30903
Granularity and Connectivity in Brains and Cognition: Toward an Information Processing Model of the Cognitive Styles over ASD and TD Populations
ASD has two diagnostic criteria: impairments of communication and restricted interests. While accompanied by disturbances of perception and/or motor coordination, most people with ASD are often good at handling objects and machines. However, we do not have a unified model that can explain these diverse characteristics. ASD models proposed so far often focus only on parts of the aspects, and a new unified model is needed for future innovative research and therapeutic practices.
Objectives:
We reconsider the phenotypical diversity of ASD from the viewpoint of "cognitive granularity" that we have been advocating, by which we consider the possibility of modeling ASD in a unified way. Cognitive granularity represents the size of semantic units (schema, basic level categories, etc.) for the agent to articulate and recognize the environment, and is involved in predicting and controlling the environment including the behavior of others. From the accumulated facts on the behavioral characteristics and the abnormality in the brain structure, it is predicted that ASD people have finer cognitive granularity. Based on the idea, we formulate a unified cognitive model over the diverse behavioral characteristics not only of ASD but also of TD on the continuous axis of cognitive granularity.
Methods:
As evidence to support the finer cognitive granularity in ASD, Casanova reported that mini-columns in ASD brains have a higher density than that of TD. A mini-column is a columnar structure of approximately 100 neurons vertically arranged through the cortical layers; being bundled up together, mini-columns cover the entire surface of the brain, forming the cerebral cortex. Mini-columns are considered to be the smallest functional unit of the brain, whose higher density suggests that (1) ASD brains employ a larger number of mini-columns in information processing, and (2) ASD brains process information in a less integrated way because the smaller mini-columns reduce long-distance connection between them [Fig. 1].
Results:
The abnormality of granularity and connectivity in ASD brains well-explains the information processing styles of the ASD population. (1) ASD people use more mini-columns to represent the environment, suggesting that they acquire categories with finer and specific distinction, often in obsessively detailed manners. (2) ASD people have difficulties in integrating information represented by distantly distributed mini-columns, resulting in the failure of sensory integration and motor coordination as well as of perceiving gestalt and forming "central coherence".
Moreover, finer granularity in ASD also explains their difficulties in mentalizing other’s behavior. With the finer cognitive granularity, a variation of human actions that share the same goal would look like arbitrary sequences of causal micro-actions without shared invariants, namely, "intentions" [Fig. 2]. This implies that "theory of mind" or "mentalization" would stem from coarser cognitive granularity that enables TD people to see the mental gestalt in other’s physical behavior.
Conclusions:
We believe that cognitive granularity works as the unified model, or endophenotype, of ASD, which explains the continuum of cognitive styles over ASD and TD populations. The idea is still in a hypothetical phase; we need in-depth discussions with INSAR community.