Mathematical Model of Evolution of Brain Parcellation.
Mathematical Model of Evolution of Brain Parcellation.
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DOI：
10.3389/fncir.2016.00043
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发表时间：
2016
影响因子：
3.5
通讯作者：
Koulakov AA
中科院分区：
文献类型：
--
作者：
Ferrante DD;Wei Y;Koulakov AA
我们研究了三个物种：小鼠，猕猴和人类的大脑和皮质面积大小[包裹单位（PU）]的分布。我们发现PU大小的分布接近对数正态分布。我们提出了基于迭代分割和特化的脑包裹演化的数学模型。在此模型中，每一现有PU具有仅取决于PU大小的待分裂的概率。这个模型表明，相同的进化过程可能导致了这三个物种的大脑分割。在我们的模型中，区域到区域（宏观）的连通性由外积形式给出。我们发现，大多数实验数据的非零猕猴皮层宏观层面的连接可以解释外积幂律形式建议我们的模型（62%的面积V1）。我们提出了一个乘法赫布学习规则的宏连接体，可以产生正确的缩放区域之间的连接强度。因此，我们提出了一个进化模型，可能有助于在哺乳动物的大脑parcellation和介观水平的连接。
We study the distribution of brain and cortical area sizes [parcellation units (PUs)] obtained for three species: mouse, macaque, and human. We find that the distribution of PU sizes is close to lognormal. We propose the mathematical model of evolution of brain parcellation based on iterative fragmentation and specialization. In this model, each existing PU has a probability to be split that depends on PU size only. This model suggests that the same evolutionary process may have led to brain parcellation in these three species. Within our model, region-to-region (macro) connectivity is given by the outer product form. We show that most experimental data on non-zero macaque cortex macroscopic-level connections can be explained by the outer product power-law form suggested by our model (62% for area V1). We propose a multiplicative Hebbian learning rule for the macroconnectome that could yield the correct scaling of connection strengths between areas. We thus propose an evolutionary model that may have contributed to both brain parcellation and mesoscopic level connectivity in mammals.