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Abstract

I propose that perceptual learning of tasks to detect targets among uniform background items involves changing intra-cortical interactions in the primary visual cortex (V1). This is the case for tasks that rely mainly on bottom-up saliency to guide attention to the task relevant locations quickly, and rely less on top-down knowledge of the stimuli or on other strategies. In particular, suppression between V1 neurons responding to background, rather than target, visual items is predicted to increase over the course of such learning. Various other predictions are derived from this proposal, based on the theory that V1 creates a bottom-up saliency map to guide attention. Different tasks depend to different degrees on attention driven by bottom-up saliency; this leads to differences among findings from various studies of perceptual learning of pop out or detection tasks.

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. B., Walton, E. J., Hupe, J. M., Bullier, J., Lund, J. S. (2002): Circuits for local and global signal integration in primary visual cortex. J Neurosci, 22 (19), 8633–8646. August, J., Zucker, S. W. (2003): Sketches with

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The primary visual cortex (V1) of the mammalian brain is equipped with a specifically connected network of neurons that can potentially solve difficult image processing tasks. These neurons are selectively tuned for locations in visual space and also for line orientation. The coupling of location and orientation tuning results in the neural representation of the visual world in terms of local features. These local features, e.g., oriented line segments, will have to be linked together in order to parse the visual world into regions corresponding to object and ground. Although standard models of V1 do not address the issue of interacting neuronal populations, we suggest that the long-range connectivity pattern of V1 provides an architecture where spreading neural activity may lead to pertinent figure-ground segmentation. The model relies on the fact that in addition to the processing units, their connections are also selectively tuned for space and orientation. From the computational point of view, the model uses a minimalist approach that applies the fundamental concepts of Gestalt psychology – proximity, similarity and continuity – to the spreading of neuronal activation signals. This model is successful in predicting psychophysical performance of human observers, and provides an account of the computational power of V1.

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Callaway, E. M. (1998) Local circuits in primary visual cortex of the macaque monkey. Ann. Rev. Neurosci. 21 , 47-74. Local circuits in primary visual cortex of the macaque monkey

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Villeneuve, M. Y., Casanova, C. (2003) On the use of isoflurane versus halothane in the study of visual response properties of single cells in the primary visual cortex. J. Neurosci. Meth. 129 , 19–31. Casanova C

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Orvosi Hetilap
Authors:
Ákos Kusnyerik
,
Miklós Resch
,
Tamás Roska
,
Kristóf Karacs
,
Florian Gekeler
,
Robert Wilke
,
Heval Benav
,
Eberhart Zrenner
,
Ildikó Süveges
, and
János Németh

–146 123 130 Warren, D. J., Normann, R. A.: Functional reorganization of primary visual cortex induced by electrical stimulation in the cat. Vision Res., 2005, 45

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1991 Where practice makes perfect in texture discrimination: Evidence for primary visual cortex plasticity Proc. Nat. Acad. Sci. U S A 88 4966 4970

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; 356 : 182 – 92 . https://doi.org/10.1016/j.neuroscience.2017.05.028 . 21. Villeneuve MY , Casanova C . On the use of isoflurane versus halothane in the study of visual response properties of single cells in the primary visual cortex . J

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in the primary visual cortex. Thus, neural responses to alcohol cues in the AUD group were dissociable from neutral cues, but not in striatal regions nor significantly different from HCs. Fig. 2: AUD patients showed (a) decreased activity during

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