39 research outputs found
Cortical Hubs Form a Module for Multisensory Integration on Top of the Hierarchy of Cortical Networks
Sensory stimuli entering the nervous system follow particular paths of processing, typically separated (segregated) from the paths of other modal information. However, sensory perception, awareness and cognition emerge from the combination of information (integration). The corticocortical networks of cats and macaque monkeys display three prominent characteristics: (i) modular organisation (facilitating the segregation), (ii) abundant alternative processing paths and (iii) the presence of highly connected hubs. Here, we study in detail the organisation and potential function of the cortical hubs by graph analysis and information theoretical methods. We find that the cortical hubs form a spatially delocalised, but topologically central module with the capacity to integrate multisensory information in a collaborative manner. With this, we resolve the underlying anatomical substrate that supports the simultaneous capacity of the cortex to segregate and to integrate multisensory information
Hierarchy and Dynamics of Neural Networks
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Evolution and development of Brain Networks: From Caenorhabditis elegans to Homo sapiens
Neural networks show a progressive increase in complexity during the time
course of evolution. From diffuse nerve nets in Cnidaria to modular,
hierarchical systems in macaque and humans, there is a gradual shift from
simple processes involving a limited amount of tasks and modalities to complex
functional and behavioral processing integrating different kinds of information
from highly specialized tissue. However, studies in a range of species suggest
that fundamental similarities, in spatial and topological features as well as
in developmental mechanisms for network formation, are retained across
evolution. 'Small-world' topology and highly connected regions (hubs) are
prevalent across the evolutionary scale, ensuring efficient processing and
resilience to internal (e.g. lesions) and external (e.g. environment) changes.
Furthermore, in most species, even the establishment of hubs, long-range
connections linking distant components, and a modular organization, relies on
similar mechanisms. In conclusion, evolutionary divergence leads to greater
complexity while following essential developmental constraints
Subcortical contributions to large-scale network communication
Higher brain function requires integration of distributed neuronal activity across large-scale brain networks. Recent scientific advances at the interface of subcortical brain anatomy and network science have highlighted the possible contribution of subcortical structures to large-scale network communication. We begin our review by examining neuroanatomical literature suggesting that diverse neural systems converge within the architecture of the basal ganglia and thalamus. These findings dovetail with those of recent network analyses that have demonstrated that the basal ganglia and thalamus belong to an ensemble of highly interconnected network hubs. A synthesis of these findings suggests a new view of the subcortex, in which the basal ganglia and thalamus form part of a core circuit that supports large-scale integration of functionally diverse neural signals. Finally, we close with an overview of some of the major opportunities and challenges facing subcortical-inclusive descriptions of large-scale network communication in the human brain
Knotty-Centrality: Finding the Connective Core of a Complex Network
A network measure called knotty-centrality is defined that quantifies the extent to which a given subset of a graphâs nodes constitutes a densely intra-connected topologically central connective core. Using this measure, the knotty centre of a network is defined as a sub-graph with maximal knotty-centrality. A heuristic algorithm for finding subsets of a network with high knotty-centrality is presented, and this is applied to previously published brain structural connectivity data for the cat and the human, as well as to a number of other networks. The cognitive implications of possessing a connective core with high knotty-centrality are briefly discussed
Further insights into the interareal connectivity of a cortical network
Over the past years, network science has proven invaluable as a means to
better understand many of the processes taking place in the brain. Recently,
interareal connectivity data of the macaque cortex was made available with
great richness of detail. We explore new aspects of this dataset, such as a
correlation between connection weights and cortical hierarchy. We also look at
the link-community structure that emerges from the data to uncover the major
communication pathways in the network, and moreover investigate its reciprocal
connections, showing that they share similar properties
Functional hubs in mild cognitive impairment
We investigate how hubs of functional brain networks are modified as a result of mild cognitive impairment (MCI), a condition causing a slight but noticeable decline in cognitive abilities, which sometimes precedes the onset of Alzheimer's disease. We used magnetoencephalography (MEG) to investigate the functional brain networks of a group of patients suffering from MCI and a control group of healthy subjects, during the execution of a short-term memory task. Couplings between brain sites were evaluated using synchronization likelihood, from which a network of functional interdependencies was constructed and the centrality, i.e. importance, of their nodes was quantified. The results showed that, with respect to healthy controls, MCI patients were associated with decreases and increases in hub centrality respectively in occipital and central scalp regions, supporting the hypothesis that MCI modifies functional brain network topology, leading to more random structures