Recognizing the gist of a visual scene: possible perceptual and neural mechanisms

Rasche, Christoph; Koch, Christof

doi:10.1016/s0925-2312(02)00500-3

Cited by 16 publications

(8 citation statements)

References 19 publications

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“…This suggests that major pictorial qualities of the paintings were flagged in the activated painting gist and likely contributed to the initial holistic impressions of the artwork. Moreover, they are consistent with Rasche and Koch's (2002) explanation of the nature of a gist response and the neural mechanisms responsible for it. According to them, gist recognition is based only on a subset of an image's information.…”

Section: Perceptual Processing Of Paintings Across the Time-course Ofsupporting

confidence: 87%

The Aesthetic Experience with Visual Art “At First Glance”

Locher

2015

Contributions to Phenomenology

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The aesthetic experience with visual art has been shown to occur in two stages. Upon initial exposure to a painting, a viewer spontaneously generates a global impression, or gist, of the work. One's first impression of a painting includes a sense of its pictorial content, overall structural organization and style, meaningfulness, and an affective reaction to it. When gist information in a painting is deemed to have sufficient interest to an observer, the second stage of aesthetic processing ensues. This consists of directed focal exploration of the image to expand knowledge concerning the work's compositional features and organization to satisfy cognitive curiosity and to develop aesthetic appreciation of a composition. This chapter presents an overview of research findings that have identified the types of visual properties and semantically related information that collectively lead to the activation of what is labeled a "painting gist" by this author. In addition, the influence of the painting gist response on the focal exploration of paintings is discussed.

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Section: Perceptual Processing Of Paintings Across the Time-course Ofsupporting

confidence: 87%

The Aesthetic Experience with Visual Art “At First Glance”

Locher

2015

Contributions to Phenomenology

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“…Studies of the attribution of overall message content, or social action, in conversation support this by pointing to the projective power of speaking turns, which creates a strong expectation for the social action of the next turn, such as an invitation projecting a response in the form of an acceptance or a declination [128] (although these studies focus on unimodal speech). Similarly, strong top-down processes from scene-context knowledge are assumed to influence the perception of visual scenes and the recognition of individual scene components outside the domain of communication ( [129]; and they may combine with gestalt-like perceptions also found at lower levels [130]), thus providing another potential source of domain-general mechanisms that may underpin multimodal utterance processing (see [131] for similar parallels in multisensory perception and social domains of metacognition).…”

Section: Top-down Prediction As a Domain-general Processmentioning

confidence: 99%

Multimodal Language Processing in Human Communication

Holler

Levinson

2019

Trends in Cognitive Sciences

289

233

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The natural ecology of human language is face-to-face interaction comprising the exchange of a plethora of multimodal signals. Trying to understand the psycholinguistic processing of language in its natural niche raises new issues, first and foremost the binding of multiple, temporally offset signals under tight time constraints posed by a turn-taking system. This might be expected to overload and slow our cognitive system, but the reverse is in fact the case. We propose cognitive mechanisms that may explain this phenomenon and call for a multimodal, situated psycholinguistic framework to unravel the full complexities of human language processing. A Binding Problem at the Core of Language Language as it is used in its central ecological nichethat is, in face-to-face interactionis embedded in multimodal displays by both speaker and addressee. This is the niche in which it is learned, in which it evolved, and where the bulk of language usage occurs. Communication in this niche involves a complex orchestration of multiple articulators (see Glossary) and modalities: messages are auditory as well as visual, as they are spread across speech, nonspeech vocalizations, and the head, face, hands, arms, and torso. From the point of view of the recipient, this ought in principle to raise two serious computational challenges. First, not all bodily or facial movements are intended as part of the signal or contentthe incidental but irrelevant movements must be set aside (we call this the segregation problem); second, those that seem to be part of the message have to be paired with their counterparts (as when we say 'There!' and point), and simultaneity alone turns out to be an unreliable cue (this is our binding problem). In this Opinion article, we ask how the multiple signals carried by multiple articulators and on different modalities can be combined rapidly to build the phenomenology of a coherent message in the temporally demanding context of conversational speech.

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“…Fourier decomposition can be considered to be a feedforward process, with a bank of filters that are tuned to different frequencies, orientations, and phases (Fourier, 1822 ), and such an interpretation is a common first-approximation to cortical visual processing (Campbell and Robson, 1968 ). On the other hand, Fourier analysis is decidedly global rather than local in the sense that the weights assigned to different frequencies are based on the pattern of luminance values across the entire image plane (Rasche and Koch, 2002 ; Cesarei and Loftus, 2011 ). It is also global in the sense that a filter that suppresses some frequencies will influence representations of luminance values across the entire image plane when the frequency weights are converted back to an image representation.…”

Section: A Feedforward Global Model: Fourier Analysismentioning

confidence: 99%

“…Distinguishing between visual processing as being local or global has long been an important aspect of the Gestalt approach to perception (see the review by Wagemans et al, 2012 ). The local vs. global distinction also plays an important role in characterizing the flow of information in visual cortex (e.g., Altmann et al, 2003 ) and identifying the order of processing for natural scenes (e.g., Rasche and Koch, 2002 ; Cesarei and Loftus, 2011 ).…”

Section: Introductionmentioning

confidence: 99%

Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

2014

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Experimentalists tend to classify models of visual perception as being either local or global, and involving either feedforward or feedback processing. We argue that these distinctions are not as helpful as they might appear, and we illustrate these issues by analyzing models of visual crowding as an example. Recent studies have argued that crowding cannot be explained by purely local processing, but that instead, global factors such as perceptual grouping are crucial. Theories of perceptual grouping, in turn, often invoke feedback connections as a way to account for their global properties. We examined three types of crowding models that are representative of global processing models, and two of which employ feedback processing: a model based on Fourier filtering, a feedback neural network, and a specific feedback neural architecture that explicitly models perceptual grouping. Simulations demonstrate that crucial empirical findings are not accounted for by any of the models. We conclude that empirical investigations that reject a local or feedforward architecture offer almost no constraints for model construction, as there are an uncountable number of global and feedback systems. We propose that the identification of a system as being local or global and feedforward or feedback is less important than the identification of a system's computational details. Only the latter information can provide constraints on model development and promote quantitative explanations of complex phenomena.

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Recognizing the gist of a visual scene: possible perceptual and neural mechanisms

Cited by 16 publications

References 19 publications

The Aesthetic Experience with Visual Art “At First Glance”

The Aesthetic Experience with Visual Art “At First Glance”

Multimodal Language Processing in Human Communication

Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

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