亮度与对比度对猫初级视皮层神经元反应影响的研究
发布时间：2018-12-11 18:53
【摘要】：目的 本研究旨在从细胞水平研究不同视觉经验条件下猫初级视皮层神经元的反应调制特性,并探讨猫初级视皮层神经元对亮度与对比度信息处理及编码的神经机制。 方法 利用在体单细胞细胞外记录技术,记录麻醉状态下成年猫V1区神经元对不同亮度(5%-100%)及不同对比度(5%～100%)视觉刺激的反应。分析神经元的发放率(spike rate)及反应潜时(response latency),分别绘制亮度调制曲线,对比度调制曲线,并进行回归拟合分析。分析发放率及反应潜时的变异系数(C.V),通过C.V比较二者在神经编码中的效能。分析神经元反应的变异性(variability),以此判断神经元反应的时间精度。 结果 1.猫V1区神经元对不同亮度刺激的反应： 猫V1区神经元发放率随亮度的增强而升高,在低亮度(5-20%)时,发放率变化较明显,而在亮度达到最大值的约40%后基本达到平台期,发放率变化幅度降低,趋于稳定。总体趋势调制曲线符合Cubic回归模型,回归方程为：Y=4.957+2.283X-0.035X2+0.0002X3(P=0.000)。 神经元反应潜时随亮度增强而缩短,在低亮度(5-20%)时,潜时变化较明显,而在亮度达到最大值的约40%以后,潜时变化幅度降低,趋于稳定。总体趋势调制曲线符合Inverse回归模型,回归方程为：Y=71.19+353.45/X(P=0.000)。 神经元对不同亮度刺激反应的潜时编码的变异度小于发放率编码,差异有统计学意义(P=0.000)。 神经元反应变异性随亮度增强而减小,其在5-20%亮度时变化较大,而在亮度达到30%以后变化均无统计学意义,反应的时间精度可达±5ms。 2.猫V1区神经元对不同对比度刺激的反应： 猫V1区神经元发放率随对比度增强而升高,在低对比度(5-20%)时,发放率变化较明显,而在对比度达到最大值的约40%后基本达到平台期,发放率变化幅度降低,趋于稳定。总体趋势调制曲线符合Cubic回归模型,回归方程为Y=-0.660+1.540X-0.013X2+0.0003X3(P=0.000)。 神经元反应潜时随对比度增强而缩短,在低对比度(5～20%)时,潜时变化较明显,而在对比度达到最大值的约40%以后,潜时变化幅度降低,趋于稳定。总体趋势调制曲线符合Inverse回归模型,回归方程为：Y=74.22+287.58/X(P=0.000)。 神经元对不同对比度刺激反应的潜时编码的变异度小于发放率编码,差异有统计学意义(P=0.000)。 神经元反应变异性随对比度增强而减小,其在5-20%亮度时变化较大,而在亮度达到30%以后变化均无统计学意义,反应的时间精度可达±5ms。 结论 发放率和反应潜时是猫V1区神经元对亮度及对比度信息进行编码重要机制,且潜时编码较发放率编码更为精确有效。神经元发放率随亮度或对比度增强而升高,反应潜时及变异性随亮度或对比度的增强而缩短。亮度或对比度信息降低至30～40%以后可造成神经元反应的明显改变,可被认为是异常的视觉经验。神经元反应的时间精度可达±5ms,有利于视觉信息的快速处理。
[Abstract]:Objective to investigate the modulation and response characteristics of primary visual cortex neurons in cats under different visual experiences at the cellular level and to explore the neural mechanism of brightness and contrast information processing and coding of primary visual cortex neurons in cats. Methods\ The luminance modulation curve and contrast modulation curve were drawn by (spike rate) and (response latency), respectively, and the regression fitting analysis was carried out. The release rate and the coefficient of variation (C.V) of response latency were analyzed, and the effectiveness of the two methods in neural coding was compared by means of C.V. The time accuracy of neuron response was evaluated by analyzing the variability of neuron response (variability),. Result 1. Responses of Cat V1 neurons to different luminance stimuli: the firing rate of Cat V1 neurons increased with the increase of luminance, and at low brightness (5-20%), the firing rate changed more obviously. When the luminance reaches about 40% of the maximum, it reaches the plateau stage, and the range of the distribution rate decreases and tends to be stable. The general trend modulation curve was in accordance with the Cubic regression model, and the regression equation was YT 4.957 2.283X-0.035X2 0.0002X3 (P0. 000). The latent time of neuronal response was shortened with the increase of brightness. When the brightness was low (5-20%), the latent time changed more obviously, but when the brightness reached about 40% of the maximum value, the amplitude of the latent time decreased and tended to be stable. The general trend modulation curve accords with the Inverse regression model, and the regression equation is: Yan 71.19 353.45% X (P0. 000). The variation of latent time coding of neurons to different luminance stimuli was lower than that of emitter rate (P0. 000). The variability of neuronal response decreased with the increase of luminance, which changed greatly at 5-20% brightness, but had no statistical significance after 30% brightness. The time precision of the reaction could reach 卤5 Ms. 2. Responses of Cat V1 neurons to different contrast stimuli: the firing rate of Cat V1 neurons increased with the increase of contrast, and at low contrast (5-20%), the firing rate changed more obviously. After reaching the maximum contrast of about 40%, the distribution rate decreases and tends to be stable. The general trend modulation curve is consistent with the Cubic regression model, and the regression equation is Y-0.660 1.540X-0.013X2 0.0003X3 (P0. 000). The latent time of neuron response was shortened with the increase of contrast. When the contrast was low (5 ~ 20%), the latent time changed more obviously, but after the contrast reached about 40% of the maximum value, the amplitude of latent time decreased and tended to be stable. The general trend modulation curve accords with the Inverse regression model, and the regression equation is: Yan 74.22 287.58 / X (P0. 000). The variation of latent time coding of neurons to different contrast stimuli was lower than that of emitter rate (P0. 000). The variability of neuronal response decreased with the increase of contrast. It changed greatly at the brightness of 5-20%, but had no statistical significance after the brightness reached 30%, and the time precision of the reaction could reach 卤5 Ms. Conclusion the firing rate and the response latency are important mechanisms for encoding the luminance and contrast information of the neurons in the V1 region of cats, and the latent time coding is more accurate and effective than the firing rate coding. The firing rate of neurons increased with the enhancement of brightness or contrast, and the latency and variability decreased with the enhancement of brightness or contrast. When the brightness or contrast information is reduced to 30 ~ 40%, it can cause obvious changes in neuronal response, which can be considered as abnormal visual experience. The time accuracy of neuronal response can reach 卤5 Ms, which is beneficial to the rapid processing of visual information.
【学位授予单位】：天津医科大学
【学位级别】：硕士
【学位授予年份】：2010
【分类号】：R77
本文编号：2373051
[Abstract]:Objective to investigate the modulation and response characteristics of primary visual cortex neurons in cats under different visual experiences at the cellular level and to explore the neural mechanism of brightness and contrast information processing and coding of primary visual cortex neurons in cats. Methods\ The luminance modulation curve and contrast modulation curve were drawn by (spike rate) and (response latency), respectively, and the regression fitting analysis was carried out. The release rate and the coefficient of variation (C.V) of response latency were analyzed, and the effectiveness of the two methods in neural coding was compared by means of C.V. The time accuracy of neuron response was evaluated by analyzing the variability of neuron response (variability),. Result 1. Responses of Cat V1 neurons to different luminance stimuli: the firing rate of Cat V1 neurons increased with the increase of luminance, and at low brightness (5-20%), the firing rate changed more obviously. When the luminance reaches about 40% of the maximum, it reaches the plateau stage, and the range of the distribution rate decreases and tends to be stable. The general trend modulation curve was in accordance with the Cubic regression model, and the regression equation was YT 4.957 2.283X-0.035X2 0.0002X3 (P0. 000). The latent time of neuronal response was shortened with the increase of brightness. When the brightness was low (5-20%), the latent time changed more obviously, but when the brightness reached about 40% of the maximum value, the amplitude of the latent time decreased and tended to be stable. The general trend modulation curve accords with the Inverse regression model, and the regression equation is: Yan 71.19 353.45% X (P0. 000). The variation of latent time coding of neurons to different luminance stimuli was lower than that of emitter rate (P0. 000). The variability of neuronal response decreased with the increase of luminance, which changed greatly at 5-20% brightness, but had no statistical significance after 30% brightness. The time precision of the reaction could reach 卤5 Ms. 2. Responses of Cat V1 neurons to different contrast stimuli: the firing rate of Cat V1 neurons increased with the increase of contrast, and at low contrast (5-20%), the firing rate changed more obviously. After reaching the maximum contrast of about 40%, the distribution rate decreases and tends to be stable. The general trend modulation curve is consistent with the Cubic regression model, and the regression equation is Y-0.660 1.540X-0.013X2 0.0003X3 (P0. 000). The latent time of neuron response was shortened with the increase of contrast. When the contrast was low (5 ~ 20%), the latent time changed more obviously, but after the contrast reached about 40% of the maximum value, the amplitude of latent time decreased and tended to be stable. The general trend modulation curve accords with the Inverse regression model, and the regression equation is: Yan 74.22 287.58 / X (P0. 000). The variation of latent time coding of neurons to different contrast stimuli was lower than that of emitter rate (P0. 000). The variability of neuronal response decreased with the increase of contrast. It changed greatly at the brightness of 5-20%, but had no statistical significance after the brightness reached 30%, and the time precision of the reaction could reach 卤5 Ms. Conclusion the firing rate and the response latency are important mechanisms for encoding the luminance and contrast information of the neurons in the V1 region of cats, and the latent time coding is more accurate and effective than the firing rate coding. The firing rate of neurons increased with the enhancement of brightness or contrast, and the latency and variability decreased with the enhancement of brightness or contrast. When the brightness or contrast information is reduced to 30 ~ 40%, it can cause obvious changes in neuronal response, which can be considered as abnormal visual experience. The time accuracy of neuronal response can reach 卤5 Ms, which is beneficial to the rapid processing of visual information.
【学位授予单位】：天津医科大学
【学位级别】：硕士
【学位授予年份】：2010
【分类号】：R77
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