Computational approaches to cognition: top-down approaches

McClelland, James L.; Plaut, David C.

doi:10.1016/0959-4388(93)90212-h

Cited by 12 publications

(7 citation statements)

References 63 publications

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“…In turn, the learning of the head-centric spatial representation requires visual inputs generated by eye movements in the absence of neck movements. Hence, the model proposes that the lack of head control in young infants is an advantage for learning spatial representations, in the same way that it has previously been proposed that limitations in motor control or cognitive ability may provide an advantage to learning complex tasks (Araujo and Grupen, 1996;Elman, 1993;Elman et al, 1996;Lungarella and Berthouze, 2002;McClelland and Plaut, 1993). Another prediction of the proposed model is that learning invariant representations will be aided by the presence of multiple stimuli.…”

Section: Discussionmentioning

confidence: 95%

Learning Posture Invariant Spatial Representations Through Temporal Correlations

Spratling

2009

IEEE Trans. Auton. Mental Dev.

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A hierarchical neural network model is used to learn, without supervision, sensory-sensory coordinate transformations like those believed to be encoded in the dorsal pathway of the cerebral cortex. The resulting representations of visual space are invariant to eye orientation, neck orientation, or posture in general. These posture invariant spatial representations are learned using the same mechanisms that have previously been proposed to operate in the cortical ventral pathway to learn object representation that are invariant to translation, scale, orientation, or viewpoint in general. This model thus suggests that the same mechanisms of learning and development operate across multiple cortical hierarchies.

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Section: Discussionmentioning

confidence: 95%

Learning Posture Invariant Spatial Representations Through Temporal Correlations

Spratling

2009

IEEE Trans. Auton. Mental Dev.

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“…Based on previous studies, perception is probably based on a bidirectional search, where the bottom-up stream of information from the sensory organs interacts with the top-down stream from memory and attention (see e.g., Churchland, Ramachandran, & Sejnowski, 1994;McClelland & Plaut, 1993;Poggio & Hurlbert, 1994;Ullman, 1994). During visual imagery, the initial bottom-up activity is missing, and the neural network necessary for the task has to be activated through top-down connections (for recent reviews about the relation of imagery and perception, see e.g., Farah, 1995a;Kosslyn & Sussman, 1995).…”

Section: Discussionmentioning

confidence: 99%

Patterns of Brain Activity during Visual Imagery of Letters

Raij¹

1999

Journal of Cognitive Neuroscience

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Cortical signals associated with visual imagery of letters were recorded from 10 healthy adults with a whole-scalp 122-channel neuromagnetometer. The auditory stimulus sequence consisted of 20 different phonemes corresponding to single letters of the Roman alphabet and of tone pips (17%), delivered once every 1.5 sec in a random order. The subjects were instructed to visually imagine the letter corresponding to the auditory stimulus and to examine its visuospatial properties: The associated brain activity was compared with activity evoked by the same stimuli when the subjects just detected the intervening tones. All subjects produced broad imagery-related responses over multiple cortical regions. After initial activation of the auditory cortices, the earliest imagery-related responses originated in the left prerolandic area 320 msec after the voice onset. They were followed within 70 msec by signals originating in the posterior parietal lobe close to midline (precuneus) and, 100 msec later, in the posterior superior temporal areas, predominantly in the left hemisphere. The activations were sustained and partially overlapping in time. Imagery-related activity in the left lateral occipital cortex was observed in two subjects, and weak late activity in the calcarine cortex in one subject. Real audiovisually presented letters activated multiple brain regions, and task-induced visuospatial processing of these stimuli further increased activity in some of these regions and activated additional areas: Some of these areas were activated during imagery as well. The results suggest that certain brain areas involved in high-level visual perception are activated during visual imagery and that the extent of imagery-related activity is dictated by the requirements of the stimuli and the task.

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“…These and other higher order processes may be distributed across multiple associational cortical networks (McClelland & Plaut, 1993), with a particular role for prefrontal circuitry in establishing and coordinating top-down phenomena. Possible defects in the structure of semantic memory organization among schizophrenic participants are also likely to reflect underlying prefrontal circuit dysfunction.…”

Section: Discussionmentioning

confidence: 99%

Semantic priming in schizophrenia: A review and synthesis

Minzenberg

Ober

Vinogradov

2002

J Int Neuropsychol Soc

132

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In this paper, we present a review of semantic priming experiments in schizophrenia. Semantic priming paradigms show utility in assessing the role of deficits in semantic memory network access in the pathology of schizophrenia. The studies are placed in the context of current models of information processing. In this review we include all English-language reports (from peer-reviewed journals) of single-word semantic priming studies involving participants with schizophrenia. The studies to date show schizophrenic patients to exhibit variable semantic priming effects under automatic processing conditions, and consistent impairments under controlled0attentional conditions. We also describe associations with other neurocognitive dysfunction, neurochemical and electrophysiological disturbances, and clinical manifestations (such as thought disorder).

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Computational approaches to cognition: top-down approaches

Cited by 12 publications

References 63 publications

Learning Posture Invariant Spatial Representations Through Temporal Correlations

Learning Posture Invariant Spatial Representations Through Temporal Correlations

Patterns of Brain Activity during Visual Imagery of Letters

Semantic priming in schizophrenia: A review and synthesis

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