A framework for macroscopic phase-resetting curves for generalised spiking neural networks

Brain rhythms emerge from synchronization among interconnected spiking neurons. Key properties of such rhythms can be gleaned from the phase-resetting curve (PRC). Inferring the PRC and developing a systematic phase reduction theory for large-scale brain rhythms remains an outstanding challenge. Here we present a theoretical framework and methodology to compute the PRC of generic spiking networks with emergent collective oscillations. We adopt a renewal approach where neurons are described by the time since their last action potential, a description that can reproduce the dynamical feature of many cell types. For a sufficiently large number of neurons, the network dynamics are well captured by a continuity equation known as the refractory density equation. We develop an adjoint method for this equation giving a semi-analytical expression of the infinitesimal PRC. We confirm the validity of our framework for specific examples of neural networks. Our theoretical framework can link key biological properties at the individual neuron scale and the macroscopic oscillatory network properties. Beyond spiking networks, the approach is applicable to a broad class of systems that can be described by renewal processes.

The formation of oscillatory neuronal assemblies at the network level has been hypothesized to be fundamental to many cognitive and motor functions. One prominent tool to understand the dynamics of oscillatory activity response to stimuli, and hence the neural code for which it is a substrate, is a nonlinear measure called Phase-Resetting Curve (PRC). At the network scale, the PRC defines the measure of how a given synaptic input perturbs the timing of next upcoming volley of spike assemblies: either advancing or delaying this timing. As a further application, one can use PRCs to make unambiguous predictions about whether communicating networks of neurons will phase-lock as it is often observed across the cortical areas and what would be this stable phase-configuration: synchronous, asynchronous or with asymmetric phase-shifts. The latter configuration also implies a preferential flow of information form the leading network to the follower, thereby giving causal signatures of directed functional connectivity. Because of the key position of the PRC in studying synchrony, information flow and entrainment to external forcing, it is crucial to move toward a theory that allows to compute the PRCs of network-wide oscillations not only for a restricted class of models, as has been done in the past, but to network descriptions that are generalized and can reflect flexibly single cell properties. In this manuscript, we tackle this issue by showing how the PRC for network oscillations can be computed using the adjoint systems of partial differential equations that define the dynamics of the neural activity density.

The value of cognitive behavioral therapy on quality of life in addition to pharmacotherapy in adults with ADHD

Introduction

Treatment options for ADHD in adults consist of psycho-education, cognitive behavioral therapy (CBT), pharmacotherapy or a combination thereof. Current studies do not yet provide insights into the additive effects of CBT and pharmacotherapy regarding the quality of life in adults with ADHD.

Objectives

In this study, we investigated the effect of CBT combined with pharmacotherapy on the quality of life in adults with ADHD compared to pharmacotherapy alone.

Methods

In this multicenter prospective cohort study a total of 627 patients were included, 305 where included in the pharmacotherapy only group and 322 in de combination group (CBT and pharmacotherapy). The Adult ADHD Quality-of-Life scale (AAQoL) was conducted at baseline and at the end of treatment.

Results

No significant differences were found in gender or age between groups at baseline. The average improvement in the AAQoL total score in the pharmacotherapy group was 26.81(17.12) and in the combination group 25.45(16.33) and showed no significant difference (t(543) = 0.96, p = 0.34). At baseline the average total score in the pharmacotherapy group was 45.5(12.37) and 42.22(12.73) in the combination group (t(543)=2.86, p = 0.004). The average total score at the end of treatment in the pharmacotherapy and combination group was 72.31(12.99) and 67.67(12.45), respectively (t(543)=426, p <0.001).

Conclusions

To our knowledge, this is the first study to describe the value of CBT in addition to pharmacotherapy on the quality of life in adults with ADHD. Contrary to our expectations, there was no significant effect of CBT in addition to pharmacotherapy on the quality of life.

Disclosure

No significant relationships.

Phase response approaches to neural activity models with distributed delay

In weakly coupled neural oscillator networks describing brain dynamics, the coupling delay is often distributed. We present a theoretical framework to calculate the phase response curve of distributed-delay induced limit cycles with infinite-dimensional phase space. Extending previous works, in which non-delayed or discrete-delay systems were investigated, we develop analytical results for phase response curves of oscillatory systems with distributed delay using Gaussian and log-normal delay distributions. We determine the scalar product and normalization condition for the linearized adjoint of the system required for the calculation of the phase response curve. As a paradigmatic example, we apply our technique to the Wilson-Cowan oscillator model of excitatory and inhibitory neuronal populations under the two delay distributions. We calculate and compare the phase response curves for the Gaussian and log-normal delay distributions. The phase response curves obtained from our adjoint calculations match those compiled by the direct perturbation method, thereby proving that the theory of weakly coupled oscillators can be applied successfully for distributed-delay-induced limit cycles. We further use the obtained phase response curves to derive phase interaction functions and determine the possible phase locked states of multiple inter-coupled populations to illuminate different synchronization scenarios. In numerical simulations, we show that the coupling delay distribution can impact the stability of the synchronization between inter-coupled gamma-oscillatory networks.

Motion-based prediction of external forces and moments and back loading during manual material handling tasks

This paper evaluates a method for motion-based prediction of external forces and moments on manual material handling (MMH) tasks. From a set of hypothesized contact points between the subject and the environment (ground and load), external forces were calculated as the minimal forces at each contact point while ensuring the dynamics equilibrium. Ground reaction forces and moments (GRF&M) and load contact forces and moments (LCF&M) were computed from motion data alone. With an inverse dynamics method, the predicted data were then used to compute kinetic variables such as back loading. On a cohort of 65 subjects performing MMH tasks, the mean correlation coefficients between predicted and experimentally measured GRF for the vertical, antero-posterior and medio-lateral components were 0.91 (0.08), 0.95 (0.03) and 0.94 (0.08), respectively. The associated RMSE were 0.51 N/kg, 0.22 N/kg and 0.19 N/kg. The correlation coefficient between L5/S1 joint moments computed from predicted and measured data was 0.95 with a RMSE of 14 Nm for the flexion/extension component. In conclusion, this method allows the assessment of MMH tasks without force platforms, which increases the ecological aspect of the tasks studied and enables performance of dynamic analyses in real settings outside the laboratory.

Accuracy and kinematics consistency of marker-based scaling approaches on a lower limb model: a comparative study with imagery data

Medical images are not typically included in protocol of motion laboratories. Thus, accurate scaling of musculoskeletal models from optoelectronic data are important for any biomechanical analysis. The aim of the current study was to identify a scaling method based on optoelectronic data, inspired from literature, which could offer the best trade-off between accurate geometrical parameters (segment lengths, orientation of joint axes, marker coordinates) and consistent inverse kinematics outputs (kinematic error, joint angles). The methods were applied on 26 subjects and assessed with medical imagery building EOS-based models, considered as a reference. The main contribution of this paper is to show that the marker-based scaling followed by an optimisation of orientation joint axes and markers local coordinates, gives the most consistent scaling and joint angles with EOS-based models. Thus, when a non-invasive mean with an optoelectronic system is considered, a marker-based scaling is preliminary needed to get accurate segment lengths and to optimise joint axes and marker local coordinates to reduce kinematic errors.AbbrevationsAJCAnkle joint centreCKEcumulative kinematic errorDoFdegree of freedomEBEOS-basedHBheight-basedHJChip joint centreKJCknee joint centreMBmarker-basedMSMmusculoskeletal modelsSPMstatistical parametric mappingSTAsoft tissue artifactEB_a.m∗EOS-based with optimised joint axes, and all model markers coordinatesMB_a.m∗marker-based with optimised joint axes, and all model markers coordinatesMB_l.a.mmarker-based with optimised segment lengths, joint axes, and selected model markers coordinatesASISanterior superior illiac spinePSISposterior superior illiac spine.

Macroscopic phase resetting-curves determine oscillatory coherence and signal transfer in inter-coupled neural circuits

Macroscopic oscillations of different brain regions show multiple phase relationships that are persistent across time and have been implicated in routing information. While multiple cellular mechanisms influence the network oscillatory dynamics and structure the macroscopic firing motifs, one of the key questions is to identify the biophysical neuronal and synaptic properties that permit such motifs to arise. A second important issue is how the different neural activity coherence states determine the communication between the neural circuits. Here we analyse the emergence of phase-locking within bidirectionally delayed-coupled spiking circuits in which global gamma band oscillations arise from synaptic coupling among largely excitable neurons. We consider both the interneuronal (ING) and the pyramidal-interneuronal (PING) population gamma rhythms and the inter coupling targeting the pyramidal or the inhibitory neurons. Using a mean-field approach together with an exact reduction method, we reduce each spiking network to a low dimensional nonlinear system and derive the macroscopic phase resetting-curves (mPRCs) that determine how the phase of the global oscillation responds to incoming perturbations. This is made possible by the use of the quadratic integrate-and-fire model together with a Lorentzian distribution of the bias current. Depending on the type of gamma (PING vs. ING), we show that incoming excitatory inputs can either speed up the macroscopic oscillation (phase advance; type I PRC) or induce both a phase advance and a delay (type II PRC). From there we determine the structure of macroscopic coherence states (phase-locking) of two weakly synaptically-coupled networks. To do so we derive a phase equation for the coupled system which links the synaptic mechanisms to the coherence states of the system. We show that a synaptic transmission delay is a necessary condition for symmetry breaking, i.e. a non-symmetric phase lag between the macroscopic oscillations. This potentially provides an explanation to the experimentally observed variety of gamma phase-locking modes. Our analysis further shows that symmetry-broken coherence states can lead to a preferred direction of signal transfer between the oscillatory networks where this directionality also depends on the timing of the signal. Hence we suggest a causal theory for oscillatory modulation of functional connectivity between cortical circuits.

Large scale brain oscillations emerge from synaptic interactions within neuronal circuits. Over the past years, such macroscopic rhythms have been suggested to play a crucial role in routing the flow of information across cortical regions, resulting in a functional connectome. The underlying mechanism is cortical oscillations that bind together following a well-known motif called phase-locking. While there is significant experimental support for multiple phase-locking modes in the brain, it is still unclear what is the underlying mechanism that permits macroscopic rhythms to phase lock. In the present paper we take up with this issue, and to show that, one can study the emergent macroscopic phase-locking within the mathematical framework of weakly coupled oscillators. We find that under synaptic delays, fully symmetrically coupled networks can display symmetry-broken states of activity, where one network starts to lead in phase the second (also sometimes known as stuttering states). When we analyse how incoming transient signals affect the coupled system, we find that in the symmetry-broken state, the effect depends strongly on which network is targeted (the leader or the follower) as well as the timing of the input. Hence we show how the dynamics of the emergent phase-locked activity imposes a functional directionality on how signals are processed. We thus offer clarification on the synaptic and circuit properties responsible for the emergence of multiple phase-locking patterns and provide support for its functional implication in information transfer.

Is There a Nonadditive Interaction Between Spontaneous and Evoked Activity? Phase-Dependence and Its Relation to the Temporal Structure of Scale-Free Brain Activity

The aim of our study was to use functional magnetic resonance imaging to investigate how spontaneous activity interacts with evoked activity, as well as how the temporal structure of spontaneous activity, that is, long-range temporal correlations, relate to this interaction. Using an extremely sparse event-related design (intertrial intervals: 52-60 s), a novel blood oxygen level-dependent signal correction approach (accounting for spontaneous fluctuations using pseudotrials) and phase analysis, we provided direct evidence for a nonadditive interaction between spontaneous and evoked activity. We demonstrated the discrepancy between the present and previous observations on why a linear superposition between spontaneous and evoked activity can be seen by using co-occurring signals from homologous brain regions. Importantly, we further demonstrated that the nonadditive interaction can be characterized by phase-dependent effects of spontaneous activity, which is closely related to the degree of long-range temporal correlations in spontaneous activity as indexed by both power-law exponent and phase-amplitude coupling. Our findings not only contribute to the understanding of spontaneous brain activity and its scale-free properties, but also bear important implications for our understanding of neural activity in general.

Macroscopic phase-resetting curves for spiking neural networks

The study of brain rhythms is an open-ended, and challenging, subject of interest in neuroscience. One of the best tools for the understanding of oscillations at the single neuron level is the phase-resetting curve (PRC). Synchronization in networks of neurons, effects of noise on the rhythms, effects of transient stimuli on the ongoing rhythmic activity, and many other features can be understood by the PRC. However, most macroscopic brain rhythms are generated by large populations of neurons, and so far it has been unclear how the PRC formulation can be extended to these more common rhythms. In this paper, we describe a framework to determine a macroscopic PRC (mPRC) for a network of spiking excitatory and inhibitory neurons that generate a macroscopic rhythm. We take advantage of a thermodynamic approach combined with a reduction method to simplify the network description to a small number of ordinary differential equations. From this simplified but exact reduction, we can compute the mPRC via the standard adjoint method. Our theoretical findings are illustrated with and supported by numerical simulations of the full spiking network. Notably our mPRC framework allows us to predict the difference between effects of transient inputs to the excitatory versus the inhibitory neurons in the network.

[The effect of mood-stabilising drugs on cytokine levels in bipolar disorder: a systematic review]

Veranderde cytokineconcentraties bij personen met een bipolaire stoornis ten opzichte van controle-personen suggereren een rol van het immuunsysteem in de pathofysiologie van bipolaire stoornis. Farmacotherapie is een belangrijke verstorende factor in klinisch onderzoek naar cytokineconcentraties.<br/> DOEL: Evalueren van cytokineconcentraties bij medicatievrije patiënten met een bipolaire stoornis en van het effect van stemmingsstabiliserende geneesmiddelen op deze concentraties.<br/> METHODE: We doorzochten systematisch PubMed en Embase naar klinische studies die cytokineconcentraties bij medicatievrije patiënten met een bipolaire stoornis beschrijven of het effect van een individueel stemmingsstabiliserend geneesmiddel op deze concentraties evalueren.<br/> RESULTATEN: Van de 564 gescreende artikelen werden er 17 geïncludeerd. Resultaten bij medicatievrije patiënten toonden stemmingsgerelateerde cytokineveranderingen. Hoewel geen data over de kortetermijneffecten van lithium beschikbaar waren, was lithiumgebruik langer dan 2 maanden geassocieerd met normale cytokineconcentraties. Twee studies rapporteerden geen effect van valproïnezuur. We vonden geen studies over carbamazepine, lamotrigine of antipsychotica.<br/> CONCLUSIE: Dit systematisch literatuuroverzicht toont stemmingsgerelateerde cytokineveranderingen bij medicatievrije patiënten met een bipolaire stoornis met de meeste evidentie voor een pro-inflammatoire immuunrespons tijdens manie. Euthymie en langdurig lithiumgebruik zijn geassocieerd met normale cytokineconcentraties. Er is een belangrijke methodologische heterogeniteit en onvoldoende replicatie tussen studies. Longitudinale studies met medicatievrije beginmetingen, gerandomiseerde monotherapeutische behandelprotocollen en nauwkeurige monitoring van stemming zijn noodzakelijk.<br/> BACKGROUND: Alterations of the cytokine level in persons with bipolar disorder - when compared to controls - suggest that the immune system plays a role in the pathophysiology of bipolar disorder. Pharmacotherapy is an important confounding factor in clinical research on cytokine levels.<br/> AIM: To evaluate the evidence on cytokine levels in medication-free bipolar disorder and to study the effects that single mood-stabilising drugs have on these levels.<br/> METHOD: We searched PubMed and Embase systematically in order to single out clinical studies that reported on cytokine levels in medication-free bipolar disorder or that commented on the effects of single mood-stabilising drugs on cytokine levels.<br/> RESULTS: Of the 564 articles that we screened, we detected 17 that were particularly relevant for our investigation. Results for medication-free patients point to mood-related alterations in cytokine levels. Although we found no data relating to short-term effects of lithium, the use of lithium in euthymic populations was associated with normal cytokine levels. Two studies reported no effect of valproate. We did not find any studies relating to carbamazepine, lamotrigine or antipsychotics.<br/> CONCLUSION: Our systematic review of the literature suggests the presence of mood-related changes in cytokine levels in medication-free patients with bipolar disorder, with the most evidence for a proinflammatory response during a manic episode. Euthymia and long-term use of lithium use are associated with normal cytokine levels. There is considerable heterogeneity in the methods used in these studies and too little replication. Future research will have to include longitudinal studies with medication-free baseline measurements. It will also be necessary to draw up single-drug treatment protocols and to conduct intensive mood-related monitoring.

Flow cytometry community fingerprinting and amplicon sequencing for the assessment of landfill leachate cellulolytic bioaugmentation

Flow cytometry (FCM) is a high throughput single cell technology that is actually becoming widely used for studying phenotypic and genotypic diversity among microbial communities. This technology is considered in this work for the assessment of a bioaugmentation treatment in order to enhance cellulolytic potential of landfill leachate. The experimental results reveal the relevant increase of leachate cellulolytic potential due to bioaugmentation. Cytometric monitoring of microbial dynamics along these assays is then realized. The flow FP package is used to establish microbial samples fingerprint from initial 2D cytometry histograms. This procedure allows highlighting microbial communities' variation along the assays. Cytometric and 16S rRNA gene sequencing fingerprinting methods are then compared. The two approaches give same evidence about microbial dynamics throughout digestion assay. There are however a lack of significant correlation between cytometric and amplicon sequencing fingerprint at genus or species level. Same phenotypical profiles of microbiota during assays matched to several 16S rRNA gene sequencing ones. Flow cytometry fingerprinting can thus be considered as a promising routine on-site method suitable for the detection of stability/variation/disturbance of complex microbial communities involved in bioprocesses.

Theoretical connections between mathematical neuronal models corresponding to different expressions of noise

Identifying the right tools to express the stochastic aspects of neural activity has proven to be one of the biggest challenges in computational neuroscience. Even if there is no definitive answer to this issue, the most common procedure to express this randomness is the use of stochastic models. In accordance with the origin of variability, the sources of randomness are classified as intrinsic or extrinsic and give rise to distinct mathematical frameworks to track down the dynamics of the cell. While the external variability is generally treated by the use of a Wiener process in models such as the Integrate-and-Fire model, the internal variability is mostly expressed via a random firing process. In this paper, we investigate how those distinct expressions of variability can be related. To do so, we examine the probability density functions to the corresponding stochastic models and investigate in what way they can be mapped one to another via integral transforms. Our theoretical findings offer a new insight view into the particular categories of variability and it confirms that, despite their contrasting nature, the mathematical formalization of internal and external variability is strikingly similar.

Linear noise approximation for oscillations in a stochastic inhibitory network with delay

Understanding neural variability is currently one of the biggest challenges in neuroscience. Using theory and computational modeling, we study the behavior of a globally coupled inhibitory neural network, in which each neuron follows a purely stochastic two-state spiking process. We investigate the role of both this intrinsic randomness and the conduction delay on the emergence of fast (e.g., gamma) oscillations. Toward that end, we expand the recently proposed linear noise approximation (LNA) technique to this non-Markovian "delay" case. The analysis first leads to a nonlinear delay-differential equation (DDE) with multiplicative noise for the mean activity. The LNA then yields two coupled DDEs, one of which is driven by additive Gaussian white noise. These equations on their own provide an excellent approximation to the full network dynamics, which are much longer to integrate. They further allow us to compute a theoretical expression for the power spectrum of the population activity. Our analytical result is in good agreement with the power spectrum obtained via numerical simulations of the full network dynamics, for the large range of parameters where both the intrinsic stochasticity and the conduction delay are necessary for the occurrence of oscillations. The intrinsic noise arises from the probabilistic description of each neuron, yet it is expressed at the system activity level, and it can only be controlled by the system size. In fact, its effect on the fluctuations in system activity disappears in the infinite network size limit, but the characteristics of the oscillatory activity depend on all model parameters including the system size. Using the Hilbert transform, we further show that the intrinsic noise causes sporadic strong fluctuations in the phase of the gamma rhythm.

Well-posedness of a density model for a population of theta neurons

Population density models used to describe the evolution of neural populations in a phase space are closely related to the single neuron model that describes the individual trajectories of the neurons of the population and which gives in particular the phase-space where the computations are made. Based on a transformation of the quadratic integrate and fire single neuron model, the so called theta-neuron model is obtained and we shall introduce in this paper a corresponding population density model for it. Existence and uniqueness of a solution will be proved and some numerical simulations are presented.

The nicotinergic receptor as a target for cognitive enhancement in schizophrenia: barking up the wrong tree?

RATIONALE

Cognitive symptoms have increasingly been recognized as an important target in the development of future treatment strategies in schizophrenia. The nicotinergic neurotransmission system has been suggested as a potentially interesting treatment target for these cognitive deficits. However, previous research yielded conflicting results, which may be explained by several methodological limitations, such as the failure to include both a group of smoking and non-smoking schizophrenic patients, the use of only a single nicotine dose, and the inclusion of a very limited cognitive battery.

OBJECTIVES

The present study aims at investigating the cognitive effects of nicotine in schizophrenia while addressing these methodological issues.

METHODS

In a double-blind placebo-controlled randomized crossover design, cognitive effects are assessed in smoking (n =16) and non-smoking (n =16) schizophrenic patients after receiving active (1 or 2 mg) or placebo oromucosal nicotine spray.

RESULTS

A modest improving effect of nicotine on attention in the smoking but not the non-smoking group was found. No enhancing effects were found on measures of visual memory, working memory, processing speed, psychomotor speed, or social cognitive functioning in either patient group.

CONCLUSIONS

These findings suggest that the nicotinic receptor only has limited value as a cognitive treatment target in schizophrenia.

Evaluation of a tactile display around the waist for physiological monitoring under different clinical workload conditions

In this study, we have assessed the usability of a tactile belt prototype for clinical monitoring of physiologic patient data in the operating room under low workload (LW) and high workload (HW) conditions. In previous investigations, we have evaluated tactile technology in clinical settings and demonstrated that anesthesiologists have enhanced situational awareness towards adverse clinical events when a tactile display prototype is used as a supplemental monitoring device. To further evaluate the effectiveness of our tactile belt prototype, we compared the effects of workload on the performance of anesthesiologists in terms of accuracy and response time in tactile alert identification. We also administered a post-study questionnaire to evaluate the usability of the tactile belt as well as users' opinions about the device. We found that the response time to tactile alert identification to be faster under LW than under HW, however the accuracy of identification was not statistically different. Participants rated the tactile belt prototype as comfortable to use and the tactile alert scheme as easy to learn. Our findings further support the feasibility and efficacy of vibrotactile devices for enhancing physiological monitoring of patients in clinical environments.

Clinical evaluation of algorithms for context-sensitive physiological monitoring in children

BACKGROUND

Subtle changes in monitored physiological signals might be used to guide clinical actions and give early warning of potential adverse events. Automated early warning systems could enhance the clinician's interpretation of data by instantaneously processing new information and presenting it within the context of previous observations. In this study, we tested algorithms for tracking the behaviour of dynamic physiological systems and automatically detecting key events over time.

METHODS

Algorithms were activated in real-time during anaesthesia to run context-sensitive monitoring of six variables (end-tidal PCO(2), heart rate, exhaled minute ventilation, non-invasive arterial pressure, respiratory rate, and oxygen saturation), alongside standard physiological monitors. The clinical evaluation included real-time feedback on each change point (change in the physiological trend) detected by the algorithms and the completion of a usability questionnaire.

RESULTS

Fifteen anaesthetists completed the evaluation during paediatric surgical cases. A total of 38 cases were evaluated, with a mean duration of 103 (102) min. The mean number of change points per case was 22.8 (23.4). Sixty-one per cent of all rated change points were considered clinically significant, and <7% were due to artifacts.

CONCLUSIONS

The algorithms were able to detect a range of clinically significant physiological changes during paediatric anaesthesia, and were considered useful by participating anaesthetists. These findings indicate that automated detection of context-sensitive changes is possible and could be used by early warning systems during physiological monitoring. Further investigations are required to assess how this information can best be communicated to the anaesthetist.

Optimizing the tactile display of physiological information: vibro-tactile vs. electro-tactile stimulation, and forearm or wrist location

Anesthesiologists use physiological data monitoring systems with visual and auditory displays of information to monitor patients in the operating room (OR). The efficacy of visual-audio systems may impose an increase in patient risk when the demand for constant switching of attention between the patient and the visual monitoring system is high. This is evidenced by auditory alarms frequently being neglected in a noisy OR environment. Hence, the use of a complementary patient data monitoring system, which utilizes other sensory modalities, could be of great value. In this paper, we describe a series of experiments designed to determine the performances of a tactile display that could be used to convey patient's physiological information to the attending anesthesiologist. We tested both vibro-tactile and electro-tactile display prototypes in their ability to convey information using an alert scheme of four distinct tactile stimuli. Using pseudo-clinical data, the display was designed, for example, to provide an alert when a change in the monitored heart rate occurred. Based on previous research in human physiology and psychophysics, we selected the forearm and wrist of the user's non-dominant hand as the stimulation site. In our study of 30 subjects, we evaluated the response time and accuracy of tactile pattern recognition to compare (1) the performance of a vibro-tactile display on the forearm (VF) and an electro-tactile display on the forearm (EF), and (2) the localization of stimulation between the forearm (VF) and a vibro-tactile display on the wrist (VW). A post-study questionnaire was completed by each subject to assess the comfort and usability of the three prototypes. We found that both VF and VW were superior to the EF in both accuracy and comfort and, that there were no differences between the wrist and the forearm. In conclusion, the tactile-display prototypes designed to alert the clinician of adverse changes in a patient's physiological state efficaciously and unobtrusively delivered these data and warranted further investigation and development.

A non invasive wearable sensor for the measurement of brain temperature

As the thermoregulation centres are deep in the brain, the cerebral temperature is one of the most important markers of fever, circadian rhythms physical and mental activities. However due to a lack of accessibility, the brain temperature is not easily measured. The axillary, buccal, tympanic and rectal temperatures do not reflect exactly the cerebral temperature. Nevertheless the rectal temperature is used as probably the most reliable indicator of the core body temperature. The brain temperature can be measured using NMR spectroscopy, microwave radiometry, near infrared spectroscopy, ultra-sound thermometry. However none of those methods are amenable to long term ambulatory use outside of the laboratory or of the hospital during normal daily activities, sport, etc. The brain core temperature "BCT" sensor, developed by the Biomedical Microsensors dpt of LPM at INSA-Lyon is a flexible active sensor using "zero-heat-flow" principle. The sensor has been used for experimental measurement: brain temperature during mental activity, and in hospital for the study of circadian rhythms. The results are in agreement with the measurement by the rectal probe. There are 2 versions of this sensor: a non ambulatory for the use in hospitals, and an ambulatory version using teletransmission. We are working for improving the autonomy of the ambulatory version up to several days. This wearable biomedical sensor (WBS) can be used for circadian assessment for chronobiology studies and in medical therapies.

Evaluations of tactile displays of physiological monitoring

Physiological monitoring devices are used in the operating room (OR) to identify abnormal changes. They are currently detected by the anesthesiologist from direct observation of visual displays or by auditory cues. In an effort to improve OR safety, we explored the use of an alternative sensory modality, touch, to effectively and accurately convey patients' physiological information. To be accepted [1] such devices need to fulfill five criteria: learnability, errors, efficiency, memorability and satisfaction. We designed and compared various tactile displays in respect to some of these criteria.

Autonomic nervous system response to vibrating and electrical stimuli on the forearm and wrist

In today's operating rooms, anesthesiologists use physiological data monitoring systems with visual and auditory cues to receive patient information. The efficacy of these visual-audio systems is limited by the human limitations of these modalities. Previous studies have shown the potential use of a complementary, or alternate, patient data monitoring technology utilizing another psychophysically relevant modality: the sense of touch via vibro-tactile or electro-tactile stimulation. In this paper, we describe an experiment designed to determine whether the specific type and/or location of such a tactile stimulation device on the arm affects the autonomic nervous system response. In our study, each of 10 participants tested a vibro-tactile display on the forearm (VF), a vibro-tactile display on the wrist (VW), and an electro-tactile display on the forearm (EF) in random order. Using the LifeShirt, system, electrocardiogram (ECG), respiratory rate (Br), tidal volume (Vt) data were collected. Results showed a higher value of the heart rate and heart rate variability (HRV) when using the VF compared to the VW and EF. We also found that the HRV response for the three tactile prototypes was correlated with the accuracy of tactile pattern identification.

[Intestinal obstruction in pregnancy]

Intestinal obstruction is a rare but dreadful complication of pregnancy. Both the mother and the foetus may be severely affected and even die. The authors here report their recent experience and review the literature. They emphasize that diagnostic pitfalls are common during pregnancy and there appropriate management most often delayed. A multidisciplinary approach is advocated and the specific aspects of this high-risk situation are discussed.

Evaluation of GHb assays in France by national quality control surveys

OBJECTIVE

To evaluate the state of the art concerning GHb assays through analysis of a large-scale quality control survey and to compare the results with those of previous surveys.

RESEARCH DESIGN AND METHODS

A lyophilized hemolyzate prepared from human erythrocytes containing a physiological HbA1c level (5.5%) was sent to 3,500 French laboratories in February of 1995 and assayed as a patient's sample under routine conditions. Distribution of values was analyzed from the reported results for each method. The results were compared with the assigned value (acceptable range: +/- 20%) and with the upper value of the reference range currently used.

RESULTS

Results were obtained from 2,674 laboratories, among which 39% used cation-exchange chromatography methods, 37.5% affinity chromatography, 16% immunological methods, and 7.5% electrophoresis. The number of laboratories using immunological methods increased from 100 to 400 between 1993 and 1995. The overall interlaboratory coefficient of variation (CV) was 20.2%, with within-method CVs ranging between 3.2 and 29.5%. Method-to-method accuracy varied dramatically, with mean HbA1c values ranging from 4.4 to 8.2%. Results from 75% of the laboratories were comprised in the acceptable range; 88% of them reported a value within the normal range of the method used.

CONCLUSIONS

The interlaboratory variability of results illustrates the difficulties encountered by diabetologists in the follow-up of diabetic patients using results obtained from different laboratories. It demonstrates the usefulness of the internationally developed standardization process of GHb measurements and points out the need for laboratories to fulfill good practices.