Bottom-up and top-down attention are independent

Pinto, Yaïr; Leij, Andries R. van der; Sligte, Ilja G.; Lamme, Victor A. F.; Scholte, H. Steven

doi:10.1167/13.3.16

Cited by 151 publications

(117 citation statements)

References 102 publications

(99 reference statements)

Supporting

Mentioning

109

Contrasting

Unclassified

Order By: Relevance

“…From a cognitive processing point of view, voluntary allocation requires top-down control, which presumably takes extra processing time. In studies of selective attention, for example, it is known that it takes more time to deploy top-down attention than bottom-up attention (Jonides, 1981; Liu, Stevens, & Carrasco, 2007; Muller & Rabbitt, 1989; Pinto, van der Leij, Sligte, Lamme, & Scholte, 2013). From an information theoretical point of view, the involuntary phase can maximize the storage of information with little cost of control, thus providing an efficient mechanism for consolidation.…”

Section: Methodsmentioning

confidence: 99%

A two-phase model of resource allocation in visual working memory.

C¹,

Hu²,

Li³

et al. 2017

Journal of Experimental Psychology: Learning, Memory, and Cogni

View full text Add to dashboard Cite

Two broad theories of visual working memory (VWM) storage have emerged from current research, a discrete slot-based theory and a continuous resource theory. However, neither the discrete slot-based theory or continuous resource theory clearly stipulates how the mental commodity for VWM (discrete slot or continuous resource) is allocated. Allocation may be based on the number of items via stimulus-driven factors, or it may be based on task demands via voluntary control. Previous studies have obtained conflicting results regarding the automaticity vs. controllability of such allocation. In the current study, we propose a two-phase allocation model, in which the mental commodity could be allocated only by stimulus-driven factors in the early consolidation phase. However, when there is sufficient time to complete the early phase, allocation can enter the late consolidation phase, where it can be flexibly and voluntarily controlled according to task demands. In an orientation recall task, we instructed participants to store either fewer items at high-precision or more items at low-precision. In three experiments, we systematically manipulated memory set size and exposure duration. We did not find an effect of task demands when the set size was high and exposure duration was short. However, when we either decreased the set size or increased the exposure duration, we found a trade-off between the number and precision of VWM representations. These results can be explained by a two-phase model, which can also account for previous conflicting findings in the literature.

show abstract

Section: Methodsmentioning

confidence: 99%

A two-phase model of resource allocation in visual working memory.

C¹,

Hu²,

Li³

et al. 2017

Journal of Experimental Psychology: Learning, Memory, and Cogni

View full text Add to dashboard Cite

show abstract

“…Neuroscientific understanding is that there are two distinct sensory processing pathways that exist in primate brains which are correlated with different forms of attention and these forms of attention are known as top-down (focused) and bottom-up (receptive) (e.g., AUSTIN, 2009;PINTO et al, 2013). These processing pathways are physical neural circuits located, respectively, in the dorsal and ventral regions of the brain (e.g., AUSTIN, 2009;KRAVITZ et al, 2011).…”

Section: Neuroscience Of Attention: Outline Of Theory Of Sensory Procmentioning

confidence: 99%

“…This MWS framework gives a way to track transition from perceptual geometry to deductive geometry through identifying how a learner's experience is processed through the links (geneses) of tool use, imagery or language (i.e., respectively: instrumental genesis, figural genesis or discursive genesis; KUZNIAK 2015). A contribution to this framework presented in this paper is to specialise the notion of top-down attention (e.g., PINTO et al, 2013;AUSTIN 2009) for circumstances in which tool use, imagery and language are processed together in 'near-to-me' geometrical work. By conceptualising 'nearto-me' attention in terms of attention-processing pathways, an explanation for a learner's transition from "it looks like" to "it has to be" can be offered which integrates influences of emotion and other affects into their spaces of geometrical work.…”

Section: Introductionmentioning

confidence: 99%

Transitioning from “It Looks Like” to “It Has To Be” in Geometrical Workspaces: affect and near-to-me attention

Rodd¹

2016

Bolema

View full text Add to dashboard Cite

Within a practitioner researcher framework, this paper draws on a particular mathematics education theory and aspects of neuroscience to show that, from a learner's perspective, moving to a deductive reasoning style appropriate to basic Euclidean geometry, can be facilitated, or impeded, by emotion and/or directed attention. This shows that the issue of a person's deductive reasoning is not a merely cognitive one, but can involve affective aspects related to perception -particularly perception of nearby sense data -and emotion. The mathematics education theory that has been used is that of the Espace de Travail Mathématique, the English translation of which is known as Mathematical Working Spaces (MWS). The aspects of neuroscience that have been used pertain to the distinct processing streams known as top-down and bottom-up attention. The practitioner research perspective is aligned with Mason's teaching-practice-based 'noticing'; qualitative data analysed in this report include individual interviews with school teachers on in-service courses and reflective notes from teaching. Basic Euclidean geometry is used as the medium for investigating transition from 'it looks like' to a reasoned 'it has to be'. ResumenEste artículo, desde un marco de referencia práctico, bosqueja desde las teorías de educación matemática y de neurociencia el paso del razonamiento del alumno al razonamiento deductivo idóneo en la Geometría Euclídea. Cómo este paso puede ser facilitado (o impedido) por la emoción y/o dirigido por la atención. Se pone de manifiesto que la cuestión de razonamiento deductivo de una persona no es una meramente cognitivo, pero puede involucrar a los aspectos afectivos relacionados con la percepción -en particular la percepción de sentido de los datos-y la emoción. El modelo utilizado es el de Espace de Travail Mathématique, la traducción en inglés de lo que se conoce como Mathematical Working Spaces (MWS). Los aspectos de neurociencia que se han utilizado pertenecen a las corrientes de tratamiento de la atención (as top-down and bottom-up attention). La perspectiva de la investigación profesional está basada en la enseñanza práctica 'noticing' de Mason. Los datos cualitativos analizados en este informe incluyen entrevistas individuales con los profesores en servicio y notas reflexivas de la enseñanza. La Geometría euclidiana se utiliza como un medio para estudio de la transición de 'parece' a una razonada tiene 'que ser'.

show abstract

“…Although, many significant medical advances have been made over the years in the field of human vision, many critical questions relating to scene understanding based on hierarchical visual processing remain unequivocally unanswered by the research community (Amano et al 2006;Diamant 2008). For example, the three schools-of-thought on hierarchical visual processing are the bottom-up, topbottom and hybrid paradigms (McMains and Kastner 2011;Pinto et al 2013;Graboi and Lisman 2013). In the bottomup approach, hierarchical processing is conceived to be achieved through the sequential aggregation of primary scene features to more defined features and then finally to the object which is recognized (Itti et al 1998).…”

Section: Introductionmentioning

confidence: 99%

Banknote recognition: investigating processing and cognition framework using competitive neural network

Oyedotun

Khashman

2016

Cogn Neurodyn

View full text Add to dashboard Cite

Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria's Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.

show abstract

Bottom-up and top-down attention are independent

Cited by 151 publications

References 102 publications

A two-phase model of resource allocation in visual working memory.

A two-phase model of resource allocation in visual working memory.

Transitioning from “It Looks Like” to “It Has To Be” in Geometrical Workspaces: affect and near-to-me attention

Banknote recognition: investigating processing and cognition framework using competitive neural network

Contact Info

Product

Resources

About