Hubert deBruin

Influence of nitric oxide and vasoactive intestinal peptide on the spontaneous and triggered electrical and mechanical activities of the canine ileum

Modulation of canine ileal pacemaker activity by nitric oxide (NO) or vasoactive intestinal peptide (VIP) was studied during recording of the intracellular electrical and mechanical activity from the entire muscularis externa and from an isolated circular muscle preparation both cut in the long axis of the circular muscle. In the whole-thickness preparation with cholinergic and adrenergic nerve function blocked, the inhibitory junction potentials (IJPs) recorded near the myenteric plexus (MyP) or deep muscular plexus (DMP) were abolished by omega-conotoxin GVIA (omega-CTX, 10(-7) to 3 x 10(-7) M), tetrodotoxin (TTX, 1 microM), or the NO synthase (NOS) inhibitor N omega-nitro-L-arginine (L-NNA at 50 microM). IJPs from electrical field stimulation triggered slow waves (TSWs); after TTX or omega-CTX, TSWs still occurred, advanced in time and increased in amplitude after TTX. Addition of L-NNA advanced the onset of the TSWs after omega-CTX. TTX, L-NNA, or omega-CTX left the resting membrane potentials, the characteristics of spontaneous slow waves, or TSWs evoked by a long stimulating pulse unchanged. L-NNA at 100 microM enhanced the amplitude but not the frequency of spontaneous slow waves. TTX and NOS blockers all increased circular muscle contractions associated with the spontaneous slow waves and TSWs. In isolated circular muscle preparations, the NOS inhibitors N omega-nitro-L-arginine methyl ester (L-NAME at 300 microM) or L-NNA at 100 microM abolished the IJPs and increased the regularity and amplitude of spontaneous slow waves and associated contractions, but TSWs could not be evoked before or after NOS inhibition. The NO donor 3-morpholinosydnonimine hydrochloride (SIN-1) at 200 microM caused hyperpolarizations (10-15 mV) similar to the IJP mediator, attenuated the IJPs, and abolished mechanical activities. SIN-1 increased the slow wave frequency but decreased the amplitude and duration of spontaneous slow waves and TSWs. VIP (10(-6) M) decreased contraction and slow wave amplitude and prolonged IJP duration without affecting membrane potential or slow wave frequency. We conclude that spontaneous slow waves and TSWs originate independently of neural activity. Pacemaking regions possess inhibitory neural inputs that release NO to mediate IJPs and relaxation and influence the delay before a TSW. NO (not VIP) release from nerves inhibits initiation of spontaneous slow waves or TSWs near the MyP, and spontaneous NO release modulates pacemaking activity from the DMP.

EEG signal classification based on a Riemannian distance measure

We proposed a k-nearest neighbor EEG signal classification algorithm using a dissimilarity measure defined with a Riemannian distance. The EEG signals are characterized by curves on the manifold of power spectral density matrices. By endowing the manifold with a Riemannian metric we obtain the Riemanian distance between two points on the manifold. Based on this, the measure of dissimilarity is then defined. To best facilitate the classification of similar and dissimilar EEG signal sets, we obtain the optimally weighted Riemannian distance aiming to render signals in different classes more separable while those in the same class more compact. The motivation of the algorithm design and verification method are also provided. Experimental results are presented showing the superior performance of the new metric in comparison to the k-nearest neighbor EEG signal classification algorithm using the commonly used Kullback-Leibler (KL) dissimilarity measure.

Using pre-treatment EEG data to predict response to SSRI treatment for MDD

The problem of identifying in advance the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, we propose a machine learning (ML) methodology to predict the response to a selective serotonin reuptake inhibitor (SSRI) medication in subjects suffering from major depressive disorder (MDD), using pre-treatment electroencephalograph (EEG) measurements. The proposed feature selection technique is a modification of the method of Peng et al [10] that is based on a Kullback-Leibler (KL) distance measure. The classifier was realized as a kernelized partial least squares regression procedure, whose output is the predicted response. A low-dimensional kernelized principal component representation of the feature space was used for the purposes of visualization and clustering analysis. The overall method was evaluated using an 11-fold nested cross-validation procedure for which over 85% average prediction performance is obtained. The results indicate that ML methods hold considerable promise in predicting the efficacy of SSRI antidepressant therapy for major depression.

Diagnosis of psychiatric disorders using EEG data and employing a statistical decision model

An automated diagnosis procedure based on a statistical machine learning methodology using electroencephalograph (EEG) data is proposed for diagnosis of psychiatric illness. First, a large collection of candidate features, mostly consisting of various statistical quantities, are calculated from the subjects EEG. This large set of candidate features is then reduced into a much smaller set of most relevant features using a feature selection procedure. The selected features are then used to evaluate the class likelihoods, through the use of a mixture of factor analysis (MFA) statistical model [7]. In a training set of 207 subjects, including 64 subjects with major depressive disorder (MDD), 40 subjects with chronic schizophrenia, 12 subjects with bipolar depression and 91 normal or healthy subjects, the average correct diagnosis rate attained using the proposed method is over 85%, as determined by various cross-validation experiments. The promise is that, with further development, the proposed methodology could serve as a valuable adjunctive tool for the medical practitioner.

Speculations surrounding a spinal reflex

A method has been developed for measuring the Ia fibre input/motoneurone output relationship for the soleus H-reflex in healthy human volunteers. The shift in the relationship during weak toe extension, and in some subjects during weak plantar flexion, indicates the imposition of an inhibitory mechanism, presumably presynaptic. From these observations, and others previously made on long-loop reflexes, it is argued that the inhibitory mechanism may have evolved to suppress unwanted information from the periphery, not only during movement but in the resting state, and that this development was a necessary accompaniment of encephalisation.

Review: Recursive hidden input estimation in nonlinear dynamic systems with varying amounts of a priori knowledge

Estimation of additive driving-forces (e.g., hidden inputs) in nonlinear dynamic systems is addressed with varying amounts of a priori knowledge on system models exemplified by three typical scenarios: (1) there is no sufficient prior knowledge to build a mathematical model of the underlying system; (2) the system is partially described by an analytic model; (3) a complete and accurate model of the underlying system is available. Three algorithms are proposed for each scenario and analyzed comprehensively. The adaptive driving-force estimator (ADFE) [1,2] is used for the retrieval of driving-forces using only the system outputs for the first scenario. A variational Bayesian and a Bayesian algorithm are established for the second and the third scenarios, respectively. All three algorithms are studied in depth on a nonlinear dynamic system with equivalent computational resources, and the Posterior Cramer-Rao Lower Bounds (PCRLB) are specified as performance metrics for each case. The results lead to a thorough understanding of the capabilities and limitations of the ADFE, which manifests itself as an effective technique for the estimation of rapidly varying hidden inputs unless a complete and accurate model is available. Moreover, the methods developed in this paper facilitate a suitable framework for the construction of new and efficient tools for various input estimation problems. In particular, the proposed algorithms constitute a readily available basis for the design of novel input residual estimators to approach the Fault Diagnosis and Isolation (FDI) problem from a new and different perspective.

Effects of Chronic Cerebellar Stimulation (CCS) Setting on the Gait and Speech of a Spastic Cerebral Palsy Adult

A single (N = 1) spastic cerebral palsy adult who had experienced Chronic Cerebellar Stimulation (CCS) for 9 years without any change in the stimulator settings was assessed at six different stimulator settings. These voitage settings varied from 0 volts to 40 volts and frequencies of stimulation from 0 to 200 Hz. Stimulation was with bipolar rectangular pulses with less than 0.2 C/mm2 charge per phase. Responses measured at each setting were quantitative gait, speech, and somatosensory evoked potential measurements. Additional clinical assessments were done by a neurologist and speech therapist. Alteration in stimulator settings occurred 1 week apart to allow for stabilization and all assessments were completed in the same sequence each day. None of the individual stimulator settings were known to any of the assessors or to the patient. The results showed consistently that the patients gait and speech were poorest when the stimulator was switched off completely. Switching on the stimulator caused improved function according to all assessments. There was consistent improvement in gait and speech when the rate of the cerebellar stimuli was high (for voltages between 0 and 40 V). Changing the voltage (within the range 0 to 40 V), while keeping the frequency of stimulation constant, did not appear to have as much effect. This preliminary evaluation suggests that the technique of CCS is safe and can improve function in a measurable manner.

Heart Rate and PO2 in the Fetal Lamb

Information about fetal oxygenation in chronically catheterized animal subjects has previously depended on intermittent measurement of PO2 or O2 saturation in blood samples withdrawn from intravascular catheters. Recently, the performance and durability of implanted oxygen electrodes in both blood and tissue has improved. Thus, continuous monitoring of oxygen levels over many hours or days is now possible and we have previously reported (1) our experience with implantation of galvanic PO2 electrodes in fetal and maternal tissues in the pregnant ewe.

Quantitative input-output relationships between human soleus muscle spindle afferents and motoneurons

A method is described that, for the first time, allows instantaneous estimation of the Ia fiber input to human soleus motoneurons following electrical stimulation of the tibial nerve. The basis of the method is to determine the thresholds of the most and least excitable 1a fibers to electrical stimulation, and to treat the intervening thresholds as having a normal distribution about the mean; the validity of this approach is discussed. It was found that, for the same Ia fiber input, the percentage of soleus motoneurons contributing to the H (Hoffmann)-reflex differed considerably among subjects; when the results were pooled, however, there was an approximately linear relationship between Ia input and motoneuron output. Weak extension of the great toe diminished the soleus motoneuron reflex discharge in all but 2 of 16 subjects; the results for weak ankle plantarflexion were less consistent, but overall, there was a reduction in soleus motoneuron output also. The methodology should provide new insights into disorders of movement and tone, especially as it permits estimates of motoneuron depolarization to be made. NEW & NOTEWORTHY Assuming a normal distribution of Ia fiber thresholds to electrical stimulation and using the H-reflex, we determined for the first time an Ia input-α-motoneuron output relationship for the human soleus muscle. The relationship varies greatly among subjects but, overall, is approximately linear. Minimal contraction of a toe muscle alters the relationship dramatically, probably due to presynaptic inhibition of Ia fibers. Drawing on the literature, we can calculate changes in α-motoneuron membrane potential.

Chapter 10 Motor unit estimates in amyotrophic lateral sclerosis

Publisher Summary There has been increasing interest in the application of motor unit number estimation (MUNE) methodology to the diagnosis and quantitative assessment of muscle denervation and of amyotrophic lateral sclerosis (ALS), in particular. MUNE is ideally suited to the study of ALS for a number of reasons. The methodology measures directly the primary effect of the disease process, the loss of motor units, and functioning motoneurons. Further, it is quantitative, reproducible, and usually noninvasive, and, therefore, lends itself to longitudinal studies, in which the natural time course of the disease and the effects of therapeutic interventions can be investigated. In the first part of this chapter, the principle of MUNE is described, together with the advantages and limitations of the original method and of the various modifications that have appeared. The muscles, to which this type of examination has been applied, are then surveyed and the corresponding means MUNEs given for the normal population. The chapter then discusses the ALS and, by presenting the MUNEs found at the initial electromyography (EMG) examination, indicates the diagnostic usefulness of this test. By studying the same patients on subsequent occasions and by measuring the amplitudes of the putative motor unit potentials (MUPs) recorded during each MUNE, it is possible to determine the time-course of the ALS disease process. The similarities and differences between ALS and spinal muscular atrophy (SMA) are considered, not only for their intrinsic interest but also for the further light that they shed on the pathogenetic mechanisms of the two types of disorder. The potential usefulness of MUNE in therapeutic trials on ALS is also examined. Finally, the chapter discusses the nature of the etiological agent in some of the sporadic cases of ALS.