A microelectrode drive for long term recording of neurons in freely moving and chaired monkeys

An electrode drive is described for recordings of neurons in freely moving and chaired monkeys during the performance of behavioural tasks. The electrode drives are implanted for periods of up to 6 months, and can advance up to 42 electrodes using 14 independent drive mechanisms. The drive samples 288 points within a 12 mm x 12 min region, with 15 min of electrode travel. Major advantages are that recordings are made in freely moving monkeys, and these recordings can be compared with those in chaired experiments; waveforms of single neurons are stable, enabling prolonged recordings of the same neurons across periods of days; recordings can be made throughout the brain, including the dorsolateral prefrontal cortex and hippocampus; the drive accommodates both sharp microelectrodes and fine wire assemblies such as tetrodes. (C) 2003 Elsevier Science B.V; All rights reserved.

Reinforcement-related neurons in the primate basal forebrain respond to the learned significance of task events rather than to the hedonic attributes of reward

The objective of this study was to determine if the responses of basal forebrain neurons are related to the cognitive processes necessary for the performance of behavioural tasks, or to the hedonic attributes of the reinforcers delivered to the monkey as

Mechanisms of H+ modulation of glycinergic response in rat sacral dorsal commissural neurons

Many ionotropic receptors are modulated by extracellular H+. So far, few studies have directly addressed the role of such modulation at synapses. In the present study, we investigated the effects of changes in extracellular pH on glycinergic miniature inhibitory postsynaptic currents (mIPSCs) as well as glycine-evoked currents (I-Gly) in mechanically dissociated spinal neurons with native synaptic boutons preserved. H+ modulated both the mIPSCs and I-Gly, biphasically, although it activated an amiloride-sensitive inward current by itself. Decreasing extracellular pH reversibly inhibited the amplitude of the mIPSCs and I-Gly, while increasing external pH reversibly potentiated these parameters. Blockade of acid-sensing ion channels (ASICs) with amiloride, the selective antagonist of ASICs, or decreasing intracellular pH did not alter the modulatory effect of H+ on either mIPSCs or I-Gly, H+ shifted the EC50 of the glycine concentration-response curve from 49.3 +/- 5.7 muM at external pH 7.4 to 131.5 +/- 8.1 muM at pH 5.5, without altering the Cl- selectivity of the glycine receptor (GlyR), the Hill coefficient and the maximal I-Gly, suggesting a competitive inhibition of I-Gly by H+. Both Zn2+ and H+ inhibited I-Gly. However, H+ induced no further inhibition of I-Gly in the presence of a saturating concentration of Zn2+. In addition, H+ significantly affected the kinetics of glycinergic mIPSCs and I-Gly. It is proposed that H+ and/or Zn2+ compete with glycine binding and inhibit the amplitude of glycinergic mIPSCs and I-Gly. Moreover, binding of H+ induces a global conformational change in GlyR, which closes the GlyR Cl- channel and results in the acceleration of the seeming desensitization of IGly as well as speeding up the decay time constant of glycinergic mIPSCs. However, the deprotonation rate is faster than the unbinding rate of glycine from the GlyR, leading to reactivation of the undesensitized GlyR after washout of agonist and the appearance of a rebound I-Gly. H+ also modulated the glycine cotransmitter, GABA-activated current (I-GABA). Taken together, the results support a 'conformational coupling' model for H+ modulation of the GlyR and suggest that W may act as a novel modulator for inhibitory neurotransmission in the mammalian spinal cord.

Characterization of acid-sensing ion channels in dorsal horn neurons of rat spinal cord

Acid-sensing ion channels (ASICs) are ligand-gated cation channels activated by extracellular protons. In periphery, they contribute to sensory transmission, including that of nociception and pain. Here we characterized ASIC-like currents in dorsal horn neurons of the rat spinal cord and their functional modulation in pathological conditions. Reverse transcriptase-nested PCR and Western blotting showed that three ASIC isoforms, ASIC1a, ASIC2a, and ASIC2b, are expressed at a high level in dorsal horn neurons. Electrophysiological and pharmacological properties of the proton-gated currents suggest that homomeric ASIC1a and/or heteromeric ASIC1a + 2b channels are responsible for the proton-induced currents in the majority of dorsal horn neurons. Acidification-induced action potentials in these neurons were compatible in a pH-dependent manner with the pH dependence of ASIC-like current. Furthermore, peripheral complete Freund's adjuvant-induced inflammation resulted in increased expression of both ASIC1a and ASIC2a in dorsal horn. These results support the idea that the ASICs of dorsal horn neurons participate in central sensory transmission/modulation under physiological conditions and may play important roles in inflammation-related persistent pain.

Properties of the proton-evoked currents and their modulation by Ca2+ and Zn2+ in the acutely dissociated hippocampus CA1 neurons

The characterization of acid-sensing ion channel (ASIC)-like currents has been reported in hippocampal neurons in primary culture. However, it is suggested that the profile of expression of ASICs changes in culture. In this study, we investigated the properties of proton-activated current and its modulation by extracellular Ca2+ and Zn2+ in neurons acutely dissociated from the rat hippocampal CA1 using conventional whole-cell patch-clamp recording. A rapidly decaying inward current and membrane depolarization was induced by exogenous application of acidic solution. The current was sensitive to the extracellular proton with a response threshold of pH 7.0-6.8 and the pH(50) Of 6.1, the reversal potential close to the Na+ equilibrium potential. It had a characteristic of acid-sensing ion channels (ASICs) as demonstrated by its sensitivity to amiloride (IC50 = 19.6 +/- 2.1 muM). Either low [Ca2+](0) or high [Zn2+](0) increased the amplitude of the current. All these characteristics are consistent with a current mediated through a mixture of homomeric ASIC1a and heteromeric ASIC1a + 2a channels and closely replicate many of the characteristics that have been previously reported for hippocampal neurons cultured for a week or more, indicating that culture artifacts do not necessarily flaw the properties of ASICs. Interestingly, we found that high [Zn2+] (>10(-4) M) slowed the decay time constant of the ASIC-like current significantly in both acutely dissociated and cultured hippocampal neurons. In addition, the facilitating effects of low [Ca2+](0) and high [Zn2+](0) on the ASIC-like current were not additive. Since tissue acidosis, extracellular Zn elevation and/or Ca2+ reduction occur concurrently under some physiological and/or pathological conditions, the present observations suggest that hippocampal ASICs may offer a novel pharmacological target for therapeutic invention. (C) 2004 Elsevier B.V. All rights reserved.

Upregulation of acid-sensing ion channel ASIC1a in spinal dorsal horn neurons contributes to inflammatory pain hypersensitivity

Development of chronic pain involves alterations in peripheral nociceptors as well as elevated neuronal activity in multiple regions of the CNS. Previous pharmacological and behavioral studies suggest that peripheral acid-sensing ion channels (ASICs) cont

Geometry property of multi-degree of freedom neurons

In this paper, we study a problem of geometric inequalities for a Multi-degree of Freedom Neurons. Some new geometric inequalities for a Multi-degree of Freedom Neurons are established. As special cases, some known inequalities are deduced.

Determining of the delay time for a heating ventilating and air-conditioning plant using multi-weights neurons approach

This paper presents an multi weights neurons approach to determine the delay time for a Heating ventilating and air-conditioning (HVAC) plan to respond to control actions. The multi weights neurons is a fully connected four-layer network. An acceleration technique was used to improve the general delta rule for the learning process. Experimental data for heating and cooling modes were used with both the multi weights neurons and a traditional mathematical method to determine the delay time. The results show that multi weights neurons can be used effectively determining the delay time for HVAC systems.

Discussion on the basic mathematical models of neurons - Double synaptic weight neuron in general-purpose neurocomputer, theory and application

Based on the introduction of the traditional mathematical models of neurons in general-purpose neurocomputer, a novel all-purpose mathematical model-Double synaptic weight neuron (DSWN) is presented, which can simulate all kinds of neuron architectures, including Radial-Basis-Function (RBF) and Back-propagation (BP) models, etc. At the same time, this new model is realized using hardware and implemented in the new CASSANN-II neurocomputer that can be used to form various types of neural networks with multiple mathematical models of neurons. In this paper, the flexibility of the new model has also been described in constructing neural networks and based on the theory of Biomimetic pattern recognition (BPR) and high-dimensional space covering, a recognition system of omni directionally oriented rigid objects on the horizontal surface and a face recognition system had been implemented on CASSANN-H neurocomputer. The result showed DSWN neural network has great potential in pattern recognition.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.

A new development on ANN in China - Biomimetic pattern recognition and multi weight vector neurons

A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

The structure and function of neurons with variable nonlinear transfer function

One novel neuron with variable nonlinear transfer function is firstly proposed, It could also be called as subsection transfer function neuron. With different transfer function components, by virtue of multi-thresholded, the variable transfer function neuron switch on among different nonlinear excitated state. And the comparison of output's transfer characteristics between it and single-thresholded neuron will be illustrated, with some practical application experiments on Bi-level logic operation, at last the simple comparison with conventional BP, RBF, and even DBF NN is taken to expect the development foreground on the variable neuron.. The novel nonlinear transfer function neuron could implement the random nonlinear mapping relationship between input layer and output layer, which could make variable transfer function neuron have one much wider applications on lots of reseach realm such as function approximation pattern recognition data compress and so on.

Face recognition based on PCA and multi-degree of freedom neurons

An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.

Research on multi-degree-of-freedom neurons with weighted graphs

In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.