Individuation of objects and object parts rely on the same neuronal mechanism

Poncet, M; Caramazza, Alfonso; Mazza, Verônica de Azevedo

doi:10.1038/srep38434

Cited by 9 publications

(13 citation statements)

References 62 publications

(112 reference statements)

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“…If parts of an object have to be enumerated, in the special case where no other objects are present, parts can be subitized as efficiently as distinct objects (Poncet et al, 2016;Porter et al, 2016;Wurm et al, 2019; see also Experiment 1). This is because the single object with parts is initially individuated at no cost by attention.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, a few studies have reported that subitizing parts of an object is as efficient as subitizing independent objects (Porter et al, 2016) and evoke the same neuronal signature (Poncet et al, 2016;Wurm et al, 2019). These results were taken to argue that components of an object occupying distinct locations, such as parts, can be individuated in parallel and that individuation is not bound to (distinct) objecthood.…”

Section: Introductionmentioning

confidence: 99%

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Subitizing object parts reveals a second stage of individuation

Poncet

Chakravarthi

2020

Psychon Bull Rev

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Humans can efficiently individuate a small number of objects. This subitizing ability is thought to be a consequence of limited attentional resources. However, how and what is selected during the individuation process remain outstanding questions. We investigated these in four experiments by examining if parts of objects are enumerated as efficiently as distinct objects in the presence and absence of distractor objects. We found that distractor presence reduced subitizing efficiency. Crucially, parts connected to multiple objects were enumerated less efficiently than independent objects or parts connected to a single object. These results argue against direct individuation of parts and show that objecthood plays a fundamental role in individuation. Objects are selected first and their components are selected in subsequent steps. This reveals that individuation operates sequentially over multiple levels.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Subitizing object parts reveals a second stage of individuation

Poncet

Chakravarthi

2020

Psychon Bull Rev

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“…Eighteen young (mean age 23.3, range 19-27, 14 female) and 20 older volunteers (mean age 68.1, range 63-77 years, 10 female) were tested in Experiment 2. The sample size was determined based on previous studies (Poncet et al, 2016;Porter et al, 2016;Trick et al, 1996;Watson et al, 2005b). No participant reported a history of neurological or psychiatric disorders.…”

Section: Methodsmentioning

confidence: 99%

“…For instance, Porter et al (2016) found that multiple parts bound to a single object can be enumerated as efficiently as multiple distinct objects. In addition, a neural signature of target individuation varies as a function of object-part numerosity in the same way as in the case of distinct objects, suggesting that the same neural mechanism triggers individuation of multiple objects and multiple parts of a single object (Poncet et al, 2016, Wurm et al, 2019. Does aging affect the sufficient requirement for individuation in enumeration?…”

Section: Introductionmentioning

confidence: 99%

Individuation of object parts in aging

Tagliabue

Lombardi

Mazza

2020

Atten Percept Psychophys

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Research on enumeration with isolated objects has indicated that young and older adults can report up to three elements with similar efficiency (subitizing effect). Recent studies on subitizing in young adults have shown that individuation occurs over parts of an object as efficiently as over physically disconnected objects, suggesting that spatial separation is the sufficient requirement for efficient individuation. Do young and older adults share this sufficient requirement? In two experiments, we tested for the presence of subitizing in an enumeration task with a varying number of distinct objects and object parts. In Experiment 1, results indicated the presence of a bilinear function (with an inflection point between 3 and 4 elements, a proxy for subitizing) in the response speed of young and older adults, and in both stimulus conditions. In addition, the enumeration slope in older participants was steeper for object parts than objects in the subitizing range, possibly due to perceptual degradation (e.g., in contour detection). The pattern found generalizes to other stimuli (Experiment 2), thus highlighting the robustness of the present findings. Overall, the results indicate that while some perceptual factors (such as contour detection or curvature polarity) may hamper subitizing speed of older individuals relative to young adults, the subitizing span remains at approximately 3-4 elements for multiple objects and object parts in both young and older adults. Thus, individuation of multiple objects and object parts is a mechanism relatively resistant to aging.

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“…Whereas the visual number sense relates to properties as object area and density, neural responses of numerosity-selective cognitive systems were found to be invariant to all visual features except quantity [28,12]. Furthermore, studies on cognitive neuroscience have shown that the perception of number functions independently from mathematical reasoning [12,33]. All these findings suggest that visual number sense is a perceptual property that emerges directly from the visual sensory input.…”

Section: Related Workmentioning

confidence: 99%

Subitizing with Variational Autoencoders

Wever

Runia

2019

Lecture Notes in Computer Science

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Numerosity, the number of objects in a set, is a basic property of a given visual scene. Many animals develop the perceptual ability to subitize: the near-instantaneous identification of the numerosity in small sets of visual items. In computer vision, it has been shown that numerosity emerges as a statistical property in neural networks during unsupervised learning from simple synthetic images. In this work, we focus on more complex natural images using unsupervised hierarchical neural networks. Specifically, we show that variational autoencoders are able to spontaneously perform subitizing after training without supervision on a large amount images from the Salient Object Subitizing dataset. While our method is unable to outperform supervised convolutional networks for subitizing, we observe that the networks learn to encode numerosity as basic visual property. Moreover, we find that the learned representations are likely invariant to object area; an observation in alignment with studies on biological neural networks in cognitive neuroscience.

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Individuation of objects and object parts rely on the same neuronal mechanism

Cited by 9 publications

References 62 publications

Subitizing object parts reveals a second stage of individuation

Subitizing object parts reveals a second stage of individuation

Individuation of object parts in aging

Subitizing with Variational Autoencoders

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