5 resultados para Nerve Net

em DigitalCommons@The Texas Medical Center


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Ciliary locomotion in the nudibranch mollusk Hermissenda is modulated by the visual and graviceptive systems. Components of the neural network mediating ciliary locomotion have been identified including aggregates of polysensory interneurons that receive monosynaptic input from identified photoreceptors and efferent neurons that activate cilia. Illumination produces an inhibition of type I(i) (off-cell) spike activity, excitation of type I(e) (on-cell) spike activity, decreased spike activity in type III(i) inhibitory interneurons, and increased spike activity of ciliary efferent neurons. Here we show that pairs of type I(i) interneurons and pairs of type I(e) interneurons are electrically coupled. Neither electrical coupling or synaptic connections were observed between I(e) and I(i) interneurons. Coupling is effective in synchronizing dark-adapted spontaneous firing between pairs of I(e) and pairs of I(i) interneurons. Out-of-phase burst activity, occasionally observed in dark-adapted and light-adapted pairs of I(e) and I(i) interneurons, suggests that they receive synaptic input from a common presynaptic source or sources. Rhythmic activity is typically not a characteristic of dark-adapted, light-adapted, or light-evoked firing of type I interneurons. However, burst activity in I(e) and I(i) interneurons may be elicited by electrical stimulation of pedal nerves or generated at the offset of light. Our results indicate that type I interneurons can support the generation of both rhythmic activity and changes in tonic firing depending on sensory input. This suggests that the neural network supporting ciliary locomotion may be multifunctional. However, consistent with the nonmuscular and nonrhythmic characteristics of visually modulated ciliary locomotion, type I interneurons exhibit changes in tonic activity evoked by illumination.

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A Pavlovian-conditioning procedure may produce modifications in multiple behavioral responses. As an example, conditioning may result in the elicitation of a specific somatomotor conditioned response (CR) and, in addition, other motor and visceral CRs. In the mollusk Hermissenda conditioning produces two conditioned responses: foot-shortening and decreased locomotion. The neural circuitry supporting ciliary locomotion is well characterized, although the neural circuit underlying foot-shortening is poorly understood. Here we describe efferent neurons in the pedal ganglion that produce contraction or extension of specific regions of the foot in semi-intact preparations. Synaptic connections between polysensory type Ib and type Is interneurons and identified foot contractile efferent neurons were examined. Type Ib and type Is interneurons receive synaptic input from the visual, graviceptive, and somatosensory systems. Depolarization of type Ib interneurons evoked spikes in identified tail and lateral foot contractile efferent neurons. Mechanical displacement of the statocyst evoked complex excitatory postsynaptic potentials (EPSPs) and spikes recorded from type Ib and type Is interneurons and complex EPSPs and spikes in identified foot contractile efferent neurons. Depolarization of type Ib interneurons in semi-intact preparations produced contraction and shortening along the rostrocaudal axis of the foot. Depolarization of Is interneurons in semi-intact preparations produced contraction of the anterior region of the foot. Taken collectively, the results suggest that type Ib and type Is polysensory interneurons may contribute to the neural circuit underlying the foot-shortening CR in Hermissenda.

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The ability to represent time is an essential component of cognition but its neural basis is unknown. Although extensively studied both behaviorally and electrophysiologically, a general theoretical framework describing the elementary neural mechanisms used by the brain to learn temporal representations is lacking. It is commonly believed that the underlying cellular mechanisms reside in high order cortical regions but recent studies show sustained neural activity in primary sensory cortices that can represent the timing of expected reward. Here, we show that local cortical networks can learn temporal representations through a simple framework predicated on reward dependent expression of synaptic plasticity. We assert that temporal representations are stored in the lateral synaptic connections between neurons and demonstrate that reward-modulated plasticity is sufficient to learn these representations. We implement our model numerically to explain reward-time learning in the primary visual cortex (V1), demonstrate experimental support, and suggest additional experimentally verifiable predictions.

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Inappropriate response tendencies may be stopped via a specific fronto/basal ganglia/primary motor cortical network. We sought to characterize the functional role of two regions in this putative stopping network, the right inferior frontal gyrus (IFG) and the primary motor cortex (M1), using electocorticography from subdural electrodes in four patients while they performed a stop-signal task. On each trial, a motor response was initiated, and on a minority of trials a stop signal instructed the patient to try to stop the response. For each patient, there was a greater right IFG response in the beta frequency band ( approximately 16 Hz) for successful versus unsuccessful stop trials. This finding adds to evidence for a functional network for stopping because changes in beta frequency activity have also been observed in the basal ganglia in association with behavioral stopping. In addition, the right IFG response occurred 100-250 ms after the stop signal, a time range consistent with a putative inhibitory control process rather than with stop-signal processing or feedback regarding success. A downstream target of inhibitory control is M1. In each patient, there was alpha/beta band desynchronization in M1 for stop trials. However, the degree of desynchronization in M1 was less for successfully than unsuccessfully stopped trials. This reduced desynchronization on successful stop trials could relate to increased GABA inhibition in M1. Together with other findings, the results suggest that behavioral stopping is implemented via synchronized activity in the beta frequency band in a right IFG/basal ganglia network, with downstream effects on M1.

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Many cell types in the retina are coupled via gap junctions and so there is a pressing need for a potent and reversible gap junction antagonist. We screened a series of potential gap junction antagonists by evaluating their effects on dye coupling in the network of A-type horizontal cells. We evaluated the following compounds: meclofenamic acid (MFA), mefloquine, 2-aminoethyldiphenyl borate (2-APB), 18-alpha-glycyrrhetinic acid, 18-beta-glycyrrhetinic acid (18-beta-GA), retinoic acid, flufenamic acid, niflumic acid, and carbenoxolone. The efficacy of each drug was determined by measuring the diffusion coefficient for Neurobiotin (Mills & Massey, 1998). MFA, 18-beta-GA, 2-APB and mefloquine were the most effective antagonists, completely eliminating A-type horizontal cell coupling at a concentration of 200 muM. Niflumic acid, flufenamic acid, and carbenoxolone were less potent. Additionally, carbenoxolone was difficult to wash out and also may be harmful, as the retina became opaque and swollen. MFA, 18-beta-GA, 2-APB and mefloquine also blocked coupling in B-type horizontal cells and AII amacrine cells. Because these cell types express different connexins, this suggests that the antagonists were relatively non-selective across several different types of gap junction. It should be emphasized that MFA was water-soluble and its effects on dye coupling were easily reversible. In contrast, the other gap junction antagonists, except carbenoxolone, required DMSO to make stock solutions and were difficult to wash out of the preparation at the doses required to block coupling in A-type HCs. The combination of potency, water solubility and reversibility suggest that MFA may be a useful compound to manipulate gap junction coupling.