Mapping the Matrix: The Ways of Neocortex

Institute of Neuroinformatics, UZH/ETH, Winterthurerstrasse 190, 8057 Zurich, Switzerland.
Neuron (Impact Factor: 15.98). 11/2007; 56(2):226-38. DOI: 10.1016/j.neuron.2007.10.017
Source: PubMed

ABSTRACT While we know that the neocortex occupies 85% of our brains and that its circuits allow an enormous flexibility and repertoire of behavior (not to mention unexplained phenomena like consciousness), a century after Cajal we have very little knowledge of the details of the cortical circuits or their mode of function. One simplifying hypothesis that has existed since Cajal is that the neocortex consists of repeated copies of the same fundamental circuit. However, finding that fundamental circuit has proved elusive, although partial drafts of a "canonical circuit" appear in many different guises of structure and function. Here, we review some critical stages in the history of this quest. In doing so, we consider the style of cortical computation in relation to the neuronal machinery that supports it. We conclude that the structure and function of cortex honors two major computational principles: "just-enough" and "just-in-time."

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    • "One approach to understanding the function of cortical pathways in general terms has been to chart regional projectivity (Oh et al., 2014) with the view that the resultant wiring diagram may be used as a template for understanding the emergent physiological properties of underlying circuits (Douglas and Martin, 2007; Reid, 2012). On the other hand, while this approach can provide an overview of connection likelihood and strength— both within (Petersen and Sakmann, 2000) and between (Binzegger et al., 2004; Feldmeyer et al., 2013; Oberlaender et al., 2012) cortical layers and regions—such descriptions are often limited by their cellular and functional resolution (Oh et al., 2014). "
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    ABSTRACT: Sensory computations performed in the neocortex involve layer six (L6) cortico-cortical (CC) and cortico-thalamic (CT) signaling pathways. Developing an understanding of the physiological role of these circuits requires dissection of the functional specificity and connectivity of the underlying individual projection neurons. By combining whole-cell recording from identified L6 principal cells in the mouse primary visual cortex (V1) with modified rabies virus-based input mapping, we have determined the sensory response properties and upstream monosynaptic connectivity of cells mediating the CC or CT pathway. We show that CC-projecting cells encompass a broad spectrum of selectivity to stimulus orientation and are predominantly innervated by deep layer V1 neurons. In contrast, CT-projecting cells are ultrasparse firing, exquisitely tuned to orientation and direction information, and receive long-range input from higher cortical areas. This segregation in function and connectivity indicates that L6 microcircuits route specific contextual and stimulus-related information within and outside the cortical network.
    Neuron 08/2014; 83(6). DOI:10.1016/j.neuron.2014.08.001 · 15.98 Impact Factor
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    • "Importantly, the conceptual models outlined above that we examine here have been developed and tested extensively for connections of the visual (Young 1992; Barone et al. 2000; Vezoli et al. 2004; Douglas and Martin 2007) and prefrontal cortex of the macaque monkey (Barbas 1986; Barbas and Pandya 1989; Barbas and Rempel- Clower 1997; Klyachko and Stevens 2003; Barbas et al. 2005; Medalla and Barbas 2006). Thus, their application to connections spanning the whole cortex in a different species provides an excellent test of the models' generality. "
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    ABSTRACT: Information processing in the brain is strongly constrained by anatomical connectivity. However, the principles governing the organization of corticocortical connections remain elusive. Here, we tested three models of relationships between the organization of cortical structure and features of connections linking 49 areas of the cat cerebral cortex. Factors taken into account were relative cytoarchitectonic differentiation ('structural model'), relative spatial position ('distance model'), or relative hierarchical position ('hierarchical model') of the areas. Cytoarchitectonic differentiation and spatial distance (themselves uncorrelated) correlated strongly with the existence of inter-areal connections, whereas no correlation was found with relative hierarchical position. Moreover, a strong correlation was observed between patterns of laminar projection origin or termination and cytoarchitectonic differentiation. Additionally, cytoarchitectonic differentiation correlated with the absolute number of corticocortical connections formed by areas, and varied characteristically between different cortical subnetworks, including a 'rich-club' module of hub areas. Thus, connections between areas of the cat cerebral cortex can, to a large part, be explained by the two independent factors of relative cytoarchitectonic differentiation and spatial distance of brain regions. As both the structural and distance model were originally formulated in the macaque monkey, their applicability in another mammalian species suggests a general principle of global cortical organization.
    Brain Structure and Function 07/2014; DOI:10.1007/s00429-014-0849-y · 4.57 Impact Factor
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    • "Connections between neurons were randomly and independently established with probabilities of 16% within columns, of 8% between columns of the same region, and with 4% between columns of different regions if a connecting fiber-tract exists. These values were in the range of those reported in the literature (Douglas and Martin, 2007; Thomson and Lamy, 2007; Young, 2000). A recent study shows that the degree distribution has an important role in the stability of the oscillation modes (Roxin 2011). "
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    ABSTRACT: Activity in coupled systems is often oscillatory, for example, the firing pattern of neuronal populations. Whereas these oscillations have been studied predominantly in local circuits, here we show how the topology of large-scale networks, leading to large feedback loops, influences oscillations in the resting state. We find that the hierarchical modular organization of neuronal networks supports distinct spectral patterns of neural rhythms similar to those observed experimentally in different species such as rat and human. For individual neurons, multiple peak frequencies with non-integer ratios between subsequent peaks occurred. These ratios occurred both for models with the spatial size of the rat as well as for the human brain. We argue that the potential influence of longer connections, and thus longer delays, are balanced by a reduced number of long-distance connections in larger brain networks. In conclusion, we show that a hierarchical neuronal network provides a scalable backbone for multiple brain rhythms. This structural backbone could complement well-studied regional and cellular mechanisms for the generation or prevention of rhythms.
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