初级视皮层神经元响应反应与撤反应的朝向选择性

朝向选择性是初级视皮层(17区或V1)神经元的基本性质,在图形感知中起着关键作用.同时这些神经元对于持续时间大于100 ms的视觉刺激具有清晰的响应反应(Onset responses)和撤反应(Offset responses).以往的研究只关注响应反应的朝向选择性,而忽视了对撤反应的朝向选择性研究.我们比较了响应与撤反应的朝向调谐性质,大多数细胞的撤反应与响应反应基本上具有相似的最优朝向,而撤反应的朝向调谐宽度有窄于响应反应的趋势,撤反应的最优延迟普遍滞后于响应反应的最优延迟.撤反应的朝向选择性略强于响应反应和具有显著长的反应延迟提示,皮层内的反馈输入可能在形成撤反应的朝向选择性中起着作用.本研究揭示了撤反应的朝向选择性在刺激朝向的连续表征和主体在形状知觉的后期对朝向的精细区分中起着作用.     

纹外皮层PMLS区反馈投射对初级视皮层神经元反应特性的影响

神经系统中存在大量下行投射,与上行输入一起形成复杂的前馈与反馈回路,调控神经信号的传导和处理,但目前对皮层内反馈投射的功能作用认识还比较薄弱.通过微量注射抑制性神经递质γ-氨基丁酸(γ-aminobutyric acid,GABA),使猫纹外皮层后内侧外上雪氏区(area posteromedial lateral suprasylvian,PMLS)局部可逆性失活,使用胞外记录方法,研究初级视皮层17区神经元反应特性的变化.实验结果显示,PMLS区失活后,17区细胞对运动刺激的反应总体减弱,反应的相对稳定性基本不变,最高发放率/自发之比有所下降.与此同时,细胞的方向选择性指数减小,朝向选择性无显著变化.除少数"双向"反应细胞外,绝大部分细胞的最优方向基本不变.进一步分析发现,细胞对各个方向刺激的反应普遍下降,最优方向上的下降程度最大,是导致方向选择性减弱的主要原因.这些结果表明,PMLS区反馈投射可增强初级视皮层的方向选择性,而对朝向选择性影响有限.这一作用特点体现了PMLS区在皮层中偏重处理运动视觉信息的功能.     

视觉刺激对猴初级视皮层神经元眼球位置效应的影响

用细胞外记录的方法,研究了视觉刺激对清醒猴初级视皮层神经元眼球位置效应的影响,当猴注视电视屏幕上２５个不同位置的小光点时,屏蔽上分别给予两种不同形式的视觉刺激：注视点周围的闪光圆环和感受野内的移动光条。这两种刺激都能增强初级视皮层神经元的眼球位置相关活动,并相应地使受眼球位置调制的神经元的比例明显增加。     

基于初级视觉皮层的图像匹配模型

提出一种基于初级视觉皮层的图像匹配模型。该模型只采用方位选择性细胞和皮层内有限范围水平连接等Ｖ１基本单元,它以链码表示的目标轮廓作为知识,允许该知识以时间脉冲的形式控制Ｖ１区内神经细胞的动态活动,使与知识轮廓形状相符合的轮廓内的细胞,逐步进入并维持在兴奋状态,最终实现对视野中特定目标轮廓的提取     

猫初级视皮层神经元不依赖于图形取向的方向调谐

设计并利用运动“随机”线条图研究了猫初级视皮层(V1)共91个细胞的方向调谐特性.结果表明, V1区神经元的方向选择性除了存在基于图形成分取向的机制以外,还存在不基于取向因素的机制.当刺激图形中的取向或非取向因素增强时,神经元的方向调谐也会相应转变.     

初级视皮层神经元非经典感受野研究的新进展

感觉皮层神经元的非经典感受野(简称"外周")对经典感受野(简称"中心")的调节作用广泛存在于哺乳动物中,被认为是感觉皮层神经元的基本特性.以初级视皮层神经元为例,刺激其外周能有效地调节刺激其中心引起的反应,这种作用主要是抑制性的.理解初级视皮层神经元的外周对中心的调节机制能够深入揭示哺乳动物的感觉皮层神经元信息处理的基本原则.本文综述了引起初级视皮层神经元非经典感受野对经典感受野调节作用的神经环路机制和计算模型研究的进展.     

初级视皮层神经元集群对拓扑特征响应的可视化表征

神经元集群响应的高维特性是脑机制研究面临的主要困难之一.拓扑特征是图像的基本特征之一,为了有效表征高维的神经元集群响应的拓扑特征特性,提出了一种基于三维自组织映射网络采用RGB颜色特征表征神经元集群响应的动态可视化方法,分析多通道微电极阵列采集的大鼠初级视觉皮层(V1区)神经元集群信号,进而研究了V1区神经元集群对图形拓扑特征的响应特性.通过与主成分分析(PCA)方法进行对比发现:该方法能够有效表征V1区神经元集群对拓扑结构的时序动态响应特征,表征方式形象直观,具有一定的优越性.     

初级视皮层神经元对瞬态刺激响应的时间性质

初级视皮层神经元对周期性运动光栅刺激具有周期性持续响应,而对没有周期性变化的静止恒定刺激的响应主要集中在刺激呈现的初期,为瞬时性响应.我们研究了在5～50 ms短时长静止刺激下神经元的响应性质,对响应时程的分析表明,猫初级视皮层神经元对瞬态刺激的响应曲线呈波峰形式.随着刺激的出现,在经过一段延迟后,响应幅度上升,出现一个或多个响应峰,随刺激的消失,响应幅度下降.神经元表现出随刺激时长的增长,响应峰主峰(第一个峰)的峰值时间和峰宽都有增加的趋势,但峰值时间在30～50 ms趋于饱和,除5 ms刺激时长诱发的峰高明显降低以外,其他刺激时长诱发的峰高较恒定.刺激消失变为灰屏时,神经元会产生撤反应峰(刺激后发放,offset responses),其强度由前面的刺激时长决定.最小响应时长约为39 ms,主峰与撤峰的最小时间差为36 ms,二者十分相近,提示了视初级视皮层神经元的基本响应时间约为35～40 ms.这可能是"视觉暂留"现象在初级视皮层水平的生理基础.     

高糖饮食对青年小鼠初级视觉皮层的功能损伤及其机制

目的 诸多研究证实高糖饮食会对视觉功能造成损伤，但是目前关于高糖饮食对视觉功能影响的研究主要聚焦于视觉通路前端，集中在眼球系统和视神经节部分，对于视觉通路的后端如中枢皮层还未有过相关报道。为了更全面地了解高糖饮食对视觉功能的影响，本文补充高糖饮食对视觉中枢皮层影响的研究。方法 本研究利用GO/NO-GO方位辨别任务的行为学范式、在体多通道电生理技术探究了高糖饮食对青年小鼠初级视觉皮层的影响。结果 行为学结果表明，经历了2个月高糖喂养的青年小鼠，方位辨别能力下降。通过电生理技术分析初级视觉皮层（V1）单个神经元的反应特性，发现高糖饮食小鼠初级视觉皮层单个神经元的方位调谐能力下降，神经元的反应变异性增加、信噪比明显降低。神经元噪音相关性分析结果表明，高糖饮食组小鼠初级视觉皮层的噪音相关性表现出明显的上调。进一步分析群体水平上信噪比和反应变异性的变化，结果表明群体水平上信噪比明显下降而反应变异性明显上升。结论 高糖饮食通过影响初级视觉皮层单个神经元的感受野特征以及群体神经元的信息处理能力，损伤了青年小鼠的方位辨别能力。     

基于等度规映射的大鼠初级视觉皮层视像整体特征识别

整体特征是视觉信息的基本特征之一。为了认知大鼠初级视觉皮层神经元对视像整体特征的处理机制,首先给出确定有效响应时间区间的方法,确定了有效响应时间区间;然后,确定有效响应时间区间内、不同整体特征视像刺激下的神经元发放特征,并利用等度规映射进行了特征整合,进而对整合后的特征使用支持向量机进行分类;最后,将该方法应用于大鼠的初级视觉皮层视像整体特征识别,并将其分类结果分别与使用主成分分析法进行特征整合以及直接统计神经元发放特征的分类结果进行了对比。对比表明:该方法较其他两种方法,对于整体特征的识别准确率均有不同程度的明显提高。     

Directional tunings independent of orientation in the primary visual cortex of the cat

A family of moving 'random-line' patterns was developed and used to study the directional tuning of 91 single units in cat primary visual cortex (V1). The results suggest that, in addition to the well-known orientation-dependent mechanism, there is also some kind of orientation-independent mechanism underlying the direction selectivity. The directional tuning of the neurons varies in accordance with the increase of orientation or non-orientation element in the stimulus.     

Directional tunings independent of orientation in the primary visual cortex of the cat

A family of moving ‘random-line’ patterns was developed and used to study the directional tuning of 91 single units in cat primary visual cortex (V1). The results suggest that, in addition to the well-known orientation-dependent mechanism, there is also some kind of orientationindependent mechanism underlying the direction selectivity. The directional tuning of the neurons varies in accordance with the increase of orientation or non-orientation element in the stimulus.     

Coarse-grained reduction and analysis of a network model of cortical response: I. Drifting grating stimuli

We present a reduction of a large-scale network model of visual cortex developed by McLaughlin, Shapley, Shelley, and Wielaard. The reduction is from many integrate-and-fire neurons to a spatially coarse-grained system for firing rates of neuronal subpopulations. It accounts explicitly for spatially varying architecture, ordered cortical maps (such as orientation preference) that vary regularly across the cortical layer, and disordered cortical maps (such as spatial phase preference or stochastic input conductances) that may vary widely from cortical neuron to cortical neuron. The result of the reduction is a set of nonlinear spatiotemporal integral equations for phase-averaged firing rates of neuronal subpopulations across the model cortex, derived asymptotically from the full model without the addition of any extra phenomological constants. This reduced system is used to study the response of the model to drifting grating stimuli—where it is shown to be useful for numerical investigations that reproduce, at far less computational cost, the salient features of the point-neuron network and for analytical investigations that unveil cortical mechanisms behind the responses observed in the simulations of the large-scale computational model. For example, the reduced equations clearly show (1) phase averaging as the source of the time-invariance of cortico-cortical conductances, (2) the mechanisms in the model for higher firing rates and better orientation selectivity of simple cells which are near pinwheel centers, (3) the effects of the length-scales of cortico-cortical coupling, and (4) the role of noise in improving the contrast invariance of orientation selectivity.     

The universal fuzzy logical framework of neural cir-cuits and its application in modeling primary visual cortex

Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.     

States of high conductance in a large-scale model of the visual cortex

This paper reports on the consequences of large, activity dependent, synaptic conductances for neurons in a large-scale neuronal network model of the input layer 4C of the Macaque primary visual cortex (Area V1). This high conductance state accounts for experimental observations about orientation selectivity, dynamics, and response magnitude (D. McLaughlin et al. (2000) Proc. Natl. Acad. Sci. USA 97: 8087–8092), and the linear dependence of Simple cells on visual stimuli (J. Wielaard et al. (2001) J. Neuroscience 21: 5203–5211). The source of large conductances in the model can be traced to inhibitory corticocortical synapses, and the model's predictions of large conductance changes are consistent with recent intracellular measurements (L. Borg-Graham et al. (1998) Nature 393: 369–373; J. Hirsch et al. (1998) J. Neuroscience 15: 9517–9528; J.S. Anderson et al. (2000) J. Neurophysiol. 84: 909–926). During visual stimulation, these conductances are large enough that their associated time-scales become the shortest in the model cortex, even below that of synaptic interactions. One consequence of this activity driven separation of time-scales is that a neuron responds very quickly to temporal changes in its synaptic drive, with its intracellular membrane potential tracking closely an effective reversal potential composed of the instantaneous synaptic inputs. From the effective potential and large synaptic conductance, the spiking activity of a cell can be expressed in an interesting and simplified manner, with the result suggesting how accurate and smoothly graded responses are achieved in the model network. Further, since neurons in this high-conductance state respond quickly, they are also good candidates as coincidence detectors and burst transmitters.     

Traveling Waves and the Processing of Weakly Tuned Inputs in a Cortical Network Module

Recent studies have shown that local cortical feedback can havean important effect on the response of neurons in primary visualcortex to the orientation of visual stimuli. In this work, westudy the role of the cortical feedback in shaping thespatiotemporal patterns of activity in cortex. Two questionsare addressed: one, what are the limitations on the ability ofcortical neurons to lock their activity to rotatingoriented stimuli within a single receptive field? Two, can thelocal architecture of visual cortex lead to the generation ofspontaneous traveling pulses of activity? We study theseissues analytically by a population-dynamic model of ahypercolumn in visual cortex. The order parameter thatdescribes the macroscopic behavior of the network is thetime-dependent population vector of the network. We firststudy the network dynamics under the influence of a weakly tunedinput that slowly rotates within the receptive field. We showthat if the cortical interactions have strong spatialmodulation, the network generates a sharply tuned activityprofile that propagates across the hypercolumn in a path thatis completely locked to the stimulus rotation. The resultantrotating population vector maintains a constant angular lagrelative to the stimulus, the magnitude of which grows with thestimulus rotation frequency. Beyond a critical frequency thepopulation vector does not lock to the stimulus but executes aquasi-periodic motion with an average frequency that is smallerthan that of the stimulus. In the second part we consider thestable intrinsic state of the cortex under the influence of isotropic stimulation. We show that if the local inhibitoryfeedback is sufficiently strong, the network does not settleinto a stationary state but develops spontaneous travelingpulses of activity. Unlike recent models of wave propagation incortical networks, the connectivity pattern in our model isspatially symmetric, hence the direction of propagation ofthese waves is arbitrary. The interaction of these waves withan external-oriented stimulus is studied. It is shown that thesystem can lock to a weakly tuned rotating stimulus if thestimulus frequency is close to the frequency of the intrinsic wave.     

Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex

In the primate visual pathway, orientation tuning of neurons is first observed in the primary visual cortex. The LGN cells that comprise the thalamic input to V1 are not orientation tuned, but some V1 neurons are quite selective. Two main classes of theoretical models have been offered to explain orientation selectivity: feedforward models, in which inputs from spatially aligned LGN cells are summed together by one cortical neuron; and feedback models, in which an initial weak orientation bias due to convergent LGN input is sharpened and amplified by intracortical feedback. Recent data on the dynamics of orientation tuning, obtained by a cross-correlation technique, may help to distinguish between these classes of models. To test this possibility, we simulated the measurement of orientation tuning dynamics on various receptive field models, including a simple Hubel-Wiesel type feedforward model: a linear spatiotemporal filter followed by an integrate-and-fire spike generator. The computational study reveals that simple feedforward models may account for some aspects of the experimental data but fail to explain many salient features of orientation tuning dynamics in V1 cells. A simple feedback model of interacting cells is also considered. This model is successful in explaining the appearance of Mexican-hat orientation profiles, but other features of the data continue to be unexplained.     

A neuronal basis of iconic memory in macaque primary visual cortex

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Age-associated reduction of nuclear shape dynamics in excitatory neurons of the visual cortex

Neurons decline in their functionality over time, and age-related neuronal alterations are associated with phenotypes of neurodegenerative diseases. In nonneural tissues, an infolded nuclear shape has been proposed as a hallmark of aged cells and neurons with infolded nuclei have also been reported to be associated with neuronal activity. Here, we performed time-lapse imaging in the visual cortex of Nex-Cre;SUN1-GFP mice. Nuclear infolding was observed within 10 min of stimulation in young nuclei, while the aged nuclei were already infolded pre-stimulation and showed reduced dynamics of the morphology. In young nuclei, the depletion of the stimuli restored the nucleus to a spherical shape and reduced the dynamic behavior, suggesting that nuclear infolding is a reversible process. We also found the aged nucleus to be stiffer than the young one, further relating to the age-associated loss of nuclear shape dynamics. We reveal temporal changes in the nuclear shape upon external stimulation and observe that these morphological dynamics decrease with age.     

Comparative study on direction selectivity and functional organization of the primary visual cortical cells in monkeys and cats

Although the directionally selective cells in many visual cortical areas are organized in columnar manner, the functional organization of direction selectivity of area Vl in the monkey still remains unclear. We quantitatively studied the proportion of directionally selective cells, direction selectivity and the functional organization of the striate cortical cells in the monkey and compared those with the cat. The results show that the direction selectivity and directional organization of striate cortical cells in the monkey are significantly weaker than those in the cat, suggesting that the species difference between the two kinds of animal is related to their different anatomic pathways.