Role of fixational eye movements and saccades in processing spatial information in V1-V2-V4 networks

这个项目关注的是V1、V2和V4(V1-2-4)区域的皮质机制。 眼跳和注视眼动(FxEM：微眼跳和漂移)在视觉中的处理作用。两者都有 扫视和微扫视之后是漂移。扫视/漂移和微扫视/漂移周期的序列， 这两个周期我们将称为扫视/漂移周期(SDC)，被认为是收集信息的关键 关于视觉场景和其中的对象。我们将记录单个单位和局部场势(LFP)活动 同时从V1-2-4区的中心凹投影，而猴子执行匹配到样本的任务 形状或纹理，其中形状充满纹理，以了解SDC在皮层处理过程中的作用 积极的视觉。通过使用凝视稳定，我们将能够扰乱视网膜对皮层的输入 这项任务是有选择地探索SDC如何控制早期视觉区域的形状和纹理的加工。 在主动视觉中，SDC将空间信息映射为神经活动的时间模式。最近的建模 而心理物理工作已经确定了周期的初始瞬变阶段编码了粗略的特征， 而后者，更长的漂移周期是提取精细细节的关键。我们感兴趣的是 在SDC中，从粗略处理到精细处理的过渡是在局部和区域间皮质网络中实施的。 我们假设，在SDC期间，这些网络中的处理从瞬时前馈阶段开始 活动之后是一个更长的重复和重入活动阶段，与伽马振荡重合 电视网。我们假设形状是在SDC的初始阶段捕获的，并且 形状的边界和形状内的区域由漂移过程中的循环阶段加工而成。我们还建议 大脑皮层使用SDC序列来积累信息，内部网络的组织 大脑皮层，就它们的层次结构和用于交流的时间频带而言，取决于 序列由扫视和漂移(注视)或微扫视和漂移(注视)主导。 在目标1中，我们重点关注锁定到SDC的活动，其中与形状或纹理的样本匹配 固定为一整天的会话。这项任务中的SDC将以微扫视/漂移为主。我们会问 如果形状的准确匹配与网络中更强的SDC瞬变重合，并且如果 纹理产生稍后在SDC中出现的健壮的Gamma一致性。在AIM 2中，我们研究了 SDC处于寻找和专注于匹配到样本任务的阶段，在该阶段中，猴子被给予关于 尝试形状或质地的正确匹配。信息是通过扫视和FxEM在整个试验过程中获得的， 我们询问V1-2-4网络活动的动态如何反映性能 和任务。凝视稳定将在这两个目标中使用，以影响样本刺激的皮质处理。多么 SDC调节皮质区域之间的因果关系和这些相互作用的动力学将 通过一种新的分析方法--频率提取层次分解进行检验。

This project focuses on cortical mechanisms in areas V1, V2, and V4 (V1-2-4) underlying the information- processing roles of saccades and fixational eye movements (FxEMs: microsaccades and drift) in vision. Both saccades and microsaccades are followed by drift. Sequences of saccade/drift and microsaccade/drift cycles, both of which we will refer to as saccade/drift cycles (SDC’s), are believed to be critical to gathering information about visual scenes and the objects within them. We will record single-unit and local field potential (LFP) activity from the foveal projection in areas V1-2-4 simultaneously while monkeys perform match-to-sample tasks for shape or texture, with shapes filled with texture, to understand the role of SDC’s in cortical processing during active vision. Through the use of gaze-stabilization, we will be able to disrupt the retinal input to the cortex during the task to probe selectively how SDC’s control processing of shape and texture in early visual areas. In active vision, the SDC maps spatial information into temporal patterns of neural activity. Recent modeling and psychophysical work have determined that the initial transient phase of the cycle encodes coarse features, while the later, more prolonged period of drift is critical for extracting fine details. We are interested in how the transition from coarse to fine processing in the SDC is implemented in local and inter-areal cortical networks. We hypothesize that processing in these networks during the SDC begins with a phase of transient feedforward activity followed by a longer phase of recurrent and re-entrant activity that coincides with gamma oscillations in the networks. We hypothesize that shape is captured in the initial phase of the SDC and finer features of the shape’s border and the region within the shape by the recurrent phase of processing during drift. We also suggest that the cortex uses sequences of SDC’s to accumulate information and that the organization of networks within the cortex, in terms of their hierarchy and temporal frequency band for communication, depends on whether the sequence is dominated by saccades and drift (looking) or by microsaccades and drift (fixating). In AIM 1, we focus on activity phase-locked to the SDC where the match to sample for shape or texture is fixed for an entire day’s session. The SDC’s in this task will be dominated by microsaccades/drifts. We will ask if accurate matches for shape coincide with stronger SDC transients in the network and if accurate matches for texture produce robust gamma coherence that emerges later in the SDC. In AIM 2, we investigate sequences of SDC’s in periods of looking and fixating for a match-to-sample task where the monkey is given a cue on every trial for the correct match of shape or texture. Information is gained across the trial through saccades and FxEMs, and we ask how the dynamics of V1-2-4 network activity, phase-locked to these sequences, reflect performance and task. Gaze-stabilization will be used in both AIMs to impact cortical processing of the sample stimulus. How the SDC’s modulate the causal relationships between cortical areas and the dynamics of those interactions will be examined through a new method of analysis, frequency-extracted hierarchical decomposition.