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Everybody likes to make a good prediction, in particular, when some sort of personal investment is involved in terms of finance, energy or time. The difficulty is to make a prediction that optimises the reward obtained from the original contribution; this is even more important when investments are the core service offered by a business or pension fund generated by monthly contributions. The complexity of finance is that the human predictor may have other interests or bias than the human investor, the trust between predictor and investor will never be completely established as the investor will never know if the predictor has generated, intentionally or unintentionally, the optimum possible reward. This paper presents the Random Neural Network in recurrent configuration that makes predictions on time series data, specifically, prices. The biological model inspired by the brain structure and neural interconnections makes predictions entirely on previous data from the time series rather than predictions based on several uncorrelated inputs. The model is validated against the property, stock and Fintech market: 1) UK property prices, 2) stock markets indice prices, 3) cryptocurrency prices. Experimental results show that the proposed method makes accurate predictions on different investment portfolios.

Objective Communicating branches between the tibial and common fibular divisions of the sciatic nerve have not been previously described. The aim of our study was to examine such neural connections. Materials and Methods Twenty unembalmed adult cadavers underwent dissection of the sciatic nerve. Observations were made for interneural communications between the tibial and common fibular divisions of this nerve. When present, these were measured and classified. Results The majority of sides (75%) had neural communications between the parts of the sciatic nerve in the gluteal/posterior thigh regions before the normal bifurcation of the nerve just above the knee. These connections were always within 20 cm of the greater sciatic notch. Most connections were represented by Testut intercommunicating branches types A (14 sides), F (8 sides), and D (2 sides). Most sides were found to have 1 location for sciatic nerve intercommunications. However, 4 sides (13%) had multiple locations (up to 3) for these intercommunications. The mean length of the communications was 4.1 cm, and the mean diameter was 2.4 mm. No statistically significant difference was found between sides or sexes. Conclusions To our knowledge, neural interconnections between the divisions of the sciatic nerve in the posterior thigh have not been described in the extant literature. Such data might help explain unusual neurologic examinations and alert the surgeon as to the potential for encountering such connections at operation.

The advances in electrophysiological methods have allowed registering the joint activity of single neurons. Thus, studies on functional dynamics of complex-valued neural networks and its information processing mechanism have been conducted. Particularly, the methods for identifying neuronal interconnections are in increasing demand in the area of neurosciences. Here, we proposed a factor analysis to identify functional interconnections among neurons via spike trains. This method was evaluated using simulations of neural discharges from different interconnections schemes. The results have revealed that the proposed method not only allows detecting neural interconnections but will also allow detecting the presence of presynaptic neurons without the need of the recording of them. Fil: Soletta, Jorge Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Bioingeniería. Laboratorio de Medios e Interfases; Argentina Fil: Farfan, Fernando Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Bioingeniería. Laboratorio de Medios e Interfases; Argentina Fil: Albarracin, Ana Lia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Bioingeniería. Laboratorio de Medios e Interfases; Argentina Fil: Pizá, Alvaro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Bioingeniería. Laboratorio de Medios e Interfases; Argentina Fil: Lucianna, Facundo Adrián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Bioingeniería. Laboratorio de Medios e Interfases; Argentina Fil: Felice, Carmelo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto Superior de Investigaciones Biológicas. Universidad Nacional de Tucumán. Instituto Superior de Investigaciones Biológicas; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Bioingeniería. Laboratorio de Medios e Interfases; Argentina

The knowledge of neural interconnections between adjacent nerves of the upper limb is important to the surgeon as such variations may lead to issues with surgical identification and thus iatrogenic injury. Trauma or entrapment of these nerves may cause functional losses different from those expected and thus result in misdiagnosis. The authors review the literature regarding such nervous system derangements.

Recalcitrant trigeminal neuralgia following surgical treatment can be a life-altering condition. To explore alternative anatomic reasons for such a complication, the authors examined the potential for nerve connections between the sensory and motor roots of the trigeminal nerve at the opening of Meckel's cave (porus trigeminus). In 15 embalmed adult cadavers (30 sides), the authors performed microdissection of the skull base and specifically at the opening of Meckel's cave. Two sides (6.67%) were found to have interneural connections between the sensory and motor roots at Meckel's cave. These occurred in one male and one female cadaver, both on right sides. Both connections were histologically verified to be neural and were 0.5 mm in diameter and 2.2 and 3.2 mm in length, respectively. Both connections traveled in an oblique fashion from the portio major to the portio minor. On the basis of authors' findings, the sensory and motor components of the trigeminal nerve at the opening of Meckel's cave may be interconnected with a neural anastomosis. Such findings may be of use during the surgical treatment of trigeminal neuralgia or other surgery of the posterior fossa so that inadvertent transection or traction does not occur.

We propose a computational model explaining the pharmacological, behavioral, and neurosurgical treatments of obsessive–compulsive disorder (OCD) in a unified framework. On the basis of the concept that the striatum stores information linked to OCD symptoms, we analyze dynamical changes of a chaotic neural network modeling the striatum. The effect of pharmacological treatment is explained by the increase in refractoriness induced by the neurotransmitter serotonin. The effect of behavior therapy is explained by the time-variant input stimulus weakening neural interconnections according to the covariance rule concerning synaptic plasticity. The effect of neurosurgical treatment is explained by the lesions to the cortical-striatal-thalamic-cortical loop decreasing the feedback of the closed loop. These treatments have a common property that they decrease the stability of stored information in the striatum.

In this study, we will focus on two aspects of neural interconnections. One is the way in which the information flow is produced, and the other has to do with the neural distribution with specific architectural arrangements in the brain. It is very important to realize that both aspects are related, but it is possible to support in the former that the information flow is not only governed by the number of spikes in the neurons, but by a series of other factors as well. Here we show the role played by GABAergic neurons in acoustic information transmission in the Central Nucleus of Inferior Colliculus (CNIC). We report a neural spatial-temporal cluster distribution, associated with each isofrequency region. With these results, we will shed some light onto the emergence of certain mental properties starting from the neural dynamic interactions.

The well known Cohen-Grossberg network is modified to include second order neural interconnections and also to have a learning component. Sufficient conditions are obtained for the existence of a globally exponentially stable equilibrium. The model provides a two-fold generalization of the Cohen-Grossberg network in the sense if one removes the learning component, then one gets a network with second order synaptic interactions; if both the learning component and the second order interactions are removed, then the model reduces to the standard Cohen-Grossberg network.

appear to be implemented by a large, highly-interconnected network of neurons [4]. Determination of neural interconnections is therefore necessary to gain an understanding of the function of particular neural pathways as desired by neurophysiologists and anatomists, and of disease and phamacological mechanisms which is of interest to neurologists, pathologists and neuropharmacologists. Neural interconnections are generally determined from extremely time-consuming, manual three-dimensional reconstructions of neural tissue [2,1]. The requirement for large numbers of reconstructions, the very large numbers of neurons and interconnections in even the smallest functional unit, and the inter- and intra-technician variability due fatigue and training make a fully-automated reconstruction system desireable. We present a new algorithm to detect neural elements (soma, dendrites, axons) in images from serial optical sections, as required for a three- dimensional reconstruction system. The algorithm is also being used in the study of diabetic retinopathy and is applicable to angiography. Determination of element depth may be found in [3].

This paper describes signal-processing techniques for the recognition of speech phonemes by machine. An attempt has been made to employ, wherever useful, basic processing functions of the human auditory system. These basic functions include neural interconnections and the mechanical transfer functions of the receptor organs. The neural interconnections bave been simulated by the use of neural logic. The purpose of this paper is to describe the logic networks that have been developed for the abstraction of speech features.

In the eyes of higher animals the retina is more than a mosaic of independent photoreceptor elements. Even in a primitive eye such as the compound eye of the horse-shoe crab,Limulus, neural interconnections exist and interaction takes place among the receptor units (the ommatidia). The structure and function of the ommatidia inLimulushas been described by Hartline, Wagner and MacNichol (1952) and recent studies of its microstructure by electron microscopy have been made by Miller (1957). Each ommatidium is a functional unit. In response to illumination of its facet it generates trains of nerve impulses in the major optic nerve fiber that arises from one of the cells within it. A network of nerve fibers lies back of the ommatidia, interconnecting them. This plexus has been figured in a recent paper (Hartline, Wagner and Ratliff, 1956), and has been shown to mediate the interacting influences. In theLimulus

A bewildering series of dynamical processes take part in the development of the nervous system. Neuron branching dynamics, the continuous formation and elimination of neural interconnections, are instrumental in constructing distinct neuronal networks, which are the functional building blocks of the nervous system. In this study, we investigate and validate the important regulative role of mechanical tension in determining the final morphology of neuronal networks. To single out the mechanical effect, we cultured relatively large invertebrate neurons on clean quartz surfaces. Applied to these surfaces were isolated anchoring sites consisting of carbon nanotube islands to which the cells and the neurites could mechanically attach. Inspection of branching dynamics and network wiring upon development revealed an innate selection mechanism in which one axon branch wins over another. The apparent mechanism entails the build-up of mechanical tension in developing axons. The tension is maintained by the attachment of the growth cone to the substrate or, alternatively, to the neurites of a target neuron. The induced tension promotes the stabilization of one set of axon branches while causing retraction or elimination of axon collaterals. We suggest that these findings represent a crucial, early step that precedes the formation of synapses and regulates neuronal interconnections. Mechanical tension serves as a signal for survival of the axonal branch and perhaps for the subsequent formation of synapses.

Intracranial glutamate administered to newly hatched chickens has previously been demonstrated to cause permanent deficits in visual learning. A study was therefore undertaken to determine whether this effect was in any way related to the visual input occurring concomitantly. It was found that for slowed visual learning to be induced the chick needed to see intersecting lines, angles or circles for 3 hr after glutamate administration on the second day of life. Stationary or moving parallel lines were not effective. Slowed visual learning appeared to result from an interaction between glutamate and the neural activity resulting from exposure to patterned input and not the processes required for learning about the patterns. These results are discussed in context of the neurophysiology of the visual system. It is proposed that glutamate causes slowed visual learning by interfering with early forebrain development of higher visual areas which results from precise and specific changes in neural connectivity occurring in response to perceptual input. Experiments utilizing ouabain indicated that the action of glutamate was predominantly extracellular. Glutamate may affect neural interconnections as a consequence of its putative neurotransmitter actions.

The complexity of the central nervous system's influence on cardiovascular integration is underscored by the extensive neural interconnections between the various higher and lower brain structures shown by electrophysiological studies to have an influence on cardiovascular function. Furthermore, complex neural connections exist within each level of cardiovascular integration (for instance, the medullary reticular formation, or the limbic system). The electrophysiological analysis of the integrative aspects of central cardiovascular regulation has been the subject of several reviews (Reis, 1972; Smith, 1974; Calaresu et al., 1975; Oberg, 1976). In recent years, the methodology of analyzing the anatomical neural pathways of central cardiovascular regulation by lesion-degeneration, evoked potential, and fluorescent histochemical procedures, has been improved with the introduction of anterograde and retrograde tracer techniques. The result is the delineation of previously undetected neural interconnections among various brain areas, long known as cardiovascular centres, such as the NTS, the parabrachial nucleus, the paraventricular nucleus of the hypothalamus, the central nucleus of the amygdala, and the bed nucleus of the stria terminalis (LoewyMcKellar, 1980). Undoubtedly the next few years will see major advances in the understanding of the neuroanatomical pathways involved in central cardiovascular control.

Neurons which initially lie in the basal region of the subcommissural organ (SCO) were investigated in 20 rabbit fetuses from day 15 to 30 of gestation, and in eight neonatal, 4 and 8 day old rabbits. These SCO-associated neurons, first observed on day 17 of gestation, develop into (1) a rostral mesodiencephalic nerve cell group situated in an area dorsal to the rostral-most part of the SCO and (2) a more caudal layer of single neurons extending throughout the length of the SCO. The present findings are discussed in relation to recent histochemical studies that demonstrated AChE-positive neurons in the pineal complex and subcommissural area of frogs and to recent fluorescence microscopic studies in fetal and adult rats in which a 5-HT system is known to extend from the nucleus raphe dorsalis (B7) along the SCO to the pineal stalk and habenular region. The term "SCO-associated neurons" is a purely morphological way of describing the neurons in question as the neural interconnections of these neurons are still a matter of speculation.