Development of horizontal intrinsic connections in cat striate cortex

Luhmann, Heiko J.; Millán, Luis Martínez; Singer, Wolf

doi:10.1007/bf00236865

Cited by 116 publications

(70 citation statements)

References 25 publications

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“…The predictable order in cluster properties suggests that there is a fundamental rule governing axonal growth and its associated Luhmann et al, 1986;Burkhalter, 1989;Kaas et al, 1989;Blasdel, 1992;Kisvárday and Eysel, 1992;Yoshioka et al, 1992;Amir et al, 1993;Lund et al, 1993;Levitt et al, 1994;Fujita and Fujita, 1996;Kisvárday et al, 1997;Malach et al, 1997;Fitzpatrick et al, 1998). bouton formation.…”

Section: Rules Of Cluster Formationmentioning

confidence: 99%

Stereotypical Bouton Clustering of Individual Neurons in Cat Primary Visual Cortex

2007

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In all species examined, with the exception of rodents, the axons of neocortical neurons form boutons in multiple separate clusters. Most descriptions of clusters are anecdotal, so here we developed an objective method for identifying clusters. We applied a mean-shift cluster-algorithm to three-dimensional reconstructions of 39 individual neurons and three thalamic afferents from the cat primary visual cortex. Both spiny (20 of 26) and smooth (7 of 13) neurons formed at least two distinct ellipsoidal clusters (range, 2-7). For all cell types, cluster formation is heterogenous, but is regulated so that cluster size and the number of boutons allocated to a cluster equalize with increasing number of clusters formed by a neuron. The bouton density within a cluster is inversely related to the spatial scale of the axon, resulting in a four times greater density for smooth neurons than for spiny neurons. Thus, the inhibitory action of the smooth neurons is much more concentrated and focal than the excitatory action of spiny neurons. The cluster with the highest number of boutons (primary cluster) was typically located around or above the soma of the parent neuron. The distance to the next cluster was proportional to the diameter of the primary cluster, suggesting that there is an optimal distance and spatial focus of the lateral influence of a neuron. The lateral spread of clustered axons may thus support a spoke-like network architecture that routes signals to localized sites, thereby reducing signal correlation and redundancy.

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Section: Rules Of Cluster Formationmentioning

confidence: 99%

Stereotypical Bouton Clustering of Individual Neurons in Cat Primary Visual Cortex

2007

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“…µm (Rumberger et al 2001), for tree shrew ξ = 230 µm (Rockland et al 1982), for cat ξ = 300 µm (Luhmann et al 1986), for macaque ξ = 230 µm (Amir et al 1993), for human ξ = 400 µm (Burkhalter and Bernardo 1989). The gray matter volumes were taken form Stephan et al, 1981.…”

Section: Figure Captionsmentioning

confidence: 99%

How Does Connectivity Between Cortical Areas Depend on Brain Size? Implications for Efficient Computation

Karbowski

2003

Journal of Computational Neuroscience

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A formula for an average connectivity between cortical areas in mammals is derived. Based on comparative neuroanatomical data, it is found, surprisingly, that this connectivity is either only weakly dependent or independent of brain size. It is discussed how this formula can be used to estimate the average length of axons in white matter. Other allometric relations, such as cortical patches and area sizes vs. brain size, are also provided. Finally, some functional implications, with an emphasis on efficient cortical computation, are discussed as well.

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“…These analyses should, in particular, apply to the perceptual grouping process, because the cortical horizontal connections that support perceptual grouping in areas like V1 develop through a learning process that is influenced by visual experience (Luhmann, Martinez Millan, and Singer, 1986;Calloway and Katz, 1990;Gilbert and Wiesel, 1992;Lowel and Singer, 1992;Antonini and Stryker, 1993a;Galuske and Singer, 1996). It is also known that many developmental and learning processes, including those that control horizontal connections, are stabilized dynamically, and can be reactivated by lesions and other sources of cortical imbalance (Das and Gilbert, 1995;Gilbert and Wiesel, 1992), and that adult learning uses the same types of mechanisms as the infant developmental processes upon which it builds (Bailey et al, 1992;Kandel and O'Dell, 1992;Mayford et al, 1992).…”

Section: What Stabilizes Perceptual Development and Learning?mentioning

confidence: 99%

How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex

Grossberg¹

1999

Spatial Vis

235

163

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The organization of neocortex into layers is one of its most salient anatomical features. These layers include circuits that form functional columns in cortical maps. A major unsolved problem concerns how bottom-up, top-down, and horizontal interactions are organized within cortical layers to generate adaptive behaviors. This article models how these interactions help visual cortex to realize: (1) the binding process whereby cortex groups distributed data into coherent object representations; (2) the attentional process whereby cortex selectively processes important events; and (3) the developmental and learning processes whereby cortex shapes its circuits to match environmental constraints. New computational ideas about feedback systems suggest how neocortex develops and learns in a stable way, and why top-down attention requires converging bottom-up inputs to fully activate cortical cells, whereas perceptual groupings do not.Introduction. The cerebral cortex is the seat of our highest forms of intelligence, and its understanding is thus a goal for all students of mind and brain. Neocortex has an intricate design which exhibits a characteristic organization into six distinct cortical layers (Brodmann, 1909; Martin, 1989). Differences in the thickness of these layers and the sizes and shapes of neurons led the German anatomist Korbinian Brodmann to identify more than fifty divisions, or areas, of neocortex. This classification has been invaluable to later scientists as a basis for discerning different functional roles for different parts of the brain. On the other hand, why the neocortex has six layers, or indeed a laminar design, has remained a mystery from a functional point of view. The present article proposes a model that provides clear functional roles for these layers for purposes of visual perception, and suggests that similar functional roles may be at work in all sensory and cognitive processing.

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Development of horizontal intrinsic connections in cat striate cortex

Cited by 116 publications

References 25 publications

Stereotypical Bouton Clustering of Individual Neurons in Cat Primary Visual Cortex

Stereotypical Bouton Clustering of Individual Neurons in Cat Primary Visual Cortex

How Does Connectivity Between Cortical Areas Depend on Brain Size? Implications for Efficient Computation

How does the cerebral cortex work? Learning, attention, and grouping by the laminar circuits of visual cortex

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