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At least 217 records · Page 12Linked to original sources
PubMed2006

Foetal heart rate power spectrum response to uterine contraction.

Cardiotocography is the most diffused prenatal diagnostic technique in clinical routine. The simultaneous recording of foetal heart rate (FHR) and uterine contractions (UC) provides useful information about foetal well-being during pregnancy and labour. However, foetal electronic monitoring interpretation still lacks reproducibility and objectivity. New methods of interpretation and new parameters can further support physicians' decisions. Besides common time-domain analysis, study of the variability of FHR can potentially reveal autonomic nervous system activity of the foetus. In particular, it is clinically relevant to investigate foetal reactions to UC to diagnose foetal distress early. Uterine contraction being a strong stimulus for the foetus and its autonomic nervous system, it is worth exploring the FHR variability response. This study aims to analyse modifications of the power spectrum of FHR variability corresponding to UC. Cardiotocographic signal tracts corresponding to 127 UC relative to 30 healthy foetuses were analysed. Results mainly show a general, statistically significant (t test, p<0.01) power increase of the FHR variability in the LF 0.03-0.2 Hz and HF 0.2-1 in correspondence of the contraction with respect to a reference tract set before contraction onset. Time evolution of the power within these bands was computed by means of time-varying spectral estimation to concisely show the FHR response along a uterine contraction. A synchronised grand average of these responses was also computed to verify repeatability, using the contraction apex as time reference. Such modifications of the foetal HRV that follow a contraction can be a sign of ANS reaction and, therefore, additional, objective information about foetal reactivity during labour.

Autonomic Nervous System↗
PubMed1980

Effects of induction of labor on the neurophysiologic functioning of newborn infants.

Neurophysiologic responses of newborn infants delivered after normal onset of labor are compared with those of newborn infants whose mothers had labor induced with oxytocin or prostaglandin F2 alpha. No differences in brain activity or heart rate were detected between groups in terms of frequency of response to auditory, visual, tactile, or olfactory stimulation. Significant differences were found for resting brain activity defined in terms of autoregressive spectral estimates or coefficients. The largest differences were between the groups with normal onset of labor and prostaglandin F2 alpha.

Autonomic Nervous System↗
PubMed1985

Topographic EEG changes with benzodiazepine administration in generalized anxiety disorder.

The regional cerebral effects of an anxiolytic (clorazepate) in 20 patients with generalized anxiety disorder were assessed using 16-channel electroencephalogram (EEG) power spectral estimate maps of the left hemisphere. Patients were studied with double-blind random assignment to placebo or drug and were assessed at baseline, day 7, and day 14 with EEG and Hamilton Anxiety Ratings. Ten age- and sex-matched normal controls were also tested. Hamilton Anxiety Ratings were decreased significantly more in the drug group than in the placebo group. Topographic maps of EEG activity revealed decreases in occipital alpha and parietal delta, together with increases in posterior frontal (central EEG leads) and parietal beta. Decreases in delta are consistent with a lack of sedation; the reciprocal beta increases in parietal cortex are similarly consistent. This pattern of regional EEG changes in the direction of alert attentiveness, together with individual differences, observed in frontal/parietal and occipital alpha activity, suggests the importance of at least these two cortical regions for anxiolytic action. Differences between patients with generalized anxiety disorder and normals were restricted to the occipital and temporal regions. These results suggest the importance of multilead recording in assessing EEG correlates of drug action.

Adult↗
PubMed1995

Imaging the dorsal hippocampus: light reflectance relationships to electroencephalographic patterns during sleep.

We assessed the correspondence of 660 nm light reflectance changes from the dorsal hippocampus with slow wave electroencephalographic (EEG) activity during quiet sleep (QS) and rapid eye movement (REM) sleep in four cats. An optic probe, attached to a charge-coupled-device (CCD) video camera, was placed on the dorsal hippocampal surface to collect reflectance images simultaneously with EEG, which was measured by macroelectrodes placed around the probe circumference. Spectral estimates of EEG and light reflectance amplitude indicated that reflectance changes occurred in a similar frequency range as EEG changes. Dividing the image into 10 subregions revealed that reflectance changes at the rhythmical slow wave activity band (RSA, 4-6 Hz) persisted in localized regions during QS and REM sleep, but regional changes showed considerable wave-by-wave independence between areas and from slow wave electrical activity. Peak frequencies for reflectance changes corresponded to fast RSA frequencies observed in the EEG. Optical changes most likely derive from fast-acting physical phenomena, rather than from alterations in blood perfusion, and provide increased spatial resolution over that offered by electrical measurements.

Animals↗
PubMed1984

Multivariate analysis of diaphragm EMG power spectral moments.

A single derived index of the power spectrum of the diaphragm electromyogram (EMG) has been used in detecting fatigue. Additional information in the EMG could be used to study diaphragm function in other respiratory conditions. Diaphragm EMGs and calculated power spectra at 12 frequencies were measured in normal subjects and patients with severe chronic obstructive pulmonary disease during several respiratory maneuvers both before and after treadmill exercise to dyspnea. The power spectra were characterized by the first five moments. Changes in the EMG were similar when assessed by multivariate analysis of variance of the spectral estimates or of the moments. Factor analysis provided two latent variables that correlated with the first and second moment respectively. The first moment was found to be the most sensitive single discriminant of fatigue and is only slightly improved by adding other information. It is concluded that the first and second moments of the EMG power spectra provide a concise, parsimonious description of the changes in the EMG.

Adult↗
PubMed1992

Very high-frequency rhythmic activity during SEEG suppression in frontal lobe epilepsy.

Intracerebral EEG (SEEG) recordings showing the development of fast rhythmic activity at seizure onset provide important evidence for the localisation of an epileptic focus. However, very high-frequency activity (greater than 50 Hz) of low amplitude relative to the background may not be apparent on the paper record due to the limited bandwidth and dynamic range of conventional SEEG recording and display methods. The use of a digital telemetry system with a fast sampling rate (400 Hz) and a wide dynamic range (1 microV resolution, 4 mV range) has allowed us to utilize expanded time scale SEEG plots and autoregressive spectral estimation to identify this activity in chronic SEEG studies. This may be particularly useful in frontal lobe epilepsy, where rapid propagation often prevents adequate localization using conventional methods of analysis.

Adult↗
PubMed1983

Development of sleep-waking temporal sequencing in infants at risk for the Sudden Infant Death Syndrome.

The periodic organization of waking, quiet sleep, and active sleep was studied in control infants and siblings of victims of the Sudden Infant Death Syndrome. Spectral estimates of all-night binary state time series recorded at 1 week and 1, 2, 3, 4, and 6 months of age revealed disturbed patterns of sleep states, especially in active sleep, from as early as the first week of life. These disruptions continued until at least 6 months of age. These data support the contention that the temporal patterning of sleep state can be used as an important neurologic marker for development.

Female↗
PubMed1985

Transient interactions between blood pressure, respiration and heart rate in man.

Auto regressive spectral estimation techniques have been used to follow transient interactions between mean blood pressure, respiration and heart rate. This demonstrates that these inter-relationships are variable. It is concluded that while central modulation of heart rate is the major factor in the interactions, when the heart rate is fixed, peripheral modulation of the blood pressure by respiration is clearly demonstrated.

Adult↗
PubMed1986

Application of the Pisarenko Harmonic Decomposition method to physiological data.

In this paper the Pisarenko Harmonic Decomposition (PHD) method is presented as a technique for short duration spectral estimation; it has been tested under various conditions to provide guidelines for its implementation. There appears to be a range of frequencies for which the PHD method gives non-biased frequency estimates. A rapid method for obtaining the sampling frequency required for non-biased frequency estimates is also discussed.

Adult↗
PubMed1996

Quantitative EEG in the prediction of antidepressant response to imipramine.

The purpose of this study was to examine the utility of quantitative electroencephalography (QEEG) in the prediction of response to imipramine in depressed patients. Forty patients with a diagnosis of unipolar depression were subjected to a placebo washout and were assessed at pre-drug, 3 h after their first dose of imipramine, and again 2 weeks into treatment. Following 4 weeks of open imipramine treatment, patients were separated into responder (R) and non-responder (NR) groups. Statistical analysis of the 29 patients who completed the study focused on group comparisons of power spectral estimates in four frequency bands from multi-channel recordings. Results showed that theta power differentiated R and NR groups prior to treatment, in response to an acute test dose, as well as after 2 weeks of active drug treatment. Results based on this exploratory study suggest that QEEG may be a useful early predictor of response to imipramine.

Adult↗
PubMed1990

Selection of the order of autoregressive models for spectral analysis of Doppler ultrasound signals.

Autoregressive modelling includes a model identification procedure, that is, it is necessary to choose the order of the autoregressive (AR) process that best describes the given finite record (frame) of the signal. Four previously suggested procedures to choose the "best order" of AR processes have been tested: The "first zero crossing" of the autocorrelation function (FZC), the "final prediction error" (FPE), "Akaike's information criterion" (AIC), and the "criterion autoregressive transfer-function" (CAT). It was found that: (i) For more than 98% of the 1280 frames of Doppler signals analyzed the order selected by the various criteria was ten or less. (ii) For the same records of Doppler signals, FPE, AIC and CAT behave in a very similar manner, but the FZC criterion underestimates the order in relation to the others. (iii) For true AR processes, the order selected is frequently different from the true AR order when frames of 64 samples are used. When more samples are used FPE, AIC and CAT tend to select the correct order. (iv) The effect on the spectral estimate of using too high a model order is usually insignificant, while using too low an order can change the estimate more dramatically, that is, overestimating the model order is better than underestimating it.

Analysis of Variance↗
PubMed1995

Adaptive SVD-based AR model order determination for time-frequency analysis of Doppler ultrasound signals.

The short-time Fourier transform provides a picture of the spectral components temporal location in time-varying signals, but its performance is limited by the intrinsic trade-off between time and frequency resolutions. In the present study, this problem is addressed using a spectral estimator based on a combination of the autoregressive (AR) modeling technique and a new automatic model order selection method. The order estimation is achieved by means of the singular value decomposition (SVD) of an appropriate data matrix in conjunction with a new criterion (dynamic mean evaluation, DME). The latter is used to decide which singular values correspond to the signal and which to the noise subspaces, avoiding an a priori threshold definition, thus giving the variable AR model order on consecutive short-time segments. Combination of the AR high frequency resolution capabilities and the SVD plus DME robustness and simplicity make the overall method reliable in many practical applications, mainly in the analysis of time-varying signals corrupted by noise. The proposed procedure has been applied to benchmark as well as to Doppler signal analysis. Some examples are reported confirming the above-mentioned properties.

Animals↗
PubMed1996

Hippocampal activity during transient respiratory events in the freely behaving cat.

We measured dorsal hippocampal activity accompanying sighs and apnea using reflectance imaging and electrophysiologic measures in freely behaving cats. Reflected 660-nm light from a 1-mm2 area of CA1 was captured during sighs and apnea at 25 Hz through a coherent image conduit coupled to a charge coupled device camera. Sighs and apnea frequently coincided with state transitions. Thus, state transitions without apnea or sighs were separately assessed to control for state-related activity changes. All dorsal hippocampal sites showed discrete regions of activation and inactivation during transient respiratory events. Imaged hippocampal activity increased 1-3 s before the enhanced inspiratory effort associated with sighs, and before resumption of breathing after apnea. State transitions lacking sighs and apnea did not elicit analogous optical activity patterns. The suprasylvian cortex, a control for site, showed no significant overall reflectance changes during phasic respiratory events, and no discrete regions of activation or inactivation. Spectral estimates of hippocampal electroencephalographic activity from 0-12 Hz showed significantly increased power at 3-4 Hz rhythmical slow activity before sighs and apnea, and increased 5-6 Hz rhythmical slow activity power during apnea, before resumption of breathing. Imaged activity and broadband hippocampal electroencephalogram power decreased during sighs. We propose that increased hippocampal activity before sigh onset and apnea termination indicates a role for the hippocampus in initiating inspiratory effort during transient respiratory events.

Animals↗
PubMed1988

Quantification of motor function in toxicology.

Disturbances of movement and other motor functions can result from exposure to toxicants and drugs. Sometimes, as with acute exposure to ethanol or solvents, these effects disappear when exposure ends. Other times, as with manganese, haloperidol, or chronic ethanol, motor disturbances are irreversible and may even lie undetected until after exposure has ended. Motor disturbances can take on many guises, including tremor, difficulty in positioning, fatigue, or rigidity. Techniques for measuring these different endpoints in primates will be addressed. One preparation that enables the simultaneous monitoring of positioning, tremor, and operant behavior in nonhuman primates is described, and tactics for obtaining spectral estimates of tremor from a positioning task are outlined. The spectra obtained from this preparation are reliable and valid: they are stable over a period of a year, they correspond to spectra obtained from accelerometers, and are altered by acute administration of ethanol or oxotremorine. These two drugs had opposite effects on tremor but affected bar positioning in a similar manner.

Animals↗
PubMed1986

Application of autoregressive modelling in magnetic resonance imaging to remove noise and truncation artifacts.

Magnetic resonance imaging data is conventionally reconstructed using two dimensional discrete Fourier transforms. However, there is growing interest in other types of spectral estimation which minimize noise and artifacts due to truncated data. This note presents preliminary results--showing the improvement obtainable using a modified autoregressive model, the Transient Error method.

Algorithms↗
PubMed1994

Spectral analysis of laser Doppler signals in real time using digital processing.

A versatile spectrum analyser was developed to generate and display laser Doppler shift signals, and derived parameters, continuously in real time using a digital signal processing chip. A major attraction of the system is that it is entirely programmable, so that both the algorithms and the attributes of the system, such as window function and frame overlap, can be easily altered. It was used to investigate the relative merits of a variety of algorithms using a blood-flow phantom. An index based on the first moment of the Doppler power spectrum was found to be the most reliable flow indicator, with linearity extending towards a velocity of 5 mm s-1 for a blood haematocrit of 5%. The system is not limited to analysis based on the fast Fourier transform (FFT), and is suitable for non-linear techniques such as maximum entropy spectral estimation (MESE).

Algorithms↗
PubMed1996

A review of parametric modelling techniques for EEG analysis.

This review provides an introduction to the use of parametric modelling techniques for time series analysis, and in particular the application of autoregressive modelling to the analysis of physiological signals such as the human electroencephalogram. The concept of signal stationarity is considered and, in the light of this, both adaptive models, and non-adaptive models employing fixed or adaptive segmentation, are discussed. For non-adaptive autoregressive models, the Yule-Walker equations are derived and the popular Levinson-Durbin and Burg algorithms are introduced. The interpretation of an autoregressive model as a recursive digital filter and its use in spectral estimation are considered, and the important issues of model stability and model complexity are discussed.

Biomedical Engineering↗
PubMed2004

Independent component analysis of dynamic brain responses during visuomotor adaptation.

To investigate the spatial and temporal changes in electro-cortical brain activity and hand kinematics during the acquisition of an internal model of a novel screen-cursor transformation, we employed single-trial infomax independent component analysis (ICA), spectral estimation, and kinematics methods. Participants performed center-out drawing movements under normal and rotated visual feedback of pen movements displayed on a computer screen. Clustering of task-related and adaptation-related independent components identified a selective recruitment of brain activation/deactivation foci associated with the exposure to the distorted visual feedback, including networks associated with frontal-, central-, and lateral-posterior alpha rhythms, and frontal-central error-related negativity potential associated with transient theta and low beta rhythms locked to movement onset. Moreover, adaptation to the rotated reference frame was associated with a reduction in the imposed directional bias and decreases in movement path length and movement time by late-exposure trials, as well as after-effects after removal of the visual distortion. The underlying spatiotemporal pattern of activations is consistent with recruitment of frontal-parietal, sensory-motor, and anterior cingulate cortical areas during visuomotor adaptation.

Adaptation, Physiological↗