Past and Present Ideas About How the Visual Scene Is Analyzed by the Brain

1997 ◽  
pp. 59-90 ◽  
Author(s):  
Peter H. Schiller
Keyword(s):  
Visual Scene ◽  
The Brain

scholarly journals Is predictability salient? A study of attentional capture by auditory patterns

2017 ◽  
Vol 372 (1714) ◽  
pp. 20160105 ◽  
Author(s):  
Rosy Southwell ◽  
Anna Baumann ◽  
Cécile Gal ◽  
Nicolas Barascud ◽  
Karl Friston ◽  
...  
Keyword(s):  
Attentional Capture ◽  
Predictive Coding ◽  
Visual Scene ◽  
Scene Analysis ◽  
Neural Responses ◽  
Eeg Data ◽  
Visual Domain ◽  
The Brain ◽  
Repeating Patterns

In this series of behavioural and electroencephalography (EEG) experiments, we investigate the extent to which repeating patterns of sounds capture attention. Work in the visual domain has revealed attentional capture by statistically predictable stimuli, consistent with predictive coding accounts which suggest that attention is drawn to sensory regularities. Here, stimuli comprised rapid sequences of tone pips, arranged in regular (REG) or random (RAND) patterns. EEG data demonstrate that the brain rapidly recognizes predictable patterns manifested as a rapid increase in responses to REG relative to RAND sequences. This increase is reminiscent of the increase in gain on neural responses to attended stimuli often seen in the neuroimaging literature, and thus consistent with the hypothesis that predictable sequences draw attention. To study potential attentional capture by auditory regularities, we used REG and RAND sequences in two different behavioural tasks designed to reveal effects of attentional capture by regularity. Overall, the pattern of results suggests that regularity does not capture attention. This article is part of the themed issue ‘Auditory and visual scene analysis’.

scholarly journals Auditory and visual scene analysis: an overview

2017 ◽  
Vol 372 (1714) ◽  
pp. 20160099 ◽  
Author(s):  
Hirohito M. Kondo ◽  
Anouk M. van Loon ◽  
Jun-Ichiro Kawahara ◽  
Brian C. J. Moore
Keyword(s):  
Scene Perception ◽  
Computational Modelling ◽  
Visual Scene ◽  
Scene Analysis ◽  
Theoretical Approaches ◽  
Visual Inputs ◽  
Sensory Modalities ◽  
Stimulus Features ◽  
The Brain ◽  
Selection Of

We perceive the world as stable and composed of discrete objects even though auditory and visual inputs are often ambiguous owing to spatial and temporal occluders and changes in the conditions of observation. This raises important questions regarding where and how ‘scene analysis’ is performed in the brain. Recent advances from both auditory and visual research suggest that the brain does not simply process the incoming scene properties. Rather, top-down processes such as attention, expectations and prior knowledge facilitate scene perception. Thus, scene analysis is linked not only with the extraction of stimulus features and formation and selection of perceptual objects, but also with selective attention, perceptual binding and awareness. This special issue covers novel advances in scene-analysis research obtained using a combination of psychophysics, computational modelling, neuroimaging and neurophysiology, and presents new empirical and theoretical approaches. For integrative understanding of scene analysis beyond and across sensory modalities, we provide a collection of 15 articles that enable comparison and integration of recent findings in auditory and visual scene analysis. This article is part of the themed issue ‘Auditory and visual scene analysis’.

scholarly journals Patterns of neural correlations in visual cortex vary with the number of objects

2019 ◽  
Author(s):  
Na Young Jun ◽  
Douglas A. Ruff ◽  
Lily E. Kramer ◽  
Brittany Bowes ◽  
Surya T Tokdar ◽  
...  
Keyword(s):  
Visual Cortex ◽  
The Other ◽  
Visual Scene ◽  
Spike Count ◽  
Neural Population ◽  
Multiple Objects ◽  
Time Period ◽  
V4 Neurons ◽  
Time Division ◽  
The Brain

AbstractHow the brain preserves information about more than one stimulus at a time remains poorly understood. We recently showed that when more than one stimulus is present, single neurons may fluctuate between coding one vs. the other(s) across some time period. A critical unanswered question is whether and how any such fluctuations are coordinated across the neural population. Here, we analyzed the spike count (“noise”) correlations observed between pairs of visual cortex (V1, V4) neurons under a variety of conditions. We report that when two separate grating stimuli are presented simultaneously, distinct distributions of positive and negative correlations emerge in V1, depending on whether the two neurons in the pair both respond more strongly to the same vs. different individual stimuli. Neural pairs that shared the same stimulus preference were more likely to show positively correlated spike count variability whereas those with different preferences were more likely to show negative correlations, suggesting that the V1 population response to one particular stimulus may be enhanced over the other on any given trial. Distinct distributions of spike count correlations based on tuning preferences were also seen in V4 for adjacent stimuli, but were not observed in either structure for single stimuli or when the two gratings were superimposed and formed a single plaid. The effects were most pronounced among pairs of neurons that showed fluctuating activity. These findings support the interpretation that the pattern of correlated fluctuations is related to the segregation of individual objects in the visual scene.Significance StatementHow the brain separates information about multiple objects despite overlap in the neurons responsive to each item is not well understood. Here we show that pairs of neurons in primate V1 and V4 show unique patterns of correlated firing when there are multiple objects in the visual scene. These patterns were most pronounced in neurons that showed fluctuating activity consistent with switching between encoding each object across time (i.e. time division multiplexing). Both strongly positive and strongly negative correlations were observed, depending on whether the neurons in the pair exhibited similar or different stimulus preferences. These patterns were absent when only one object was presented, suggesting that they may play a key role in preserving information about multiple items.

scholarly journals The Ferrier Lecture 1995 Behind the Seen: The functional specialization of the brain in space and time

2005 ◽  
Vol 360 (1458) ◽  
pp. 1145-1183 ◽  
Author(s):  
Semir Zeki
Keyword(s):  
Visual Perception ◽  
Visual Scene ◽  
Functional Specialization ◽  
Visual Attributes ◽  
Space And Time ◽  
Visual Areas ◽  
Visual Consciousness ◽  
The Brain

The visual brain consists of many different visual areas, which are functionally specialized to process and perceive different attributes of the visual scene. However, the time taken to process different attributes varies; consequently, we see some attributes before others. It follows that there is a perceptual asynchrony and hierarchy in visual perception. Because perceiving an attribute is tantamount to becoming conscious of it, it follows that we become conscious of different attributes at different times. Visual consciousness is therefore distributed in time. Given that we become conscious of different visual attributes because of activity at different, functionally specialized, areas of the visual brain, it follows that visual consciousness is also distributed in space. Therefore, visual consciousness is not a single unified entity, but consists of many microconsciousnesses.

scholarly journals A massively asynchronous, parallel brain

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140174 ◽  
Author(s):  
Semir Zeki
Keyword(s):  
Parallel Processing ◽  
Time Windows ◽  
Stimulus Onset ◽  
Visual Scene ◽  
Visual Signals ◽  
Visual Attributes ◽  
Visual Areas ◽  
New Generation ◽  
Perceptual Systems ◽  
The Brain

Whether the visual brain uses a parallel or a serial, hierarchical, strategy to process visual signals, the end result appears to be that different attributes of the visual scene are perceived asynchronously—with colour leading form (orientation) by 40 ms and direction of motion by about 80 ms. Whatever the neural root of this asynchrony, it creates a problem that has not been properly addressed, namely how visual attributes that are perceived asynchronously over brief time windows after stimulus onset are bound together in the longer term to give us a unified experience of the visual world, in which all attributes are apparently seen in perfect registration. In this review, I suggest that there is no central neural clock in the (visual) brain that synchronizes the activity of different processing systems. More likely, activity in each of the parallel processing-perceptual systems of the visual brain is reset independently, making of the brain a massively asynchronous organ, just like the new generation of more efficient computers promise to be. Given the asynchronous operations of the brain, it is likely that the results of activities in the different processing-perceptual systems are not bound by physiological interactions between cells in the specialized visual areas, but post-perceptually, outside the visual brain.

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