Biomedical signal processing (in four parts). Part 3. The power spectrum and coherence function

Alterations of synaptic plasticity and brain oscillation are associated with autophagy induced synaptic pruning during adolescence

Adolescent brain development is characterized by significant anatomical and physiological alterations, but little is known whether and how these alterations impact the neural network. Here we investigated the development of functional networks by measuring synaptic plasticity and neural synchrony of local filed potentials (LFPs), and further explored the underlying mechanisms. LFPs in the hippocampus were recorded in young (21 ~ 25 days), adolescent (1.5 months) and adult (3 months) rats. Long term potentiation (LTP) and neural synchrony were analyzed. The results showed that the LTP was the lowest in adolescent rats. During development, the theta coupling strength was increased progressively but there was no significant change of gamma coupling between young rats and adolescent rats. The density of dendrite spines was decreased progressively during development. The lowest levels of NR2A, NR2B and PSD95 were detected in adolescent rats. Importantly, it was found that the expression levels of autophagy markers were the highest during adolescent compared to that in other developmental stages. Moreover, there were more co-localization of autophagosome and PSD95 in adolescent rats. It suggests that autophagy is possibly involved in synaptic elimination during adolescence, and further impacts synaptic plasticity and neural synchrony.

Assessing brain-muscle networks during motor imagery to detect covert command-following

BACKGROUND

In this study, we evaluated the potential of a network approach to electromyography and electroencephalography recordings to detect covert command-following in healthy participants. The motivation underlying this study was the development of a diagnostic tool that can be applied in common clinical settings to detect awareness in patients that are unable to convey explicit motor or verbal responses, such as patients that suffer from disorders of consciousness (DoC).

METHODS

We examined the brain and muscle response during movement and imagined movement of simple motor tasks, as well as during resting state. Brain-muscle networks were obtained using non-negative matrix factorization (NMF) of the coherence spectra for all the channel pairs. For the 15/38 participants who showed motor imagery, as indexed by common spatial filters and linear discriminant analysis, we contrasted the configuration of the networks during imagined movement and resting state at the group level, and subject-level classifiers were implemented using as features the weights of the NMF together with trial-wise power modulations and heart response to classify resting state from motor imagery.

RESULTS

Kinesthetic motor imagery produced decreases in the mu-beta band compared to resting state, and a small correlation was found between mu-beta power and the kinesthetic imagery scores of the Movement Imagery Questionnaire-Revised Second version. The full-feature classifiers successfully distinguished between motor imagery and resting state for all participants, and brain-muscle functional networks did not contribute to the overall classification. Nevertheless, heart activity and cortical power were crucial to detect when a participant was mentally rehearsing a movement.

CONCLUSIONS

Our work highlights the importance of combining EEG and peripheral measurements to detect command-following, which could be important for improving the detection of covert responses consistent with volition in unresponsive patients.

Characterizing Natural Frequencies of the Hybrid III and NOCSAE Headforms

The vibrational characteristics of the Hybrid III and NOCSAE headforms are not well understood. It is hypothesized that they may perform differently in certain loading environments due to their structural differences; their frequency responses may differ depending on the impact characteristics. Short-duration impacts excite a wider range of headform frequencies than longer-duration (padded) impacts. While headforms generally perform similarly during padded head impacts where resonant frequencies are avoided, excitation of resonant frequencies during short-duration impacts can result in differences in kinematic measurements between headforms for the matched impacts. This study aimed to identify the natural frequencies of each headform through experimental modal analysis techniques. An impulse hammer was used to excite various locations on both the Hybrid III and NOCSAE headforms. The resulting frequency response functions were analyzed to determine the first natural frequencies. The average first natural frequency of the NOCSAE headform was 812 Hz. The Hybrid III headform did not exhibit any natural frequencies below 1000 Hz. Comparisons of our results with previous studies of the human head suggest that the NOCSAE headform's vibrational response aligns more closely with that of the human head, as it exhibits lower natural frequencies. This insight is particularly relevant for assessing head injury risk in short-duration impact scenarios, where resonant frequencies can influence the injury outcome.

Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends

Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural activation and connectivity. In this work, we provide a technical account and a categorization of the most-used data-driven approaches to assess brain-functional connectivity, intended as the study of the statistical dependencies between the recorded EEG signals. Different pairwise and multivariate, as well as directed and non-directed connectivity metrics are discussed with a pros-cons approach, in the time, frequency, and information-theoretic domains. The establishment of conceptual and mathematical relationships between metrics from these three frameworks, and the discussion of novel methodological approaches, will allow the reader to go deep into the problem of inferring functional connectivity in complex networks. Furthermore, emerging trends for the description of extended forms of connectivity (e.g., high-order interactions) are also discussed, along with graph-theory tools exploring the topological properties of the network of connections provided by the proposed metrics. Applications to EEG data are reviewed. In addition, the importance of source localization, and the impacts of signal acquisition and pre-processing techniques (e.g., filtering, source localization, and artifact rejection) on the connectivity estimates are recognized and discussed. By going through this review, the reader could delve deeply into the entire process of EEG pre-processing and analysis for the study of brain functional connectivity and learning, thereby exploiting novel methodologies and approaches to the problem of inferring connectivity within complex networks.

Effects of auditory feedback on fine motor output and corticomuscular coherence during a unilateral finger pinch task

Auditory feedback is important to reduce movement error and improve motor performance during a precise motor task. Accurate motion guided by auditory feedback may rely on the neural muscle transmission pathway between the sensorimotor area and the effective muscle. However, it remains unclear how neural activities and sensorimotor loops play a role in enhancing performance. The present study uses an auditory feedback system by simultaneously recording electroencephalogram (EEG), electromyography (EMG), and exert force information to measure corticomuscular coherence (CMC), neural activity, and motor performance during precise unilateral right-hand pinch by using the thumb and the index finger with and without auditory feedback. This study confirms three results. First, compared with no auditory feedback, auditory feedback decreases movement errors. Second, compared with no auditory feedback, auditory feedback decreased the power spectrum in the beta band in the bimanual sensorimotor cortex and the alpha band in the ipsilateral sensorimotor cortex. Finally, CMC was computed between effector muscle of right hand and contralateral sensorimotor cortex. Analyses reveals that the CMC of beta band significantly decreases in auditory feedback condition compared with no auditory feedback condition. The results indicate that auditory feedback decreases the power spectral in the alpha and beta bands and decreases corticospinal connection in the beta band during precise hand control. This study provides a new perspective on the effect of auditory feedback on behavior and brain activity and offers a new idea for designing more suitable and effective rehabilitation and training strategies to improve fine motor performance.

Exercise Effects on Motor Skill Consolidation and Intermuscular Coherence Depend on Practice Schedule

Cardiorespiratory or aerobic exercise immediately after practice of an upper-extremity motor skill task can facilitate skill consolidation, as demonstrated by enhanced performances at 24 h and 7-day retention tests. The purpose of this study was to examine the effect of acute cardiorespiratory exercise on motor skill consolidation when skill practice involved low and high levels of contextual interference introduced through repetitive and interleaved practice schedules, respectively. Forty-eight young healthy adults were allocated to one of four groups who performed either repetitive or interleaved practice of a pinch grip motor sequence task, followed by either a period of seated rest or a bout of high-intensity interval cycling. At pre- and post-practice and 24 h and 7-day retention tests, we assessed motor skill performance and β-band (15–35 Hz) intermuscular coherence using surface electromyography (EMG) collected from the abductor pollicis brevis and first dorsal interosseous. At the 7-day retention test, off-line consolidation was enhanced in the cardiorespiratory exercise relative to the rest group, but only among individuals who performed interleaved motor skill practice (p = 0.02). Similarly, at the 7-day retention test, β-band intermuscular coherence increased to a greater extent in the exercise group than in the rest group for those who performed interleaved practice (p = 0.02). Under the present experimental conditions, cardiorespiratory exercise preferentially supported motor skill consolidation and change in intermuscular coherence when motor skill practice involved higher rather than lower levels of contextual interference.

Quantitative analysis of inter- and intrahemispheric coherence on epileptic electroencephalography signal

When an epileptic seizure occurs, the neuron's activity of the brain is dynamically changed, which affects the connectivity between brain regions. The connectivity of each brain region can be quantified by electroencephalography (EEG) coherence, which measures the statistical correlation between electrodes spatially separated on the scalp. Previous studies conducted a coherence analysis of all EEG electrodes covering all parts of the brain. However, in an epileptic condition, seizures occur in a specific region of the brain then spreading to other areas. Therefore, this study applies an energy-based channel selection process to determine the coherence analysis in the most active brain regions during the seizure. This paper presents a quantitative analysis of inter- and intrahemispheric coherence in epileptic EEG signals and the correlation with the channel activity to glean insights about brain area connectivity changes during epileptic seizures. The EEG signals are obtained from ten patients’ data from the CHB-MIT dataset. Pair-wise electrode spectral coherence is calculated in the full band and five sub-bands of EEG signals. The channel activity level is determined by calculating the energy of each channel in all patients. The EEG coherence observation in the preictal (Coh_pre) and ictal (Coh_ictal) conditions showed a significant decrease of Coh_ictal in the most active channel, especially in the lower EEG sub-bands. This finding indicates that there is a strong correlation between the decrease of mean spectral coherence and channel activity. The decrease of coherence in epileptic conditions (Coh_ictal <Coh_pre) indicates low neuronal connectivity. There are some exceptions in some channel pairs, but a constant pattern is found in the high activity channel. This shows a strong correlation between the decrease of coherence and the channel activity. The finding in this study demonstrates that the neuronal connectivity of epileptic EEG signals is suitable to be analyzed in the more active brain regions.

Electromyogram-Based Classification of Hand and Finger Gestures Using Artificial Neural Networks

Electromyogram (EMG) signals have been increasingly used for hand and finger gesture recognition. However, most studies have focused on the wrist and whole-hand gestures and not on individual finger (IF) gestures, which are considered more challenging. In this study, we develop EMG-based hand/finger gesture classifiers based on fixed electrode placement using machine learning methods. Ten healthy subjects performed ten hand/finger gestures, including seven IF gestures. EMG signals were measured from three channels, and six time-domain (TD) features were extracted from each channel. A total of 18 features was used to build personalized classifiers for ten gestures with an artificial neural network (ANN), a support vector machine (SVM), a random forest (RF), and a logistic regression (LR). The ANN, SVM, RF, and LR achieved mean accuracies of 0.940, 0.876, 0.831, and 0.539, respectively. One-way analyses of variance and F-tests showed that the ANN achieved the highest mean accuracy and the lowest inter-subject variance in the accuracy, respectively, suggesting that it was the least affected by individual variability in EMG signals. Using only TD features, we achieved a higher ratio of gestures to channels than other similar studies, suggesting that the proposed method can improve the system usability and reduce the computational burden.

TMS-induced brain connectivity modulation in Genetic Generalized Epilepsy

OBJECTIVE

In epilepsy patients, Transcranial Magnetic Stimulation (TMS) may result in the induction and modulation of epileptiform discharges (EDs). We hereby investigate the modulatory effects of TMS on brain connectivity in Genetic Generalized Epilepsy (GGE) and explore their potential as a diagnostic biomarker in GGE.

METHODS

Patients with GGE (n=18) and healthy controls (n=11) were investigated with a paired-pulse TMS-EEG protocol. The brain network was studied at local and at global levels using Coherence as an EEG connectivity measure. Comparison of patients vs controls was performed in a time-resolved manner by analyzing comparatively pre- vs post-TMS brain networks.

RESULTS

There was statistically significant TMS-induced modulation of connectivity at specific frequency bands within groups and difference in TMS-induced modulation between the two groups. The most significant difference between patients and controls related to connectivity modulation in the γ band at 1-3 sec post-TMS (p=0.004).

CONCLUSIONS

TMS modulates the healthy and epileptic brain connectivity in different ways. Our results indicate that TMS-EEG connectivity analysis can be a basis for a diagnostic biomarker of GGE.

SIGNIFICANCE

The analysis identifies specific time periods and frequency bands of interest of TMS-induced connectivity modulation and elucidates the effect of TMS on the healthy and epileptic brain connectivity.

Intermuscular Coherence in the Presence of Electrical Stimulation

The nervous system uses oscillations to convey information efficiently. Inter-muscular coherence in the 15-35 Hz range is thought to represent common cortical drive to muscles, but is also in the frequency band in which electrical stimulation is applied to restore movement following neurological disease or injury. We wished to determine if, when stimulation is applied at the peak frequency of the coherence spectra it was still possible to determine voluntary effort. Using healthy human subjects we stimulated muscles in the arms and legs, separate experiments, while recording EMG activity from pairs of muscles including the stimulated muscles. Offline coherence analysis was performed. When stimulation is greater than motor threshold, and applied at the peak of the coherence spectra a new peak appears in the spectra, presumably representing a new frequency of oscillation within the nervous system. This does not appear at lower stimulation levels, or with lower frequencies. The nervous system is capable of switching oscillatory frequencies to account for noise in the environment.

Pattern Reorganization of Corticomuscular Connection with the Tactile Stimulation

Sensitivity to tactile stimuli is an indispensable feedback in human motion control. However, previous studies on tactile stimulation mainly focused on the effects of superficial tactile stimulation on the motor cortex, but the role of deep tactile feedback stimulation in motor tasks is not clear. Corticomuscular coherence (CMC) is an effective method for studying dynamic motion tasks. Recent evidence suggests that CMC is enhanced by tactile stimulation in the beta-band. But, the mechanism of tactile stimulation in dynamic motor tasks is still undetermined. In order to explore the role of tactile stimulation in dynamic motion tasks, we examined the correlation between EEG/EMG in a motor task with tactile stimulus input, including the corticomuscular coherence and the causal connections (convergent cross mapping, CCM). In this study, seventeen subjects were recruited to complete stimuli and non-stimuli motor tasks. After the experiment, the time-frequency analysis of CMC showed that the somatosensory association cortex was clearly involved in the dynamic motor tasks. During the contraction of hand muscles, the activity of CMC was concentrated in gamma band, while in the maintenance process, it was concentrated in beta-band. After eliminating the distractors of attention, we did not find a similar result as previous studies had found-tactile stimuli lead to increased CMC activity in gamma band. On the contrary, CCM causality analysis showed that tactile stimulation could significantly enhance the connection between the cerebral cortex and a muscle. We speculate that tactile stimulation can enhance the corticomuscular causal relationship, and that the effect of tactile stimulation on corticomuscular coherence may have more complex mechanisms. This study provides new insights into neural mechanism of tactile feedback and provides more information about the causality of brain networks in tactile feedback task.

Wearable-Sensor-based Detection and Prediction of Freezing of Gait in Parkinson's Disease: A Review

Freezing of gait (FOG) is a serious gait disturbance, common in mid- and late-stage Parkinson's disease, that affects mobility and increases fall risk. Wearable sensors have been used to detect and predict FOG with the ultimate aim of preventing freezes or reducing their effect using gait monitoring and assistive devices. This review presents and assesses the state of the art of FOG detection and prediction using wearable sensors, with the intention of providing guidance on current knowledge, and identifying knowledge gaps that need to be filled and challenges to be considered in future studies. This review searched the Scopus, PubMed, and Web of Science databases to identify studies that used wearable sensors to detect or predict FOG episodes in Parkinson's disease. Following screening, 74 publications were included, comprising 68 publications detecting FOG, seven predicting FOG, and one in both categories. Details were extracted regarding participants, walking task, sensor type and body location, detection or prediction approach, feature extraction and selection, classification method, and detection and prediction performance. The results showed that increasingly complex machine-learning algorithms combined with diverse feature sets improved FOG detection. The lack of large FOG datasets and highly person-specific FOG manifestation were common challenges. Transfer learning and semi-supervised learning were promising for FOG detection and prediction since they provided person-specific tuning while preserving model generalization.

Modulation of the Visual to Auditory Human Inhibitory Brain Network: An EEG Dipole Source Localization Study

Auditory alarms are used to direct people's attention to critical events in complicated environments. The capacity for identifying the auditory alarms in order to take the right action in our daily life is critical. In this work, we investigate how auditory alarms affect the neural networks of human inhibition. We used a famous stop-signal or go/no-go task to measure the effect of visual stimuli and auditory alarms on the human brain. In this experiment, go-trials used visual stimulation, via a square or circle symbol, and stop trials used auditory stimulation, via an auditory alarm. Electroencephalography (EEG) signals from twelve subjects were acquired and analyzed using an advanced EEG dipole source localization method via independent component analysis (ICA) and EEG-coherence analysis. Behaviorally, the visual stimulus elicited a significantly higher accuracy rate (96.35%) than the auditory stimulus (57.07%) during inhibitory control. EEG theta and beta band power increases in the right middle frontal gyrus (rMFG) were associated with human inhibitory control. In addition, delta, theta, alpha, and beta band increases in the right cingulate gyrus (rCG) and delta band increases in both right superior temporal gyrus (rSTG) and left superior temporal gyrus (lSTG) were associated with the network changes induced by auditory alarms. We further observed that theta-alpha and beta bands between lSTG-rMFG and lSTG-rSTG pathways had higher connectivity magnitudes in the brain network when performing the visual tasks changed to receiving the auditory alarms. These findings could be useful for further understanding the human brain in realistic environments.

Measurement of Neurovascular Coupling in Neonates

Neurovascular coupling refers to the mechanism that links the transient neural activity to the subsequent change in cerebral blood flow, which is regulated by both chemical signals and mechanical effects. Recent studies suggest that neurovascular coupling in neonates and preterm born infants is different compared to adults. The hemodynamic response after a stimulus is later and less pronounced and the stimulus might even result in a negative (hypoxic) signal. In addition, studies both in animals and neonates confirm the presence of a short hypoxic period after a stimulus in preterm infants. In clinical practice, different methodologies exist to study neurovascular coupling. The combination of functional magnetic resonance imaging or functional near-infrared spectroscopy (brain hemodynamics) with EEG (brain function) is most commonly used in neonates. Especially near-infrared spectroscopy is of interest, since it is a non-invasive method that can be integrated easily in clinical care and is able to provide results concerning longer periods of time. Therefore, near-infrared spectroscopy can be used to develop a continuous non-invasive measurement system, that could be used to study neonates in different clinical settings, or neonates with different pathologies. The main challenge for the development of a continuous marker for neurovascular coupling is how the coupling between the signals can be described. In practice, a wide range of signal interaction measures exist. Moreover, biomedical signals often operate on different time scales. In a more general setting, other variables also have to be taken into account, such as oxygen saturation, carbon dioxide and blood pressure in order to describe neurovascular coupling in a concise manner. Recently, new mathematical techniques were developed to give an answer to these questions. This review discusses these recent developments.

Patterns of cardiovascular variability after long-term sino-aortic denervation in unanesthetized adult rats

Baroreflex dysfunction is a diffuse chronic condition that is expected to be followed by a profound loss of organization of BP and HR variability. Nevertheless, long-term effects of baroreflex withdrawal are still debated. Aim of our work was to study BP and HR changes long term after sino-aortic denervation (SAD). Inter-beat-interval (IBI) and intra-arterial BP were recorded beat-by-beat in 43 Wistar-Kyoto rats (Controls, n = 33; SAD rats, n = 10). Power spectra were calculated in controls and in SAD rats within three days and at seven months from denervation. Compared to controls, chronic SAD rats showed 1) similar mean BP (control vs SAD: 95 ± 16 vs 87 ± 22 mmHg) and IBI (171 ± 22 vs 181 ± 15 ms) values, 2) dramatically higher values of BP variance (12 ± 2 vs 64 ± 2 mmHg2, p < 0.01) and of ultra- (ULF) and very-low-frequency (VLF) BP oscillations, 3) dramatically higher values of IBI variability (24 ± 2 vs 71 ± 4 ms2, p < 0.01) and of ULF-IBI oscillations that were synchronized with BP oscillations. Chronic SAD rats reveal a marked change in the pattern of cardiovascular variability characterized by the appearance of synchronized slower oscillations of BP and HR. The cardiovascular system, therefore, retains a high level of organization despite the absence of a reflex control mechanism.

Neural Correlates of Explicit Versus Implicit Facial Emotion Processing in ASD

The underlying neural mechanisms of implicit and explicit facial emotion recognition (FER) were studied in children and adolescents with autism spectrum disorder (ASD) compared to matched typically developing controls (TDC). EEG was obtained from N = 21 ASD and N = 16 TDC. Task performance, visual (P100, N170) and cognitive (late positive potential) event-related-potentials, as well as coherence were compared across groups. TDC showed a task-dependent increase and a stronger lateralization of P100 amplitude during the explicit task and task-dependent modulation of intra-hemispheric coherence in the beta band. In contrast, the ASD group showed no task dependent modulation. Results indicate disruptions in early visual processing and top-down attentional processes as contributing factors to FER deficits in ASD.

Automated quality control of forced oscillation measurements: respiratory artifact detection with advanced feature extraction

The forced oscillation technique (FOT) can provide unique and clinically relevant lung function information with little cooperation with subjects. However, FOT has higher variability than spirometry, possibly because strategies for quality control and reducing artifacts in FOT measurements have yet to be standardized or validated. Many quality control procedures rely on either simple statistical filters or subjective evaluation by a human operator. In this study, we propose an automated artifact removal approach based on the resistance against flow profile, applied to complete breaths. We report results obtained from data recorded from children and adults, with and without asthma. Our proposed method has 76% agreement with a human operator for the adult data set and 79% for the pediatric data set. Furthermore, we assessed the variability of respiratory resistance measured by FOT using within-session variation (wCV) and between-session variation (bCV). In the asthmatic adults test data set, our method was again similar to that of the manual operator for wCV (6.5 vs. 6.9%) and significantly improved bCV (8.2 vs. 8.9%). Our combined automated breath removal approach based on advanced feature extraction offers better or equivalent quality control of FOT measurements compared with an expert operator and computationally more intensive methods in terms of accuracy and reducing intrasubject variability.NEW & NOTEWORTHY The forced oscillation technique (FOT) is gaining wider acceptance for clinical testing; however, strategies for quality control are still highly variable and require a high level of subjectivity. We propose an automated, complete breath approach for removal of respiratory artifacts from FOT measurements, using feature extraction and an interquartile range filter. Our approach offers better or equivalent performance compared with an expert operator, in terms of accuracy and reducing intrasubject variability.

The influence of unilateral contraction of hand muscles on the contralateral corticomuscular coherence during bimanual motor tasks

The mechanisms behind how muscle contractions in one hand influence corticomuscular coherence in the opposite hand are still undetermined. Twenty-two subjects were recruited to finish bimanual and unimanual motor tasks. In the unimanual tasks, subjects performed precision grip using their right hand with visual feedback of exerted forces. The bimanual tasks involved simultaneous finger abduction of their left hand with visual feedback and precision grip of their right hand. They were divided into four conditions according to the two contraction levels of the left-hand muscles and whether visual feedback existed for the right hand. Measures of coherence and power spectrum were calculated from EEG and EMG data and statistically analyzed to identify changes in corticomuscular coupling and oscillatory activity. Results showed that compared with the unimanual task, a significant increase in the mean corticomuscular coherence of the right hand was found when left-hand muscles contracted at 5% of the maximal isometric voluntary contraction (MVC). No significant changes were found when the contraction level was 50% of the MVC. Furthermore, both the increase of muscle contraction levels and the elimination of visual feedback for right hand can significantly decrease the corticomuscular coupling in right hand during bimanual tasks. In summary, the involvement of moderate left-hand muscle contractions resulted in an increase tendency of corticomuscular coherence in right hand while strong left-hand muscle contractions eliminated it. We speculated that the perturbation of activities in one corticospinal tract resulted from the movement of the opposite hand can enhance the corticomuscular coupling when attention distraction is limited.

Design of a novel biomedical signal processing and analysis tool for functional neuroimaging

In this paper, a MATLAB-based graphical user interface (GUI) software tool for general biomedical signal processing and analysis of functional neuroimaging data is introduced. Specifically, electroencephalography (EEG) and electrocardiography (ECG) signals can be processed and analyzed by the developed tool, which incorporates commonly used temporal and frequency analysis methods. In addition to common methods, the tool also provides non-linear chaos analysis with Lyapunov exponents and entropies; multivariate analysis with principal and independent component analyses; and pattern classification with discriminant analysis. This tool can also be utilized for training in biomedical engineering education. This easy-to-use and easy-to-learn, intuitive tool is described in detail in this paper.

Functional corticospinal projections from human supplementary motor area revealed by corticomuscular coherence during precise grip force control

The purpose of the present study was to investigate whether corticospinal projections from human supplementary motor area (SMA) are functional during precise force control with the precision grip (thumb-index opposition). Since beta band corticomuscular coherence (CMC) is well-accepted to reflect efferent corticospinal transmission, we analyzed the beta band CMC obtained with simultaneous recording of electroencephalographic (EEG) and electromyographic (EMG) signals. Subjects performed a bimanual precise visuomotor force tracking task by applying isometric low grip forces with their right hand precision grip on a custom device with strain gauges. Concurrently, they held the device with their left hand precision grip, producing similar grip forces but without any precision constraints, to relieve the right hand. Some subjects also participated in a unimanual control condition in which they performed the task with only the right hand precision grip while the device was held by a mechanical grip. We analyzed whole scalp topographies of beta band CMC between 64 EEG channels and 4 EMG intrinsic hand muscles, 2 for each hand. To compare the different topographies, we performed non-parametric statistical tests based on spatio-spectral clustering. For the right hand, we obtained significant beta band CMC over the contralateral M1 region as well as over the SMA region during static force contraction periods. For the left hand, however, beta band CMC was only found over the contralateral M1. By comparing unimanual and bimanual conditions for right hand muscles, no significant difference was found on beta band CMC over M1 and SMA. We conclude that the beta band CMC found over SMA for right hand muscles results from the precision constraints and not from the bimanual aspect of the task. The result of the present study strongly suggests that the corticospinal projections from human SMA become functional when high precision force control is required.

Propagation direction of natural mechanical oscillations in the biceps brachii muscle during voluntary contraction

The aim of the study was to determine the directionality of the coupling of mechanical vibrations across the biceps brachii muscle at different frequencies of interest during voluntary contraction. The vibrations that are naturally generated by skeletal muscles were recorded by a two-dimensional array of skin mounted accelerometers over the biceps brachii muscle (surface mechanomyogram, S-MMG) during voluntary isometric contractions in ten healthy young men. As a measure of the similarity of vibration between a given pair of accelerometers, the spatial coherence of S-MMG at low (f<25Hz) and high (f>25Hz) frequency bands were investigated to determine if the coupling of the natural mechanical vibrations were due to the different physiological muscle activity at low and high frequencies. In both frequency bands, spatial coherence values for sensor pairs aligned longitudinally along the proximal to distal ends of the biceps were significantly higher compared with those for the sensor pairs oriented perpendicular to the muscle fibers. This difference was more evident at the higher frequency band. The findings indicated that coherent mechanical oscillations mainly propagated along the longitudinal direction of the biceps brachii muscle fibers at high frequencies (f>25Hz).

Two dimensional spatial coherence of the natural vibrations of the biceps brachii muscle generated during voluntary contractions

Surface mechanomyograms (S-MMGs) are recorded from low frequency (〈100 Hz) mechanical oscillations that are naturally generated by skeletal muscle during voluntary contractions. This study investigates a method to determine the propagation directionality of the S-MMG waves. A 3×5 grid of skin mounted accelerometers was mounted on the biceps brachii muscle during submaximal voluntary contractions. This method resulted in findings that the propagation directionality of the S-MMGs are frequency dependent. At high frequencies (>25 Hz), high spatial coherence values were only measured for sensor pairs aligned along the proximal to distal (i.e. longitudinal) orientation, thus indicating that coherent S-MMG were mainly propagating along the muscle fibers direction of the biceps brachii at those frequencies. On the other hand, at lower frequencies (〈25 Hz), the S-MMG spatial coherence values did not exhibit a specific directionality. This method provides results that have an important implication of finding the average phase velocity of the propagating S-MMG wave, which can be used to determine viscoelastic properties of skeletal muscles.

Granger causality: cortico-thalamic interdependencies during absence seizures in WAG/Rij rats

Linear Granger causality was used to identify the coupling strength and directionality of information transport between frontal cortex and thalamus during spontaneous absence seizures in a genetic model, the WAG/Rij rats. Electroencephalograms were recorded at the cortical surface and from the specific thalamus. Granger coupling strength was measured before, during and after the occurrence of spike-wave discharges (SWD). Before the onset of SWD, coupling strength was low, but associations from thalamus-to-cortex were stronger than vice versa. The onset of SWD was associated with a rapid and significant increase of coupling strength in both directions. There were no changes in Granger causalities before the onset of SWD. The strength of thalamus-to-cortex coupling remained constantly high during the seizures. The strength of cortex-to-thalamus coupling gradually diminished shortly after the onset of SWD and returned to the pre-SWD level when SWD stopped. In contrast, the strength of thalamus-to-cortex coupling remained elevated even after cessation of SWD. The strong and sustained influence of thalamus-to-cortex may facilitate propagation and maintenance of seizure activity, while rapid reduction of cortex-to-thalamus coupling strength may prompt the cessation of SWD. However, the linear estimation of Granger coupling strength does not seem to be sufficient for predicting episodes with absence epilepsy.

Comparison of time-variant coherence algorithms in single-trial: a dynamic analysis

Synchronization in the electroencephalogram, which can be quantified by time-variant coherence measures, reveals a communication between brain regions reflecting different functions (e.g. learning or memory). Aim of this work is to compare three time-variant coherence algorithms in single-trial. The first algorithm is based on the short-time Fourier transform, the second one on the adaptive discrete Fourier transform, whereas the third algorithm is based on a recursive smoothed pseudo Wigner-distribution. Parameters which describe the dynamic properties of the algorithms were calculated and compared on simulated data. Differences were observed in the estimation performance of the algorithms. Based on the obtained results, the algorithms are discussed for their utilization in future applications.

Effect of short-term, low-dose treatment with tamoxifen in patients with primary dysmenorrhea

Current treatment of painful periods and other symptoms related to primary dysmenorrhea (PD) is usually commenced with non-steroidal anti-inflammatory drugs or oral contraceptives, which fails in about 10% of affected patients. Tamoxifen, a selective estrogen-receptor modulator (SERM), has been demonstrated to directly inhibit uterine contractions, causing improvement in uterine blood flow. It could be considered for application in selected groups of dysmenorrheic patients, for instance carriers of breast cancer-associated antigen (BRCA) genes, breast cancer survivors or women with advanced endometriosis. Thus the aim of the present study was to investigate the effect of short-term treatment with tamoxifen on PD and PD-related symptoms, as well as its direct effect on parameters of intrauterine pressure during the painful menstruation, in a group of dysmenorrheic patients. After two cycles of administration of tamoxifen we noted a significant decrease in bleeding together with reductions in the severity of menstrual cramps, diarrhea, headache, fatigue and anxiety. In intrauterine pressure assessments, tamoxifen significantly decreased propagation of uterine contractions. In conclusion, SERMs such as tamoxifen may constitute a therapeutic option in selected groups of patients, improving dysmenorrheic symptoms. Additionally to its receptor-mediated effects, tamoxifen was shown to exert a direct influence on uterine contractile activity that may explain the decrease of menstrual pain and cramps noted in the studied group.

Mechanisms of blood pressure and heart rate variability: an insight from low-level paraplegia

It is still unclear whether the low-frequency oscillation in heart rate is generated by an endogenous neural oscillator or by a baroreflex resonance. Our aim was to investigate this issue by analyzing blood pressure and heart rate variability and the baroreflex function in paraplegic subjects with spinal cord injury below the fourth thoracic vertebra. These subjects were selected because they represent a model of intact central neural drive to the heart, with a partially impaired autonomic control of the vessels. In our study, arterial blood pressure and ECG were recorded in 33 able-bodied controls and in 33 subjects with spinal cord lesions between the fifth thoracic and the fourth lumbar vertebra 1) during supine rest (lowest sympathetic activation), 2) sitting on a wheelchair (light sympathetic activation), and 3) during exercise (moderate sympathetic activation). Blood pressure and heart rate spectra, coherence, and baroreflex function (sequence technique) were estimated in each condition. Compared with controls, paraplegic subjects showed a reduction of the low-frequency power of blood pressure and heart rate, and, unlike controls, a 0.1-Hz peak did not appear in their spectra. Sympathetic activation increased the 0.1-Hz peak of blood pressure and heart rate and the coherence at 0.1 Hz in controls only. Paraplegic subjects also had significantly lower baroreflex effectiveness and greater blood pressure variability. In conclusion, the disappearance of the 10-s oscillation of heart rate and blood pressure in subjects with spinal cord lesion supports the hypothesis of the baroreflex nature of this phenomenon.

Transcranial direct current stimulation of the primary motor cortex affects cortical drive to human musculature as assessed by intermuscular coherence

Intermuscular coherence analysis can be used to assess the common drive to muscles. Coherence in the beta-frequency band (15-35 Hz) is thought to arise from common cortical sources. Intermuscular coherence analysis is a potentially attractive tool for the investigation of motor cortical excitability changes because it is non-invasive and can be done relatively quickly. We carried out this study to test the hypothesis that intermuscular coherence analysis was able to detect cortical excitability changes in healthy subjects following transcranial direct current stimulation (tDCS). tDCS has been shown to increase (anodal stimulation) or decrease (cathodal stimulation) the size of the muscle potential evoked by TMS. We found that anodal tDCS caused an increase in motor evoked potential (MEP) size that was paralleled by an increase in beta-band intermuscular coherence. Similarly, the reduction in MEP size produced by cathodal tDCS was paralleled by a reduction in beta-band intermuscular coherence, while sham stimulation did not result in any change in either MEP amplitude or beta-band intermuscular coherence. The similar pattern of change observed for MEP and intermuscular coherence may indicate similar mechanisms of action, although this cannot be assumed without further investigation. These changes do suggest that at least some of the action of tDCS is on cortical networks, and that combined tDCS and intermuscular coherence analysis may be useful in the diagnosis of pathologies affecting motor cortical excitability.

Cortical and thalamic coherence during spike–wave seizures in WAG/Rij rats

The study examines cortico-cortical and cortico-thalamic network synchronization at the onset of spike-wave discharges (SWD) in a genetic model of absence epilepsy, WAG/Rij rats. Coherence was measured between multiple cortical areas (intracortical), reticular and rely thalamic nuclei (intrathalamic) and between the cortex and the thalamus. SWD-related increase of coherence (5-60 Hz) was found in all investigated pairs. The highest increase of coherence was around the mean frequency of SWD (8-11.5 Hz) and in the harmonic band 16-21.5 Hz with two central maxima around 10 and 20 Hz. The frequency profile of coherence was different in different intracortical networks, therefore latter were divided into local, global and transhemispheric networks. The presumable source of SWD in the somatosensory cortex and its closest surroundings formed a minimal (local) circuit, in which occurrence of SWD was facilitated by a consistent shift of network synchrony from delta to alpha/beta frequencies. Transhemispheric coherence revealed the largest increase with an additional 16 Hz peak, suggesting a crucial involvement of the corpus callosum in the pathophysiology of absence seizures. The increase in interhemispheric coherence was largest between relatively remote somatosensory or frontal areas, supporting the assumption that SWD originate from the lateral fronto-parietal cortical area.

Hemodynamics and Autonomic Control of Heart Rate Turbulence

INTRODUCTION

Late heart rate deceleration parallels the increase of systolic blood pressure during heart rate turbulence (HRT) after ventricular premature complexes (VPC). This is consistent with the involvement of baroreflex mechanism. Physiological background of systolic blood pressure dynamics is not known. Enhanced sympathetic activation and nonautonomic post-VPC changes of stroke volume have been speculated on.

METHODS AND RESULTS

We studied 28 subjects (aged 56 +/- 11 years; 20 males; 18 normal and 10 abnormal left ventricular (LV) function) with spontaneous occurrence of VPCs. HRT indices and baroreflex sensitivity were analyzed from the ECGs and finger arterial pressure recordings during 30 minutes of spontaneous respiration in supine position. Beat-by-beat stroke volume and peripheral vascular resistance were computed by a nonlinear, self-adaptive model of aortic input impedance (Modelflow, Finapres Medical Systems, Arnhem, The Netherlands). Indices of HRT and baroreflex sensitivity were highly correlated. In patients with preserved LV function, there was no substantial dynamics of stroke volume in the late phase after VPC, while peripheral vascular resistance increased significantly. In patients with impaired LV function, potentiated first sinus beat after VPC triggered transient hemodynamic alternans. Dynamics of peripheral vascular resistance was attenuated and stroke volume was depressed in the late phase after VPC.

CONCLUSIONS

Delayed sympathetically mediated vasomotor response to VPC produces systolic blood pressure overshoot. This subsequently induces vagally mediated late heart rate deceleration. Under physiologic conditions, there is no evidence of other hemodynamic and/or mechanical effect outside the autonomic reflex arch. In patients with LV dysfunction, both depressed vagal and sympathetic modulation and, indirectly, enhanced postextrasystolic potentiation account for attenuated HRT.

Changes in cortically related intermuscular coherence accompanying improvements in locomotor skills in incomplete spinal cord injury

In human spinal cord injury, the neuronal mechanisms mediating the improvement of locomotor function in response to intensive treadmill training are not well understood. In this study, we examined if such recovery is mediated, in part, by increases in residual corticospinal drive to muscles of the leg during walking. To do this, we measured the coherence of electromyogram (EMG) activity between two antagonist muscles (intermuscular coherence), specifically at frequencies between 24 and 40 Hz, which is thought to indicate common drive to two muscles from corticospinal inputs. In 12 subjects with incomplete spinal cord injury, intermuscular coherence was measured between hamstrings and vastus lateralis EMG that was activated during walking on a motorized treadmill. Before training, appreciable coherence in the 24-40 Hz frequency band was only present in subjects with moderate volitional motor strength in their leg muscles (n = 8 subjects) compared with subjects with little or no leg muscle strength (n = 4 subjects), reconfirming that 24-40 Hz frequency coherence is likely mediated by common supraspinal inputs. After training, increases in 24-40 Hz coherence only occurred in the eight subjects with moderate leg muscle strength who also exhibited improvements in locomotor recovery as assessed by the 21 point WISCI II scale (termed responders). In contrast, development of intermuscular coherence in the 24-40 Hz frequency band did not occur in the four subjects with absent or weak muscle strength. These subjects also did not improve in their locomotor ability as reflected in unchanging WISCI II scores (termed nonresponders). Lower-frequency coherence (5-18 Hz), which is thought to contain common drive from spinal inputs, did not change in either group. In a subset of subjects that were previously assessed with transcranial magnetic stimulation (TMS) before and after training (n = 5 responders and 3 nonresponders), there was a significant and positive relationship between increases in 24-40 Hz coherence and increases in evoked muscle responses to TMS of the primary motor cortex. Taken together, increases in higher-frequency EMG coherence in subjects with residual voluntary muscle strength and its parallel relation to changes in TMS-evoked responses provides further evidence that improvements in locomotor function from treadmill training are mediated, in part, by increases in corticospinal drive to muscles of the leg during walking.

Rhinal-hippocampal connectivity determines memory formation during sleep

Compared with waking state attention, volition and semantic processing play a minor role during sleep. Thus, investigating declarative memory formation during sleep may allow us to isolate mnemonic core processes. The most feasible approach to memory formation during sleep is the analysis of dream memories. Lesion and imaging studies have demonstrated that encoding of declarative memories, i.e. consciously accessible events and facts, depends on operations within the rhinal cortex and the hippocampus, two substructures of the medial temporal lobe. Successful memory formation is accompanied by a transient rhinal-hippocampal interaction. Consequently, the ability to memorize dreams may be related to mediotemporal connectivity. Therefore, we recorded EEG during sleep from rhinal and hippocampal depth electrodes implanted in 12 epilepsy patients (eight women, mean age 41.1 +/- 6.4 years). They were awakened during rapid eye movement sleep (REM) and asked to recall their dream. Via coherence analyses we show that rhinal-hippocampal connectivity values are approximately twice as large for patients with good dream recall versus those patients with poor recall. This suggests that rhinal-hippocampal connectivity is a key factor in determining declarative memory formation.

Coherence between oxygen saturation and heart rate obtained from pulse oximetric recordings in obstructive sleep apnoea

In obstructive sleep apnoea (OSA) cyclical changes in oxygen saturation and heart rate in the period range of 30-120 s are observed. In these patients, we prospectively analyse the coherence of nocturnal SaO(2) and heart rate signals. A sample of 201 clinically suspected of having OSA were studied using nocturnal pulse oximetric and complete polysomnography. Coherence function versus period curves were categorized into three patterns: a positive pattern showing a predominant positive peak value of coherence in the period range of 30-120 s; a negative pattern if the predominant coherence was negative in the same range; and an undetermined pattern if no predominance was detected. One hundred and thirteen patients present a positive coherence pattern; 74.3% of these have OSA. A negative coherence pattern was observed for 28 patients; 85.7% of these have OSA. The remaining 60 patients present an undetermined pattern. Patients with OSA presented significantly higher maximal positive coherence and maximal negative coherence than those without OSA. We conclude that OSA patients present dynamic coordination and interdependence between SaO(2) and heart rate in specific frequencies.

Waveform analysis of ventricular fibrillation to predict defibrillation

PURPOSE OF REVIEW

Ventricular fibrillation occurs during many cases of cardiac arrest and is treated with rescue shocks. Coarse ventricular fibrillation occurs earlier after the onset of cardiac arrest and is more likely to be converted to an organized rhythm with pulses by rescue shocks. Less organized or fine ventricular fibrillation occurs later, has less power concentrated within narrow frequency bands and lower amplitude, and is less likely to be converted to an organized rhythm by rescue shocks. Quantitative analysis of the ventricular fibrillation waveform may distinguish coarse ventricular fibrillation from fine ventricular fibrillation, allowing more appropriate delivery of rescue shocks.

RECENT FINDINGS

A variety of studies in animals and humans indicate that there is underlying structure within the ventricular fibrillation waveform. Highly organized or coarse ventricular fibrillation is characterized by large power contributions from a few component frequencies and higher amplitude. Amplitude, decomposition into power spectra, or probability-based, nonlinear measures all can quantify the organization of human ventricular fibrillation waveforms. Clinical data have accumulated that these quantitative measures, or combinations of these measures, can predict the likelihood of rescue shock success, restoration of circulation, and survival to hospital discharge.

SUMMARY

Many quantitative ventricular fibrillation measures could be implemented in current generations of monitors/defibrillators to assist the timing of rescue shocks during clinical care. Emerging data suggest that a period of chest compressions or reperfusion can increase the likelihood of successful defibrillation. Therefore, waveform-based prediction of defibrillation success could reduce the delivery of failed rescue shocks.

Diabetic neuropathy is a more important determinant of baroreflex sensitivity than carotid elasticity in type 2 diabetes

The object of this study was to evaluate the contribution of carotid distensibilty on baroreflex sensitivity in patients with type 2 diabetes mellitus with at least 2 additional cardiovascular risk factors. Carotid distensibility was measured bilaterally at the common carotid artery in 79 consecutive diabetic patients and 60 matched subjects without diabetes. Spontaneous baroreflex sensitivity assessment was obtained using time and frequency methods. Baroreflex sensitivity was lower in diabetic subjects as compared with nondiabetic control subjects (5.25+/-2.80 ms/mm Hg versus 7.55+/-3.79 ms/mm Hg; P<0.01, respectively). Contrary to nondiabetic subjects, diabetic subjects showed no significant correlation between carotid distensibility and baroreflex sensitivity (r2=0.08, P=0.04 and r2=0.04, P=0.13, respectively). In diabetic subjects, baroreflex sensitivity was significantly lower in subjects with peripheral neuropathy than in those with preserved vibration sensation (4.1+/-0.5 versus 6.1+/-0.4 ms/mm Hg, respectively; P=0.005). Age in nondiabetic subjects, diabetes duration, systolic blood pressure, peripheral or sensitive neuropathy, and carotid distensibility were introduced in a stepwise multivariate analysis to identify the determinants of baroreflex sensitivity. In diabetic patients, neuropathy is a more sensitive determinant of baroreflex sensitivity than the reduced carotid distensibility (stepwise analysis; F ratio=5.1, P=0.028 versus F ratio=1.9, P=0.16, respectively). In diabetic subjects with 2 additional cardiovascular risk factors, spontaneous baroreflex sensitivity is not related to carotid distensibility. Diabetic subjects represent a particular population within the spectrum of cardiovascular risk situations because of the marked neuropathy associated with their metabolic disorder. Therefore, neuropathy is a more significant determinant of baroreflex sensitivity than carotid artery elasticity in patients with type 2 diabetes.

Human mediotemporal EEG characteristics during propofol anesthesia

Evidence for a response-control-related kind of declarative memory during deep propofol anesthesia has recently been reported. Connectivity within the mediotemporal lobe (MTL), and in particular rhinal-hippocampal synchronization within the gamma band, has been shown to be crucial for declarative memory formation. Thus, we analyzed EEG recordings obtained from the scalp, as well as directly from within the hippocampus and from the anterior parahippocampal gyrus, which is covered by rhinal cortex, in patients with unilateral temporal lobe epilepsy during propofol anesthesia, which preceded electrode explantation. For the gamma band a power decrease starting with induction of anesthesia was observed at scalp position Cz, but a power increase was detected at MTL locations. In contrast to prior results for sleep recordings, rhinal-hippocampal coherence did not decrease within the gamma band at deeper levels of anesthesia. These findings may represent an indirect electrophysiological correlate of partially intact declarative memory formation during deep propofol sedation. Furthermore, we investigated how well the plasma propofol level, as well as different stages of anesthesia including the burst suppression phase, could be monitored by different spectral as well as by nonlinear EEG measures. We observed that conventional spectral power measures, most prominently those recorded from mediotemporal locations, are most closely correlated with the plasma propofol level, whereas different stages of anesthesia can be distinguished best by nonconventional spectral as well as nonlinear measures.

Effects of RR segment duration on HRV spectrum estimation

Although patterns of heart rate variability (HRV) hold considerable promise for clarifying issues in clinical applications, the inappropriate quantification and interpretation of these patterns may obscure critical issues or relationships and may impede rather than foster the development of clinical applications. The duration of the RR interval series is not a matter of convenience but a fine balance between two important issues: acceptable variance and stationarity of the time series on one hand, and acceptable resolution of the spectral estimate and reduced spectral leakage on the other. Further, in the standard short-term HRV analysis, it has been observed that the previous studies in HRV spectral analysis use a wide range of RR interval segment duration for spectral estimation by Welch's algorithm. The standardization of RR interval segment duration is also important for comparisons among studies and is essential for within-study experimental contrasts. In the present study, a comparative analysis for RR interval segment durations has been made to propose an optimal RR interval segment duration. Firstly a simulated signal was analyzed with Hann window and zero padding for the segment lengths of 1024, 512, 256 and 128 samples resampled at 4 Hz with 50% overlapping. Again, the above procedure was applied to RR interval series and it was concluded that segment length of 256 samples with 50% overlapping provides a smoothed spectral estimate with clearly outlined peaks in low- and high-frequency bands. This easily understandable and interpretable spectral estimate leads to a better visual and automated analysis, which is not only desirable in basic physiology studies, but also a prerequisite for a widespread utilization of frequency domain techniques in clinical studies, where simplicity and effectiveness of information are of primary importance.

Surrogate Data Analysis for Assessing the Significance of the Coherence Function

In cardiovascular variability analysis, the significance of the coupling between two time series is commonly assessed by setting a threshold level in the coherence function. While traditionally used statistical tests consider only the parameters of the adopted estimator, the required zero-coherence level may be affected by some features of the observed series. In this study, three procedures, based on the generation of surrogate series sharing given properties with the original but being structurally uncoupled, were considered: independent identically distributed (IID), Fourier transform (FT), and autoregressive (AR). IID surrogates maintained the distribution of the original series, while FT and AR surrogates preserved the power spectrum. The ability of the three methods to define the threshold for zero coherence was validated and compared by computer simulations reproducing typical cardiovascular interactions. While the IID threshold depended only on record length and design parameters of the coherence estimator, FT and AR thresholds were frequency-dependent with peaks corresponding to the local maxima of the estimated coherence. FT and AR surrogates were able to compensate spurious coherence peaks due to equal-frequency but independent oscillations in the two series. The benefit of frequency-dependent thresholds was evident for short series with narrow-band oscillations. Thus, surrogates preserving the power spectrum of the original series are recommended to avoid false coupling detections in the presence of oscillations occurring at nearby frequencies but produced by different mechanisms, as may frequently happen in cardiovascular and cardiorespiratory regulation.

EEG coherence changes between right and left motor cortical areas during voluntary muscular contraction

It is known that movements of the right side of the body are controlled by the left motor cortex of the brain. The aim of this study is to evaluate the contribution of right motor cortex of the brain in the central motor control of right-sided muscle contraction. EEG/EEG coherence analysis has been used to determine the functional coupling between the right and left motor cortical areas in twenty normal volunteers, during maximum voluntary contraction (MVC) and 50% MVC of right Adductor Pollicis muscle (APM). It shows that the maximum mean coherence values were: 0.751 during MVC at 10 and 12 Hz, and 0.274 during 50% of MVC at 22 Hz. The minimum mean coherence values were: 0.716 during MVC at 48 and 50 Hz, and 0.242 during 50% MVC at 34 Hz. The high coherence values obtained during MVC, and to a lesser extent during 50% of MVC, could be attributed to the need of recruitment of both motor cortical areas during the decision phase of central motor control of voluntary muscular contraction. The "will" to perform maximum voluntary contraction could be a major factor, which contribute to the higher coherence values obtained during MVC than these associated with 50% of MVC.

Assessing dynamic cerebral autoregulation after stroke using a novel technique of combining transcranial Doppler ultrasonography and rhythmic handgrip

OBJECTIVES

Dynamic cerebral autoregulation (CA) is impaired after stroke. Methods employed to assess this phenomenon usually involve deliberate alterations in blood pressure (BP) by physical means. We performed a pilot study to assess dynamic CA in acute stroke patients using a novel technique of combining transcranial Doppler (TCD) ultrasonography with rhythmic handgrip.

METHODS

Ten patients with ischaemic stroke in the middle cerebral artery (MCA) territory were studied. We performed continuous recordings of bilateral MCA velocities and used rhythmic handgrip to induce BP oscillations. Changes in autoregulation were indicated by changes in phase shift and gain of MCA velocity in relation to BP. Patients were examined at <7 days, 6 weeks, and 3 months after stroke.

RESULTS

There were no significant differences in phase shift or gain between the affected and unaffected cerebral hemispheres. Combining the results from both hemispheres, there was a trend of increasing phase shift (P=0.04) and decreasing gain (P=0.24) over the first three months after stroke, indicating improving CA. Rhythmic handgrip produced an average percentage change in BP (peak-to-trough) of 10% around the mean, and the frequency of the induced BP oscillations was very similar to that of the rhythmic handgrip.

CONCLUSIONS

Combining TCD with rhythmic handgrip appeared to be a useful technique for assessing dynamic CA and it deserves further studies. In this pilot study, there was some evidence that CA might improve up to 3 months after ischaemic stroke.

Rhinal-hippocampal EEG coherence is reduced during human sleep

The deficiency of declarative memory compared with waking state is an often overlooked characteristic of sleep. Here, we investigated whether rhinal-hippocampal coherence, an electrophysiological correlate of declarative memory formation, is significantly altered during sleep as compared with waking state. For this purpose, we analysed recordings of intracranial EEG activity during sleep obtained directly from within the medial temporal lobe in patients with unilateral temporal lobe epilepsy. We found a general reduction of rhinal-hippocampal EEG coherence during sleep compared with waking state, which was most pronounced within the upper gamma bands (average decrease up to 56%). The observed coherence changes clearly differ from findings reported for surface EEG data and thus appear to be specific for the medial temporal lobe. The decrease of rhinal-hippocampal EEG coherence from waking state towards sleep may yield an electrophysiological explanation for the sleep-related deficiency of declarative memory.

The contribution of EEG coherence to the investigation of language

The contribution of EEG coherence analysis to the investigation of cognition and, in particular, language processing is demonstrated with examples of recent EEG studies. The concept of EEG coherence analysis is explained, and its importance emphasized in the light of recent neurobiological findings on frequency-dependent synchrony as a code of information processing between nerve cell assemblies. Furthermore, EEG coherence studies on naturally spoken and written word and sentence processing are reviewed and experimental results are presented giving new insights into the occurrence of "transient functional language centers" within the brain.

Rhinal-hippocampal theta coherence during declarative memory formation: interaction with gamma synchronization?

The hippocampus and the rhinal cortex, two substructures of the medial temporal lobe, together play a crucial role in human declarative memory formation. To investigate in detail the mechanism connecting these two structures transiently during memory formation we recorded depth EEG in epilepsy patients from within the hippocampus and the rhinal cortex. During this recording, patients performed a single-trial word list-learning paradigm with a free recall memory test following a distraction task. Rhinal-hippocampal EEG coherence and spectral power at both locations in the time interval up to 2 s after onset of word presentation were analysed in the frequency range 1-19 Hz. Successful as opposed to unsuccessful memory formation was associated with a general rhinal-hippocampal coherence enhancement, but without alterations in spectral power. Coherence increases in the theta range were correlated with the previously reported memory-related changes in rhinal-hippocampal gamma phase synchronization. This correlation may suggest an interaction of the two mechanisms during declarative memory formation. While theta coherence might be associated with slowly modulated coupling related to an encoding state, rhinal-hippocampal gamma synchronization may be more closely related to actual memory processes by enabling fast coupling and decoupling of the two structures.