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Is vision continuous with cognition. The case for cognitive penetrability of vision. Genes, brain, and cognition: A roadmap for the cognitive scientist. Modularity and mental architecture. Basic objects in natural categories. Massively modular minds: Evolutionary psychology and cognitive architecture. The complexity of scopus author feedback wizard Tractability arguments for massive modularity.

Scopus author feedback wizard modularity of theory of mind. The Influence of Culture on Visual Perception, New York: Bobbs-Merrill. Illusions: What you see is what you hear. Cognitive penetrability and perceptual justification.

Initial knowledge: Six suggestions. The modularity of scopus author feedback wizard Tetanus Toxoid, Reduced Diphtheria Toxoid and Acellular Pertussis Vaccine, Adsorbed (Boostrix)- FDA the epidemiology of representations. Scopus author feedback wizard defense of massive modularity.

Pragmatics, modularity and mind-reading. Perceiving and desiring: A new look at the cognitive penetrability of experience. Cognitive penetrability of perception. Modular architectures and informational encapsulation: A dilemma. Selective impairment of reasoning about social exchange in a patient with bilateral limbic system damage. Cognitive and neural aspects of language acquisition.

Cross-cultural evidence of cognitive adaptations for social exchange among the Shiwiar of Ecuadorian Amazonia. Perceptual restoration of missing speech sounds. Auditory illusions and confusions. Putting to a bigger hole: Golf performance relates to perceived size.

Perceiving distances: A role of effort and intent. The various perceptions of distance: An alternative view of how effort affects distance judgments. The mind is not (just) a system of modules shaped (just) by natural selection. Academic Tools How to cite this entry. Preview the PDF version of this entry at the Friends of the SEP Society. Look lactancia topics and thinkers related to this entry at the Internet Philosophy Ontology Project (InPhO).

Enhanced bibliography for this entry at PhilPapers, with links to its database. Other Internet Resources Modularity in Cognitive Science, bibliography category at philpapers.

The Modularity Home Page, maintained by Raffaele Calabretta (Institute of Cognitive Sciences and Technologies, Italian National Research Council). Moreover, brain regions with diverse connectivity across the modules appear to play a role in enabling modules to interact while remaining mostly autonomous. This generates the counterintuitive idea that regions with diverse connectivity across modules are necessary for modular biological networks.

Network-based analyses of brain imaging data consistently reveal distinct modules and connector nodes with diverse global connectivity across the modules.

For example, gene expression in the brain is modular; the transcriptomes of human brain regions are robustly organized into modules of coexpressed genes that reflect the underlying cellular composition of brain tissue (8), and the spatial topography of cortex is also strongly reflected in its genetic topography-the closer two cortical regions, the more similar their transcriptomes (9).

Brain regions also exhibit cytoarchitectonic differences (12). A modular structural wiring network (i. Network models represent the brain as a graph with a scopus author feedback wizard of nodes, usually around 101 to 105 areas of the brain, with edges (i. This level of analysis complements analyses that measure activity magnitudes within particular brain regions, not connectivity between all regions.

These two approaches are not redundant; a brain region can decrease in activity, but increase in connectivity with other brain regions (28). Thus, in this study, we use both types of analyses. Nodes can be divided into modules by grouping the nodes that are most tightly connected to each other into a single module.

When applied to spontaneous neural activity in humans measured via rs-fMRI, this procedure reveals a modular network architecture, in that a large fraction of the edges falls within the modules compared to the expected fraction if edges were distributed at random (7, 16). Moreover, the spatial organization of scopus author feedback wizard modules corresponds to regions that have more highly scopus author feedback wizard gene expression than expected by chance (11).

These two metrics capture the topological roles of nodes in many large-scale complex networks, such as the mouse brain (45), the cat brain, the macaque brain (46), the Internet, air scopus author feedback wizard networks, Arabidopsis thaliana, the protein interactome scopus author feedback wizard Caenorhabditis elegans, scopus author feedback wizard metabolic networks (44).

In humans, regions with high participation coefficients are implicated in a diverse range of tasks (41, 48, 49) and are located where many modules are within close physical proximity (40). Each light green circle represents a set of nodes comprising a scopus author feedback wizard module. The four types of nodes are represented in different colors. Activity is scopus author feedback wizard from low activity in blue to high activity in dark red.

We also compared the spatial distribution of the cognitive components (derived from BrainMap) to the modules (derived from rs-fMRI of spontaneous neural activity), as well as their engagement across BrainMap tasks. Our network model of the brain was built from 24 healthy human subjects. We recorded six separate 10-min blocks of whole-brain spontaneous neural activity with rs-fMRI in each scopus author feedback wizard (2,610 time points per subject). As there is no agreement regarding the optimal brain atlas to parcellate the brain into nodes in the network, we used four different brain atlases, which we refer to by the name of the first author of the publication.

We also validated our results with a publicly available spontaneous neural activity (measured via rs-fMRI) correlation matrix that used a fifth brain atlas (35). For ease of presentation, only results from the Shen network are presented in Figs. We scopus author feedback wizard the Shen network because it has extensive brain coverage, and the number of nodes is common for graph theory analyses of rs-fMRI in humans (16, 56).



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