibly attributed to untreated HL. This paper describes four possible mechanisms that have been suggested for the relationship between age-related hearing loss (ARHL) and Alzheimer’s disease (AD), which is the most common form of dementia. The first mechanism suggests mitochondrial dysfunction and altered signal pathways due to aging as a possible link between ARHL and AD. The second mechanism proposes that sensory degradation in hearing impaired people could explain the relationship between ARHL and AD. The occupation of cognitive resource (third) mechanism indicates that the association between ARHL and AD is a result of increased cognitive processing that is required to compensate for the degraded sensory input. The fourth mechanism is an expansion of the third mechanism, i.e., the function and structure interaction involves both cognitive resource occupation (neural activity) and AD pathology as the link between ARHL and AD. Exploring the specific mechanisms that provide the link between ARHL and AD has the potential to lead to innovative ideas for the diagnosis, prevention, and/or treatment of AD. This paper also provides insight into the current evidence for the use of hearing treatments as a possible treatment/prevention for AD, and if auditory assessments could provide an avenue for early detection of cognitive impairment associated with AD.

Towards high-accuracy classifying attention-deficit/hyperactivity disorders using CNN-LSTM model

OBJECTIVE

The neurocognitive attention functions involve the cooperation of multiple brain regions, and the defects in the cooperation will lead to attention-deficit/hyperactivity disorder (ADHD), which is one of the most common neuropsychiatric disorders for children. The current ADHD diagnosis is mainly based on a subjective evaluation that is easily biased by the experience of the clinicians and lacks the support of objective indicators. The purpose of this study is to propose a method that can effectively identify children with ADHD.

APPROACH

In this study, we proposed a CNN-LSTM model to solve the three-class problems of classifying ADHD, attention deficit disorder (ADD) and healthy children, based on a public EEG dataset that includes event-related potential (ERP) EEG signals of 144 children. The convolution visualization and saliency map methods were used to observe the features automatically extracted by the proposed model, which could intuitively explain how the model distinguished different groups.

MAIN RESULTS

The results showed that our CNN-LSTM model could achieve an accuracy as high as 98.23% in a 5-fold cross-validation method, which was significantly better than the current state-of-the-art CNN models. The features extracted by the proposed model were mainly located in the frontal and central areas, with significant differences in the time period mappings among the three different groups. The P300 and contingent negative variation (CNV) in the frontal lobe had the largest decrease in the healthy control (HC) group, and the ADD group had the smallest decrease. In the central area, only the HC group had a significant negative oscillation of CNV waves.

SIGNIFICANCE

The results of this study suggest that the CNN-LSTM model can effectively identify children with ADHD and its subtypes. The visualized features automatically extracted by this model could better explain the differences in the ERP response among different groups, which is more convincing than previous studies, and it could be used as more reliable neural biomarkers to help with more accurate diagnosis in the clinics.

Cognitive and neuroimaging markers for preclinical vascular cognitive impairment

Detection of incipient cognitive impairment and dementia pathophysiology is critical to identify preclinical populations and target potentially disease modifying interventions towards them. There are currently concerted efforts for such detection for Alzheimer's disease (AD). By contrast, the examination of cognitive markers and their relationship to biomarkers for Vascular Cognitive Impairment (VCI) is far less established, despite VCI being highly prevalent and often concomitantly presenting with AD. Critically, vascular risk factors are currently associated with the most viable treatment options via pharmacological and non-pharmacological intervention, hence early identification of vascular factors have important implications for modifying dementia disease trajectories. The aim of this review is to examine the current evidence of cognitive marker correlates to VCI pathology. We begin by examining midlife risk factors that predict VCI. Next, discuss preclinical cognitive hallmarks of VCI informed by insights from neuropsychological assessment, network connectivity and ERP/EEG experimental findings. Finally, we discuss limitations of current cognitive assessments and the need for future cognitive test development to inform diagnostic assessment. As well as, intervention outcome measures for preclinical VCI. In turn, these tests will inform earlier detection of vascular changes and allow implementation of disease intervention approaches.

Memory Clinics and Day Care Centers in Thessaloniki, Northern Greece: 30 Years of Clinical Practice and Experience

Background: This review describes the diagnostic and interventional procedures conducted in two university memory clinics (established network of G. Papanikolaou Hospital: 1988–2017 and AHEPA hospital: 2017–today) and 2 day care centers (established network of DCCs: 2005–today) in North Greece and their contribution in the scientific field of dementia. The aims of this work are (1) to provide a diagnosis and treatment protocol established in the network of memory clinics and DCCs and (2) to present further research conducted in the aforementioned network during the last 30 years of clinical practice.

Methods: The guidelines to set a protocol demand a series of actions as follows: (1) set the diagnosis criteria, neuropsychological assessment, laboratory examinations, and examination of neurophysiological, neuroimaging, cerebrospinal fluid, blood, and genetic markers; and (2) apply non-pharmacological interventions according to the needs and specialized psychosocial interventions of the patient to the caregivers of the patient.

Results: In addition to the guidelines followed in memory clinics at the 1st and 3rd Department of Neurology and two DCCs, a database of patients, educational programs, and further participation in international research programs, including clinical trials, make our contribution in the dementia field strong.

Conclusion: In the current paper, we provide useful guidelines on how major and minor neurocognitive disorders are being treated in Thessaloniki, Greece, describing successful practices which have been adapted in the last 30 years.

Altered mismatch response of inferior parietal lobule in amnestic mild cognitive impairment: A magnetoencephalographic study

Background

Mismatch negativity (MMN) reflects the functional integrity of sensory memory function. With the advantages of independence of individual's focused attention and behavioral cooperation, this neurophysiological signal is particularly suitable for investigating elderly with cognitive decline such as amnestic mild cognitive impairment (aMCI). However, the existing results remain substantially inconsistent whether these patients show deficits of MMN. In order to reconcile the previous disputes, the present study used magnetoencephalography combined with distributed source imaging methods to determine the source‐level magnetic mismatch negativity (MMNm) in aMCI.

Methods

A total of 26 healthy controls (HC) and 26 patients with aMCI underwent an auditory oddball paradigm during the MEG recordings. MMNm amplitudes and latencies in the bilateral superior temporal gyrus, inferior frontal gyrus, and inferior parietal lobule (IPL) were compared between HC and aMCI groups. The correlations of MMNm responses with performance of auditory/verbal memory tests were examined. Finally, MMNm and its combination with verbal/auditory memory tests were submitted to receiver operating characteristic (ROC) curve analysis.

Results

Compared to HC, patients with aMCI showed significantly delayed MMNm latencies in the IPL. Among the patients with aMCI, longer MMNm latencies of left IPL were associated with lower scores of Chinese Version Verbal Learning Test (CVVLT). The ROC curve analysis revealed that the combination of MMNm latencies of left IPL and CVVLT scores yielded a moderate accuracy in the discrimination of aMCI from HC at an individual level.

Conclusions

Our data suggest dysfunctional MMNm in patients with aMCI, particularly in the IPL.

Multimodal neuroimaging markers of variation in cognitive ability in older HIV+ men

OBJECTIVE

This study used converging methods to examine the neural substrates of cognitive ability in middle-aged and older men with well-controlled HIV infection.

METHODS

Seventy-six HIV+ men on antiretroviral treatment completed an auditory oddball task and an inhibitory control (Simon) task while time-locked high-density EEG was acquired; 66 had usable EEG data from one or both tasks; structural MRI was available for 43. We investigated relationships between task-evoked EEG responses, cognitive ability and immunocompromise. We also explored the structural correlates of these EEG markers in the sub-sample with complete EEG and MRI data (N = 27).

RESULTS

EEG activity was associated with cognitive ability at later (P300) but not earlier stages of both tasks. Only the oddball task P300 was reliably associated with HIV severity (nadir CD4). Source localization confirmed that the tasks engaged partially distinct circuits. Thalamus volume correlated with oddball task P300 amplitude, while globus pallidus volume was related to the P300 in both tasks.

INTERPRETATION

This is the first study to use task-evoked EEG to identify neural correlates of individual differences in cognition in men living with well-controlled HIV infection, and to explore the structural basis of the EEG markers. We found that EEG responses evoked by the oddball task are more reliably related to cognitive performance than those evoked by the Simon task. We also provide preliminary evidence for a subcortical contribution to the effects of HIV infection severity on P300 amplitudes. These results suggest brain mechanisms and candidate biomarkers for individual differences in cognition in HIV.

Screening Tools and Assessment Methods of Cognitive Decline Associated With Age-Related Hearing Loss: A Review

Strong links between hearing and cognitive function have been confirmed by a growing number of cross-sectional and longitudinal studies. Seniors with age-related hearing loss (ARHL) have a significantly higher cognitive impairment incidence than those with normal hearing. The correlation mechanism between ARHL and cognitive decline is not fully elucidated to date. However, auditory intervention for patients with ARHL may reduce the risk of cognitive decline, as early cognitive screening may improve related treatment strategies. Currently, clinical audiology examinations rarely include cognitive screening tests, partly due to the lack of objective quantitative indicators with high sensitivity and specificity. Questionnaires are currently widely used as a cognitive screening tool, but the subject's performance may be negatively affected by hearing loss. Numerous electroencephalogram (EEG) and magnetic resonance imaging (MRI) studies analyzed brain structure and function changes in patients with ARHL. These objective electrophysiological tools can be employed to reveal the association mechanism between auditory and cognitive functions, which may also find biological markers to be more extensively applied in assessing the progression towards cognitive decline and observing the effects of rehabilitation training for patients with ARHL. In this study, we reviewed clinical manifestations, pathological changes, and causes of ARHL and discussed their cognitive function effects. Specifically, we focused on current cognitive screening tools and assessment methods and analyzed their limitations and potential integration.

Advances in Electrical Source Imaging: A Review of the Current Approaches, Applications and Challenges

Brain source localization has been consistently implemented over the recent years to elucidate complex brain operations, pairing the high temporal resolution of the EEG with the high spatial estimation of the estimated sources. This review paper aims to present the basic principles of Electrical source imaging (ESI) in the context of the recent progress for solving the forward and the inverse problems, and highlight the advantages and limitations of the different approaches. As such, a synthesis of the current state-of-the-art methodological aspects is provided, offering a complete overview of the present advances with regard to the ESI solutions. Moreover, the new dimensions for the analysis of the brain processes are indicated in terms of clinical and cognitive ESI applications, while the prevailing challenges and limitations are thoroughly discussed, providing insights for future approaches that could help to alleviate methodological and technical shortcomings.

Mismatch negativity as EEG biomarker supporting CNS drug development: a transnosographic and translational study

The lack of translation from basic research into new medicines is a major challenge in CNS drug development. The need to use novel approaches relying on (i) patient clustering based on neurobiology irrespective to symptomatology and (ii) quantitative biomarkers focusing on evolutionarily preserved neurobiological systems allowing back-translation from clinical to nonclinical research has been highlighted. Here we sought to evaluate the mismatch negativity (MMN) response in schizophrenic (SZ) patients, Alzheimer's disease (AD) patients, and age-matched healthy controls. To evaluate back-translation of the MMN response, we developed EEG-based procedures allowing the measurement of MMN-like responses in a rat model of schizophrenia and a mouse model of AD. Our results indicate a significant MMN attenuation in SZ but not in AD patients. Consistently with the clinical findings, we observed a significant attenuation of deviance detection (~104.7%) in rats subchronically exposed to phencyclidine, while no change was observed in APP/PS1 transgenic mice when compared to wild type. This study provides new insight into the cross-disease evaluation of the MMN response. Our findings suggest further investigations to support the identification of neurobehavioral subtypes that may help patients clustering for precision medicine intervention. Furthermore, we provide evidence that MMN could be used as a quantitative/objective efficacy biomarker during both preclinical and clinical stages of SZ drug development.

Altered mismatch response precedes gray matter atrophy in subjective cognitive decline

The cross-sectional identification of subjective cognitive decline (SCD) in cognitively normal adults is particularly important for the early effective prevention or intervention of the future development of mild cognitive impairments (MCI) or Alzheimer's disease (AD). A pre-attentive neurophysiological signal that reflects the brain's ability to detect the changes of the environment is called mismatch negativity (MMN) or its magnetic counterpart (MMNm). It has been shown that patients with MCI or AD demonstrate reduced MMN/MMNm responses, while the exact profile of MMN/MMNm in SCD is substantially unknown. We applied magnetoencephalographic recordings to interrogate MMNm activities in healthy controls (HC, n = 29) and individuals with SCD (n = 26). Furthermore, we analyzed gray matter (GM) volumes in the MMNm-related regions through voxel-based morphometry and performed apolipoprotein E4 (APOE4) genotyping for all the participants. Our results showed that there were no significant differences in GM volume and proportions of APOE4 carriers between HC and SCD groups. However, individuals with SCD exhibited weakened z-corrected MMNm responses in the left inferior parietal lobule and right inferior frontal gyrus (IFG) as compared to HC. Based on the regions showing significant between-group differences, z-corrected MMNm amplitudes of the right IFG significantly correlated with the memory performance among the SCD participants. Our data suggest that neurophysiological changes of the brain, as indexed by MMNm, precede structural atrophy in the individuals with SCD compared to those without SCD.

Investigating Auditory Electrophysiological Measures of Participants with Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review and Meta-Analysis of Event-Related Potential Studies

BACKGROUND

Objectively measuring auditory functions has been proposed as an avenue in differentiating normal age-related cognitive dysfunction from Alzheimer's disease (AD) and its prodromal states. Previous research has suggested auditory event-related potentials (AERPs) to be non-invasive, cost-effective, and efficient biomarkers for the diagnosis of AD.

OBJECTIVE

The objective of this paper is to review the published literature on AERPs measures in older adults diagnosed with AD and those at higher risk of developing AD, i.e., mild cognitive impairment (MCI) and subjective cognitive decline.

METHODS

The search was performed on six major electronic databases (Ovid MEDLINE, OVID EMBASE, PsycINFO, PubMed, Scopus, and CINAHL Plus). Articles identified prior to 7 May 2019 were considered for this review. A random effects meta-analysis and analysis of between study heterogeneity was conducted using the Comprehensive Meta-Analysis software.

RESULTS

The search identified 1,076 articles; 74 articles met the full inclusion criteria and were included in the systematic review, and 47 articles were included into the analyses. Pooled analysis suggests that AD participants can be differentiated from controls due to significant delays in ABR, N100, P200, N200, and P300 latencies. P300 amplitude was significantly smaller in AD participants compared to controls. P300 latencies differed significantly between MCI participants and controls based on the pooled analysis.

CONCLUSION

The findings of this review indicate that some AERPs may be valuable biomarkers of AD. In conjunction with currently available clinical and neuropsychological assessments, AERPs can aid in screening and diagnosis of prodromal AD.

Mismatch negativity in older adults and its relationship with the cognitive and behavioral aspects of central auditory processing

OBJECTIVES

This study aimed to describe and compare the performance of older adults with normal hearing and hearing impairments in mismatch negativity (MMN), correlate MMN with cognitive tasks and central auditory processing (CAP), and identify normal values for MMN in older adults.

METHODS

This study had 54 participants. The Montreal Cognitive Assessment (MoCA) was used to assess cognition and the random gap detection test (RGDT), dichotic digit test (DDT), and speech to noise (SN) test were used to evaluate CAP. MMN was elicited with the verbal stimulus /da/ (frequent) and /ta/ (rare), and the latency, amplitude, duration, and area were analyzed.

RESULTS

When comparing the normal-hearing group to those with hearing loss, there was no significant difference in MMN. When correlating MMN with MoCA, RGDT, DDT, and the SN test, there was a weak correlation between the MMN amplitude and the RGDT and DDT. When comparing the MMN of participants with normal and altered cognitive aspects and those with normal and altered DDT, the MMN duration was found to be affected by the DDT. The mean latency value of the MMN in the normal-hearing group was 199.8 ms, the amplitude was -2.2 µV, area was 116.1 µV/ms, and duration was 81.2 ms.

CONCLUSION

Mild hearing loss did not influence MMN. There was no correlation between MMN and cognitive aspects, and there were weak correlations with CAP. Alterations in CAP led to longer durations in MMN. Normal values for MMN in adults aged between 60 and 77 years were generated.

Locus coeruleus connectivity alterations in late-life major depressive disorder during a visual oddball task

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Patients with late-life MDD show lower global LC connectivity in an oddball task.

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Lower LC connectivity was observed with the ACC, fusiform gyrus and cerebellum.

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LC-ACC connectivity correlated with two different measures of depression severity.

The Locus Coeruleus (LC) is the major source of noradrenergic neurotransmission. Structural alterations in the LC have been observed in neurodegenerative disorders and at-risk individuals, although functional connectivity studies between the LC and other brain areas have not been yet performed in these populations. Patients with late-life major depressive disorder (MDD) are indeed at increased risk for neurodegenerative disorders, and here we investigated LC connectivity in late-life MDD in comparison to individuals with amnestic type mild cognitive impairment (aMCI) and healthy controls (HCs). We assessed 20 patients with late-life MDD, 16 patients with aMCI, and 26 HCs, who underwent a functional magnetic resonance scan while performing a visual oddball task. We assessed task-related modulations of LC connectivity (i.e., Psychophysiological Interactions, PPI) with other brain areas. A T1-weighted fast spin-echo sequence for LC localization was also obtained. Patients with late-life MDD showed lower global connectivity during target detection in a cluster encompassing the right caudal LC. Specifically, we observed lower LC connectivity with the left anterior cingulate cortex (ACC), the right fusiform gyrus, and different cerebellar clusters. Moreover, alterations in LC-ACC connectivity correlated negatively with depression severity (i.e., Geriatric Depression Scale and number of recurrences). Reduced connectivity of the LC during oddball performance seems to specifically characterize patients with late-life MDD, but not other populations of aged individuals with cognitive alterations. Such alteration is associated with different measures of disease severity, such as the current presence of symptoms and the burden of disease (number of recurrences).

Hyperexcitability in Aging Is Lost in Alzheimer's: What Is All the Excitement About?

Neuronal hyperexcitability has emerged as a potential biomarker of late-onset early-stage Alzheimer's disease (LEAD). We hypothesize that the aging-related posterior cortical hyperexcitability anticipates the loss of excitability with the emergence of impairment in LEAD. To test this hypothesis, we compared the behavioral and neurophysiological responses of young and older (ON) normal adults, and LEAD patients during a visuospatial attentional control task. ONs show frontal cortical signal incoherence and posterior cortical hyper-responsiveness with preserved attentional control. LEADs lose the posterior hyper-responsiveness and fail in the attentional task. Our findings suggest that signal incoherence and cortical hyper-responsiveness in aging may contribute to the development of functional impairment in LEAD.

A systematic review of cognitive event-related potentials in mild cognitive impairment and Alzheimer's disease

This systematic review examined whether event-related potentials (ERPs) during higher cognitive processing can detect subtle, early signs of neurodegenerative disease. Original, empirical studies retrieved from PsycINFO and PubMed were reviewed if they analyzed patterns in cognitive ERPs (≥150 ms post-stimulus) differentiating mild cognitive impairment (MCI), Alzheimer's disease (AD), or cognitively intact elders who carry AD risk through the Apolipoprotein-E ε4 allele (ε4+) from healthy older adult controls (HC). The 100 studies meeting inclusion criteria (MCI = 47; AD = 47; ε4+ = 6) analyzed N200, P300, N400, and occasionally, later components. While there was variability across studies, patterns of reduced amplitude and delayed latency were apparent in pathological aging, consistent with AD-related brain atrophy and cognitive impairment. These effects were particularly evident in advanced disease progression (i.e., AD > MCI) and in later ERP components measured during complex tasks. Although ERP studies in intact ε4+ elders are thus far scarce, a similar pattern of delayed latency was notable, along with a contrasting pattern of increased amplitude, consistent with compensatory neural activation. This limited work suggests ERPs might be able to index early neural changes indicative of future cognitive decline in otherwise healthy elders. As ERPs are also accessible and affordable relative to other neuroimaging methods, their addition to cognitive assessment might substantively enhance early identification and characterization of neural dysfunction, allowing opportunity for earlier differential diagnosis and targeting of intervention. To evaluate this possibility there is urgent need for well-powered studies assessing late cognitive ERPs during complex tasks, particularly in healthy elders at risk for cognitive decline.

Deviance detection in physiologically identified cell types in the rat auditory cortex

Auditory deviance detection is a function of the auditory system that allows reduction of the processing demand for repetitive stimuli while stressing unpredictable ones, which are potentially more informative. Deviance detection has been extensively studied in humans using the oddball paradigm, which evokes an event-related potential known as mismatch negativity (MMN). The same stimulation paradigms are used in animal studies that aim to elucidate the neuronal mechanisms underlying deviance detection. In order to understand the circuitry responsible for deviance detection in the auditory cortex (AC), it is necessary to determine the properties of excitatory and inhibitory neurons separately. Measuring the spike widths of neurons recorded extracellularly from the anaesthetized rat AC, we classified them as fast spiking or regular spiking units. These two neuron types are generally considered as putative inhibitory or excitatory, respectively. In response to an oddball paradigm, we found that both types of units showed similar amounts of deviance detection overall. When considering each AC field separately, we found that only in A1 fast spiking neurons showed higher deviance detection levels than regular spiking neurons, while in the rest of the fields there was no such distinction. Interpreting these responses in the context of the predictive coding framework, we found that the responses of both types of units reflect mainly prediction error signaling (i.e., genuine deviance detection) rather than repetition suppression.

Neuropsychiatric Symptoms and Risk Factors in Mild Cognitive Impairment: A Cohort Investigation of Elderly Patients

BACKGROUND

Neuropsychiatric symptoms (NPS) have been shown to affect the progression and development of Alzheimer's disease (AD) in the elderly. However, the published data are still controversial and limited in large cohort-based NPS study.

AIM

To explore the potential relationship between NPS and mild cognitive impairment (MCI) among the elderly of Chinese community.

METHODS

A total of 465 Chinese community-dwelling elderly (age ≥ 60 years) with mild cognitive impairment (MCI) were recruited into this investigation. At baseline, enrolled participants were assessed for Clinical Dementia Rating (CDR), mini-psychiatric examination. They were also subjected to categorical language fluency test, list learning and delayed recall. We assessed the NPS severity by Neuropsychological Inventory (NPI). The global cognitive status (GCS) of the participants at the end of the 3-year study period were measured with the CDR.

RESULTS

Approximately 41.6% of subjects had 1 or more NPS (total NPI score ≥ 1) at baseline. The most common NPSs were nocturnal behavior (20.8%), depression (17.3%), apathy (12.7%) and anxiety (13.2%). At the end of 3-year follow-up, 26.9% of baseline depressed patients developed AD, while 15.2% of baseline non-depressed patients developed AD (χ2 = 4.86, P=0. 04). Abnormal motor behavior was significantly correlated with cognitive deterioration as well (χ2 = 5.75, P=0. 03). Logistic regression analysis revealed that depression was considered as a risk factor for AD progression at baseline (95% CI: 1.12-5.67, OR=2.37, P=0.03).

CONCLUSIONS

Depression may be an independent factor representing early neurodegeneration in elder patients with MCI. Further studies are warranted to assess whether effective management of NPS promotes the cognitive functions.

Mental workload characteristics of manipulator teleoperators with different spatial cognitive abilities

The main research on manipulator teleoperation includes robust of high-degree of freedom manipulators, sensor measurement accuracy, time delay, and mechanical structure design. Increased mental capacity requirements for complex assignments result in an increased mental workload. Spatial cognitive ability was considered to be the key factor affecting teleoperation performance. To accomplish this, we had 50 participants performed teleoperation while recorded their electroencephalogram. Electroencephalogram data of each task were divided into two periods, which correspond to the observation and large-scale transfer stages of teleoperation, respectively (period 1) and adjust the attitude of the manipulator to approach and align with the target stage (period 2). Brain topographic maps of period 1 (period 1 wavelet packet energy minus resting state wavelet packet energy) and period 2 (period 2 wavelet packet energy minus resting state wavelet packet energy) show that the frontal, central, and occipital regions are the main working areas of low spatial cognitive operators in period 1, while the frontal, central, and occipital regions are the main working areas of high spatial cognitive operators in period 1. The main changes in period 2 were frontal, central, parietal, and occipital regions. This study has implication for the analysis of electroencephalogram signal characteristics of mental workload in different populations to improve operators’ well-being and safety at teleoperation work.

More Reliable EEG Electrode Digitizing Methods Can Reduce Source Estimation Uncertainty, but Current Methods Already Accurately Identify Brodmann Areas

Electroencephalography (EEG) and source estimation can be used to identify brain areas activated during a task, which could offer greater insight on cortical dynamics. Source estimation requires knowledge of the locations of the EEG electrodes. This could be provided with a template or obtained by digitizing the EEG electrode locations. Operator skill and inherent uncertainties of a digitizing system likely produce a range of digitization reliabilities, which could affect source estimation and the interpretation of the estimated source locations. Here, we compared the reliabilities of five digitizing methods (ultrasound, structured-light 3D scan, infrared 3D scan, motion capture probe, and motion capture) and determined the relationship between digitization reliability and source estimation uncertainty, assuming other contributors to source estimation uncertainty were constant. We digitized a mannequin head using each method five times and quantified the reliability and validity of each method. We created five hundred sets of electrode locations based on our reliability results and applied a dipole fitting algorithm (DIPFIT) to perform source estimation. The motion capture method, which recorded the locations of markers placed directly on the electrodes had the best reliability with an average electrode variability of 0.001 cm. Then, in order of decreasing reliability were the method using a digitizing probe in the motion capture system, an infrared 3D scanner, a structured-light 3D scanner, and an ultrasound digitization system. Unsurprisingly, uncertainty of the estimated source locations increased with greater variability of EEG electrode locations and less reliable digitizing systems. If EEG electrode location variability was ∽1 cm, a single source could shift by as much as 2 cm. To help translate these distances into practical terms, we quantified Brodmann area accuracy for each digitizing method and found that the average Brodmann area accuracy for all digitizing methods was >80%. Using a template of electrode locations reduced the Brodmann area accuracy to ∽50%. Overall, more reliable digitizing methods can reduce source estimation uncertainty, but the significance of the source estimation uncertainty depends on the desired spatial resolution. For accurate Brodmann area identification, any of the digitizing methods tested can be used confidently.

Source activity during emotion processing and its relationship to cognitive impairment in Parkinson's disease

BACKGROUND

Neural mechanisms contributing to an underlying cognitive impairment in Parkinson's disease (PD) are poorly understood. An effective method to probe cognitive processing deficits in PD is the examination of brain activity during emotional processes, particularly in explicit language emotion recognition contexts.

METHODS

The present study utilised cortical source imaging of event related potentials (ERP) from electroencephalography (EEG) to evaluate valence judgements on negative and neutral target words in an automatic affective priming paradigm. Fifty non-demented PD patients, unmedicated for depression or anxiety, completed affective priming tasks during EEG monitoring. Cognitive impairment was measured using the validated Parkinson's Disease-Cognitive Rating Scale (PD-CRS).

RESULTS

Results reveal that compared to healthy age-matched controls, PD patients demonstrate a reduced N400 activation during affective priming tasks in bilateral regions of the middle frontal gyrus (MFG), inferior parietal lobule (IPL) and, notably, have a late wave ERP component (LPP) in left MFG, present between 600 and 800 ms, following family-wise error correction (p_FWE < 0.05). LPP in PD patients were significantly associated with PD-CRS scores.

LIMITATIONS

Although affective priming paradigms are an effective means for various domains of cognition, it is not a focused cognitive behavioural test for cognitive dysfunction. Our study is thus limited to a surrogate measure of cognitive dysfunction via examination of emotional word processing cues.

CONCLUSIONS

These findings suggest that source imaging methods with ERP paradigms in PD are effective in identifying delayed cognitive processes in PD.

A Single-Channel EEG-Based Approach to Detect Mild Cognitive Impairment via Speech-Evoked Brain Responses

Mild cognitive impairment (MCI) is the preliminary stage of dementia, which may lead to Alzheimer's disease (AD) in the elderly people. Therefore, early detection of MCI has the potential to minimize the risk of AD by ensuring the proper mental health care before it is too late. In this paper, we demonstrate a single-channel EEG-based MCI detection method, which is cost-effective and portable, and thus suitable for regular home-based patient monitoring. We collected the scalp EEG data from 23 subjects, while they were stimulated with five auditory speech signals. The cognitive state of the subjects was evaluated by the Montreal cognitive assessment test (MoCA). We extracted 590 features from the event-related potential (ERP) of the collected EEG signals, which included time and spectral domain characteristics of the response. The top 25 features, ranked by the random forest method, were used for classification models to identify subjects with MCI. Robustness of our model was tested using leave-one-out cross-validation while training the classifiers. Best results (leave-one-out cross-validation accuracy 87.9%, sensitivity 84.8%, specificity 95%, and F score 85%) were obtained using support vector machine (SVM) method with radial basis kernel (RBF) (sigma = 10/cost = 10² ). Similar performances were also observed with logistic regression (LR), further validating the results. Our results suggest that single-channel EEG could provide a robust biomarker for early detection of MCI.

The Neuronal Basis of Predictive Coding Along the Auditory Pathway: From the Subcortical Roots to Cortical Deviance Detection

In this review, we attempt to integrate the empirical evidence regarding stimulus-specific adaptation (SSA) and mismatch negativity (MMN) under a predictive coding perspective (also known as Bayesian or hierarchical-inference model). We propose a renewed methodology for SSA study, which enables a further decomposition of deviance detection into repetition suppression and prediction error, thanks to the use of two controls previously introduced in MMN research: the many-standards and the cascade sequences. Focusing on data obtained with cellular recordings, we explain how deviance detection and prediction error are generated throughout hierarchical levels of processing, following two vectors of increasing computational complexity and abstraction along the auditory neuraxis: from subcortical toward cortical stations and from lemniscal toward nonlemniscal divisions. Then, we delve into the particular characteristics and contributions of subcortical and cortical structures to this generative mechanism of hierarchical inference, analyzing what is known about the role of neuromodulation and local microcircuitry in the emergence of mismatch signals. Finally, we describe how SSA and MMN are occurring at similar time frame and cortical locations, and both are affected by the manipulation of N-methyl- D-aspartate receptors. We conclude that there is enough empirical evidence to consider SSA and MMN, respectively, as the microscopic and macroscopic manifestations of the same physiological mechanism of deviance detection in the auditory cortex. Hence, the development of a common theoretical framework for SSA and MMN is all the more recommendable for future studies. In this regard, we suggest a shared nomenclature based on the predictive coding interpretation of deviance detection.

A Novel, Fast, Reliable, and Data-Driven Method for Simultaneous Single-Trial Mining and Amplitude-Latency Estimation Based on Proximity Graphs and Network Analysis

Both amplitude and latency of single-trial EEG/MEG recordings provide valuable information regarding functionality of the human brain. In this article, we provided a data-driven graph and network-based framework for mining information from multi-trial event-related brain recordings. In the first part, we provide the general outline of the proposed methodological approach. In the second part, we provide a more detailed illustration, and present the obtained results on every step of the algorithmic procedure. To justify the proposed framework instead of presenting the analytic data mining and graph-based steps, we address the problem of response variability, a prerequisite to reliable estimates for both the amplitude and latency on specific N/P components linked to the nature of the stimuli. The major question addressed in this study is the selection of representative single-trials with the aim of uncovering a less noisey averaged waveform elicited from the stimuli. This graph and network-based algorithmic procedure increases the signal-to-noise (SNR) of the brain response, a key pre-processing step to reveal significant and reliable amplitude and latency at a specific time after the onset of the stimulus and with the right polarity (N or P). We demonstrated the whole approach using electroencephalography (EEG) auditory mismatch negativity (MMN) recordings from 42 young healthy controls. The method is novel, fast and data-driven succeeding first to reveal the true waveform elicited by MMN on different conditions (frequency, intensity, duration, etc.). The proposed graph-oriented algorithmic pipeline increased the SNR of the characteristic waveforms and the reliability of amplitude and latency within the adopted cohort. We also demonstrated how different EEG reference schemes (REST vs. average) can influence amplitude-latency estimation. Simulation results revealed robust amplitude-latency estimations under different SNR and amplitude-latency variations with the proposed algorithm.

Early enhanced processing and delayed habituation to deviance sounds in autism spectrum disorder

Children with autism spectrum disorder (ASD) exhibit difficulties processing and encoding sensory information in daily life. Cognitive response to environmental change in control individuals is naturally dynamic, meaning it habituates or reduces over time as one becomes accustomed to the deviance. The origin of atypical response to deviance in ASD may relate to differences in this dynamic habituation. The current study of 133 children and young adults with and without ASD examined classic electrophysiological responses (MMN and P3a), as well as temporal patterns of habituation (i.e., N1 and P3a change over time) in response to a passive auditory oddball task. Individuals with ASD showed an overall heightened sensitivity to change as exhibited by greater P3a amplitude to novel sounds. Moreover, youth with ASD showed dynamic ERP differences, including slower attenuation of the N1 response to infrequent tones and the P3a response to novel sounds. Dynamic ERP responses were related to parent ratings of auditory sensory-seeking behaviors, but not general cognition. As the first large-scale study to characterize temporal dynamics of auditory ERPs in ASD, our results provide compelling evidence that heightened response to auditory deviance in ASD is largely driven by early sensitivity and prolonged processing of auditory deviance.

Decreased Event-Related Beta Synchronization During Memory Maintenance Marks Early Cognitive Decline in Mild Cognitive Impairment

Mild cognitive impairment (MCI) refers to a measurable deficit in cognition in the absence of dementia or impairment in activities of daily living. Working memory impairment is among the earliest signs of MCI. Oscillatory analysis of working memory might be a potential tool for identifying patients at increased risk of developing dementia. Our study aimed to assess the temporospatial pattern of spectral differences during working memory maintenance between MCI patients and healthy controls and to compare the sources of oscillatory activity between the two groups. Event-related spectral perturbation of 17 MCI patients and 21 healthy control participants was studied with 128-channel EEG during the Sternberg working memory task. Source localization was performed by using the eLORETA software. Among the participants, 13 MCI and 15 control participants underwent a structural brain MRI examination. Event-related synchronization (ERS) in the alpha and beta frequency band was significantly lower in MCI patients compared to healthy control participants during retention. Both study groups showed significant memory load-related enhancement in both frequency band. In the MCI group, source localization revealed significantly attenuated beta oscillatory activity in the inferior and middle temporal gyrus, in the fusiform gyrus, and in the cuneus. Beta ERS correlated significantly with the size of the hippocampus, entorhinal cortex, and parahippocampal gyrus. During the retention period, MCI is characterized by decreased alpha and beta ERS compared to controls indicating early impairment in neural networks serving working memory maintenance. The assessment of electrophysiological changes in the beta frequency range may provide a useful diagnostic tool for the early detection of cognitive impairment.

Auditory Memory Decay as Reflected by a New Mismatch Negativity Score Is Associated with Episodic Memory in Older Adults at Risk of Dementia

The auditory mismatch negativity (MMN) is an event-related potential (ERP) peaking about 100–250 ms after the onset of a deviant tone in a sequence of identical (standard) tones. Depending on the interstimulus interval (ISI) between standard and deviant tones, the MMN is suitable to investigate the pre-attentive auditory discrimination ability (short ISIs, ≤ 2 s) as well as the pre-attentive auditory memory trace (long ISIs, >2 s). However, current results regarding the MMN as an index for mild cognitive impairment (MCI) and dementia are mixed, especially after short ISIs: while the majority of studies report positive associations between the MMN and cognition, others fail to find such relationships. To elucidate these so far inconsistent results, we investigated the validity of the MMN as an index for cognitive impairment exploring the associations between different MMN indices and cognitive performance, more specifically with episodic memory performance which is among the most affected cognitive domains in the course of Alzheimer’s dementia (AD), at baseline and at a 5-year-follow-up. We assessed the amplitude of the MMN for short ISI (stimulus onset asynchrony, SOA = 0.05 s) and for long ISI (3 s) in a neuropsychologically well-characterized cohort of older adults at risk of dementia (subjective memory impairment, amnestic and non-amnestic MCI; n = 57). Furthermore, we created a novel difference score (ΔMMN), defined as the difference between MMNs to short and to long ISI, as a measure to assess the decay of the auditory memory trace, higher values indicating less decay. ΔMMN and MMN amplitude after long ISI, but not the MMN amplitude after short ISI, was associated with episodic memory at baseline (β = 0.38, p = 0.003; β = −0.27, p = 0.047, respectively). ΔMMN, but not the MMN for long ISIs, was positively associated with episodic memory performance at the 5-year-follow-up (β = 0.57, p = 0.013). The results suggest that the MMN after long ISI might be suitable as an indicator for the decline in episodic memory and indicate ΔMMN as a potential biomarker for memory impairment in older adults at risk of dementia.