Theta oscillations are affected by amnestic mild cognitive impairment and cognitive load

Mild Cognitive Impairment in African Americans Is Associated with Differences in EEG Theta/Beta Ratio

BACKGROUND

Identification of older individuals with increased risk for cognitive decline can contribute not only to personal benefits (e.g., early treatment, evaluation of treatment), but could also benefit clinical trials (e.g., patient selection). We propose that baseline resting-state electroencephalography (rsEEG) could provide markers for early identification of cognitive decline.

OBJECTIVE

To determine whether rsEEG theta/beta ratio (TBR) differed between mild cognitively impaired (MCI) and healthy older adults.

METHODS

We analyzed rsEEG from a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling older African Americans (58 cognitively typical and 41 MCI). Eyes closed rsEEGs were acquired before and after participants engaged in a visual motion direction discrimination task. rsEEG TBR was calculated for four midline locations and assessed for differences as a function of MCI status. Hemispheric asymmetry of TBR was also analyzed at equidistant lateral electrode sites.

RESULTS

Results showed that MCI participants had a higher TBR than controls (p = 0.04), and that TBR significantly differed across vertex location (p < 0.001) with the highest TBR at parietal site. MCI and cognitively normal controls also differed in hemispheric asymmetries, such that MCI show higher TBR at frontal sites, with TBR greater over right frontal electrodes in the MCI group (p = 0.003) and no asymmetries found in the cognitively normal group. Lastly, we found a significant task aftereffect (post-task compared to pre-task measures) with higher TBR at posterior locations (Oz p = 0.002, Pz p = 0.057).

CONCLUSION

TBR and TBR asymmetries differ between MCI and cognitively normal older adults and may reflect neurodegenerative processes underlying MCI symptoms.

EEG asymmetry and cognitive testing in MCI identification

BACKGROUND

Finding the baseline resting-state EEG markers for early identification of cognitive decline can contribute to the identification of individuals at risk of further change. Potential applications include identifying participants for clinical trials, early treatment, and evaluation of treatment, accessible even from a community setting.

METHODS

Analyses were completed on a sample of 99 (ages 60-90) consensus-diagnosed, community-dwelling African Americans (58 cognitively typical/HC, and 41 mildly cognitively impaired/MCI), who were recruited from the Michigan Alzheimer's Disease Research Center (MADRC) and the Wayne State University Institute of Gerontology. In addition to neuropsychological testing with CogState and Toolbox computerized batteries, resting-state EEGs (rsEEG, eyes closed) were acquired before and after participants were engaged in a visual motion direction discrimination task. rsEEG frontal alpha asymmetry (FAA) and frontal beta asymmetry (FBA) were calculated.

RESULTS

FAA showed no difference across groups for the pre-task resting state. FBA was significantly different between groups, with more asymmetric frontal beta in MCI. Both physiological indices, however, along with computerized neuropsychological tests were significant predictors in logistic regression classification of MCI vs. control participants.

CONCLUSION

rsEEG asymmetries can contribute significantly to successful discrimination of older persons with MCI from those without, over and above cognitive testing, alone.

Treatment effects on event-related EEG potentials and oscillations in Alzheimer's disease

Alzheimer's disease dementia (ADD) is the most diffuse neurodegenerative disorder belonging to mild cognitive impairment (MCI) and dementia in old persons. This disease is provoked by an abnormal accumulation of amyloid-beta and tauopathy proteins in the brain. Very recently, the first disease-modifying drug has been licensed with reserve (i.e., Aducanumab). Therefore, there is a need to identify and use biomarkers probing the neurophysiological underpinnings of human cognitive functions to test the clinical efficacy of that drug. In this regard, event-related electroencephalographic potentials (ERPs) and oscillations (EROs) are promising candidates. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association and Global Brain Consortium reviewed the field literature on the effects of the most used symptomatic drug against ADD (i.e., Acetylcholinesterase inhibitors) on ERPs and EROs in ADD patients with MCI and dementia at the group level. The most convincing results were found in ADD patients. In those patients, Acetylcholinesterase inhibitors partially normalized ERP P300 peak latency and amplitude in oddball paradigms using visual stimuli. In these same paradigms, those drugs partially normalize ERO phase-locking at the theta band (4-7 Hz) and spectral coherence between electrode pairs at the gamma (around 40 Hz) band. These results are of great interest and may motivate multicentric, double-blind, randomized, and placebo-controlled clinical trials in MCI and ADD patients for final cross-validation.

Disrupted Value-Directed Strategic Processing in Individuals with Mild Cognitive Impairment: Behavioral and Neural Correlates

Value-directed strategic processing involves attending to higher-value information while inhibiting lower-value information. This preferential processing is relatively preserved in cognitively normal older adults but is impaired in individuals with dementia. No studies have investigated whether value-directed strategic processing is disrupted in earlier stages of cognitive decline, namely, mild cognitive impairment (MCI). The current study examined behavioral and EEG differences in value-directed strategic processing between 18 individuals with MCI and 18 cognitively normal older controls using a value-directed list learning task. Behaviorally, individuals with MCI recalled fewer total and high-value words compared to controls, but no group differences were observed in low-value word recall. Neurally, individuals with MCI had reduced theta synchronization relative to controls between 100 and 200 ms post-stimulus. Greater alpha desynchronization was observed for high- versus low-value words between 300 and 400 ms in controls but not in the MCI group. The groups showed some processing similarities, with greater theta synchronization for low-value words between 700 and 800 ms and greater alpha desynchronization for high-value words between 500 and 1100 ms. Overall, value-directed strategic processing was compromised in individuals with MCI on both behavioral and neural measures relative to controls. These findings add to the growing body of literature on differences between typical cognitive aging and MCI.

Are there consistent abnormalities in event-related EEG oscillations in patients with Alzheimer's disease compared to other diseases belonging to dementia?

Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer's disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer's, Parkinson's (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4-7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8-12 Hz) and beta (13-30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias.

Theta and gamma oscillatory dynamics in mouse models of Alzheimer's disease: A path to prospective therapeutic intervention

Understanding the neural basis of cognitive deficits, a key feature of Alzheimer's disease (AD), is imperative for achieving the therapy of the disease. Rhythmic oscillatory activities in neural systems are a fundamental mechanism for diverse brain functions, including cognition. In several neurological conditions like AD, aberrant neural oscillations have been shown to play a central role. Furthermore, manipulation of brain oscillations in animals has confirmed their impact on cognition and disease. In this article, we review the evidence from mouse models that shows how synchronized oscillatory activity is intricately linked to AD machinery. We primarily focus on recent reports showing abnormal oscillatory activities at theta and gamma frequencies in AD condition and their influence on cellular disturbances and cognitive impairments. A thorough comprehension of the role that neuronal oscillations play in AD pathology should pave the way to therapeutic interventions that can curb the disease.

Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals

The oscillatory patterns of electroencephalography (EEG), during resting states, are informative and helpful in understanding the functional states of brain network and their contribution to behavioral performances. The aim of this study is to characterize the functional brain network alterations in patients with amnestic mild cognitive impairment (aMCI). To this end, rsEEG signals were recorded before and after a cognitive task. Functional connectivity metrics were calculated using debiased weighted phase lag index (DWPLI). Topological features of the functional connectivity network were analyzed using both the classical graph approach and minimum spanning tree (MST) algorithm. Subsequently, the network and connectivity values together with Mini-Mental State Examination cognitive test were used as features to classify the participants. Results showed that: (1) across the pre-task condition, in the theta band, the aMCI group had a significantly lower global mean DWPLI than the control group; the functional connectivity patterns were different in the left hemisphere between two groups; the aMCI group showed significantly higher average clustering coefficient and the remarkably lower global efficiency than the control. (2) Analysis of graph measures under post-task resting state, unveiled that for the percentage change of post-task vs. pre-task in beta EEG, a significant increase in tree hierarchy was observed in aMCI group (2.41%) than in normal control (-3.89%); (3) Furthermore, the classification analysis of combined measures of functional connectivity, brain topology, and MMSE test showed improved accuracy compared to the single method, for which the connectivity patterns and graph metrics were used as separate inputs. The classification accuracy obtained for the case of post-task resting state was 87.2%, while the one achieved under pre-task resting state was found to be 77.7%. Therefore, the functional network alterations in aMCI patients were more prominent during the post-task resting state. This study suggests that the disintegration observed in MCI functional network during the resting states, preceding and following a task, might be possible biomarkers of cognitive dysfunction in aMCI patients.

Mild Cognitive Impairment and Neurofeedback: A Randomized Controlled Trial

Background and Objectives: Mild cognitive impairment (MCI) is often a precursor of dementia, and in particular of Alzheimer's Disease (AD) which is the most common cause of dementia. Individuals with amnestic MCI are several-fold more likely to develop AD than the general population. Therefore, MCI comprises a well-detectable, early stage time-point for therapeutic intervention and strategic prevention. Based on common electroencephalographical (EEG) pattern changes seen in individuals with MCI, we postulated that EEG-based neurofeedback could help improve the memory performance of patients with MCI. Memory performance is of particular importance in these patients, since memory decline is the most prominent symptom in most patients with MCI, and is the most predictive symptom for cognitive deterioration and the development of AD.

Methods: In order to improve the memory performance of patients with MCI we used a system of EEG-based neurofeedback in an attempt to reverse alterations of the EEG that are known to be common in patients with MCI. Our protocol comprised the provision of positive feedback in order to enhance the activity level of the upper alpha band. Participants were divided to two groups receiving either neurofeedback training to enhance the upper alpha frequency (Experimental group) or random feedbacks (Sham group)

Results: We witnessed a significant improvement in memory performance in subjects in the experimental group compared to those in the sham group. This improvement was maintained for at least 1 month.

Conclusions: Neurofeedback may be a promising and affordable novel approach for treating the decline in memory witnessed in patients with MCI.

Increased Relative Delta Bandpower and Delta Indices Revealed by Continuous qEEG Monitoring in a Rat Model of Ischemia-Reperfusion

The present study describes the electroencephalographic changes that occur during cerebral ischemia and reperfusion in animals submitted to transient focal cerebral ischemia by middle cerebral artery occlusion (MCAO) for 30 min. For this, male Wistar rats were divided into two groups (n = 6 animals/group): (1) sham (control) group, and (2) ischemic/reperfusion group. The quantitative electroencephalography (qEEG) was recorded during the ischemic and immediate reperfusion (acute) phases, and then once a day for 7 days after the MCAO (subacute phase). The acute phase was characterized by a marked increase in the relative delta wave band power (p < 0.001), with a smaller, but significant increase in the relative alpha wave bandpower in the ischemic stroke phase, in comparison with the control group (p = 0.0054). In the immediate reperfusion phase, however, there was an increase in the theta, alpha, and beta waves bandpower (p < 0.001), but no alteration in the delta waves (p = 0.9984), in comparison with the control group. We also observed high values in the delta/theta ratio (DTR), the delta/alpha ratio (DAR), and the (delta+theta)/(alpha+beta) ratio (DTABR) indices during the ischemia (p < 0.05), with a major reduction in the reperfusion phase. In the subacute phase, the activity of all the waves was lower than that of the control group (p < 0.05), although the DTR, DAR, and DTABR indices remained relatively high. In conclusion, early and accurate identification of decreased delta wave bandpower, DTR, DAR, and DTABR indices, and an increase in the activity of other waves in the immediate reperfusion phase may represent an important advance for the recognition of the effectiveness of reperfusion therapy.

Virtual reality alters cortical oscillations related to visuo-tactile integration during rubber hand illusion

Virtual reality (VR) enables the fast, free, and highly controllable setting of experimental body images. Illusions pertaining to a body, such as the rubber hand illusion (RHI), can be easily conducted in VR settings, and some phenomena, such as full-body illusions, are only realized in virtual environments. However, the multisensory-integration process in VR is not yet fully understood. Thus, it remains to be clarified if specific phenomena that occur under VR settings manifest in real life as well. One useful investigative approach is measuring brain activities during a psychological experiment. Electroencephalography (EEG) oscillatory activities provide insight into the human multisensory integration process. Nevertheless, EEG data can be vulnerable to VR noise, which causes measurement and analytical difficulties for EEG data recorded in VR environments. Here, we achieve an experimental RHI setting using a head-mounted display that provides a VR visual space and VR dummy hand along with EEG measurements. We compared EEG data collected in both real and VR environments and observed the gamma and theta band oscillatory activities. Ultimately, we observed statistically significant differences between congruent (RHI) and incongruent (not RHI) conditions in the real environment, which is consistent with previous studies. Differences in the VR condition were observed only on the late theta band oscillation, suggesting that the VR setting itself altered the perceptual and sensory integration mechanisms. Thus, we must model this difference between real and VR settings whenever we use VR to investigate our bodily self-perception.

Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis

Background:

Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS). Though several studies measured alpha power and synchronization in MCI, findings have not yet been integrated.

Objective:

To consolidate findings on power and synchronization of alpha oscillations across stages of cognitive decline.

Methods:

We included studies published until January 2020 that compared power or functional connectivity between 1) people with MCI and cognitively healthy older adults (OA) or people with a neurodegenerative dementia, and 2) people with progressive and stable MCI. Random-effects meta-analyses were performed when enough data was available.

Results:

Sixty-eight studies were included in the review. Global RS alpha power was lower in AD than in MCI (ES = –0.30; 95% CI = –0.51, –0.10; k = 6), and in MCI than in OA (ES = –1.49; 95% CI = –2.69, –0.29; k = 5). However, the latter meta-analysis should be interpreted cautiously due to high heterogeneity. The review showed lower RS alpha power in progressive than in stable MCI, and lower task-related alpha reactivity in MCI than in OA. People with MCI had both lower and higher functional connectivity than OA. Publications lacked consistency in MCI diagnosis and EEG measures.

Conclusion:

Research indicates that RS alpha power decreases with increasing impairment, and could—combined with measures from other frequency bands—become a biomarker of early cognitive decline.

Electroencephalographic prediction of global and domain specific cognitive performance of clinically active Australian Nurses

OBJECTIVE

To investigate the relationship between EEG activity and the global and domain specific cognitive performance of healthy nurses, and determine the predictive capabilities of these relationships.

APPROACH

Sixty-four nurses were recruited for the present study, and data from 61 were utilised in the present analysis. Global and domain specific cognitive performance of each participant was assessed psychometrically using the Mini-mental state exam and the Cognistat, and a 32-lead monopolar EEG was recorded during a resting baseline phase and an active phase in which participants completed the Stroop test.

MAIN RESULTS

Global cognitive performance was successfully predicted (81%-85% of variance) by a combination of fast wave activity variables in the alpha, beta and theta frequency bands. Interestingly, predicting domain specific performance had varying degrees of success (42%-99% of the variance predicted) and relied on combinations of both slow and fast wave activity, with delta and gamma activity predicting attention performance; delta, theta, and gamma activity predicting memory performance; and delta and beta variables predicting judgement performance.

SIGNIFICANCE

Global and domain specific cognitive performance of Australian nurses may be predicted with varying degrees of success by a unique combination of EEG variables. These proposed models image transitory cognitive declines and as such may prove useful in the prediction of early cognitive impairment, and may enable better diagnosis, and management of cognitive impairment.

Functional Alterations in the Olfactory Neuronal Circuit Occur before Hippocampal Plasticity Deficits in the P301S Mouse Model of Tauopathy: Implications for Early Diagnosis and Translational Research in Alzheimer's Disease

Alzheimer's disease (AD) is characterized by neuronal loss and impaired synaptic transmission, ultimately leading to cognitive deficits. Early in the disease, the olfactory track seems most sensitive to tauopathy, while most plasticity studies focused on the hippocampal circuits. Functional network connectivity (FC) and long-term potentiation (LTP), considered as the plasticity substrate of learning and memory, were longitudinally assessed in mice of the P301S model of tauopathy following the course (time and location) of progressively neurodegenerative pathology (i.e., at 3, 6, and 9 months of age) and in their wild type (WT) littermates. Using in vivo local field potential (LFP) recordings, early (at three months) dampening in the gamma oscillatory activity and impairments in the phase-amplitude theta-gamma coupling (PAC) were found in the olfactory bulb (OB) circuit of P301S mice, which were maintained through the whole course of pathology development. In contrast, LFP oscillatory activity and PAC indices were normal in the entorhinal cortex, hippocampal CA1 and CA3 nuclei. Field excitatory postsynaptic potential (fEPSP) recordings from the Shaffer collateral (SC)-CA1 hippocampal stratum pyramidal revealed a significant altered synaptic LTP response to high-frequency stimulation (HFS): at three months of age, no significant difference between genotypes was found in basal synaptic activity, while signs of a deficit in short term plasticity were revealed by alterations in the fEPSPs. At six months of age, a slight deviance was found in basal synaptic activity and significant differences were observed in the LTP response. The alterations in network oscillations at the OB level and impairments in the functioning of the SC-CA1 pyramidal synapses strongly suggest that the progression of tau pathology elicited a brain area, activity-dependent disturbance in functional synaptic transmission. These findings point to early major alterations of neuronal activity in the OB circuit prior to the disturbance of hippocampal synaptic plasticity, possibly involving tauopathy in the anomalous FC. Further research should determine whether those early deficits in the OB network oscillations and FC are possible mechanisms that potentially promote the emergence of hippocampal synaptic impairments during the progression of tauopathy.

Early-stage dysfunction of hippocampal theta and gamma oscillations and its modulation of neural network in a transgenic 5xFAD mouse model

Alzheimer's disease (AD) is pathologically characterized by amyloid-β (Aβ) accumulation, which induces Aβ-dependent neuronal dysfunctions. We focused on the early-stage disease progression and examined the neuronal network functioning in the 5xFAD mice. The simultaneous intracranial recordings were obtained from the hippocampal perforant path (PP) and the dentate gyrus (DG). Concomitant to Aβ accumulation, theta power was strongly attenuated in the PP and DG regions of 5xFAD mice compared to those in nontransgenic littermates. For either theta rhythm or gamma oscillation, the phase synchronization on the PP-DG pathway was impaired, evidenced by decreased phase locking value and diminished coherency index. To alleviate the neural oscillatory deficits in early-stage AD, a neural modulation approach (rTMS) was used to activate gamma oscillations and strengthen the synchronicity of neuronal activity on the PP-DG pathway. In brief, there was a significant neuronal network dysfunction at an early-stage AD-like pathology, which preceded the onset of cognitive deficits and was likely driven by Aβ accumulation, suggesting that the neural oscillation analysis played an important role in early AD diagnosis.

Abnormalities in auditory and visual cognitive processes are differentiated with theta responses in patients with Parkinson's disease with and without dementia

The research on the abnormalities of event-related oscillations in Parkinson's disease (PD) was mostly studied with cognitively normal patients. The present study aims to show the adverse effects of cognitive decline in PD patients via the EEG-Brain Oscillations approach by comparing the electrophysiological responses in two modalities, i.e. auditory, and visual in which PD group show deficit. We conducted a study in which we analyzed event-related theta power and phase-locking during auditory and visual oddball paradigm. Cognitively normal PD (PDCN) patients (N = 15), PD with mild cognitive impairment (PDMCI) patients (N = 22), PD dementia (PDD) patients (N = 11) and healthy controls (HC) (N = 17) were included in the study. Neuropsychological assessments were applied to all participants. There was a gradual decrease in scores of neuropsychological tests (HC, PDCN, PDMCI, PDD, respectively). Most of the neuropsychological test scores of the participants were highly correlated with the theta power and theta phase locking values, especially over frontal-central areas. HC had higher theta phase-locking and power in comparison to PDMCI and PDD. The differentiation between HC and PDCN was specific to frontal-central areas. Theta power and theta phase-locking were decreased overall locations in PDMCI and PDD both during visual and auditory oddball paradigms compared with PDCN. The results indicate that theta responses in PD patients decreased gradually as the cognitive decline increased. We can conclude that complex abnormalities in their neurotransmitter and neuronal signal systems that occur with the progression of the disease could be responsible for these results.

Neurofeedback Improves Memory and Peak Alpha Frequency in Individuals with Mild Cognitive Impairment

Mild cognitive impairment (MCI) is a syndrome characterized by a decrease in cognitive abilities, while daily function is maintained. This condition, which is associated with an increased risk for the development of Alzheimer's disease, has no known definitive treatment at present. In this open-label pilot study we explored the possible benefits of neurofeedback for subjects with MCI. Eleven participants diagnosed with MCI were trained to increase the power of their individual upper alpha band of the electroencephalogram (EEG) signal over the central parietal region. This was achieved using an EEG-based neurofeedback training protocol. Training comprised ten 30-min sessions delivered over 5 weeks. Cognitive and electroencephalographic assessments were conducted before and after training and at 30 days following the last training session. A dose-dependent increase in peak alpha frequency was observed throughout the period of training. Memory performance also improved significantly following training, and this improvement was maintained at 30-day follow-up, while peak alpha frequency returned to baseline at this evaluation. Our findings suggest that neurofeedback may improve memory performance in subjects with mild cognitive impairment, and this benefit may be maintained beyond the training period.

Spatiotemporal Oscillatory Patterns During Working Memory Maintenance in Mild Cognitive Impairment and Subjective Cognitive Decline

Working memory (WM) is a crucial cognitive process and its disruption is among the earliest symptoms of Alzheimer’s disease. While alterations of the neuronal processes underlying WM have been evidenced in mild cognitive impairment (MCI), scarce literature is available in subjective cognitive decline (SCD). We used magnetoencephalography during a WM task performed by MCI [Formula: see text], SCD [Formula: see text] and healthy elders [Formula: see text] to examine group differences during the maintenance period (0–4000[Formula: see text]ms). Data were analyzed using time–frequency analysis and significant oscillatory differences were localized at the source level. Our results indicated significant differences between groups, mainly during the early maintenance (250–1250[Formula: see text]ms) in the theta, alpha and beta bands and in the late maintenance (2750–3750[Formula: see text]ms) in the theta band. MCI showed lower local synchronization in fronto-temporal cortical regions in the early theta–alpha window relative to controls [Formula: see text] and SCD [Formula: see text], and in the late theta window relative to controls [Formula: see text] and SCD [Formula: see text]. Early theta–alpha power was significantly correlated with memory scores [Formula: see text] and late theta power was correlated with task performance [Formula: see text] and functional activity scores [Formula: see text]. In the early beta window, MCI showed reduced power in temporo-posterior regions relative to controls [Formula: see text] and SCD [Formula: see text]. Our results may suggest that these alterations would reflect that memory-related networks are damaged.

Single amyloid-beta injection exacerbates 4-aminopyridine-induced seizures and changes synaptic coupling in the hippocampus

Accumulation of amyloid-beta (Aβ) in temporal lobe structures, including the hippocampus, is related to a variety of Alzheimer's disease symptoms and seems to be involved in the induction of neural network hyperexcitability and even seizures. Still, a direct evaluation of the pro-epileptogenic effects of Aβ in vivo, and of the underlying mechanisms, is missing. Thus, we tested whether the intracisternal injection of Aβ modulates 4-aminopyridine (4AP)-induced epileptiform activity, hippocampal network function, and its synaptic coupling. When tested 3 weeks after its administration, Aβ (but not its vehicle) reduces the latency for 4AP-induced seizures, increases the number of generalized seizures, exacerbates the time to fully recover from seizures, and favors seizure-induced death. These pro-epileptogenic effects of Aβ correlate with a reduction in the power of the spontaneous hippocampal network activity, involving all frequency bands in vivo and only the theta band (4-10 Hz) in vitro. The pro-epileptogenic effects of Aβ also correlate with a reduction of the Schaffer-collateral CA1 synaptic coupling in vitro, which is exacerbated by the sequential bath application of 4-AP and Aβ. In summary, Aβ produces long-lasting pro-epileptic effects that can be due to alterations in the hippocampal circuit, impacting its coordinated network activity and its synaptic efficiency. It is likely that normalizing synaptic coupling and/or coordinated neural network activity (i.e., theta activity) may contribute not only to improve cognitive function in Alzheimer's disease but also to avoid hyperexcitation in conditions of amyloidosis.

Electroencephalography as a predictor of self-report fatigue/sleepiness during monotonous driving in train drivers

OBJECTIVE

In this study, electroencephalography activity recorded during monotonous driving was investigated to examine the predictive capability of monopolar EEG analysis for fatigue/sleepiness in a cohort of train drivers.

APPROACH

Sixty-three train drivers participated in the study, where 32- lead monopolar EEG data was recorded during a monotonous driving task. Participant sleepiness was assessed using the Pittsburgh sleep quality index (PSQI), the Epworth sleepiness scale (ESS), the Karolinksa sleepiness scale (KSS) and the checklist of individual strength 20 (CIS20).

MAIN RESULTS

Self-reported fatigue/sleepiness scores of the train driver cohort were primarily associated with EEG delta, theta, and alpha variables; however, some beta and gamma associations were also implicated. Furthermore, general linear models informed by these EEG variables were able to predict self-reported scores with varying degrees of success, representing between 48% and 54% of variance in fatigue scores.

SIGNIFICANCE

Self-reported fatigue/sleepiness scores of train drivers were predicted with varying degrees of success (dependent upon the self-reported fatigue/sleepiness measure) by alterations to monopolar delta, theta, and alpha band activity variables, indicating EEG as a potential indicator for fatigue/sleepiness in train drivers.

Early diagnosis of mild cognitive impairment and Alzheimer's with event-related potentials and event-related desynchronization in N-back working memory tasks

BACKGROUND AND OBJECTIVE

In this study we investigate whether or not event-related potentials (ERP) and/or event-related (de)synchronization (ERD/ERS) can be used to differentiate between 27 healthy elderly (HE), 21 subjects diagnosed with mild cognitive impairment (MCI) and 15 mild Alzheimer's disease (AD) patients.

METHODS

Using 32-channel EEG recordings, we measured ERP responses to a three-level (N-back, N = 0,1,2) visual working memory task. We also performed ERD analysis over the same EEG data, dividing the full-band signal into the well-known delta, theta, alpha, beta and gamma bands. Both ERP and ERD analyses were followed by cluster analysis with correction for multicomparisons whenever significant differences were found between groups.

RESULTS

Regarding ERP (full-band analysis), our findings have shown both patient groups (MCI and AD) with reduced P450 amplitude (compared to HE controls) in the execution of the non-match 1-back task at many scalp electrodes, chiefly at parietal and centro-parietal areas. However, no significant differences were found between MCI and AD in ERP analysis whatever was the task. As for sub-band analyses, ERD/ERS measures revealed that HE subjects elicited consistently greater alpha ERD responses than MCI and AD patients during the 1-back task in the match condition, with all differences located at frontal, central and occipital regions. Moreover, in the non-match condition, it was possible to distinguish between MCI and AD patients when they were performing the 0-back task, with MCI presenting more desynchronization than AD on the theta band at temporal and fronto-temporal areas. In summary, ERD analyses have revealed themselves more valuable than ERP, since they showed significant differences in all three group comparisons: HE vs. MCI, HE vs. AD, and MCI vs. AD.

CONCLUSIONS

Based on these findings, we conclude that ERD responses to working memory (N-back) tasks could be useful not only for early MCI diagnosis or for improved AD diagnosis, but probably also for assessing the likelihood of MCI progression to AD, after further validated by a longitudinal study.

The Relationship of Cognitive Performance and the Theta-Alpha Power Ratio Is Age-Dependent: An EEG Study of Short Term Memory and Reasoning during Task and Resting-State in Healthy Young and Old Adults

Objective: The Theta-Alpha ratio (TAR) is known to differ based upon age and cognitive ability, with pathological electroencephalography (EEG) patterns routinely found within neurodegenerative disorders of older adults. We hypothesized that cognitive ability would predict EEG metrics differently within healthy young and old adults, and that healthy old adults not showing age-expected EEG activity may be more likely to demonstrate cognitive deficits relative to old adults showing these expected changes. Methods: In 216 EEG blocks collected in 16 young and 20 old adults during rest (eyes open, eyes closed) and cognitive tasks (short-term memory [STM]; matrix reasoning [RM; Raven's matrices]), models assessed the contributing roles of cognitive ability, age, and task in predicting the TAR. A general linear mixed-effects regression model was used to model this relationship, including interaction effects to test whether increased cognitive ability predicted TAR differently for young and old adults at rest and during cognitive tasks. Results: The relationship between cognitive ability and the TAR across all blocks showed age-dependency, and cognitive performance at the CZ midline location predicted the TAR measure when accounting for the effect of age (p < 0.05, chi-square test of nested models). Age significantly interacted with STM performance in predicting the TAR (p < 0.05); increases in STM were associated with increased TAR in young adults, but not in old adults. RM showed similar interaction effects with aging and TAR (p < 0.10). Conclusion: EEG correlates of cognitive ability are age-dependent. Adults who did not show age-related EEG changes were more likely to exhibit cognitive deficits than those who showed age-related changes. This suggests that healthy aging should produce moderate changes in Alpha and TAR measures, and the absence of such changes signals impaired cognitive functioning.

Emergence of early alterations in network oscillations and functional connectivity in a tau seeding mouse model of Alzheimer's disease pathology

Synaptic dysfunction and disconnectivity are core deficits in Alzheimer’s disease (AD), preceding clear changes in histopathology and cognitive functioning. Here, the early and late effects of tau pathology induction on functional network connectivity were investigated in P301L mice. Multichannel EEG oscillations were used to compute (1) coherent activity between the prefrontal cortex (PFC) and hippocampus (HPC) CA1-CA3 networks; (2) phase-amplitude cross frequency coupling (PAC) between theta and gamma oscillations, which is instrumental in adequate cognitive functioning; (3) information processing as assessed by auditory evoked potentials and oscillations in the passive oddball mismatch negativity-like (MMN) paradigm. At the end, the density of tau aggregation and GABA parvalbumin (PV+) interneurons were quantified by immunohistochemistry. Early weakening of EEG theta oscillations and coherent activity were revealed between the PFC and HPC CA1 and drastic impairments in theta–gamma oscillations PAC from week 2 onwards, while PV+ interneurons count was not altered. Moreover, the tau pathology disrupted the MMN complex amplitude and evoked gamma oscillations to standard and deviant stimuli suggesting altered memory formation and recall. The induction of intracellular tau aggregation by tau seed injection results in early altered connectivity and strong theta–gamma oscillations uncoupling, which may be exploited as an early electrophysiological signature of dysfunctional neuronal networks.

Acute single channel EEG predictors of cognitive function after stroke

BACKGROUND

Early and accurate identification of factors that predict post-stroke cognitive outcome is important to set realistic targets for rehabilitation and to guide patients and their families accordingly. However, behavioral measures of cognition are difficult to obtain in the acute phase of recovery due to clinical factors (e.g. fatigue) and functional barriers (e.g. language deficits). The aim of the current study was to test whether single channel wireless EEG data obtained acutely following stroke could predict longer-term cognitive function.

METHODS

Resting state Relative Power (RP) of delta, theta, alpha, beta, delta/alpha ratio (DAR), and delta/theta ratio (DTR) were obtained from a single electrode over FP1 in 24 participants within 72 hours of a first-ever stroke. The Montreal Cognitive Assessment (MoCA) was administered at 90-days post-stroke. Correlation and regression analyses were completed to identify relationships between 90-day cognitive function and electrophysiological data, neurological status, and demographic characteristics at admission.

RESULTS

Four acute qEEG indices demonstrated moderate to high correlations with 90-day MoCA scores: DTR (r = -0.57, p = 0.01), RP theta (r = 0.50, p = 0.01), RP delta (r = -0.47, p = 0.02), and DAR (r = -0.45, p = 0.03). Acute DTR (b = -0.36, p < 0.05) and stroke severity on admission (b = -0.63, p < 0.01) were the best linear combination of predictors of MoCA scores 90-days post-stroke, accounting for 75% of variance.

CONCLUSIONS

Data generated by a single pre-frontal electrode support the prognostic value of acute DAR, and identify DTR as a potential marker of post-stroke cognitive outcome. Use of single channel recording in an acute clinical setting may provide an efficient and valid predictor of cognitive function after stroke.

Cognitive workload across the spectrum of cognitive impairments: A systematic review of physiological measures

Our objective was to identify the physiological measures that are sensitive to assessing cognitive workload across the spectrum of cognitive impairments. Three database searches were conducted: PubMed, PsychINFO, and Web of Science. Studies from the last decade that used physiological measures of cognitive workload in older adults (mean age >65 years-old) were reviewed. The cognitive workload of healthy older individuals was compared with the cognitive workload of younger adults, patients with mild cognitive impairment (MCI), and patients with Alzheimer's diseases (AD). The most common measures of cognitive workload included: electroencephalography, magnetoencephalography, functional magnetic resonance imaging, pupillometry, and heart rate variability. These physiological measures consistently showed greater cognitive workload in healthy older adults compared to younger adults when performing the same task. The same was observed in patients with MCI compared to healthy older adults. Behavioral performance declined when the available cognitive resources became insufficient to cope with the cognitive demands of a task, such as in AD. These findings may have implications for clinical practice and future cognitive interventions.

Increased long distance event-related gamma band connectivity in Alzheimer's disease

BACKGROUND

Brain oscillatory responses can be used for non-invasive analyses of cortico-cortical connectivity, local neuronal synchronization, and coherence of oscillations in many neuropsychiatric conditions including Alzheimer's disease (AD). In the present paper, we examine sensory-evoked and event-related gamma coherences elicited by visual stimuli in three sub-gamma bands in two sub-groups of patients with AD (i.e., acetylcholinesterase-inhibitor treated and untreated) and healthy controls.

METHODS

We studied a total of 39 patients with probable mild AD (according to NINCDS-ADRDA criteria) who had been sub-divided into untreated (n = 21) and treated (n = 18) (patients either on cholinergic monotherapy or combined therapy with memantine) AD groups, and 21 age-, gender-, and education-matched healthy elderly controls. A simple flash visual paradigm was applied for the acquisition of sensory-evoked coherences. Event-related coherences were elicited using a classical visual oddball paradigm. Both sensory-evoked and event-related gamma coherences were calculated for long-distance intrahemispheric pairs for three frequency ranges: 25-30 Hz, 30-35 Hz, and 40-48 Hz in post-stimulus 0-800 ms duration. The long-distance intrahemispheric pairs from both sides were fronto-parietal, fronto-temporal, fronto-temporoparietal, fronto-occipital, centro-occipital and parieto-occipital.

RESULTS

The sensory-evoked or event-related gamma coherences revealed that both treated and untreated AD patients had significantly increased values compared to healthy controls in all three sub-gamma bands. Moreover, the treated AD patients demonstrated significantly higher fronto-parietal gamma coherences during both sensory stimulation and oddball paradigm and lower occipito-parietal coherences during oddball paradigm in comparison to untreated AD patients.

CONCLUSION

The present study demonstrated that an increase of gamma coherences was present in response to both visual sensory and cognitive stimulation in AD patients in all gamma sub-bands. Therefore, gamma oscillatory activity seems to be fundamental in brain functions at both the sensory and cognitive levels. The increase of gamma coherence values was not due to cholinergic treatment to any significant extent, as both treated and untreated AD patients had increased gamma coherence values compared to healthy controls. The use of coherence values reflecting brain connectivity holds potential for neuroimaging of AD and understanding brain dynamics related to the effects of medication.

Gender-Specific Hippocampal Dysrhythmia and Aberrant Hippocampal and Cortical Excitability in the APPswePS1dE9 Model of Alzheimer's Disease

Alzheimer's disease (AD) is a multifactorial disorder leading to progressive memory loss and eventually death. In this study an APPswePS1dE9 AD mouse model has been analyzed using implantable video-EEG radiotelemetry to perform long-term EEG recordings from the primary motor cortex M1 and the hippocampal CA1 region in both genders. Besides motor activity, EEG recordings were analyzed for electroencephalographic seizure activity and frequency characteristics using a Fast Fourier Transformation (FFT) based approach. Automatic seizure detection revealed severe electroencephalographic seizure activity in both M1 and CA1 deflection in APPswePS1dE9 mice with gender-specific characteristics. Frequency analysis of both surface and deep EEG recordings elicited complex age, gender, and activity dependent alterations in the theta and gamma range. Females displayed an antithetic decrease in theta (θ) and increase in gamma (γ) power at 18-19 weeks of age whereas related changes in males occurred earlier at 14 weeks of age. In females, theta (θ) and gamma (γ) power alterations predominated in the inactive state suggesting a reduction in atropine-sensitive type II theta in APPswePS1dE9 animals. Gender-specific central dysrhythmia and network alterations in APPswePS1dE9 point to a functional role in behavioral and cognitive deficits and might serve as early biomarkers for AD in the future.

Electroencephalogram associations to cognitive performance in clinically active nurses

Cognitive impairment is traditionally identified via cognitive screening tools that have limited ability in detecting early or transitional stages of impairment. The dynamic nature of physiological variables such as the electroencephalogram (EEG) may provide alternate means for detecting these transitions. However, previous research examining EEG and cognitive performance is largely confined to samples with diagnosed cognitive impairments, and research examining non-impaired, and occupation specific samples, is limited. The present study aimed to investigate the associations between frontal pole and central EEG and cognitive performance in a sample of male and female nurses, and to determine the significance of these associations. Fifty seven nurses participated in the study, in which two lead bipolar EEG was recorded at positions Fp1 (frontal polar), Fp2, C3 (central) and C4 during a baseline and an active phase involving the common neuropsychological Stroop test. Participants' cognitive performance was assessed using the mini-mental state exam (MMSE) and Cognistat screening tools. Significant correlations between EEG beta activity and the outcome of MMSE and Cognistat were revealed, where an increased beta activity was associated to an increased global cognitive performance. Additionally, domain specific cognitive performance was also significantly associated to various EEG variables. The study identified potential EEG biomarkers for global and domain specific cognitive performance, and provides initial groundwork for the development of future EEG based biomarkers for detection of cognitive pathologies.

Defining abnormal slow EEG activity in acute ischaemic stroke: Delta/alpha ratio as an optimal QEEG index

OBJECTIVE

Quantitative electroencephalographic (QEEG) indices sensitive to abnormal slow (relative to faster) activity power seem uniquely informative for clinical management of ischaemic stroke (IS), including around acute reperfusion therapies. However these have not been compared between IS and control samples. The primary objective was to identify the QEEG slowing index and threshold value which can most accurately discriminate between IS patients and controls.

METHODS

The samples comprised 28 controls (mean age: 70.4; range: 56-84) and 18 patients (mean age: 69.3; range: 51-86). Seven indices were analysed: relative bandpower (delta, theta, alpha, beta), delta/alpha power ratio (DAR), (delta+theta)/(alpha+beta) ratio (DTABR) and QSLOWING. The accuracies of each index for classifying participants (IS or control) were analysed using receiver operating characteristic (ROC) techniques.

RESULTS

All indices differed significantly between the samples (p<.001). DAR alone exhibited optimal classifier accuracy, with a threshold of 3.7 demonstrating 100% sensitivity and 100% specificity for discriminating between radiologically-confirmed, acute IS or control. DTABR and relative delta were the next most accurate classifiers.

CONCLUSIONS

DAR of 3.7 demonstrated maximal accuracy for classifying all 46 participants as acute IS or control.

SIGNIFICANCE

DAR assessment may inform clinical management of IS and perhaps other neurocritical patients.

Neuronal Network Oscillations in Neurodegenerative Diseases

Cognitive and behavioral acts go along with highly coordinated spatiotemporal activity patterns in neuronal networks. Most of these patterns are synchronized by coherent membrane potential oscillations within and between local networks. By entraining multiple neurons into a common time regime, such network oscillations form a critical interface between cellular activity and large-scale systemic functions. Synaptic integrity is altered in neurodegenerative diseases, and it is likely that this goes along with characteristic changes of coordinated network activity. This notion is supported by EEG recordings from human patients and from different animal models of such disorders. However, our knowledge about the pathophysiology of network oscillations in neurodegenerative diseases is surprisingly incomplete, and increased research efforts are urgently needed. One complicating factor is the pronounced diversity of network oscillations between different brain regions and functional states. Pathological changes must, therefore, be analyzed separately in each condition and affected area. However, cumulative evidence from different diseases may result, in the future, in more unifying "oscillopathy" concepts of neurodegenerative diseases. In this review, we report present evidence for pathological changes of network oscillations in Alzheimer's disease (AD), one of the most prominent and challenging neurodegenerative disorders. The heterogeneous findings from AD are contrasted to Parkinson's disease, where motor-related changes in specific frequency bands do already fulfill criteria of a valid biomarker.

Altered theta oscillations and aberrant cortical excitatory activity in the 5XFAD model of Alzheimer's disease

Alzheimer's disease (AD) is an age-related neurodegenerative disorder characterized by impairment of memory function. The 5XFAD mouse model was analyzed and compared with wild-type (WT) controls for aberrant cortical excitability and hippocampal theta oscillations by using simultaneous video-electroencephalogram (EEG) monitoring. Seizure staging revealed that 5XFAD mice exhibited cortical hyperexcitability whereas controls did not. In addition, 5XFAD mice displayed a significant increase in hippocampal theta activity from the light to dark phase during nonmotor activity. We also observed a reduction in mean theta frequency in 5XFAD mice compared to controls that was again most prominent during nonmotor activity. Transcriptome analysis of hippocampal probes and subsequent qPCR validation revealed an upregulation of Plcd4 that might be indicative of enhanced muscarinic signalling. Our results suggest that 5XFAD mice exhibit altered cortical excitability, hippocampal dysrhythmicity, and potential changes in muscarinic signaling.

Distinguishing rhythmic from non-rhythmic brain activity during rest in healthy neurocognitive aging

Rhythmic brain activity at low frequencies (<12Hz) during rest are thought to increase in neurodegenerative disease, but findings in healthy neurocognitive aging are mixed. Here we address two reasons conventional spectral analyses may have led to inconsistent results. First, spectral-power measures are compared to a baseline condition; when resting activity is the signal of interest, it is unclear what the baseline should be. Second, conventional methods do not clearly differentiate power due to rhythmic versus non-rhythmic activity. The Better OSCillation detection method (BOSC; Caplan et al., 2001; Whitten et al., 2011) avoids these problems by using the signal's own spectral characteristics as a reference to detect elevations in power lasting a few cycles. We recorded electroencephalographic (EEG) signal during rest, alternating eyes open and closed, in healthy younger (18-25 years) and older (60-74 years) participants. Topographic plots suggested the conventional and BOSC analyses measured different sources of activity, particularly at frequencies, like delta (1-4Hz), at which rhythms are sporadic; topographies were more similar in the 8-12Hz alpha band. There was little theta-band activity meeting the BOSC method's criteria, suggesting prior findings of theta power in healthy aging may reflect non-rhythmic signal. In contrast, delta oscillations were present at higher levels than theta in both age groups. In summary, applying strict and standardized criteria for rhythmicity, slow rhythms appear present in the resting brain at delta and alpha, but not theta frequencies, and appear unchanged in healthy aging.

Frontal midline theta connectivity is related to efficiency of WM maintenance and is affected by aging

Representations in working memory (WM) are temporary, but can be refreshed for longer periods of time through maintenance mechanisms, thereby establishing their availability for subsequent memory tests. Frontal brain regions supporting WM maintenance operations undergo anatomical and functional changes with advancing age, leading to age related decline of memory functions. The present study focused on age-related functional connectivity changes of the frontal midline (FM) cortex in the theta band (4-8 Hz), related to WM maintenance. In the visual delayed-match-to-sample WM task young (18-26 years, N=20) and elderly (60-71 years N=16) adults had to memorize sample stimuli consisting of 3 or 5 items while 33 channel EEG recording was performed. The phase lag index was used to quantify connectivity strength between cortical regions. The low and high memory demanding WM maintenance periods were classified based on whether they were successfully maintained (remembered) or unsuccessfully maintained (unrecognized later). In the elderly reduced connectivity strength of FM brain region and decreased performance were observed. The connectivity strength between FM and posterior sensory cortices was shown to be sensitive to both increased memory demands and memory performance regardless of age. The coupling of frontal regions (midline and lateral) and FM-temporal cortices characterized successfully maintained trials and declined with advancing age. The findings provide evidence that a FM neural circuit of theta oscillations that serves a possible basis of active maintenance process is especially vulnerable to aging.

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

OBJECTIVE

Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes.

MATERIALS AND METHODS

In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well.

RESULTS

The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased.

CONCLUSION

The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

Relative power and coherence of EEG series are related to amnestic mild cognitive impairment in diabetes

Objective: Diabetes is a risk factor for dementia and mild cognitive impairment. The aim of this study was to investigate whether some features of resting-state EEG (rsEEG) could be applied as a biomarker to distinguish the subjects with amnestic mild cognitive impairment (aMCI) from normal cognitive function in type 2 diabetes.

Materials and Methods: In this study, 28 patients with type 2 diabetes (16 aMCI patients and 12 controls) were investigated. Recording of the rsEEG series and neuropsychological assessments were performed. The rsEEG signal was first decomposed into delta, theta, alpha, beta, gamma frequency bands. The relative power of each given band/sum of power and the coherence of waves from different brain areas were calculated. The extracted features from rsEEG and neuropsychological assessments were analyzed as well.

Results: The main findings of this study were that: (1) compared with the control group, the ratios of power in theta band [P(theta)] vs. power in alpha band [P(alpha)] [P(theta)/P(alpha)] in the frontal region and left temporal region were significantly higher for aMCI, and (2) for aMCI, the alpha coherences in posterior, fronto-right temporal, fronto-posterior, right temporo-posterior were decreased; the theta coherences in left central-right central (LC-RC) and left posterior-right posterior (LP-RP) regions were also decreased; but the delta coherences in left temporal-right temporal (LT-RT) region were increased.

Conclusion: The proposed indexes from rsEEG recordings could be employed to track cognitive function of diabetic patients and also to help in the diagnosis of those who develop aMCI.

Amyloid Beta peptides differentially affect hippocampal theta rhythms in vitro

Soluble amyloid beta peptide (A β ) is responsible for the early cognitive dysfunction observed in Alzheimer's disease. Both cholinergically and glutamatergically induced hippocampal theta rhythms are related to learning and memory, spatial navigation, and spatial memory. However, these two types of theta rhythms are not identical; they are associated with different behaviors and can be differentially modulated by diverse experimental conditions. Therefore, in this study, we aimed to investigate whether or not application of soluble A β alters the two types of theta frequency oscillatory network activity generated in rat hippocampal slices by application of the cholinergic and glutamatergic agonists carbachol or DHPG, respectively. Due to previous evidence that oscillatory activity can be differentially affected by different A β peptides, we also compared Aβ 25-35 and Aβ 1-42 for their effects on theta rhythms in vitro at similar concentrations (0.5 to 1.0  μ M). We found that Aβ 25-35 reduces, with less potency than Aβ 1-42, carbachol-induced population theta oscillatory activity. In contrast, DHPG-induced oscillatory activity was not affected by a high concentration of Aβ 25-35 but was reduced by Aβ 1-42. Our results support the idea that different amyloid peptides might alter specific cellular mechanisms related to the generation of specific neuronal network activities, instead of exerting a generalized inhibitory effect on neuronal network function.

Amyloid Beta-Protein and Neural Network Dysfunction

Understanding the neural mechanisms underlying brain dysfunction induced by amyloid beta-protein (Aβ) represents one of the major challenges for Alzheimer's disease (AD) research. The most evident symptom of AD is a severe decline in cognition. Cognitive processes, as any other brain function, arise from the activity of specific cell assemblies of interconnected neurons that generate neural network dynamics based on their intrinsic and synaptic properties. Thus, the origin of Aβ-induced cognitive dysfunction, and possibly AD-related cognitive decline, must be found in specific alterations in properties of these cells and their consequences in neural network dynamics. The well-known relationship between AD and alterations in the activity of several neural networks is reflected in the slowing of the electroencephalographic (EEG) activity. Some features of the EEG slowing observed in AD, such as the diminished generation of different network oscillations, can be induced in vivo and in vitro upon Aβ application or by Aβ overproduction in transgenic models. This experimental approach offers the possibility to study the mechanisms involved in cognitive dysfunction produced by Aβ. This type of research may yield not only basic knowledge of neural network dysfunction associated with AD, but also novel options to treat this modern epidemic.

Amyloid Beta Peptide slows down sensory-induced hippocampal oscillations

Alzheimer's disease (AD) progresses with a deterioration of hippocampal function that is likely induced by amyloid beta (Aβ) oligomers. Hippocampal function is strongly dependent on theta rhythm, and disruptions in this rhythm have been related to the reduction of cognitive performance in AD. Accordingly, both AD patients and AD-transgenic mice show an increase in theta rhythm at rest but a reduction in cognitive-induced theta rhythm. We have previously found that monomers of the short sequence of Aβ (peptide 25-35) reduce sensory-induced theta oscillations. However, considering on the one hand that different Aβ sequences differentially affect hippocampal oscillations and on the other hand that Aβ oligomers seem to be responsible for the cognitive decline observed in AD, here we aimed to explore the effect of Aβ oligomers on sensory-induced theta rhythm. Our results show that intracisternal injection of Aβ1-42 oligomers, which has no significant effect on spontaneous hippocampal activity, disrupts the induction of theta rhythm upon sensory stimulation. Instead of increasing the power in the theta band, the hippocampus of Aβ-treated animals responds to sensory stimulation (tail pinch) with an increase in lower frequencies. These findings demonstrate that Aβ alters induced theta rhythm, providing an in vivo model to test for therapeutic approaches to overcome Aβ-induced hippocampal and cognitive dysfunctions.