Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity.
Neural activity underlying the detection of an object movement by an observer during forward self-motion: Dynamic decoding and temporal evolution of directional cortical connectivity.
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在正向自我运动过程中观察者检测对象运动的基础神经活动：方向皮层连通性的动态解码和时间演变。
DOI：
10.1016/j.pneurobio.2020.101824
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发表时间：
2020-12
影响因子：
6.7
通讯作者：
Vaina LM
中科院分区：
文献类型：
--
作者：
Kozhemiako N;Nunes AS;Samal A;Rana KD;Calabro FJ;Hämäläinen MS;Khan S;Vaina LM
相对而言，我们对人类大脑如何识别物体的运动知之甚少，而观察者也在环境中移动。从生态学的角度来看，这是最基本的运动处理问题之一，对生存至关重要。为了研究这个问题，我们使用了一个任务，其中涉及九个纹理球体在深度移动，八个模拟观察者的向前运动，而第九个，目标，独立地以不同的速度朝向或远离观察者。利用脑磁图（MEG）的高时间分辨率，我们使用传感器级数据训练支持向量分类器（SVC）来识别正确和不正确的反应。使用相同的MEG数据，我们解决了独立移动对象的检测中涉及的皮层过程的动态，并研究了我们是否可以获得分类器所使用的大脑活动模式的确证性证据。我们的研究结果表明，响应的正确性可以可靠地预测SVC，在运动后的空白期和之前的响应具有最高的准确性。对正确预测至关重要的区域的空间分布与诱发活动相关的区域相似，但不完全相同。重要的是，SVC确定了额叶区域，否则不会检测到诱发活动，这似乎是重要的成功执行任务。动态连接进一步支持任务期间额叶和枕颞区的参与。这是第一个研究动态映射皮层区域使用完全数据驱动的方法，以调查在观察者的自我运动过程中检测移动物体的神经机制。
Relatively little is known about how the human brain identifies movement of objects while the observer is also moving in the environment. This is, ecologically, one of the most fundamental motion processing problems, critical for survival. To study this problem, we used a task which involved nine textured spheres moving in depth, eight simulating the observer’s forward motion while the ninth, the target, moved independently with a different speed towards or away from the observer. Capitalizing on the high temporal resolution of magnetoencephalography (MEG) we trained a Support Vector Classifier (SVC) using the sensor-level data to identify correct and incorrect responses. Using the same MEG data, we addressed the dynamics of cortical processes involved in the detection of the independently moving object and investigated whether we could obtain confirmatory evidence for the brain activity patterns used by the classifier. Our findings indicate that response correctness could be reliably predicted by the SVC, with the highest accuracy during the blank period after motion and preceding the response. The spatial distribution of the areas critical for the correct prediction was similar but not exclusive to areas underlying the evoked activity. Importantly, SVC identified frontal areas otherwise not detected with evoked activity that seem to be important for the successful performance in the task. Dynamic connectivity further supported the involvement of frontal and occipital-temporal areas during the task periods. This is the first study to dynamically map cortical areas using a fully data-driven approach in order to investigate the neural mechanisms involved in the detection of moving objects during observer’s self-motion.
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影响因子：
3
作者：
Arnoldussen DM;Goossens J;van den Berg AV
通讯作者：
van den Berg AV
影响因子：
3.7
作者：
Cardin V;Sherrington R;Hemsworth L;Smith AT
通讯作者：
Smith AT
DOI：
10.3758/bf03207077
发表时间：
1990-08-01
期刊：
PERCEPTION & PSYCHOPHYSICS
影响因子：
--
作者：
GOGEL, WC
通讯作者：
GOGEL, WC
影响因子：
5.7
作者：
Dale, AM;Fischl, B;Sereno, MI
通讯作者：
Sereno, MI
DOI：
10.1098/rspb.2010.2757
发表时间：
2011-09-22
影响因子：
4.7
作者：
Calabro, F. J.;Soto-Faraco, S.;Vaina, L. M.
通讯作者：
Vaina, L. M.