922 resultados para Callosal Neurons
Resumo:
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
Resumo:
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.
Resumo:
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.
Resumo:
A computational model of visual processing in the vertebrate retina provides a unified explanation of a range of data previously treated by disparate models. Three results are reported here: the model proposes a functional explanation for the primary feed-forward retinal circuit found in vertebrate retinae, it shows how this retinal circuit combines nonlinear adaptation with the desirable properties of linear processing, and it accounts for the origin of parallel transient (nonlinear) and sustained (linear) visual processing streams as simple variants of the same retinal circuit. The retina, owing to its accessibility and to its fundamental role in the initial transduction of light into neural signals, is among the most extensively studied neural structures in the nervous system. Since the pioneering anatomical work by Ramón y Cajal at the turn of the last century[1], technological advances have abetted detailed descriptions of the physiological, pharmacological, and functional properties of many types of retinal cells. However, the relationship between structure and function in the retina is still poorly understood. This article outlines a computational model developed to address fundamental constraints of biological visual systems. Neurons that process nonnegative input signals-such as retinal illuminance-are subject to an inescapable tradeoff between accurate processing in the spatial and temporal domains. Accurate processing in both domains can be achieved with a model that combines nonlinear mechanisms for temporal and spatial adaptation within three layers of feed-forward processing. The resulting architecture is structurally similar to the feed-forward retinal circuit connecting photoreceptors to retinal ganglion cells through bipolar cells. This similarity suggests that the three-layer structure observed in all vertebrate retinae[2] is a required minimal anatomy for accurate spatiotemporal visual processing. This hypothesis is supported through computer simulations showing that the model's output layer accounts for many properties of retinal ganglion cells[3],[4],[5],[6]. Moreover, the model shows how the retina can extend its dynamic range through nonlinear adaptation while exhibiting seemingly linear behavior in response to a variety of spatiotemporal input stimuli. This property is the basis for the prediction that the same retinal circuit can account for both sustained (X) and transient (Y) cat ganglion cells[7] by simple morphological changes. The ability to generate distinct functional behaviors by simple changes in cell morphology suggests that different functional pathways originating in the retina may have evolved from a unified anatomy designed to cope with the constraints of low-level biological vision.
Resumo:
This paper describes a self-organizing neural model for eye-hand coordination. Called the DIRECT model, it embodies a solution of the classical motor equivalence problem. Motor equivalence computations allow humans and other animals to flexibly employ an arm with more degrees of freedom than the space in which it moves to carry out spatially defined tasks under conditions that may require novel joint configurations. During a motor babbling phase, the model endogenously generates movement commands that activate the correlated visual, spatial, and motor information that are used to learn its internal coordinate transformations. After learning occurs, the model is capable of controlling reaching movements of the arm to prescribed spatial targets using many different combinations of joints. When allowed visual feedback, the model can automatically perform, without additional learning, reaches with tools of variable lengths, with clamped joints, with distortions of visual input by a prism, and with unexpected perturbations. These compensatory computations occur within a single accurate reaching movement. No corrective movements are needed. Blind reaches using internal feedback have also been simulated. The model achieves its competence by transforming visual information about target position and end effector position in 3-D space into a body-centered spatial representation of the direction in 3-D space that the end effector must move to contact the target. The spatial direction vector is adaptively transformed into a motor direction vector, which represents the joint rotations that move the end effector in the desired spatial direction from the present arm configuration. Properties of the model are compared with psychophysical data on human reaching movements, neurophysiological data on the tuning curves of neurons in the monkey motor cortex, and alternative models of movement control.
Resumo:
Growth differentiation factor-5 (GDF-5) is a member of the transforming growth factor-β superfamily, a family of proteins that play diverse roles in many aspects of cell growth, proliferation and differentiation. GDF-5 has also been shown to be a trophic factor for embryonic midbrain dopaminergic neurons in vitro (Krieglstein et al. 1995) and after transplantation to adult rats in vivo (Sullivan et al. 1998). GDF-5 has also been shown to have neuroprotective and neurorestorative effects on adult dopaminergic neurons in the substantia nigra in animal models of Parkinson’s disease (Sullivan et al. 1997, 1999; Hurley et al. 2004). This experimental evidence has lead to GDF-5 being proposed as a neurotrophic factor with potential for use in the treatment of Parkinson’s disease. However, it is not know if GDF-5 is expressed in the brain and whether it plays a role in dopaminergic neuron development. The experiments presented here aim to address these questions. To that end this thesis is divided into five separate studies each addressing a particular question associated with GDF-5 and its expression patterns and roles during the development of the rat midbrain. Expression of the GDF-5 in the developing rat ventral mesencephalon (VM) was found to begin at E12 and peak on E14, the day that dopaminergic neurons undergo terminal differentiation. In the adult rat, GDF-5 was found to be restricted to heart and brain, being expressed in many areas of the brain, including striatum and midbrain. This indicated a role for GDF-5 in the development and maintenance of dopaminergic neurons. The appropriate receptors for GDF-5 (BMPR-II and BMPR-Ib) were found to be expressed at high levels in the rat VM at E14 and BMPR-II expression was demonstrated on dopaminergic neurons in the E13 mouse VM. GDF-5 resulted in a three-fold increase in the numbers of dopaminergic neurons in cultures of E14 rat VM, without affecting the numbers of neurones or total cells. GDF-5 was found to increase the proportion of neurons that were dopaminergic. The numbers of Nurr1-positive cells were not affected by GDF-5 treatment, but GDF-5 did increase the numbers of Nurr1- positive cells that expressed tyrosine hydroxylase (TH). Taken together this data indicated that GDF-5 increases the conversion of Nurr1-positive, TH-negative cells to Nurr1-positive, TH-positive cells. In GDF-5 treated cultures, total neurite length, neurite arborisation and somal area of dopaminergic were all significantly increased compared to control cultures. Thus this study showed that GDF-5 increased the numbers and morphological differentiation of VM dopaminergic neurones in vitro. In order to examine if GDF-5 could induce a dopaminergic phenotype in neural progenitor cells, neurosphere cultures prepared from embryonic rat VM were established. The effect of the gestational age of the donor VM on the proportion of cell types generated from neurospheres from E12, E13 and E14 VM was examined. Dopaminergic neurons could only be generated from neurospheres which were prepared from E12 VM. Thus in subsequent studies the effect of GDF-5 on dopaminergic induction was examined in progentior cell cultures prepared from the E12 rat VM. In primary cultures of E12 rat VM, GDF-5 increased the numbers of TH-positive cells without affecting the proliferation or survival of these cells. In cultures of expanded neural progenitor cells from the E12 rat VM, GDF-5 increased the expression of Nurr1 and TH, an action that was dependent on signalling through the BMPR-Ib receptor. Taken together, these experiments provide evidence that GDF-5 is expressed in the developing rat VM, is involved in both the induction of a dopaminergic phenotype in cells of the VM and in the subsequent morphological development of these dopaminergic neurons
Resumo:
Growth/differentiation factor 5 (GDF5) and glial cell line-derived neurotrophic factor (GDNF) are neurotrophic factors that promote the survival of midbrain dopaminergic neurons in vitro and in vivo. Both factors have potent neurotrophic and neuroprotective effects in rat models of Parkinson's disease (PD), and may represent promising new therapies for PD. The aim of the present study was to investigate the endogenous expression and function of GDF5 and GDNF in the nigrostriatal dopaminergic system during development and in rat models of PD. Examination of the temporal expression patterns of endogenous GDF5, GDNF, and their respective receptors, in the developing and adult nigrostriatal dopaminergic system suggest that these factors play important roles in promoting the survival and maturation of midbrain dopaminergic neurons during the period of postnatal programmed cell death. The relative levels of GDF5 and GDNF mRNAs in the midbrain and striatum, and their individual temporal expression patterns during development, suggest that their modes of actions are quite distinct in vivo. Furthermore, the sustained expression of GDF5, GDNF, and their receptors into adulthood suggest roles for these factors in the continued support and maintenance of mature nigrostriatal dopaminergic neurons. The present study found that endogenous GDF5, GDNF, and their receptors are differentially expressed in two 6-hydroxydopamine-induced lesion adult rat models of PD. In both terminal and axonal lesion models of PD, GDF5 mRNA levels in the striatum increased at 10 days post-lesion, while GDNF mRNA levels in the nigrostriatal system decreased at 10 and 28 days post-lesion. Thus, despite the fact that exogenous GDF5 and GDNF have similar effects on midbrain dopaminergic neurons in vitro and in vivo, their endogenous responses to a neurotoxic injury are quite distinct. These results highlight the importance of studying the temporal dynamic changes in neurotrophic factor expression during development and in animal models of PD.