Electroencephalogram Power Spectra Research Articles

Identifying montages that best detect the electroencephalogram power spectrum alteration during freezing of gait in Parkinson's disease patients.

Our research team has previously used four Electroencephalography (EEG) leads to successfully detect and predict Freezing of Gait (FOG) in Parkinson's disease (PD). However, it remained to be determined whether these four sensor locations that were arbitrarily chosen based on their role in motor control are indeed the most optimal for FOG detection. The aim of this study was therefore to determine the most optimal location and combination of sensors to detect FOG amongst a 32-channel EEG montage using our EEG classification system. EEG measures, including power spectral density, centroid frequency and power spectral entropy, were extracted from 7 patients with PD and FOG during a series of Timed up and Go tasks. By applying a feed-forward neural networks to classify EEG data, the obtained results showed that even a small number of electrodes suffice to construct a FOG detector with expected performance, which is comparable to the use of a full 32 channels montage. This finding therefore progresses the realization of a FOG detection system that can be effectively implemented on a daily basis for FOG prevention, improving the quality of life for many patients with PD.

Basal Forebrain Cholinergic Neurons Primarily Contribute to Inhibition of Electroencephalogram Delta Activity, Rather Than Inducing Behavioral Wakefulness in Mice

The basal forebrain (BF) cholinergic neurons have long been thought to be involved in behavioral wakefulness and cortical activation. However, owing to the heterogeneity of BF neurons and poor selectivity of traditional methods, the precise role of BF cholinergic neurons in regulating the sleep-wake cycle remains unclear. We investigated the effects of cell-selective manipulation of BF cholinergic neurons on the sleep-wake behavior and electroencephalogram (EEG) power spectrum using the pharmacogenetic technique, the 'designer receptors exclusively activated by designer drugs (DREADD)' approach, and ChAT-IRES-Cre mice. Our results showed that activation of BF cholinergic neurons expressing hM3Dq receptors significantly and lastingly decreased the EEG delta power spectrum, produced low-delta non-rapid eye movement sleep, and slightly increased wakefulness in both light and dark phases, whereas inhibition of BF cholinergic neurons expressing hM4Di receptors significantly increased EEG delta power spectrum and slightly decreased wakefulness. Next, the projections of BF cholinergic neurons were traced by humanized Renilla green fluorescent protein (hrGFP). Abundant and highly dense hrGFP-positive fibers were observed in the secondary motor cortex and cingulate cortex, and sparse hrGFP-positive fibers were observed in the ventrolateral preoptic nucleus, a known sleep-related structure. Finally, we found that activation of BF cholinergic neurons significantly increased c-Fos expression in the secondary motor cortex and cingulate cortex, but decreased c-Fos expression in the ventrolateral preoptic nucleus. Taken together, these findings reveal that the primary function of BF cholinergic neurons is to inhibit EEG delta activity through the activation of cerebral cortex, rather than to induce behavioral wakefulness.

Is the Electroencephalogram Power Spectrum Valuable for Diagnosis of the Elderly with Cognitive Impairment?

To study the changes of electroencephalogram (EEG) power spectrum in the elderly with mild cognitive dysfunction in resting and working memory task states. In this study, 40 patients with mild Alzheimer's disease (AD group), 40 patients with mild cognitive impairment (MCI group), and 40 normal controls (NC group) were enrolled. Their EEGs were recorded in resting and working memory task states. The EEG power spectrum, including δ, θ, α1, α2, β1, and β2, were analyzed from 10 channels: right and left frontal (F3, F4), central (C3, C4), parietal (P3, P4), temporal (T3, T4), and occipital (O1, O2). In the resting state, the δ and θ powers from some regions in the AD group were higher than those in the NC group and the MCI group ( p < 0.05). The δ powers from some regions in the MCI group were higher than those in the NC group ( p < 0.05). During the working memory task, the δ, θ, and α1 powers from some regions in the MCI and AD groups were higher than those in the NC group ( p < 0.05). The slow EGG waves and increased δ and θ power spectrum from some regions in patients with mild AD and MCI could be found during the resting state. The increased δ, θ, and α1 powers from some regions in AD and MCI patients were obvious in the working memory task. It can thus be postulated that the EEG power spectrum may have a certain value in the diagnosis of elderly patients with mild cognitive dysfunction.

The acute effects of alcohol on sleep electroencephalogram power spectra in late adolescence.

Alcohol's effect on sleep electroencephalogram (EEG) power spectra during late adolescence is of interest given that this age group shows both dramatic increases in alcohol consumption and major sleep-related developmental changes in quantitative EEG measures. This study examined the effect of alcohol on sleep EEG power spectra in 18- to 21-year-old college students. Participants were 24 (12 female) healthy 18- to 21-year-old social drinkers. Participants underwent 2 conditions: presleep alcohol and placebo, followed by standard polysomnography with comprehensive EEG recordings. After alcohol, mean breath alcohol concentration at lights-out was 0.084%. Interaction effects indicated simultaneous increases in frontal non-rapid eye movement sleep (NREM) delta (p=0.031) and alpha (p=0.005) power in the first sleep cycles following alcohol consumption which was most prominent at frontal scalp sites (p<0.001). A decrease in sigma power (p=0.001) was also observed after alcohol. As hypothesized, alcohol increased slow wave sleep-related NREM delta power. However, there was a simultaneous increase in frontal alpha power. Results suggest that alcohol may exert an arousal influence which may compete with the sleep maintenance influence of increased delta activity. The phenomenon is similar to, or the same as, alpha-delta sleep which has been associated with the presence of disruptive stimuli during sleep. This may have negative implications for the impact of presleep alcohol consumption on sleep and consequent daytime functioning.

EEG theta and beta power spectra in adolescents with ADHD versus adolescents with ASD + ADHD.

Attention problems are common in youngsters with attention deficit hyperactivity disorder (ADHD) as well as in adolescents with combined autism spectrum disorder (ASD) and ADHD. However, it is unknown whether there is psychophysiological overlap and/or a difference in electroencephalogram (EEG) power spectra between ADHD and comorbid ASD and ADHD (ASD + ADHD), on and off stimulant medication. To explore potential differences and overlap, measures of theta and beta power in adolescents diagnosed with ADHD (n = 33) versus adolescents with combined ASD + ADHD (n = 20), categorized by stimulant medication use (57 % of the total sample), were compared. EEG measures were acquired in three conditions: (1) resting state, eyes closed (2) resting state, eyes open and (3) during an oddball task. In addition, performance on the d2 attention test was analyzed. Adolescents with ADHD displayed more absolute theta activity than adolescents with ASD + ADHD during the eyes open and task conditions, independent of stimulant medication use. In addition, only the adolescents with ADHD showed an association between diminished attention test performance and increased theta in the eyes open condition. Results of the current study suggest that although there is behavioral overlap between ADHD characteristics in adolescents with ADHD and adolescents with combined ASD + ADHD, the underlying psychophysiological mechanisms may be different. Adolescents with ASD + ADHD exhibited fewer of the EEG physiological signs usually associated with ADHD, although there was an overlap in attentional problems between the groups. This may indicate that treatments developed for ADHD work differently in some adolescents with ASD + ADHD and adolescents with ADHD only.

Modulatory effects of aromatherapy massage intervention on electroencephalogram, psychological assessments, salivary cortisol and plasma brain-derived neurotrophic factor

Aromatherapy massage is commonly used for the stress management of healthy individuals, and also has been often employed as a therapeutic use for pain control and alleviating psychological distress, such as anxiety and depression, in oncological palliative care patients. However, the exact biological basis of aromatherapy massage is poorly understood. Therefore, we evaluated here the effects of aromatherapy massage interventions on multiple neurobiological indices such as quantitative psychological assessments, electroencephalogram (EEG) power spectrum pattern, salivary cortisol and plasma brain-derived neurotrophic factor (BDNF) levels. A control group without treatment (n = 12) and aromatherapy massage group (n = 13) were randomly recruited. They were all females whose children were diagnosed as attention deficit hyperactivity disorder and followed up in the Department of Psychiatry, Jeju National University Hospital. Participants were treated with aromatherapy massage for 40 min twice per week for 4 weeks (8 interventions). A 4-week-aromatherapy massage program significantly improved all psychological assessment scores in the Stat-Trait Anxiety Index, Beck Depression Inventory and Short Form of Psychosocial Well-being Index. Interestingly, plasma BDNF levels were significantly increased after a 4 week-aromatherapy massage program. Alpha-brain wave activities were significantly enhanced and delta wave activities were markedly reduced following the one-time aromatherapy massage treatment, as shown in the meditation and neurofeedback training. In addition, salivary cortisol levels were significantly reduced following the one-time aromatherapy massage treatment. These results suggest that aromatherapy massage could exert significant influences on multiple neurobiological indices such as EEG pattern, salivary cortisol and plasma BDNF levels as well as psychological assessments.

Alcohol Reduces Cross‐Frequency Theta‐Phase Gamma‐Amplitude Coupling in Resting Electroencephalography

The electrophysiological inhibitory mechanism of cognitive control for alcohol remains largely unknown. The purpose of the study was to compare electroencephalogram (EEG) power spectra and cross-frequency phase-amplitude coupling (CFPAC) at rest and during a simple subtraction task after acute alcohol ingestion. Twenty-one healthy subjects participated in this study. Two experiments were performed 1week apart, and the order of the experiments was randomly assigned to each subject. During the experiments, each subject was provided with orange juice containing alcohol or orange juice only. We recorded EEG activity and analyzed power spectra and CFPAC data. The results showed prominent theta-phase gamma-amplitude coupling at the frontal and parietal electrodes at rest. This effect was significantly reduced after alcohol ingestion. Our findings suggest that theta-phase gamma-amplitude coupling is deficiently synchronized at rest after alcohol ingestion. Therefore, cross-frequency coupling could be a useful tool for studying the effects of alcohol on the brain and investigating alcohol addiction.

EEG Markers for Characterizing Anomalous Activities of Cerebral Neurons in NAT (Neuronal Activity Topography) Method

A pair of markers, sNAT and vNAT, is derived from the electroencephalogram (EEG) power spectra (PS) recorded for 5 min with 21 electrodes (4-20 Hz) arranged according to the 10-20 standard. These markers form a new diagnosis tool "NAT" aiming at characterizing various brain disorders. Each signal sequence is divided into segments of 0.64 s and its discrete PS consists of eleven frequency components from 4.68 (3 × 1.56) Hz through 20.34 (13 × 1.56) Hz. PS is normalized to its mean and the bias of PS components on each frequency component across the 21 signal channels is reset to zero. The marker sNAT consists of ten frequency components on 21 channels, characterizing neuronal hyperactivity or hypoactivity as compared with NLc (normal controls). The marker vNAT consists of ten ratios between adjacent PS components denoting the over- or undersynchrony of collective neuronal activities as compared with NLc. The likelihood of a test subject to a specified brain disease is defined in terms of the normalized distance to the template NAT state of the disease in the NAT space. Separation of MCI-AD patients (developing AD in 12-18 months) from NLc is made with a false alarm rate of 15%. Locations with neuronal hypoactivity and undersynchrony of AD patients agree with locations of rCBF reduction measured by SPECT. The 2-D diagram composed of the binary likelihoods between ADc and NLc in the two representations of sNAT and vNAT enables tracing the NAT state of a test subject approaching the AD area, and the follow-up of the treatment effects.

Identification of Resting and Active State EEG Features of Alzheimer’s Disease using Discrete Wavelet Transform

Alzheimer's disease (AD) is associated with deficits in a number of cognitive processes and executive functions. Moreover, abnormalities in the electroencephalogram (EEG) power spectrum develop with the progression of AD. These features have been traditionally characterized with montage recordings and conventional spectral analysis during resting eyes-closed and resting eyes-open (EO) conditions. In this study, we introduce a single lead dry electrode EEG device which was employed on AD and control subjects during resting and activated battery of cognitive and sensory tasks such as Paced Auditory Serial Addition Test (PASAT) and auditory stimulations. EEG signals were recorded over the left prefrontal cortex (Fp1) from each subject. EEG signals were decomposed into sub-bands approximately corresponding to the major brain frequency bands using several different discrete wavelet transforms and developed statistical features for each band. Decision tree algorithms along with univariate and multivariate statistical analysis were used to identify the most predictive features across resting and active states, separately and collectively. During resting state recordings, we found that the AD patients exhibited elevated D4 (~4-8 Hz) mean power in EO state as their most distinctive feature. During the active states, however, the majority of AD patients exhibited larger minimum D3 (~8-12 Hz) values during auditory stimulation (18 Hz) combined with increased kurtosis of D5 (~2-4 Hz) during PASAT with 2 s interval. When analyzed using EEG recording data across all tasks, the most predictive AD patient features were a combination of the first two feature sets. However, the dominant discriminating feature for the majority of AD patients were still the same features as the active state analysis. The results from this small sample size pilot study indicate that although EEG recordings during resting conditions are able to differentiate AD from control subjects, EEG activity recorded during active engagement in cognitive and auditory tasks provide important distinct features, some of which may be among the most predictive discriminating features.

Driver fatigue detection from electroencephalogram spectrum after electrooculography artefact removal

A driver fatigue monitoring and detection system with high accuracy could be a valuable countermeasure to decrease fatigue-related traffic accidents. This study proposes methods for drowsiness detection based on electroencephalogram (EEG) power spectrum analysis. First, a new algorithm is proposed for independent component analysis with reference (ICA-R) for electrooculography artefacts removal. Comparison is then carried out between the proposed ICA-R algorithm and an adaptive filter. Secondly, 75 EEG spectrum features are extracted from the cleaned EEG. Among all the EEG spectrum-related features, 40 key features are selected by support vector machine recursive feature elimination to improve the performance of the classifier. The validation results show that 86% of the driver's drowsiness states can be accurately detected among drivers, who participate a driving simulator study.

Generalized EEG-Based Drowsiness Prediction System by Using a Self-Organizing Neural Fuzzy System

A generalized EEG-based Neural Fuzzy system to predict driver's drowsiness was proposed in this study. Driver's drowsy state monitoring system has been implicated as a causal factor for the safety driving issue, especially when the driver fell asleep or distracted in driving. However, the difficulties in developing such a system are lack of significant index for detecting the driver's drowsy state in real-time and the interference of the complicated noise in a realistic and dynamic driving environment. In our past studies, we found that the electroencephalogram (EEG) power spectrum changes were highly correlated with the driver's behavior performance especially the occipital component. Different from presented subject-dependent drowsy state monitor systems, whose system performance may decrease rapidly when different subject applies with the drowsiness detection model constructed by others, in this study, we proposed a generalized EEG-based Self-organizing Neural Fuzzy system to monitor and predict the driver's drowsy state with the occipital area. Two drowsiness prediction models, subject-dependent and generalized cross-subject predictors, were investigated in this study for system performance analysis. Correlation coefficients and root mean square errors are showed as the experimental results and interpreted the performances of the proposed system significantly better than using other traditional Neural Networks ( p-value <;0.038). Besides, the proposed EEG-based Self-organizing Neural Fuzzy system can be generalized and applied in the subjects' independent sessions. This unique advantage can be widely used in the real-life applications.

A New Method of Intracranial Pressure Monitoring by EEG Power Spectrum Analysis

To investigate the feasibility of Electroencephalogram (EEG) power spectrum analysis as a noninvasive method for monitoring intracranial pressure (ICP). The EEG signals were recorded in 62 patients (70 cases) with central nervous system (CNS) disorders in our hospital. By using self-designed software, EEG power spectrum analysis was conducted and pressure index (PI) was calculated automatically. Intracranial pressure was measured by lumbar puncture (LP). We found a significant negative correlation between PI and ICP (r = -0.849, p < 0.01). The PI obtained from EEG analysis is correlated with ICP. Analysis of specific parameters from EEG power spectrum might reflect the ICP.

Generalized Semilinear Canonical Correlation Analysis Applied to the Analysis of Electroencephalogram (EEG) Data

Semilinear canonical correlation analysis (SLCCA) is a technique developed by Gregg, Varvel, and Schafer to combine the powers in an electroencephalogram (EEG) power spectrum at each time point. This was used to give a single response that, over all time points, best correlated with a model that describes the response over time to changing levels of a drug in the brain. In this article, we generalize SLCCA so that both sides of the equation now have linear parameters. We call this generalized semilinear canonical correlation analysis (GSLCCA). In this form, it can readily deal with complex treatment structures. These power spectra matrices typically have significant colinearity between columns, which are effectively of reduced rank. We use a data-smoothing approach based on singular value decomposition (SVD) to reduce the dimensionality of these matrices. This increases the efficiency of the algorithm and also improves the results. The model being fitted by GSLCCA is applicable to other areas apart from the analysis of EEG power spectra. As an example of the use of GSLCCA, we use the algorithm to detect pharmacokinetic/pharmacodynamic (PK/PD)-like signals in EEG power spectra, and to obtain drug “signatures” (i.e., loadings in CCA terminology), which can be readily compared for different drugs, as detecting drug entry into the brain is important clinically.

Seizure susceptibility and electroencephalogram power spectra alterations at various phases of the lipopolysaccharide-induced hypothermic response in biotelemetered rats

The neuronal excitability has been evaluated at various phases of lipopolysaccharide (LPS; E. coli O111:B4, 250 μg/kg, ip)-induced hypothermia including the initial phase, the plateau (including the nadir) and the end of the response in biotelemetered adult Wistar rats. The latency of pentylenetetrazole-induced seizures (60 mg/kg, ip) was lower at the initial phase, but a clear anticonvulsive activity was observed at the end of the hypothermic response. Seizure parameters did not change at the nadir. There was no electroencephalogram (EEG) spike-wave activity generation at either phase of the LPS-induced hypothermia. Meanwhile, the power of the 12-32 Hz beta band of the EEG spectra increased at the initial phase. This increment persisted at the plateau where there was also a decrease in the 1-4 Hz delta power. The data indicate that spike-wave activity is not facilitated during LPS-induced hypothermia but, proconvulsant and anticonvulsant activities occur sequentially depending on the phase of the response. The EEG power spectra also change. These effects may not be attributed merely to the reduction of body temperature. Thus, it is possible that pathophysiological mechanisms involved in the development of hypothermia may also be responsible for neuronal excitability changes in rats.

Differential effects of a dual orexin receptor antagonist (SB-649868) and zolpidem on sleep initiation and consolidation, SWS, REM sleep, and EEG power spectra in a model of situational insomnia.

Orexins have a role in sleep regulation, and orexin receptor antagonists are under development for the treatment of insomnia. We conducted a randomised, double-blind, placebo-controlled, four-period crossover study to investigate the effect of single doses of the dual orexin receptor antagonist SB-649868 (10 or 30 mg) and a positive control zolpidem (10 mg), an allosteric modulator of GABA(A) receptors. Objective and subjective sleep parameters and next-day performance were assessed in 51 healthy male volunteers in a traffic noise model of situational insomnia. Compared with placebo, SB-649868 10 and 30 mg increased total sleep time (TST) by 17 and 31 min (p<0.001), whereas after zolpidem TST was increased by 11.0 min (p=0.012). Wake after sleep onset was reduced significantly by 14.7 min for the SB-6489698 30 mg dose (p<0.001). Latency to persistent sleep was significantly reduced after both doses of SB-6489698 (p=0.003), but not after zolpidem. Slow wave sleep (SWS) and electroencephalogram (EEG) power spectra in non-REM sleep were not affected by either dose of SB-640868, whereas SWS (p< 0.001) and low delta activity (<=1.0 Hz) were increased, and 2.25-11.0 Hz activity decreased after zolpidem. REM sleep duration was increased after SB-649868 30 mg (p=0.002) and reduced after zolpidem (p=0.049). Latency to REM sleep was reduced by 20.1 (p=0.034) and 34.0 min (p<0.001) after 10 and 30 mg of SB-649868. Sleep-onset REM episodes were observed. SB-649868 was well tolerated. This dual orexin receptor antagonist exerts hypnotic activity, with effects on sleep structure and the EEG that are different from those of zolpidem.

Ketamine Activates Breathing and Abolishes the Coupling between Loss of Consciousness and Upper Airway Dilator Muscle Dysfunction

Procedural sedation is frequently performed in spontaneously breathing patients, but hypnotics and opioids decrease respiratory drive and place the upper airway at risk for collapse. In a randomized, controlled, cross-over, pharmaco-physiologic study in 12 rats, we conducted acute experiments to compare breathing and genioglossus electromyogram activity at equianesthetic concentrations of ketamine, a noncompetitive N-methyl-D-aspartate receptor antagonist that combines potent analgesic with hypnotic action effects, versus propofol. In 10 chronically instrumented rats resting in a plethysmograph, we measured these variables as well as electroencephalography during five conditions: quiet wakefulness, nonrapid-eye-movement sleep, rapid eye movement sleep, and low-dose (60 mg/kg intraperitoneally) and high-dose ketamine anesthesia (125 mg/kg intraperitoneally). Ketamine anesthesia was associated with markedly increased genioglossus activity (1.5 to fivefold higher values of genioglossus electromyogram) compared with sleep- and propofol-induced unconsciousness. Plethysmography revealed a respiratory stimulating effect: higher values of flow rate, respiratory rate, and duty-cycle (effective inspiratory time, 1.5-to-2-fold higher values). During wakefulness and normal sleep, the δ (f = 6.51, P = 0.04) electroencephalogram power spectrum was an independent predictor of genioglossus activity, indicating an association between electroencephalographic determinants of consciousness and genioglossus activity. Following ketamine administration, electroencephalogram power spectrum and genioglossus electroencephalogram was dissociated (P = 0.9 for the relationship between δ/θ power spectrum and genioglossus electromyogram). Ketamine is a respiratory stimulant that abolishes the coupling between loss-of-consciousness and upper airway dilator muscle dysfunction in a wide dose-range. Ketamine compared with propofol might help stabilize airway patency during sedation and anesthesia.

Effects of Stimulation of Glutamatergic Receptors in Medial Septum on Power Spectrum Analysis of EEG in Rats

Brain stem arousal systems transmit their effects to the cerebral cortex partly through basal forebrain including medial septum (MS). Cholinergic neurones of basal forebrain are inhibited by norepinephrine and acetylcholine. Glutamatergic neurones in MS may be an excitatory link between brain stem projecting systems and cholinergic system of MS. The present study has been designed to investigate the role of glutamate receptors present in MS on the duration of sleep-wake and electroencephalogram (EEG) power spectra in conscious rats. The duration of wake was increased and duration of slow wave sleep (SWS) was decreased after infusion of glutamate into MS. The durations of wake and SWS remained unaltered after infusion of glutamate receptor antagonist 6,7-dinitroquinoxaline-2,3-dione (DNQX) in MS of rats. The power of delta waves of EEG was decreased in both wake and SWS after infusion of glutamate in MS. There was a generalized increase of power of alpha, beta, theta and delta waves of EEG after infusion of DNQX in MS. Results of this study indicate that glutamate receptors in MS may modulate the cortical arousal mechanism.

Effects of synthetic cannabinoids on electroencephalogram power spectra in rats

Several synthetic cannabinoids have recently been distributed as psychoactive adulterants in many herbal products on the illegal drug market around the world. However, there is little information on pharmacology and toxicology of such compounds. Although Δ(9)-tetrahydrocannabinol (Δ(9)-THC), a psychoactive cannabinoid of marijuana, was reported to affect electroencephalograms (EEG) of rats, the effects of synthetic cannabinoids are unknown. We examined the pharmacological activities of three synthetic cannabinoids; cannabicyclohexanol (CCH), CP-47,497 and JWH-018; by analyzing EEG power spectra and locomotor activity after intraperitoneal administration to rats and compared them with those of Δ(9)-THC. The three compounds significantly increased the EEG power in the frequency range of 5.0-6.0 Hz for the first 3h, while Δ(9)-THC decreased the power spectra in the wide range of 7.0-20.0 Hz during the first hour. These results indicate that the effect of the three compounds on EEG is different from that of Δ(9)-THC. Additionally, CCH, CP-47,497 and JWH-018 significantly decreased the locomotor activity for 11.5h, 11h and 4.5h, respectively, after administration which was longer than that of Δ(9)-THC (3.5h). Furthermore, all three compounds significantly reduced the total amounts of locomotor activity during a 3-h, 6-h and 12-h period after injection, whereas no statistical difference was observed for the Δ(9)-THC injection. Among the three compounds, CCH and CP-47,497 exerted a longer duration of the change in the EEG power spectra and suppression of the locomotor activity than JWH-018.

Early onset of age-related changes on neural processing in rats

Altered perceptual and emotional processing might bind impaired cognitive mechanisms during aging; however the nature of these sensory perception modifications is still unknown. In the present experiment we analyzed in rats, from early to mature life (2 to 11 months old), the response to unattended auditory evoked stimulation (Auditory evoked potential, AEP) and the power spectrum of spontaneous electroencephalogram (EEG), with the aim of unraveling the onset and target functional effects of aging. Somatosensory and cingulate cortex, mediodorsal thalamus and CA3 hippocampus were chosen for examination based on their involvement in sensory processing and age-related deficits. The main finding of this study is the early onset of age-related changes in adult rats as can be established with both AEP's and frequency analyses, and its diversity between brain regions during normal aging.

Cognitive control in the intertrial interval: Evidence from EEG alpha power

This study used electroencephalogram (EEG) power spectrum analyses to characterize neural activity during the intertrial interval, a period during which online cognitive adjustments in response to errors or conflict are thought to occur. EEG alpha power was quantified as an inverse index of cerebral activity during the period between each response and the next stimulus in a Stroop task. Alpha power was significantly reduced following error responses compared to correct responses, indicating greater cerebral activity following errors. Reduced alpha power was also observed following Stroop conflict trials compared to no-conflict trials, suggesting that conflict engages processes of mental adjustment. Finally, hemispheric differences in alpha power during the intertrial interval supported the complementary roles of the left and right hemispheres in behavioral activation and inhibition.