Sirosh, J. and Miikkulainen, R. (1996). Selforganization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters, 3(1):39--48.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....that uses the time shift of the incoming spikes with a reference to a global signal as a mechanism of encoding information. Topology preserving maps have been found in many areas in the brain [Arbib, 1995] and are believed to emerge as a result of a competitive learning mechanism [Miller, 1996, Sirosh and Miikkulainen, 1996] The Self Organizing Map (SOM) architecture has provided a good explanation and computational models of the mechanism of developing such topological maps [Kohonen, 1993] There has been a fair amount of realizations of the basic idea of self organization in artificial neural networks, most of ....

Sirosh, J. and Miikkulainen, R. (1996). Selforganization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters, 3(1):39--48.

....of such stimuli (e.g. Hubel 1988, Gallistel et al. 1991, as above) This learning is again only meaningful on a modular level, not an individual cell level. For example, very early ontogenetic learning is concerned with simply organising cortical cells to be topological maps of the retinal input (Sirosh Miikkulainen 1996). The third reason that a simple reactive model cannot be applied to the visual system is the multidirectional interaction between the internal, learned state of the visual systems various components. This is evidenced not only by their interconnectivity (MacKay 1956) already mentioned above, ....

Sirosh, J. & Miikkulainen, R. (1996), `Self-organization and functional role of lateral connections and multisize receptive fields in the primary visual cortex', Neural Processing Letters .

....of topographic input and ON OFF middle layer is used in the model. Third, to keep the size of the model manageable, the PGO patterns are assumed to vary little in size and orientation, and are presented statically. With larger maps, moving patterns and larger variations can be taken into account (Sirosh and Miikkulainen 1996; Sirosh, Miikkulainen, and Bednar 1996) The input patterns consisted of multiple (3 4) triples of 2 D Gaussian dots on a 132 132 array representing the PGO waves. These stimuli are an implementation of the genetically encoded template postulated by Johnson and Morton (1991) but they are used ....

Sirosh, J., and Miikkulainen, R. 1996. Self-organization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters 3:39--48.

....and during visual processing, filter out these correlations from cortical activity to form a redundancy reduced sparse coding of the visual input. 2 The Receptive Field LISSOM (RF LISSOM) model RF LISSOM, or Receptive Field Laterally Interconnected Synergetically Self Organizing Map (Sirosh 1995; Sirosh and Miikkulainen 1994, 1996, 1997; Sirosh et al. 1996; figure 1) was designed to give a computational account for the observed self organization, plasticity, and low level functional phenomena in the primary visual cortex. The cortical architecture has been simplified to the minimum necessary configuration to account for ....

....correlations from cortical activity to form a redundancy reduced sparse coding of the visual input. 2 The Receptive Field LISSOM (RF LISSOM) model RF LISSOM, or Receptive Field Laterally Interconnected Synergetically Self Organizing Map (Sirosh 1995; Sirosh and Miikkulainen 1994, 1996, 1997; Sirosh et al. 1996; figure 1) was designed to give a computational account for the observed self organization, plasticity, and low level functional phenomena in the primary visual cortex. The cortical architecture has been simplified to the minimum necessary configuration to account for the observed phenomena. ....

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Sirosh, J., and Miikkulainen, R. (1996). Self-organization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters, 3:39--48.

....and segmentation can be achieved in such a network, thus presenting a unified model of development and functional dynamics in the primary visual cortex. 1 Introduction Several models of the visual cortex that take into account lateral interactions between neurons have recently been proposed (see Sirosh et al. 1996b ] for an overview) In the early stages of the development of the visual cortex, lateral connections are believed to self organize in synergy with the afferent connections to form a topological map of the input space. This process can be modeled computationally, showing how structures such as ....

.... showing how structures such as ocular dominance and orientation columns and patterned lateral connections between them form based on input driven Hebbian learning process (the Laterally Interconnected Synergetically Self Organizing Map, or LISSOM [ Miikkulainen et al. 1997; Sirosh, 1995; Sirosh and Miikkulainen, 1994; 1996; 1997; Sirosh et al. 1996a ] Lateral connections may also play a central role in the function of the visual cortex, by modulating the spiking behavior of neuronal groups. They could cause synchronization and desynchronization of spiking activity, thus mediating feature binding and ....

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J. Sirosh and R. Miikkulainen. Self-organization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters, 3:39--48, 1996.

....tilt aftereffect. Adapted from Campbell and Maffei 1971. to test in a detailed model of cortical function. A Hebbian selforganizing process (the Receptive Field Laterally Interconnected Synergetically Self Organizing Map, or RF LISSOM; Miikkulainen, Bednar, Choe, and Sirosh, 1997; Sirosh 1995; Sirosh and Miikkulainen 1994a, 1996, 1997; Sirosh, Miikkulainen, and Bednar, 1996) has been shown to develop feature detectors and specific lateral connections that could produce such aftereffects. The RF LISSOM model gives rise to anatomical and functional characteristics of the cortex such as topographic maps, ocular dominance, ....

....corresponds to the neuron s preferred stimulus orientation. This organization reflects the activity correlations caused by the elongated Gaussian input pattern: such a stimulus activates primarily those neurons that are tuned to the same orientation as the stimulus, and located along its length (Sirosh et al..1996). Since the long range lateral connections are inhibitory, the net result is decorrelation: redundant activation is removed, resulting in a sparse representation of the novel features of each input (Barlow 1990; Field 1994; Sirosh et al..1996) As a side effect, illusions and aftereffects may ....

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Sirosh, J., and Miikkulainen, R. (1996). Self-organization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters, 3:39--48.

....(from neurons marked black in the cortex) and longrange lateral inhibitory connections (from neurons marked black plus the ones marked gray) Each cortical neuron (i; j) receives input from a receptive field of retinal neurons centered at the corresponding location on the retina. Map, or RF LISSOM [22, 29, 31, 32, 33]) Lateral connections may also play a central role in the function of the visual cortex, by modulating the spiking behavior of neuronal groups. They could cause synchronization and desynchronization of spiking activity, thus mediating feature binding and segmentation. Such synchronization of ....

....connections can play a central role in both the development and function of the visual cortex. 2 The RF SLISSOM Architecture RF SLISSOM consists of two layers of interconnected neurons: the retina and the cortex . The overall organization of RF SLISSOM is based on the RF LISSOM architecture [22, 29, 31, 32, 33], and the neuron model on the leaky integrator neurons of Eckhorn el al. 10] and Reitbock et al. 28] RF LISSOM provides the self organizing structure and the leaky integrator neuron introduces temporal dynamics into the model. Each cortical neuron receives afferent connections from the input ....

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J. Sirosh and R. Miikkulainen. Self-organization and functional role of lateral connections and multisize receptive fields in the primary visual cortex. Neural Processing Letters, 3:39--48, 1996.

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