Abstract
Elucidating the multi-scale detailed differences between the human brain and other brains will help shed light on what makes us unique as a species. Computational models help link biochemical and anatomical properties to cognitive functions and predict key properties of the cortex. Here, we present a detailed human neocortex network, with all human neuron parameters derived from the newest Allen Brain human brain cell database. Compared with that of rodents, the human neural network maintains more complete and accurate information under the same graphic input. Unique membrane properties in human neocortical neurons enhance the human brain’s capacity for signal processing.
Highlights
The neocortex processes higher-level cognitive function, including working memory, attention, and perception (Miller, 2000; Koechlin et al, 2003; Nieder and Miller, 2003; Wood and Grafman, 2003; Bishop et al, 2004)
We and Eyal et al (2016) both found that the membrane capacitance of certain types of human pyramidal cells (PCs) in the neocortex was significantly lower than that of rodents
Even if we further increase the Vth by 25% on human neurons, the correct rate was not improved from a computational point of view, and the output image had a lot of noise (Figure 5F)
Summary
The neocortex processes higher-level cognitive function, including working memory, attention, and perception (Miller, 2000; Koechlin et al, 2003; Nieder and Miller, 2003; Wood and Grafman, 2003; Bishop et al, 2004). As a result of developments in neuroimaging and neurophysiology, we can explore the human neocortex from the macro connectome level (Klein et al, 2010; Ford and Kensinger, 2014; Samara et al, 2017) and the micro cellular level (Beaulieu-Laroche et al, 2018; Colangelo et al, 2019; Gidon et al, 2020). These technologies allow us to compare features across species, in terms of their function and structure. Determining the differences between human neurons and other species appears to be important because they are considered to play a key role in human high-level cognition and evolution (Golgi, 1906; Cajal et al, 1995; Defelipe, 2011; Mohan et al, 2015)
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