Biomedical subjects

J Muthuswamy

Publications and source records attributed to J Muthuswamy.

7 recordsLinked to original sources

PubMed2002

Vulnerability of the thalamic somatosensory pathway after prolonged global hypoxic-ischemic injury.

The aim of this study was to test the hypothesis that under prolonged global ischemic injury, the somatosensory thalamus and the cortex would manifest differential susceptibility leading to varying degrees of thalamo-cortical dissociation. The thalamic electrical responses displayed increasing suppression with longer durations of ischemia leading to a significant thalamo-cortical electrical dissociation. The data also point to a selective vulnerability of the network oscillations involving the thalamic relay and reticular thalamic neurons. An adult rat model of asphyxial cardiac arrest involving three cohorts with 3 min (G1, n=5), 5 min (G2, n=5) and 7 min (G3, n=5) of asphyxia respectively was used. The cortical evoked response, as quantified by the peak amplitude at 20 ms in the cortical evoked potential, recovers to more than 60% of baseline in all the cases. The multi-unit responses to the somatosensory stimuli recorded from the thalamic ventral posterior lateral (VPL) nuclei consists typically of three components: (1). the ON response (<30 ms after stimulus), (2). the OFF response (period of inhibition, from 30 ms to 100 ms after stimulus) and (3). rhythmic spindles (beyond 100 ms after stimulus). Asphyxia has a significant effect on the VPL ON response at 30 min (P<0.025), 60 min (P<0.05) and 90 min (P<0.05) after asphyxia. Only animals in G3 show a significant suppression (P<0.05) of the VPL ON response when compared to the sham group at 30 min, 60 min and 90 min after asphyxia. There was no significant reduction in somatosensory cortical N20 (negative peak in the cortical response at 20 ms after stimulus) amplitude in any of the three groups with asphyxia indicating a thalamo-cortical dissociation in G3. Further, rhythmic spindle oscillations in the thalamic VPL nuclei that normally accompany the ON response recover either slowly after the recovery of ON response (in the case of G1 and G2) or do not recover at all (in the case of G3).We conclude that there is strong evidence for selective vulnerability of thalamic relay neurons and its network interactions with the inhibitory interneurons in the somatosensory pathway leading to a thalamo-cortical dissociation after prolonged durations of global ischemia.

Action Potentials↗

PubMed2000

Early electrophysiological and histologic changes after global cerebral ischemia in rats.

INTRODUCTION: Cerebral anoxia is fundamental to morbidity and mortality after resuscitation from cardiac arrest. With no proven effective primary therapy for post-anoxic brain injury, the goal of neurologic care are supportive, to provide prognosis and prevention of further complications. With the multifaceted approach using electroencephalography (EEG), somatosensory evoked potentials (SEP), multiunit recordings, behavioral and histologic assessment, we investigated the hyperacute recovery period after resuscitation from cardiac arrest in a rat model to define the value of EEG and SEP in assessing neurologic injury. METHODS: Two cohorts of rats were subjected to sham and graded asphyxic-cardiac arrest. EEG was collected during baseline, at injury, and 90 minutes into recovery in the first rat cohort. EEG bursting during the first 90 minutes of recovery was visually analyzed and correlated with the neurologic recovery at 24 hours after injury. The neurologic recovery was assessed using a neurodeficit score (NDS) with 80 as normal and 0 as brain dead. The next rat cohort subjected to asphyxic-cardiac arrest was studied using SEP and multiunit recording in the VPL; brain histologic studies were performed at 4 hours after the asphyxia. RESULTS: The first rat cohort subjected to graded asphyxic-cardiac arrest emerged from EEG isoelectricity by burst-suppression pattern during the first 90 minutes after asphyxia. Six rats in the good outcome group (NDS >60) showed increased frequency of bursting, leading to return of EEG background activity. Six rats with a bad outcome (NDS <60) had low-intensity and persistent bursting without return of EEG background activity within 90 minutes of observation. Visual assessment showed increased EEG peak burst counts during the first 90 minutes of recovery for the rats with a good outcome compared with the rats with a bad outcome. In the second cohort, the rats were subjected to 3 minutes, 5 minutes, and 7 minutes of asphyxia. The N20 recovered to 60% of baseline in all three cases. The recovery profile of VPL is similar to that of cortical N2O for the animal with 3 minutes of asphyxia. However, VPL response is suppressed after 7 minutes of asphyxia leading to a divergence in the rate of recovery of the cortical N20 and VPL response. In both the animals (with mild and intermediate injury) in which the early response in VPL recovered to more than 50% of baseline, the recovery profile was similar to the N20 in cortical evoked potential (EP). The rats were killed 4 hours after asphyxia and the hematoxylin and eosin stain performed on the brains showed evidence of neuronal injury in the thalamic reticular nucleus (TRN) which seemed to correlate with the duration of asphyxia. CONCLUSION: We present a multimodality assessment of early neurologic recovery following resuscitation from cardiac arrest. The recovery of bursting and high-frequency oscillations may be regulated by interneurons in the TRN. The early selective vulnerability of these interneurons in the TRN may be crucial to the early neurologic recovery as assessed by EP, multiunit recording, EEG, and neurologic behavioral recovery.

Animals↗

PubMed1999

Somatosensory stimulus entrains spindle oscillations in the thalamic VPL nucleus in barbiturate anesthetized rats.

This study reports the effect of external stimuli on spindle oscillations in the somatosensory thalamus of barbiturate anesthetized rats. Multi-unit responses to somatosensory stimuli were measured from the contralateral thalamic ventral posterior lateral (VPL) nucleus at different stimulus strengths and periods. Spindle oscillations could be entrained by the somatosensory stimuli at periods between 2 and 5 s. A resonance phenomenon described as a quiescent pre-stimulus period followed by entrained post-stimulus oscillations, was observed for somatosensory stimuli above the threshold for eliciting cortical evoked potentials and a stimulus period between 2 and 5 s. This study demonstrates an ascending pathway for localized modulation of spindle oscillations.

Anesthesia↗

PubMed1999

Higher-order spectral analysis of burst patterns in EEG.

Burst suppression patterns in electroencephalograms (EEG's) have been observed in a variety of situations including recovery of a subject from a traumatic brain injury. They are associated with grave prognostic outcomes in neonates. We study power spectral parameters and bispectral parameters of the EEG at baseline, during early recovery from an asphyxic arrest (EEG burst patterns) and during late recovery after EEG evolves into a more continuous activity. The bicoherence indexes, which indicate the degree of phase coupling between two frequency components of a signal, are significantly higher within the delta-theta band of the EEG bursts than in the baseline or late recovery waveforms. The bispectral parameters show a more detectable trend than the power spectral parameters. In the second part of the study, we looked into the possibility of higher (> 2)--order nonlinearities in the EEG bursts using the diagonal slices of the polyspectrum. The diagonal elements of the polyspectrum reveal the presence of self-frequency and self-phase coupling of orders higher than two in majority of the EEG bursts studied. The bicoherence indexes and the diagonal elements of the polyspectrum strongly indicate the presence of nonlinearities of order two and in many cases higher, in the EEG generator during episodes of bursting. This indication of nonlinearity in EEG signals provides a novel quantitative measure of brain's response to injury.

Animals↗

PubMed1999

The use of fuzzy integrals and bispectral analysis of the electroencephalogram to predict movement under anesthesia.

The objective of this study was to design and evaluate a methodology for estimating the depth of anesthesia in a canine model that integrates electroencephalogram (EEG)-derived autoregressive (AR) parameters, hemodynamic parameters, and the alveolar anesthetic concentration. Using a parameters, and the alveolar anesthetic concentration. Using a parametric approach, two separate AR models of order ten were derived for the EEG, one from the third-order cumulant sequence and the other from the autocorrelation lags of the EEG. Since the anesthetic dose versus depth of anesthesia curve is highly nonlinear, a neural network (NN) was chosen as the basic estimator and a multiple NN approach was conceived which took hemodynamic parameters, EEG derived parameters, and anesthetic concentration as input feature vectors. Since the estimation of the depth of anesthesia involves cognitive as well as statistical uncertainties, a fuzzy integral was used to integrate the individual estimates of the various networks and to arrive at the final estimate of the depth of anesthesia. Data from 11 experiments were used to train the NN's which were then tested on nine other experiments. The fuzzy integral of the individual NN estimates (when tested on 43 feature vectors from seven of the nine test experiments) classified 40 (93%) of them correctly, offering a substantial improvement over the individual NN estimates.

Anesthesia↗

PubMed1998

Spectral analysis methods for neurological signals.

This paper reviews some novel spectral analysis techniques that are useful for neurological signals in general and EEG signals in particular. First, some drawbacks and limitations of the commonly used Fast Fourier transforms (FFTs) are presented, and then alternative algorithms are outlined. An auto-regressive (AR) modeling based spectral estimation procedure is presented to overcome the problems of lower resolution and 'leakage' effects inherent in the FFT algorithm. For signals which are transient in nature or rapidly time-varying, two alternative algorithms are presented. The first is an adaptive AR parameter estimation algorithm and the second is a wavelet based time-frequency representation algorithm. Finally, a Spectral Distance measure and the Itakura distance measure are presented to quantify the differences between the spectra of two signals in a succinct manner. The application and performance of all the algorithms is illustrated using electroencephalograms (EEGs) recorded in animals during hypoxic asphyxic injury to brain.

Algorithms↗

PubMed1996

A study of electroencephalographic descriptors and end-tidal concentration in estimating depth of anesthesia.

OBJECTIVE: To study the usefulness of three electro-encephalographic descriptors, the average median frequency, the average 90% spectral edge frequency, and a bispectral variable were used with the anesthetic concentrations in estimating the depth of anesthesia. METHODS: Four channels of raw EEG data were collected from seven mongrel dogs in nine separate experiments under different levels of halothane anesthesia and nitrous oxide in oxygen. A tail clamp was used as the stimulus and the dog was labeled as a non-responder or responder based on its response. A bispectral variable of the EEG (just before a tail clamp) and the estimated MAC level of halothane and nitrous oxide combined were the two features used to characterize a single data point. A neural network analysis was done on 48 such data points. A second neural network analysis was done on 47 data points using average 90% spectral edge frequency and the estimated MAC level. The average median frequency of EEG was also evaluated, although a neural network analysis was not done. RESULTS: The first neural network needed nine weights in order to train and correctly classify all of the 12 points in the training set under a training tolerance of 0.2. It could correctly classify all of the remaining 36 data points as either belonging to responders or non-responders. A cross-validation procedure, which estimated the overall performance of the network against future data points, showed that the network misclassified two out of the 48 data points. The second neural network needed 25 weights in order to train and classify correctly all of the 26 points in the training set under a tolerance of 0.2. It was later able to classify all of the 21 points of the test group correctly. CONCLUSIONS: The bispectral variable seems to reduce the non-linearity in the boundary separating the class of non-responders from the class of responders. Consequently, the neural network based on the bispectral variable is less complex than the neural network that uses a power spectral variable as one of its inputs.

Anesthesia, Inhalation↗