Spike-Train Responses of a Pair of Hodgkin-Huxley Neurons with Time-Delayed Couplings

Model calculations have been performed on the spike-train response of a pair of Hodgkin-Huxley (HH) neurons coupled by recurrent excitatory-excitatory couplings with time delay. The coupled, excitable HH neurons are assumed to receive the two kinds of spike-train inputs: the transient input consisting of $M$ impulses for the finite duration ($M$: integer) and the sequential input with the constant interspike interval (ISI). The distribution of the output ISI $T_{\rm o}$ shows a rich of variety depending on the coupling strength and the time delay. The comparison is made between the dependence of the output ISI for the transient inputs and that for the sequential inputs.Comment: 19 pages, 4 figure

Working memory dynamics and spontaneous activity in a flip-flop oscillations network model with a Milnor attractor

Many cognitive tasks require the ability to maintain and manipulate simultaneously several chunks of information. Numerous neurobiological observations have reported that this ability, known as the working memory, is associated with both a slow oscillation (leading to the up and down states) and the presence of the theta rhythm. Furthermore, during resting state, the spontaneous activity of the cortex exhibits exquisite spatiotemporal patterns sharing similar features with the ones observed during specific memory tasks. Here to enlighten neural implication of working memory under these complicated dynamics, we propose a phenomenological network model with biologically plausible neural dynamics and recurrent connections. Each unit embeds an internal oscillation at the theta rhythm which can be triggered during up-state of the membrane potential. As a result, the resting state of a single unit is no longer a classical fixed point attractor but rather the Milnor attractor, and multiple oscillations appear in the dynamics of a coupled system. In conclusion, the interplay between the up and down states and theta rhythm endows high potential in working memory operation associated with complexity in spontaneous activities

A Neurodynamic Account of Spontaneous Behaviour

The current article suggests that deterministic chaos self-organized in cortical dynamics could be responsible for the generation of spontaneous action sequences. Recently, various psychological observations have suggested that humans and primates can learn to extract statistical structures hidden in perceptual sequences experienced during active environmental interactions. Although it has been suggested that such statistical structures involve chunking or compositional primitives, their neuronal implementations in brains have not yet been clarified. Therefore, to reconstruct the phenomena, synthetic neuro-robotics experiments were conducted by using a neural network model, which is characterized by a generative model with intentional states and its multiple timescales dynamics. The experimental results showed that the robot successfully learned to imitate tutored behavioral sequence patterns by extracting the underlying transition probability among primitive actions. An analysis revealed that a set of primitive action patterns was embedded in the fast dynamics part, and the chaotic dynamics of spontaneously sequencing these action primitive patterns was structured in the slow dynamics part, provided that the timescale was adequately set for each part. It was also shown that self-organization of this type of functional hierarchy ensured robust action generation by the robot in its interactions with a noisy environment. This article discusses the correspondence of the synthetic experiments with the known hierarchy of the prefrontal cortex, the supplementary motor area, and the primary motor cortex for action generation. We speculate that deterministic dynamical structures organized in the prefrontal cortex could be essential because they can account for the generation of both intentional behaviors of fixed action sequences and spontaneous behaviors of pseudo-stochastic action sequences by the same mechanism

Multi-site and multi-depth near-infrared spectroscopy in a model of simulated (central) hypovolemia: lower body negative pressure

Purpose: To test the hypothesis that the sensitivity of near-infrared spectroscopy (NIRS) in reflecting the degree of (compensated) hypovolemia would be affected by the application site and probing depth. We simultaneously applied multi-site (thenar and forearm) and multi-depth (15-2.5 and 25-2.5 mm probe distance) NIRS in a model of simulated hypovolemia: lower body negative pressure (LBNP). Methods: The study group comprised 24 healthy male volunteers who were subjected to an LBNP protocol in which a baseline period of 30 min was followed by a step-wise manipulation of negative pressure in the following steps: 0, -20, -40, -60, -80 and -100 mmHg. Stroke volume and heart rate were measured using volume-clamp finger plethysmography. Two multi-depth NIRS devices were used to measure tissue oxygen saturation (StO2) and tissue hemoglobin index (THI) continuously in the thenar and the forearm. To monitor the shift of blood volume towards the lower extremities, calf THI was measured by single-depth NIRS. Results: The main findings were that the application of LBNP resulted in a significant reduction in stroke volume which was accompanied by a reduction in forearm StO2 and THI. Conclusions: NIRS can be used to detect changes in StO2 and THI consequent upon central hypovolemia. Forearm NIRS measurements reflect hypovolemia more sensitively than thenar NIRS measurements. The sensitivity of these NIRS measurements does not depend on NIRS probing depth. The LBNP-induced shift in blood volume is reflected by a decreased THI in the forearm and an increased THI in the calf

Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis

BACKGROUND: Invasive ductal and lobular carcinomas (IDC and ILC) are the most common histological types of breast cancer. Clinical follow-up data and metastatic patterns suggest that the development and progression of these tumors are different. The aim of our study was to identify gene expression profiles of IDC and ILC in relation to normal breast epithelial cells. METHODS: We examined 30 samples (normal ductal and lobular cells from 10 patients, IDC cells from 5 patients, ILC cells from 5 patients) microdissected from cryosections of ten mastectomy specimens from postmenopausal patients. Fifty nanograms of total RNA were amplified and labeled by PCR and in vitro transcription. Samples were analysed upon Affymetrix U133 Plus 2.0 Arrays. The expression of seven differentially expressed genes (CDH1, EMP1, DDR1, DVL1, KRT5, KRT6, KRT17) was verified by immunohistochemistry on tissue microarrays. Expression of ASPN mRNA was validated by in situ hybridization on frozen sections, and CTHRC1, ASPN and COL3A1 were tested by PCR. RESULTS: Using GCOS pairwise comparison algorithm and rank products we have identified 84 named genes common to ILC versus normal cell types, 74 named genes common to IDC versus normal cell types, 78 named genes differentially expressed between normal ductal and lobular cells, and 28 named genes between IDC and ILC. Genes distinguishing between IDC and ILC are involved in epithelial-mesenchymal transition, TGF-beta and Wnt signaling. These changes were present in both tumor types but appeared to be more prominent in ILC. Immunohistochemistry for several novel markers (EMP1, DVL1, DDR1) distinguished large sets of IDC from ILC. CONCLUSION: IDC and ILC can be differentiated both at the gene and protein levels. In this study we report two candidate genes, asporin (ASPN) and collagen triple helix repeat containing 1 (CTHRC1) which might be significant in breast carcinogenesis. Besides E-cadherin, the proteins validated on tissue microarrays (EMP1, DVL1, DDR1) may represent novel immunohistochemical markers helpful in distinguishing between IDC and ILC. Further studies with larger sets of patients are needed to verify the gene expression profiles of various histological types of breast cancer in order to determine molecular subclassifications, prognosis and the optimum treatment strategies

Extracorporeal Membrane Oxygenation for Acute Pediatric Respiratory Failure

This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.The use of extracorporeal membrane oxygenation (ECMO) to support children with acute respiratory failure has steadily increased over the past several decades, with major advancements having been made in the care of these children. There are, however, many controversies regarding indications for initiating ECMO in this setting and the appropriate management strategies thereafter. Broad indications for ECMO include hypoxia, hypercarbia, and severe air leak syndrome, with hypoxia being the most common. There are many disease-specific considerations when evaluating children for ECMO, but there are currently very few, if any, absolute contraindications. Venovenous rather than veno-arterial ECMO cannulation is the preferred configuration for ECMO support of acute respiratory failure due to its superior side-effect profile. The approach to lung management on ECMO is variable and should be individualized to the patient, with the main goal of reducing the risk of VILI. ECMO is a relatively rare intervention, and there are likely a minimum number of cases per year at a given center to maintain competency. Patients who have prolonged ECMO runs (i.e., greater than 21 days) are less likely to survive, though no absolute duration of ECMO that would mandate withdrawal of ECMO support can be currently recommended