Brain Grain

In the last blog I described the canonical six layer cortical structure. That was intentionally a very simplified description. For one thing, the cortical layers include multitudes of cell types the distribution of which differ among different areas. There certainly should be non-systematic variances among brain regions that are shaped by evolution. However, one systematic citoarchitectonic variation in the brain is granularity, ranging from granular (clear layer IV and dense neurons) to dysgranular to agranular (lacking layer IV). The first figure below shows the granularity distribution in the human brain (Beul and Hilgetag 2015, based on Economo 2009). In the sensory modality, granularity seems to decrease as the paths move from the primary to association to higher order association cortices. In the motor modality, it may seem the opposite, as granularity increases from primary to association to higher association cortices. This however is also natural, since in the sensory modality the primary neural pulse propagates from sensory organs, whereas in the motor modality the primary neural pulse propagates to motor organs.

There have been some important observations made in terms of inter-layer connection patterns. One is that the cortico-cortical connectivity pattern in terms of the source and target layers differs depending on the difference of granularity between the source and target areas in non-human primates (Barbas 1986, Barbas and Rempel-Clower 1997). When the granularity difference is large, the connections go either from neurons in the shallow layers of the higher granularity area to shallow layers in the lower granularity area, or to the opposite direction (Figure 2). When granularity difference is small, the source and destination layers are more distributed along the depths. Also, it is observed in the rodent cortex that there are less inter-laminar inhibitory connections in less granular regions (Beul and  Hilgetag 2015). More specifically, in the most granular area (striate), there is inhibition V/VI->(IV and II/III), IV->II/II. In a less granular area (somatosensory), less long-range inhibition to the shallow layer, thus V/VI->IV, IV->(II/III and V/VI). In agranular area (primary motor), no clear inhibitory interlaminar connections were found.

So this sounds simple enough, but just in case you’re itching to hear more about neural modeling at this point, Beul and  Hilgetag (2015) presented neural models based on literature survey on inter- and intralaminar connections as well as prior modeling efforts. In an agranular, rodent frontal cortex model (right column in Figure 3), there are recurrent interlaminar connections V/VI<->II/III and intralaminar inhibitory connections. In a granular, cat striate cortex model (left column in Figure 3), there are linked interlaminar loops VI->IV->V->VI  and VI->IV->II/III->V->VI, intralaminar inhibitions, plus interlaminar inhibitions V->II and IV->II. These recurrent connections may serve amplification, gain control, and normalization (Beul and  Hilgetag 2015).

Fig 1. Granularity gradient

Fig 2. Between-area connectivity patterns

Fig 3. Within-area connectivity models (left:granular area, right: granular area)

References

Barbas H. Pattern in the laminar origin of corticocortical connections. Journal of Comparative Neurology. 1986 Oct 15;252(3):415-22.

Barbas H, Rempel-Clower N. Cortical structure predicts the pattern of corticocortical connections. Cerebral Cortex. 1997 Oct 1;7(7):635-46.

Beul SF, Hilgetag CC. Towards a “canonical” agranular cortical microcircuit. Frontiers in neuroanatomy. 2015 Jan 14;8:165.

von Economo C. Cellular structure of the human cerebral cortex. Karger Medical and Scientific Publishers; 2009.