Comparison of tube-taping versus a tube-holding device for securing endotracheal tubes in adults undergoing surgery in prone position.

BACKGROUND: Endotracheal tube displacement is one of the leading causes for airway related complications. Endotracheal tube displacement is much more common in the prone position than in the supine position. METHOD: The study population consisted of 120 patients aged between 18-60 years, ASA class 1 and 2, undergoing surgery in the prone position who were randomly allocated into two groups of sixty patients each. The endotracheal tube was secured either with adhesive tape (Group A) or a Thomas tube holder (Group B). The ease of application and removal, effect on caliber of endotracheal tube, amount of displacement of endotracheal tube and also any injuries with either fixation method were studied. RESULT: Both groups were comparable with respect to mean time taken for the application of the fixation device, peak airway pressure change after the application of the fixation device in the supine position and after positioning the patient in the prone position and the time taken for removal of the fixation device. Displacement was significantly larger in group A than in group B. CONCLUSION: Both methods of fixation of the endotracheal tube are clinically useful in the prone position but the Thomas tube holder is more effective than adhesive tape in preventing displacement of endotracheal tube.

High gamma mapping using EEG.

High gamma (HG) power changes during motor activity, especially at frequencies above 70 Hz, play an important role in functional cortical mapping and as control signals for BCI (brain-computer interface) applications. Most studies of HG activity have used ECoG (electrocorticography) which provides high-quality spatially localized signals, but is an invasive method. Recent studies have shown that non-invasive modalities such as EEG and MEG can also detect task-related HG power changes. We show here that a 27 channel EEG (electroencephalography) montage provides high-quality spatially localized signals non-invasively for HG frequencies ranging from 83 to 101 Hz. We used a generic head model, a weighted minimum norm least squares (MNLS) inverse method, and a self-paced finger movement paradigm. The use of an inverse method enables us to map the EEG onto a generic cortex model. We find the HG activity during the task to be well localized in the contralateral motor area. We find HG power increases prior to finger movement, with average latencies of 462 ms and 82 ms before EMG (electromyogram) onset. We also find significant phase-locking between contra- and ipsilateral motor areas over a similar HG frequency range; here the synchronization onset precedes the EMG by 400 ms. We also compare our results to ECoG data from a similar paradigm and find EEG mapping and ECoG in good agreement. Our findings demonstrate that mapped EEG provides information on two important parameters for functional mapping and BCI which are usually only found in HG of ECoG signals: spatially localized power increases and bihemispheric phase-locking.

Signal recovery from stimulation artifacts in intracranial recordings with dictionary learning.

OBJECTIVE: Electrical stimulation of the human brain is commonly used for eliciting and inhibiting neural activity for clinical diagnostics, modifying abnormal neural circuit function for therapeutics, and interrogating cortical connectivity. However, recording electrical signals with concurrent stimulation results in dominant electrical artifacts that mask the neural signals of interest. Here we develop a method to reproducibly and robustly recover neural activity during concurrent stimulation. We concentrate on signal recovery across an array of electrodes without channel-wise fine-tuning of the algorithm. Our goal includes signal recovery with trains of stimulation pulses, since repeated, high-frequency pulses are often required to induce desired effects in both therapeutic and research domains. We have made all of our code and data publicly available. APPROACH: We developed an algorithm that automatically detects templates of artifacts across many channels of recording, creating a dictionary of learned templates using unsupervised clustering. The artifact template that best matches each individual artifact pulse is subtracted to recover the underlying activity. To assess the success of our method, we focus on whether it extracts physiologically interpretable signals from real recordings. MAIN RESULTS: We demonstrate our signal recovery approach on invasive electrophysiologic recordings from human subjects during stimulation. We show the recovery of meaningful neural signatures in both electrocorticographic (ECoG) arrays and deep brain stimulation (DBS) recordings. In addition, we compared cortical responses induced by the stimulation of primary somatosensory (S1) by natural peripheral touch, as well as motor cortex activity with and without concurrent S1 stimulation. SIGNIFICANCE: Our work will enable future advances in neural engineering with simultaneous stimulation and recording.

Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects.

We describe a model of visual processing in which feedback connections from a higher- to a lower-order visual cortical area carry predictions of lower-level neural activities, whereas the feedforward connections carry the residual errors between the predictions and the actual lower-level activities. When exposed to natural images, a hierarchical network of model neurons implementing such a model developed simple-cell-like receptive fields. A subset of neurons responsible for carrying the residual errors showed endstopping and other extra-classical receptive-field effects. These results suggest that rather than being exclusively feedforward phenomena, nonclassical surround effects in the visual cortex may also result from cortico-cortical feedback as a consequence of the visual system using an efficient hierarchical strategy for encoding natural images.

Concurrent control of a brain-computer interface and natural overt movements.

OBJECTIVE: A primary control signal in brain-computer interfaces (BCIs) have been cortical signals related to movement. However, in cases where natural motor function remains, BCI control signals may interfere with other possibly simultaneous activity for useful ongoing movement. We sought to determine if the brain could learn to control both a BCI and concurrent overt movement execution in such cases. APPROACH: We designed experiments where BCI and overt movements must be used concurrently and in coordination to achieve a 2D centre out control. Power in the 70-90 Hz band of human electrocorticography (ECoG) signals, was used to generate BCI control commands for vertical movement of the cursor. These signals were deliberately recorded from the same human cortical site that produced the strongest movement related activity associated with the concurrent overt finger movements required for the horizontal movement of the cursor. MAIN RESULTS: We demonstrate that three subjects were able to perform the concurrent BCI task, controlling BCI and natural movements simultaneously and to a large extent independently. We conclude that the brain is capable of dissociating the original control signal dependency on movement, producing specific BCI control signals in the presence of motor related responses from the ongoing overt behaviour with which the BCI signal was initially correlated. SIGNIFICANCE: We demonstrate a novel human brain-computer interface (BCI) which can be used to control movement concurrently and in coordination with movements of the natural limbs. This demonstrates the dissociation of cortical activity from the behaviour with which it was originally associated despite the ongoing behaviour and shows the feasibility of achieving simultaneous BCI control of devices with natural movements.

Synthesis and antitrichomonal activity of certain pyrazolo (1,5-a) pyrimidines.

Several bridgehead nitrogen heterocycles were synthesized to be screened as antimicrobial agents, modeled after nalidixic acid. The activity of these new compounds, all derivatives of 3-nitro-4,6-disubstituted pyrazolo (1,5-a)pyrimidin-7-ones (3,7,8, and 9), however, was found to be highly specific for Trichomonas foetus and completely lacking in activity against bacteria, fungi, and parasites other than Trichomonas. Of the nine componds synthesized, including the intermediate 4,6-disubstituted pyrazolo (1,5-a) pyrimidin-7-ones (2-6) and the 6-substituted or unsubstituted pyrazolo (1,5-a) pyrimidin-7-ones (1 and 4), only 6-carbethoxy-4-ethyl-3-nitropyrazolo(1,5-a)pyrimidin-7-one (7) was found to be a potent antitrichomal agent, being comparable or perhaps better than metronidazole. From a tentative structure-activity relationship study, it was apparent that the combination of the 3-mitro, 4-ethyl, and 6-carbethoxy groups imparted specific activity, wheras other substitutions imparted little or no antitrichomonal activity.

Predictive learning of temporal sequences in recurrent neocortical circuits.

When a spike is initiated near the soma of a cortical pyramidal neuron, it may back-propagate up dendrites toward distal synapses, where strong depolarization can trigger spike-timing dependent Hebbian plasticity at recently activated synapses. We show that (a) these mechanisms can implement a temporal-difference algorithm for sequence learning, and (b) a population of recurrently connected neurons with this form of synaptic plasticity can learn to predict spatiotemporal input patterns. Using biophysical simulations, we demonstrate that a network of cortical neurons can develop direction selectivity similar to that observed in complex cells in alert monkey visual cortex as a consequence of learning to predict moving stimuli.

Regulation of peri-attachment embryo development in the golden hamster: role of growth factors.

The molecular regulation of mammalian peri-implantation development is complex and difficult to study in vivo. We successfully cultured hamster blastocysts through hatching and peri-attachment stages, using a chemically defined medium, HECM-2h. Using this system, we showed that a species-specific, embryonic cysteine-like protease is involved in blastocyst hatching and that the process is modulated by growth factors. In particular, heparin binding-epidermal growth factor (HB-EGF) or leukemia inhibitory factor (LIF) enhance blastocyst hatching, and the former also improves attachment and trophoblast outgrowth. We observed interesting changing patterns of expression of mRNA and/or immunoreactive protein for EGF, HB-EGF, LIF and transforming growth factor-beta (TGF-beta) in the embryo and/or endometrial tissue, during peri-implantation development. Together, it appears that hamster blastocyst hatching, attachment and trophoblast outgrowth are regulated by autocrine and/or paracrine growth factors, produced by the embryo-endometrial tissues.

An optimal estimation approach to visual perception and learning.

How does the visual system learn an internal model of the external environment? How is this internal model used during visual perception? How are occlusions and background clutter so effortlessly discounted for when recognizing a familiar object? How is a particular object of interest attended to and recognized in the presence of other objects in the field of view? In this paper, we attempt to address these questions from the perspective of Bayesian optimal estimation theory. Using the concept of generative models and the statistical theory of Kalman filtering, we show how static and dynamic events occurring in the visual environment may be learned and recognized given only the input images. We also describe an extension of the Kalman filter model that can handle multiple objects in the field of view. The resulting robust Kalman filter model demonstrates how certain forms of attention can be viewed as an emergent property of the interaction between top-down expectations and bottom-up signals. Experimental results are provided to help demonstrate the ability of such a model to perform robust segmentation and recognition of objects and image sequences in the presence of occlusions and clutter.

Lost intrauterine devices and their localization.

With the increasing popularity of intrauterine devices for contraception, an increase in the number of IUD-related complications has been observed. A common clinical problem is loss of marker strings at the external os. It could be due to translocation or unnoticed expulsion, both of which reduce the contraceptive effectiveness of the method. Even with the most scrupulous IUD insertion technics, uterine perforation is a recognized complication. Ectopic devices should be removed because extensive sepsis and adhesions between adjacent organs with subsequent bowel strangulation have been reported. Determining the location of the device is facilitated by flat plate X-rays of the abdomen, hysterography, ultrasound or hysteroscopy. The best method of IUD removal depends upon its location, extent of adhesions and the experience of the operator.

Acute pulmonary edema following inflation of arterial tourniquet.

Arterial tourniquets are used as one of the methods for reducing blood loss and for allowing blood free surgical field. A 20-year-old, 45 kg healthy female with a sphere shaped pendunculated hemangioma in the popliteal fossa of her left lower limb was applied with arterial tourniquet after exsanguination. The procedure was performed under general anesthesia. Soon after exsanguination and tourniquet inflation, the patient developed pulmonary edema which subsided after deflating the tourniquet. The clinical evolution, treatment and pathophysiology of this complication are described.

Dynamic model of visual recognition predicts neural response properties in the visual cortex.

The responses of visual cortical neurons during fixation tasks can be significantly modulated by stimuli from beyond the classical receptive field. Modulatory effects in neural responses have also been recently reported in a task where a monkey freely views a natural scene. In this article, we describe a hierarchical network model of visual recognition that explains these experimental observations by using a form of the extended Kalman filter as given by the minimum description length (MDL) principle. The model dynamically combines input-driven bottom-up signals with expectation-driven top-down signals to predict current recognition state. Synaptic weights in the model are adapted in a Hebbian manner according to a learning rule also derived from the MDL principle. The resulting prediction-learning scheme can be viewed as implementing a form of expectation-maximization (EM) algorithm. The architecture of the model posits an active computational role of the reciprocal connections between adjoining visual cortical areas in determining neural response properties. In particular, the model demonstrates the possible role of feedback from higher cortical areas in mediating neurophysiological effects due to stimuli from beyond the classical receptive field. Simulations of the model are provided that help explain the experimental observations regarding neural responses in both free viewing and fixation conditions.

Intrauterine contraception.

Newer medicated IUDs, such as the copper or progesterone-releasing devices, are more effective, better tolerated and have fewer side effects than nonmedicated IUDs. Major complications are rare if adequate precautions are taken. The IUD is an ideal contraceptive for patients with contraindications to oral contraception and for those who have difficulty remembering to utilize other methods.

Development of localized oriented receptive fields by learning a translation-invariant code for natural images.

Neurons in the mammalian primary visual cortex are known to possess spatially localized, oriented receptive fields. It has previously been suggested that these distinctive properties may reflect an efficient image encoding strategy based on maximizing the sparseness of the distribution of output neuronal activities or alternately, extracting the independent components of natural image ensembles. Here, we show that a strategy for transformation-invariant coding of images based on a first-order Taylor series expansion of an image also causes localized, oriented receptive fields to be learned from natural image inputs. These receptive fields, which approximate localized first-order differential operators at various orientations, allow a pair of cooperating neural networks, one estimating object identity ('what') and the other estimating object transformations ('where'), to simultaneously recognize an object and estimate its pose by jointly maximizing the a posteriori probability of generating the observed visual data. We provide experimental results demonstrating the ability of such networks to factor retinal stimuli into object-centred features and object-invariant transformation estimates.

Spike-timing-dependent Hebbian plasticity as temporal difference learning.

A spike-timing-dependent Hebbian mechanism governs the plasticity of recurrent excitatory synapses in the neocortex: synapses that are activated a few milliseconds before a postsynaptic spike are potentiated, while those that are activated a few milliseconds after are depressed. We show that such a mechanism can implement a form of temporal difference learning for prediction of input sequences. Using a biophysical model of a cortical neuron, we show that a temporal difference rule used in conjunction with dendritic backpropagating action potentials reproduces the temporally asymmetric window of Hebbian plasticity observed physio-logically. Furthermore, the size and shape of the window vary with the distance of the synapse from the soma. Using a simple example, we show how a spike-timing-based temporal difference learning rule can allow a network of neocortical neurons to predict an input a few milliseconds before the input's expected arrival.

Optimal smoothing in visual motion perception.

When a flash is aligned with a moving object, subjects perceive the flash to lag behind the moving object. Two different models have been proposed to explain this "flash-lag" effect. In the motion extrapolation model, the visual system extrapolates the location of the moving object to counteract neural propagation delays, whereas in the latency difference model, it is hypothesized that moving objects are processed and perceived more quickly than flashed objects. However, recent psychophysical experiments suggest that neither of these interpretations is feasible (Eagleman & Sejnowski, 2000a, 2000b, 2000c), hypothesizing instead that the visual system uses data from the future of an event before committing to an interpretation. We formalize this idea in terms of the statistical framework of optimal smoothing and show that a model based on smoothing accounts for the shape of psychometric curves from a flash-lag experiment involving random reversals of motion direction. The smoothing model demonstrates how the visual system may enhance perceptual accuracy by relying not only on data from the past but also on data collected from the immediate future of an event.

The effectiveness of glass lenses in reducing exposure to the eyes.

A study was done to determine the degree of radiation protection afforded by various types of prescription lenses, including commercially available lead glasses. A wide variation in measured attenuation was found. Two commonly available types of prescription lenses were found to provide greater than 92% attenuation of the x-ray beam generated at 108 kVp.