Grid Cell Hexagonal Patterns Formed by Fast Self-Organized Learning within Entorhinal Cortex

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. How these hexagonal patterns arise has excited intense interest. It has previously been shown how a selforganizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? A neural model is proposed that converts path integration signals into hexagonal grid cell patterns of multiple scales. This GRID model creates only grid cell patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support a unified computational framework for explaining how entorhinal-hippocampal interactions support spatial navigation.

A Memory Model for Concept Hierarchy Representation and Commonsense Reasoning

Most associative memory models perform one level mapping between predefined sets of input and output patterns1 and are unable to represent hierarchical knowledge. Complex AI systems allow hierarchical representation of concepts, but generally do not have learning capabilities. In this paper, a memory model is proposed which forms concept hierarchy by learning sample relations between concepts. All concepts are represented in a concept layer. Relations between a concept and its defining lower level concepts, are chunked as cognitive codes represented in a coding layer. By updating memory contents in the concept layer through code firing in the coding layer, the system is able to perform an important class of commonsense reasoning, namely recognition and inheritance.

Simulating Effects of Learning and Lesions with a Model of Intrinsic and Synaptically Gated Responses of Striatal Cholinergic Interneurons

The giant cholinergic interneurons of the striatum are tonically active neurons (TANs) that respond with characteristic pauses to novel events and to appetitive and aversive conditioned stimuli. Fluctuations in acetylcholine release by TANs modulate performance- and learning-related dynamics in the striatum. Whereas tonic activity emerges from intrinsic properties of these neurons, glutamatergic inputs from thalamic centromedian-parafascicular nuclei, and dopaminergic inputs from midbrain, are required for the generation of pause responses. No prior computational models encompass both intrinsic and synaptically-gated dynamics. We present a mathematical model that robustly accounts for behavior-related electrophysiological properties of TANs in terms of their intrinsic physiological properties and known afferents. In the model, balanced intrinsic hyperpolarizing and depolarizing currents engender tonic firing, and glutamatergic inputs from thalamus (and cortex) both directly excite and indirectly inhibit TANs. If the latter inhibition, presumably mediated by GABAergic interneurons, exceeds a threshold, its effect is amplified by a KIR current to generate a prolonged pause. In the model, the intrinsic mechanisms and external inputs are both modulated by learning-dependent dopamine (DA) signals and our simulations revealed that many learning-dependent behaviors of TANs are explicable without recourse to learning-dependent changes in synapses onto TANs. The "teaching signal" that modulates reinforcement learning at cortico-striatal synapses may be a sequence composed of an adaptively scaled DA burst, a brief ACh burst, and a scaled ACh pause. Such an interpretation is consistent with recent data on cholinergic control of LTD of cortical synapses onto striatal spiny projection neurons.

Synchronized Oscillations During Cooperative Feature Lining in a Cortical Model of Visual Perception

A neural network model of synchronized oscillations in visual cortex is presented to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these experiments, synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained for single bar stimuli and also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli using different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models.

Synchronized Oscillations During Cooperative Feature Linking in a Cortical Model of Visual Perception

A neural network model of synchronized oscillator activity in visual cortex is presented in order to account for recent neurophysiological findings that such synchronization may reflect global properties of the stimulus. In these recent experiments, it was reported that synchronization of oscillatory firing responses to moving bar stimuli occurred not only for nearby neurons, but also occurred between neurons separated by several cortical columns (several mm of cortex) when these neurons shared some receptive field preferences specific to the stimuli. These results were obtained not only for single bar stimuli but also across two disconnected, but colinear, bars moving in the same direction. Our model and computer simulations obtain these synchrony results across both single and double bar stimuli. For the double bar case, synchronous oscillations are induced in the region between the bars, but no oscillations are induced in the regions beyond the stimuli. These results were achieved with cellular units that exhibit limit cycle oscillations for a robust range of input values, but which approach an equilibrium state when undriven. Single and double bar synchronization of these oscillators was achieved by different, but formally related, models of preattentive visual boundary segmentation and attentive visual object recognition, as well as nearest-neighbor and randomly coupled models. In preattentive visual segmentation, synchronous oscillations may reflect the binding of local feature detectors into a globally coherent grouping. In object recognition, synchronous oscillations may occur during an attentive resonant state that triggers new learning. These modelling results support earlier theoretical predictions of synchronous visual cortical oscillations and demonstrate the robustness of the mechanisms capable of generating synchrony.

Serotonin synthesis, release and reuptake in terminals: a mathematical model.

BACKGROUND: Serotonin is a neurotransmitter that has been linked to a wide variety of behaviors including feeding and body-weight regulation, social hierarchies, aggression and suicidality, obsessive compulsive disorder, alcoholism, anxiety, and affective disorders. Full understanding of serotonergic systems in the central nervous system involves genomics, neurochemistry, electrophysiology, and behavior. Though associations have been found between functions at these different levels, in most cases the causal mechanisms are unknown. The scientific issues are daunting but important for human health because of the use of selective serotonin reuptake inhibitors and other pharmacological agents to treat disorders in the serotonergic signaling system. METHODS: We construct a mathematical model of serotonin synthesis, release, and reuptake in a single serotonergic neuron terminal. The model includes the effects of autoreceptors, the transport of tryptophan into the terminal, and the metabolism of serotonin, as well as the dependence of release on the firing rate. The model is based on real physiology determined experimentally and is compared to experimental data. RESULTS: We compare the variations in serotonin and dopamine synthesis due to meals and find that dopamine synthesis is insensitive to the availability of tyrosine but serotonin synthesis is sensitive to the availability of tryptophan. We conduct in silico experiments on the clearance of extracellular serotonin, normally and in the presence of fluoxetine, and compare to experimental data. We study the effects of various polymorphisms in the genes for the serotonin transporter and for tryptophan hydroxylase on synthesis, release, and reuptake. We find that, because of the homeostatic feedback mechanisms of the autoreceptors, the polymorphisms have smaller effects than one expects. We compute the expected steady concentrations of serotonin transporter knockout mice and compare to experimental data. Finally, we study how the properties of the the serotonin transporter and the autoreceptors give rise to the time courses of extracellular serotonin in various projection regions after a dose of fluoxetine. CONCLUSIONS: Serotonergic systems must respond robustly to important biological signals, while at the same time maintaining homeostasis in the face of normal biological fluctuations in inputs, expression levels, and firing rates. This is accomplished through the cooperative effect of many different homeostatic mechanisms including special properties of the serotonin transporters and the serotonin autoreceptors. Many difficult questions remain in order to fully understand how serotonin biochemistry affects serotonin electrophysiology and vice versa, and how both are changed in the presence of selective serotonin reuptake inhibitors. Mathematical models are useful tools for investigating some of these questions.

Different stimuli, different spatial codes: a visual map and an auditory rate code for oculomotor space in the primate superior colliculus.

Maps are a mainstay of visual, somatosensory, and motor coding in many species. However, auditory maps of space have not been reported in the primate brain. Instead, recent studies have suggested that sound location may be encoded via broadly responsive neurons whose firing rates vary roughly proportionately with sound azimuth. Within frontal space, maps and such rate codes involve different response patterns at the level of individual neurons. Maps consist of neurons exhibiting circumscribed receptive fields, whereas rate codes involve open-ended response patterns that peak in the periphery. This coding format discrepancy therefore poses a potential problem for brain regions responsible for representing both visual and auditory information. Here, we investigated the coding of auditory space in the primate superior colliculus(SC), a structure known to contain visual and oculomotor maps for guiding saccades. We report that, for visual stimuli, neurons showed circumscribed receptive fields consistent with a map, but for auditory stimuli, they had open-ended response patterns consistent with a rate or level-of-activity code for location. The discrepant response patterns were not segregated into different neural populations but occurred in the same neurons. We show that a read-out algorithm in which the site and level of SC activity both contribute to the computation of stimulus location is successful at evaluating the discrepant visual and auditory codes, and can account for subtle but systematic differences in the accuracy of auditory compared to visual saccades. This suggests that a given population of neurons can use different codes to support appropriate multimodal behavior.

PDLA a potential new potent topical analgesic: a case report.

Polymer D-lactic acid (PDLA) is a hydrogel that has been shown to sequester L-lactate (lactate). This reaction is rapid, spontaneous, and non-enzymatic. Lactate has been shown to have many functions within the nervous system including its use as a secondary fuel to sustain neural activity and as a neuromodulator. In the central nervous system, lactate is produced in glial cells and shuttled to neurons to be used mostly as a fuel. Lactate dehydrogenase (LDH)1 is the predominant LDH isoform within neurons and unlike LDH5, it preferentially converts lactate to pyruvate which can be used to produce adenosine triphosphate (ATP). Considering that lactate is intimately involved in the sustenance of neural activity, PDLA was applied to an open wound and its effects were examined. The results showed that the application of PDLA induced topical analgesia. This may be the first report to demonstrate that sequestering lactate, a source of energy required to sustain the firing of action potentials in neurons, may produce analgesia.

Spatial and temporal scales of neuronal correlation in visual area V4.

The spiking activity of nearby cortical neurons is correlated on both short and long time scales. Understanding this shared variability in firing patterns is critical for appreciating the representation of sensory stimuli in ensembles of neurons, the coincident influences of neurons on common targets, and the functional implications of microcircuitry. Our knowledge about neuronal correlations, however, derives largely from experiments that used different recording methods, analysis techniques, and cortical regions. Here we studied the structure of neuronal correlation in area V4 of alert macaques using recording and analysis procedures designed to match those used previously in primary visual cortex (V1), the major input to V4. We found that the spatial and temporal properties of correlations in V4 were remarkably similar to those of V1, with two notable differences: correlated variability in V4 was approximately one-third the magnitude of that in V1 and synchrony in V4 was less temporally precise than in V1. In both areas, spontaneous activity (measured during fixation while viewing a blank screen) was approximately twice as correlated as visual-evoked activity. The results provide a foundation for understanding how the structure of neuronal correlation differs among brain regions and stages in cortical processing and suggest that it is likely governed by features of neuronal circuits that are shared across the visual cortex.

Optimizing the operation of straight-grate iron-ore pellet induration systems using process models

Mathematical models of straight-grate pellet induration processes have been developed and carefully validated by a number of workers over the past two decades. However, the subsequent exploitation of these models in process optimization is less clear, but obviously requires a sound understanding of how the key factors control the operation. In this article, we show how a thermokinetic model of pellet induration, validated against operating data from one of the Iron Ore Company of Canada (IOCC) lines in Canada, can be exploited in process optimization from the perspective of fuel efficiency, production rate, and product quality. Most existing processes are restricted in the options available for process optimization. Here, we review the role of each of the drying (D), preheating (PH), firing (F), after-firing (AF), and cooling (C) phases of the induration process. We then use the induration process model to evaluate whether the first drying zone is best to use on the up- or down-draft gas-flow stream, and we optimize the on-gas temperature profile in the hood of the PH, F, and AF zones, to reduce the burner fuel by at least 10 pct over the long term. Finally, we consider how efficient and flexible the process could be if some of the structural constraints were removed (i.e., addressed at the design stage). The analysis suggests it should be possible to reduce the burner fuel lead by 35 pct, easily increase production by 5+ pct, and improve pellet quality.

Production of lightweight aggregate from industrial waste and carbon dioxide

The concomitant recycling of waste and carbon dioxide emissions is the subject of developing technology designed to close the industrial process loop and facilitate the bulk-re-use of waste in, for example, construction. The present work discusses a treatment step that employs accelerated carbonation to convert gaseous carbon dioxide into solid calcium carbonate through a reaction with industrial thermal residues. Treatment by accelerated carbonation enabled a synthetic aggregate to be made from thermal residues and waste quarry fines. The aggregates produced had a bulk density below 1000 kg/m3 and a high water absorption capacity. Aggregate crushing strengths were between 30% and 90% stronger than the proprietary lightweight expanded clay aggregate available in the UK. Cast concrete blocks containing the carbonated aggregate achieve compressive strengths of 24 MPa, making them suitable for use with concrete exposed to non-aggressive service environments. The energy intensive firing and sintering processes traditionally required to produce lightweight aggregates can now be augmented by a cold-bonding, low energy method that contributes to the reduction of green house gases to the atmosphere.

Simulation of Dynamic Operation of a Single-Cylinder Two-Stroke Engine

Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the engine and drivetrain models developed previously by Callahan, et al. (1) to examine a variety of engines. The predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The single-cylinder, high performance four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation in the model. Measured speed fluctuations from a firing Yamaha YZ426 engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar changes in performance. The multiple-cylinder, high performance two-stroke engine also showed significant changes in performance depending on the firing configuration. With both engines, the change in performance diminished with increasing mean engine speed. The low output, single-cylinder two-stroke engine simulation showed only a negligible change in performance, even with high amplitude speed fluctuations. Because the torque versus engine speed characteristic for the engine was so flat, this was expected. The cross-charged, multi-cylinder two-stroke engine also showed only a negligible change in performance. In this case, the combination of a relatively high inertia rotating assembly and the multiple cylinder firing events within the revolution smoothing the torque pulsations reduced the speed fluctuation amplitude itself.

Drivetrain Effects on Small Engine Performance

Presented is a study that expands the body of knowledge on the effect of in-cycle speed fluctuations on performance of small engines. It uses the methods developed previously by Callahan, et al. (1) to examine a variety of two-stroke engines and one four-stroke engine. The two-stroke engines were: a high performance single-cylinder, a low performance single-cylinder, a high performance multi-cylinder, and a medium performance multi-cylinder. The four-stroke engine was a high performance single-cylinder unit. Each engine was modeled in Virtual Engines, which is a fully detailed one-dimensional thermodynamic engine simulator. Measured or predicted in-cycle speed data were input into the engine models. Predicted performance changes due to drivetrain effects are shown in each case, and conclusions are drawn from those results. The simulations for the high performance single-cylinder two-stroke engine predicted significant in-cycle crankshaft speed fluctuation amplitudes and significant changes in performance when the fluctuations were input into the engine model. This was validated experimentally on a firing test engine based on a Yamaha YZ250. The four-stroke engine showed significant changes in predicted performance compared to the prediction with zero speed fluctuation assumed in the model. Measured speed fluctuations from a firing Yamaha YZ400F engine were applied to the simulation in addition to data from a simple free mass model. Both methods predicted similar fluctuation profiles and changes in performance. It is shown that the gear reduction between the crankshaft and clutch allowed for this similar behavior. The multi-cylinder, high performance two-stroke engine also showed significant changes in performance, in this case depending on the firing configuration. The low output two-stroke engine simulation showed only a negligible change in performance in spite of high amplitude speed fluctuations. This was due to its flat torque versus speed characteristic. The medium performance multi-cylinder two-stroke engine also showed only a negligible change in performance, in this case due to a relatively high inertia rotating assembly and multiple cylinder firing events within the revolution. These smoothed the net torque pulsations and reduced the amplitude of the speed fluctuation itself.

Kit positive cells in the guinea pig bladder.

PURPOSE: We describe the presence of interstitial cells of Cajal (ICC) throughout the wall of the guinea pig bladder. MATERIALS AND METHODS: Bladders obtained from male guinea pigs were prepared for immunohistochemical investigations using various primary antibodies, including the specific ICC marker c-kit (Gibco BRL, Grand Island, New York). Enzymatically dispersed cells with a branched morphology were identified as ICC using anti-c-kit. They were loaded with fluo-4acetoxymethyl (Molecular Probes, Eugene, Oregon) and studied using confocal laser scanning microscopy. RESULTS: Anti-c-kit labeling demonstrated that ICC were oriented in parallel with the smooth muscle bundles that run diagonally throughout the bladder. Double labeling with anti-smooth muscle myosin (Sigma Chemical Co., St. Louis, Missouri) revealed that ICC were located on the boundary of smooth muscle bundles. When anti-c-kit was used in combination with the general neuronal antibody protein gene product 9.5 (Ultraclone Ltd., Isle of Wight, United Kingdom) or anti-neuronal nitric oxide synthase, it was noted that there was a close association between nerves and ICC. Enzymatic dissociation of cells from tissue pieces yielded a heterogeneous population of cells containing typical spindle-shaped smooth muscle cells and branched cells resembling ICC from other preparations. The latter could be identified immunohistochemically as ICC using anti-c-kit, whereas the majority of spindle-shaped cells were not Kit positive. Branched cells responded to the application of carbachol by firing Ca2+ waves and they were often spontaneously active. CONCLUSIONS: ICC are located on the boundary of smooth muscle bundles in the guinea pig bladder. They fire Ca2+ waves in response to cholinergic stimulation and can be spontaneously active, suggesting that they could act as pacemakers or intermediaries in the transmission of nerve signals to smooth muscle cells.

The Function of Intestinal Afferent Neurons in Regulating Satiety During Health and Obesity

Background and aim: Within the gastrointestinal tract, vagal afferents regulate satiety and food intake via chemical and mechanical mechanisms. Cysteinyl Leukotrienes (CysLTs) are lipid mediators that are believed to regulate food intake and body weight. However, the involvement of vagal afferents in this effect remains to be established. Conversely, Glucagon like peptide-1 (GLP-1) is a satiety and incretin peptide hormone. The effect of obesity on GLP-1 mediated gut-brain signaling has yet to be investigated. Since intestinal vagal afferents’ activity is reduced during obesity, it is intriguing to investigate their responses to GLP-1 in such conditions. Methods: Extracellular recordings were performed on intestinal afferents from normal C57Bl6, low fat fed (LFF), and high fat fed (HFF) mice. To examine the effect on neuronal calcium signaling, calcium-imaging experiments were performed on isolated nodose ganglion neurons. Food intake experiments were conducted using LFF and HFF mice. Oral glucose tolerance tests (OGTT) were carried out. Whole cell patch clamp recordings were performed on nodose ganglion neurons from A) normal C57Bl mice to test the effect of CysLTs on membrane excitability, B) LFF and HFF mice to examine GLP-1 effect on membrane excitability during obesity. c-Fos immunohistochemical techniques were performed to measure the level of neuronal activation in the brainstem of both LFF and HFF mice in response to Ex-4. Results: CysLTs increased intestinal afferent firing rate and mechanosensitivity. In single nodose neuron experiments, CysLTs increased excitability. The GLP-1 agonist Ex-4 significantly decreased food intake in LFF but not HFF mice. However, Ex-4 markedly attenuated the rise in blood glucose in both LFF and HFF mice. The observed increase in nerve firing and mechanosensitivity following the application of GLP-1 and Ex-4 was abolished in HFF mice. Cell membrane excitability was significantly increased by Ex-4 in nodose from LFF but not HFF mice. Ex-4 significantly increased the number of activated neurons in the NTS area of LFF mice but not in their HFF counterparts. Conclusion: The previous observations indicate that the role CysLTs play in regulating satiety is likely to be vagally mediated. Also that satiety, but not incretin, effects of GLP-1 are impaired during obesity.