Reading without saccadic eye movements

Rubin, Gary S.; Turano, Kathleen A.

doi:10.1016/0042-6989(92)90032-e

Cited by 168 publications

(131 citation statements)

References 18 publications

Supporting

Mentioning

121

Contrasting

Order By: Relevance

“…Similarly, although our results do not speak to effects of explicit manipulation of visual attention (Treue and Maunsell, 1996;Connor et al, 1997;Chelazzi et al, 1998;Reynolds et al, 1999), our data are highly relevant to conditions without such pretrial cuing, and robust recognition in clutter is still observed under such conditions (Potter, 1976;Intraub, 1980;Rubin and Turano, 1992). Critically, we have shown that the observed average effect in IT cannot be explained by simple attentional shifts but instead behaves as if it were a primarily feedforward property of the ventral visual stream.…”

Section: Generality Limitations and Implicationscontrasting

confidence: 63%

“…For one, neuronal responses were assessed using a relatively rapid stimulus presentation rate. However, because our presentation rate was similar to that produced by freeviewing monkeys (Motter and Belky, 1998a,b;DiCarlo and Maunsell, 2000;Sheinberg and Logothetis, 2001), gives robust object selectivity in IT (Keysers et al, 2001), and is clearly within the abilities of human recognition (Potter, 1976;Intraub, 1980;Rubin and Turano, 1992), our data provide reasonable estimates of the neuronal responses that underlie fast recognition in clutter. Furthermore, we also found the same average effect for more standard presentation conditions (first stimulus) and previous studies have reported a similar effect in areas V2 and V4 with longer presentation times (Reynolds et al, 1999).…”

Section: Generality Limitations and Implicationssupporting

confidence: 60%

“…Because recognition performance shows remarkable clutter tolerance even for brief presentation conditions (e.g., ϳ100 ms) without explicit attentional instruction (Potter, 1976;Intraub, 1980;Rubin and Turano, 1992), this suggests that top-down attention is not strictly required for robust recognition in clutter but that powerful, primarily feedforward processing mechanisms are also at work. Thus, although previous studies have investigated how attention modulates processing of targets in the presence of distracters (Moran and Desimone, 1985;Maunsell, 1995;Connor et al, 1997;Chelazzi et al, 1998), here we seek to understand the "core" feedforward processing of multiple objects.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multiple Object Response Normalization in Monkey Inferotemporal Cortex

Zoccolan¹,

Cox²,

DiCarlo³

2005

J. Neurosci.

192

217

View full text Add to dashboard Cite

The highest stages of the visual ventral pathway are commonly assumed to provide robust representation of object identity by disregarding confounding factors such as object position, size, illumination, and the presence of other objects (clutter). However, whereas neuronal responses in monkey inferotemporal cortex (IT) can show robust tolerance to position and size changes, previous work shows that responses to preferred objects are usually reduced by the presence of nonpreferred objects. More broadly, we do not yet understand multiple object representation in IT. In this study, we systematically examined IT responses to pairs and triplets of objects in three passively viewing monkeys across a broad range of object effectiveness. We found that, at least under these limited clutter conditions, a large fraction of the response of each IT neuron to multiple objects is reliably predicted as the average of its responses to the constituent objects in isolation. That is, multiple object responses depend primarily on the relative effectiveness of the constituent objects, regardless of object identity. This average effect becomes virtually perfect when populations of IT neurons are pooled. Furthermore, the average effect cannot simply be explained by attentional shifts but behaves as a primarily feedforward response property. Together, our observations are most consistent with mechanistic models in which IT neuronal outputs are normalized by summed synaptic drive into IT or spiking activity within IT and suggest that normalization mechanisms previously revealed at earlier visual areas are operating throughout the ventral visual stream.

show abstract

Section: Generality Limitations and Implicationscontrasting

confidence: 63%

Section: Generality Limitations and Implicationssupporting

confidence: 60%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiple Object Response Normalization in Monkey Inferotemporal Cortex

Zoccolan¹,

Cox²,

DiCarlo³

2005

J. Neurosci.

192

217

View full text Add to dashboard Cite

show abstract

“…Using digital compression, speech can be accelerated up to ϳ40% of its original duration and remain largely comprehensible (Chodorow, 1979;Mehler et al, 1993;Dupoux and Green, 1997;Pallier et al, 1998;Sebastian-Galles et al, 2000). Furthermore, during reading, expert readers typically attain 250 -300 wpm, and reading speed can be doubled or tripled by removing the need for eye movements (Rubin and Turano, 1992).…”

Section: Introductionmentioning

confidence: 99%

A Temporal Bottleneck in the Language Comprehension Network

Vagharchakian¹,

Dehaene‐Lambertz²,

Pallier³

et al. 2012

Journal of Neuroscience

100

View full text Add to dashboard Cite

Humans can understand spoken or written sentences presented at extremely fast rates of ϳ400 wpm, far exceeding the normal speech rate (ϳ150 wpm). How does the brain cope with speeded language? And what processing bottlenecks eventually make language incomprehensible above a certain presentation rate? We used time-resolved fMRI to probe the brain responses to spoken and written sentences presented at five compression rates, ranging from intelligible (60 -100% of the natural duration) to challenging (40%) and unintelligible (20%). The results show that cortical areas differ sharply in their activation speed and amplitude. In modality-specific sensory areas, activation varies linearly with stimulus duration. However, a large modality-independent left-hemispheric language network, including the inferior frontal gyrus (pars orbitalis and triangularis) and the superior temporal sulcus, shows a remarkably time-invariant response, followed by a sudden collapse for unintelligible stimuli. Finally, linear and nonlinear responses, reflecting a greater effort as compression increases, are seen at various prefrontal and parietal sites. We show that these profiles fit with a simple model according to which the higher stages of language processing operate at a fixed speed and thus impose a temporal bottleneck on sentence comprehension. At presentation rates faster than this internal processing speed, incoming words must be buffered, and intelligibility vanishes when buffer storage and retrieval operations are saturated. Based on their temporal and amplitude profiles, buffer regions can be identified with the left inferior frontal/anterior insula, precentral cortex, and mesial frontal cortex.

show abstract

“…The primate visual system has solved this problem: primates robustly and effortlessly discriminate among visual objects over the wide range of images that each object produces during natural vision (Potter, 1976;Intraub, 1980;Rubin and Turano, 1992;Logothetis and Sheinberg, 1996;Thorpe et al, 1996;Edelman, 1999;Rousselet et al, 2004). What neuronal architecture and computations create such a selective and tolerant representation of visual objects?…”

Section: Introductionmentioning

confidence: 99%

Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex

Zoccolan

Kouh²,

Poggio³

et al. 2007

J. Neurosci.

156

162

View full text Add to dashboard Cite

Object recognition requires both selectivity among different objects and tolerance to vastly different retinal images of the same object, resulting from natural variation in (e.g.) position, size, illumination, and clutter. Thus, discovering neuronal responses that have object selectivity and tolerance to identity-preserving transformations is fundamental to understanding object recognition. Although selectivity and tolerance are found at the highest level of the primate ventral visual stream [the inferotemporal cortex (IT)], both properties are highly varied and poorly understood. If an IT neuron has very sharp selectivity for a unique combination of object features ("diagnostic features"), this might automatically endow it with high tolerance. However, this relationship cannot be taken as given; although some IT neurons are highly object selective and some are highly tolerant, the empirical connection of these key properties is unknown. In this study, we systematically measured both object selectivity and tolerance to different identity-preserving image transformations in the spiking responses of a population of monkey IT neurons. We found that IT neurons with high object selectivity typically have low tolerance (and vice versa), regardless of how object selectivity was quantified and the type of tolerance examined. The discovery of this trade-off illuminates object selectivity and tolerance in IT and unifies a range of previous, seemingly disparate results. This finding also argues against the idea that diagnostic conjunctions of features guarantee tolerance. Instead, it is naturally explained by object recognition models in which object selectivity is built through AND-like tuning mechanisms.

show abstract

Reading without saccadic eye movements

Cited by 168 publications

References 18 publications

Multiple Object Response Normalization in Monkey Inferotemporal Cortex

Multiple Object Response Normalization in Monkey Inferotemporal Cortex

A Temporal Bottleneck in the Language Comprehension Network

Trade-Off between Object Selectivity and Tolerance in Monkey Inferotemporal Cortex

Contact Info

Product

Resources

About