Neuroinnovation Technology & Brain Mapping Laboratory, Federal University of Piauí, Parnaíba, Brazil; The Northeast Biotechnology Network, Federal University of Piauí, Teresina, Brazil.
Neuroinnovation Technology & Brain Mapping Laboratory, Federal University of Piauí, Parnaíba, Brazil.
Med Hypotheses. 2019 Apr;125:37-40. doi: 10.1016/j.mehy.2019.02.021. Epub 2019 Feb 5.
Electroencephalogram (EEG) is one of the mechanisms used to collect complex data. Its use includes evaluating neurological disorders, investigating brain function and correlations between EEG signals and real or imagined movements. The Topographic Image of Cortical Activity (TICA) records obtained by the EEG make it possible to observe, through color discrimination, the cortical areas that represent greater or lesser activity. Percolation Theory (PT) reveals properties on the aspects of fluid spreading from a central point, these properties being related to the aspects of the medium, topological characteristics and ease of penetration of a fluid in materials. The hypothesis presented so far considers that synaptic activities originate in points and spread from them, causing different areas of the brain to interact in a diffusive associative behavior, generating electric and magnetic fields by the currents that spread through the brain tissue and have an effect on the scalp sensors. Brain areas spatially separated create large-scale dynamic networks that are described by functional and effective connectivity. The proposition is that this phenomenon behaves like a fluidic spreading, so we can use the PT, through the topological analysis we detect specific signatures related to neural phenomena that manifest changes in the behavior of synaptic diffusion. This signature must be characterized by the Fractal Dimension (FD) values of the scattering clusters, these values will be used as properties in the k-Nearest Neighbors (kNN) method, an TICA will be categorized according to the degree of similarity to the preexisting patterns. In this context, our hypothesis will consolidate as a more computational resource in the service of medicine and another way that opens with the possibility of analysis and detailed inferences of the brain through TICA that go beyond a simply visual observation, as it happens in the present day.
脑电图（EEG）是用于收集复杂数据的机制之一。它的用途包括评估神经障碍、研究大脑功能以及 EEG 信号与实际或想象运动之间的相关性。通过 EEG 获得的皮质活动地形图（TICA）记录，可以通过颜色识别观察代表更大或更小活动的皮质区域。渗流理论（PT）揭示了从中心点扩散的流体的属性，这些属性与介质、拓扑特征和流体在材料中的渗透难易度有关。到目前为止提出的假设认为，突触活动起源于点并从这些点扩散，导致大脑的不同区域以扩散联想的行为相互作用，通过流经脑组织的电流产生电场和磁场，并对头皮传感器产生影响。空间上分离的脑区形成大规模动态网络，这些网络由功能和有效连接来描述。该假设是，这种现象表现得像流体扩散，因此我们可以使用 PT，通过拓扑分析检测到与神经现象相关的特定特征，这些特征表现为突触扩散行为的变化。该特征必须由散射簇的分形维数（FD）值来表征，这些值将用作 k-最近邻（kNN）方法的属性，根据与现有模式的相似程度对 TICA 进行分类。在这种情况下，我们的假设将巩固为医学服务的更具计算资源的方法，以及通过 TICA 对大脑进行分析和详细推断的另一种方法，这种方法超越了简单的视觉观察，就像当今发生的那样。
