Cortical hierarchy

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Hierarchical cortical organization is found in all sensory systems, in the reward system, and in the memory systems. Adjacent cortical areas in the hierarchy are connected by strong forward connections, and weaker backprojections which have synapses in cortical layer 1. There is convergence from cortical area to cortical area, in that neurons in a cortical area receive inputs from a limited region topologically of the preceding cortical area. This enables neurons to operate with the number of synapses from the preceding cortical area received by a neuron limited to in the order of 10, synapses. This is a major cortical principle of operation, for if each processing system consisted of only an input and an output cortical area, any neuron in the output area would need to receive the biologically implausible number of tens of millions of synapses to cover the whole space of the input cortical area. The convergence from cortical area to cortical area is such that after approximately at most four areas or stages of cortical processing, the convergence is sufficient to enable a single neuron at the top of the hierarchy to receive input from anywhere in the first cortical area, as illustrated in Fig.

Cortical hierarchy

Cortical information processing is structurally and functionally organized into hierarchical pathways, with primary sensory cortical regions providing modality specific information and associative cortical regions playing a more integrative role. Historically, there has been debate as to whether primary cortical regions mature earlier than associative cortical regions, or whether both primary and associative cortical regions mature simultaneously. Identifying whether primary and associative cortical regions mature hierarchically or simultaneously will not only deepen our understanding of the mechanisms that regulate brain maturation, but it will also provide fundamental insight into aspects of adolescent behavior, learning, neurodevelopmental disorders and computational models of neural processing. This mini-review article summarizes the current evidence supporting the sequential and hierarchical nature of cortical maturation, and then proposes a new cellular model underlying this process. Finally, unresolved issues associated with hierarchical cortical maturation are also addressed. The concept of cortical hierarchy has been widely recognized for years Guillery, It is based on established structure-function relationships in the thalamo-cortical system that consist of primary sensory areas and several distinct higher-order association areas that are important for cognitive functions Komura et al. Area-specific functions become more and more integrative as neural information moves through successive cortical tiers in the hierarchy. Historically, there has been debate as to whether postnatal cortical maturation of these hierarchies proceeds sequentially or simultaneously Guillery, Whether the cortex matures sequentially or simultaneously has important implications. Answering this question is critical to our understanding of the basic neurobiological processes involved in brain maturation and cognitive function. It will also further our understanding of aspects related to adolescent behavior, neurodevelopmental disorders and emergent properties associated with neuro-computational models Quartz, ; Guillery, ; Westermann et al. Much of the earlier work supporting simultaneous maturation was based on synaptic counts Rakic et al.

Theory of Architecture. Henschke, J. Visual areas exert feedforward and feedback influences through distinct frequency channels.

Many studies have identified the role of localized and distributed cognitive functionality by mapping either local task-related activity or distributed functional connectivity FC. However, few studies have directly explored the relationship between a brain region's localized task activity and its distributed task FC. Here we systematically evaluated the differential contributions of task-related activity and FC changes to identify a relationship between localized and distributed processes across the cortical hierarchy. We found that across multiple tasks, the magnitude of regional task-evoked activity was high in unimodal areas, but low in transmodal areas. In contrast, we found that task-state FC was significantly reduced in unimodal areas relative to transmodal areas. This revealed a strong negative relationship between localized task activity and distributed FC across cortical regions that was associated with the previously reported principal gradient of macroscale organization. Moreover, this dissociation corresponded to hierarchical cortical differences in the intrinsic timescale estimated from resting-state fMRI and region myelin content estimated from structural MRI.

Federal government websites often end in. The site is secure. Preview improvements coming to the PMC website in October Learn More or Try it out now. Author contribution. Hierarchy is a major organizational principle of the cortex and underscores modern computational theories of cortical function.

Cortical hierarchy

Federal government websites often end in. The site is secure. Preview improvements coming to the PMC website in October Learn More or Try it out now. Concepts shape the interpretation of facts. However, this concept has been interpreted in many different ways, which are not well aligned. This observation suggests that the concept is ill defined. Hierarchy is one of the most popular terms in current network and systems neuroscience.

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Activity is transformed at each stage of its journey, and circuits often perform multiple tasks in parallel 1 , 2 , so it is challenging to disambiguate which facets of neural activity contribute to a specific behavior or process. A value of zero indicates that the overlap is equal to the expected overlap. Classical Mechanics. Philosophy of Perception. Marriage and the Family. We specifically chose the parcellation by Power et al. Neurons were sorted for visual clarity only in Fig. International Law. Gunnar and C. This study had two main aims. Annotate Cite Icon Cite. Probability and Statistics.

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Anzellotti and Coutanche, Cognitive Neuroscience. Development of large-scale functional brain networks in children. Chen, J. This metric identifies the optimal number of state boundaries such that the Pearson correlations across voxels of timepoints within a state are maximized and correlations of timepoints in consecutive states are minimized. For each pair of searchlights, we tested whether the boundary overlap was significantly different from zero across the 15 independent samples. Literary Studies Early and Medieval. Neuron 93 , — Data collection and analysis were not performed blinded to the conditions of the experiments. Since the GSBS algorithm was fine-tuned based on the data that was later used for analysis, it would be helpful to include additional information demonstrating the choices in the optimization procedure are independent of the eventual results. We observed particularly fast states in primary sensory regions and long periods of information integration in the left middle frontal gyrus and medial prefrontal cortex. Economic Systems. Contemporary and Public Archaeology.