William Guild Building, Room S7
University of Aberdeen
The United Kingdom
A crucial question in vision science is how do we recognize objects? It seems trivial, easy, and self-evident, but taking a cursory look at today's artificial intelligence research (or at face detection software in cameras) is enough to suggest how incredibly complex the process is. At our lab, we have been working on uncovering the mechanisms underlying object recognition, using visual crowding as a tool. Currently, we are working on determining the neural processes underlying attention, object recognition and visual short term memory (VSTM) using a combination of psychophysics and EEG.
Object recognition takes place in two steps. First, the features (orientation, color, etc) of an object are detected independently. Then these features are put together to form the representation of that object. Crowding is a breakdown of the second step. When a target object is flanked closely by other objects, the features of the target and the flankersget mixed up leading to a jumbled percept. This is crowding. It offers a direct window into how feature integration occurs, and hence serves as a handy tool in investigating object recognition.
Crowding is illustrated below. Fixate (keep your eyes focused) on the black square in the center. If you try to read the central letter of the triplet on the right, you will find it very hard. The same letter at the same distance on the left is extremely easy to identify. It is the presence of the the flanking letters on the right that makes the target letter unidentifiable.
Visual attention directs the limited resources of the visual system to the currently relevant input. We are interested in how attention is deployed in space in order to select objects. Currently, We are applying a variety of techniques including Steady State Visual Evoked Potentials, Multivariate Classifiers and Representational Similarity Analysis to EEG data obtained in attentional tasks to determine the shifts in spatial attention as a function of time. Similar techniques are also being applied to determine how the brain represents various features of objects, such as location and motion.
- Neural oscillations in attention, awareness and VSTM
- Neural basis of crowding
- Time perception
Lecturer and PI
Former Postgraduate Members
Former Undergraduate Members
Robert's summer internship was supported by the Developing Scientisits fund, during the summer of 2014. He worked on whether visual crowding could be alleviated by priming.
Robert is a tennis enthusiast and runs his own tennis training service. He recently graduated from the University of Aberdeen.
- Soo, L., Chakravarthi, R., and Andersen, S. K. (accepted). Critical resolution: a superior measure of crowding, Vision Research. abstract pdf
- § Reuther, J. and Chakravarthi, R. (2017). Does self-prioritization affect perceptual processes?, Visual Cognition, 1 - 18. abstract pdf
- Jennings, B. J., Tsattalios, K., Chakravarthi, R., and Martinovic, J. (2016). Combining S-cone and luminance signals adversely affects discrimination of objects within backgrounds, Scientific Reports, 6 (20504): 1-10. abstract pdf
- Costa, S. L., Gonçalves, O. F., DeLuca, J. Chiaravalloti, N., Chakravarthi, R., and Almeida, J. (2015). The temporal dynamics of visual processing in Multiple Sclerosis, Applied Neuropsychology: Adult, 23 (2): 133 - 140. abstract pdf
- Rosen, S., Chakravarthi, R., and Pelli, D. G. (2014). The Bouma law of crowding, revised: Critical spacing is equal across parts, not objects, Journal of Vision, 14 (6): 10, 1-15. abstract pdf
- Chakravarthi, R., Carlson, T. A., Chaffin, J., Turret, J., and VanRullen, R. (2014). The temporal evolution of coarse location coding of objects: Evidence for feedback. Journal of Cognitive Neuroscience, 26 (10): 2370 - 2384. abstract pdf
- Reuther, J. and Chakravarthi, R. (2014). Categorical membership modulates crowding: evidence from characters, Journal of Vision, 14 (6): 5, 1-13. abstract pdf
- Van Vugt, M. K., Chakravarthi, R., and Lachaux, J. P. (2014). For whom the bell tolls: periodic reactivation of sensory cortex in the gamma band as a substrate of visual working memory maintenance, Frontiers in Human Neuroscience, 8: 696. abstract pdf
- Chakravarthi, R. and VanRullen, R. (2012). Conscious updating is a rhythmic process, Proceedings of the National Academy of Sciences, 109 (26): 10599-10604. abstract pdf
- Freeman, J.,Chakravarthi, R., and Pelli, D. G. (2012). Substitution and pooling in crowding, Attention, Perception, & Psychophysics, 72 (4): 379 - 396 abstract pdf
- Chakravarthi, R. and Pelli, D. G. (2011). The same binding in contour integration and crowding, Journal of Vision, 11 (8): 10, 1-12. abstract pdf
- Chakravarthi, R. and VanRullen, R. (2011). Bullet trains and steam engines: Exogenous attention zips but endogenous attention chugs along, Journal of Vision, 11 (4):12, 1-12. abstract pdf
- Chakravarthi, R. and Cavanagh, P. (2009). Recovery of a crowded object by masking the distracters: Determining the locus of feature integration, Journal of Vision, 9 (10):4, 1-9. abstract pdf
- Chakravarthi, R. and Cavanagh, P. (2009). Bilateral field advantage in visual crowding, Vision Research, 49 (13): 1638 – 1646. abstract pdf
- Vickery, T. J., Shim, W. M., Chakravarthi, R., Jiang, Y. V., and Luedeman, R. (2009). Supercrowding: Weakly masking a target expands the range of crowding, Journal of Vision, 9 (2):12, 1-15. abstract pdf
- Chakravarthi, R. and Cavanagh, P. (2007). Temporal properties of the polarity advantage effect in crowding, Journal of Vision, 7 (11): 1 – 12. abstract pdf
- Ramakrishna, C. (2002). Real latencies and facilitation, Consciousness and Cognition, 11(2): 300 – 303. pdf
Manuscripts in progress
- Poncet, M., Chakravarthi, R., and Fabre-Thorpe, M (Submitted). Interactions between visual categories can be explained by overlap of neural activity.
- Reuther, J. and Chakravarthi, R. (in preparation). Higher level crowding: Is it all just experimental design?
- Soo, L., Chakravarthi, R., and Andersen, S. A. (2015). The effects of contrast dissimilarity on crowding. Talk presented at the 14th annual meeting of the Scottish Vision Group, Scotland, UK.
- Reuther, J. and Chakravarthi, R. (2015). Category effect in visual crowding = feature differences + overlap differences. Talk presented at the 14th annual meeting of the Scottish Vision Group, Scotland, UK.
- Reuther, J. and Chakravarthi, R. (2014). Evidence for categorical crowding. Talk presented at the 13th annual meeting of the Scottish Vision Group, Scotland, UK.
- Marosi, D-M. and Chakravarthi, R. (2014). Losing track of time: Time perception in cooperation and competition. Talk presented at the British Psychological Society Scottish Branch UG conference at Edinburgh, UK.
- Poncet, M., Chakravarthi, R., and Fabre-Thorpe, M. (2014). The clash of visual categories. Poster presented at the 14th annual meeting of Vision Sciences Society, St Petersburg, FL.
- Chakravarthi, R. and VanRullen, R. (2012). Evidence for the Lisman model of short-term memory: Modulation of theta-gamma coupling by the number of items in memory. Poster presented at the annual meeting of the Society for Neuroscience, New Orleans, USA.
- Chakravarthi, R., Carlson, T. A., Chaffin, J., Turret, J. and VanRullen, R. (2011). O brother, where art thou? Locations of 1st and 2nd order objects are represented in the same way but at different times, as revealed by single-trial decoding of EEG signals. Talk presented at the European Conference on Vision and Perception, Toulouse, France.
- Chakravarthi, R. and VanRullen, R. (2011). Attention is a state of mind: Phase of ongoing EEG oscillations predicts the timing of attentional deployment. Poster presented at the 11th annual meeting of Vision Sciences Society, Naples, FL.
- Rosen, S., Chakravarthi, R., and Pelli, D. G. (2010). Crowding is grouping. Talk presented at the 11th annual meeting of Vision Sciences Society, Naples, FL.
- Rosen, S., Chakravarthi, R., and Pelli, D. G. (2010). Grouping is fundamental to object recognition. Talk presented at the European Conference on Vision and Perception, Lausanne, Switzerland.
- Chakravarthi, R. (2010). Mechanisms in crowding and blink: what can they tell us about consciousness? Symposium chaired at the 14th annual meeting of Association for the Scientific Study of Consciousness, Toronto, Canada.
- Chakravarthi, R. and Rosen, S. (2010). Pool party: Admit one. Talk presented at the 14th annual meeting of Association for the Scientific Study of Consciousness, Toronto, Canada.
- Chakravarthi, R. and VanRullen, R. (2010). Beam me up Scotty! Exogenous attention teleports but endogenous attention takes the shuttle. Talk presented at the 10th annual meeting of Vision Sciences Society, Naples, FL.
- Pelli, D. G., Freeman, J., and Chakravarthi, R. (2010). Crowding combines. Talk presented at the 10th annual meeting of Vision Sciences Society, Naples, FL.
- Rosen, S., Chakravarthi, R., and Pelli, D. G. (2010). Pool party, objects rule! Poster presented at the 10th annual meeting of Vision Sciences Society, Naples, FL.
- Granata, Y., Chakravarthi, R., Rosen, S., and Pelli. D. G. (2010). Size pooling. Poster presented at the 10th annual meeting of Vision Sciences Society, Naples, FL.
- Chakravarthi, R., Tillman, K., and Pelli, D. G. (2009). Features used or features available? Talk presented at the 9th annual meeting of Vision Sciences Society, Naples, FL.
- Veenemans, A., Cavanagh, P., and Chakravarthi, R. (2009). Crowding by invisible flankers. Poster presented at the 9th annual meeting of Vision Sciences Society, Naples, FL.
- Chakravarthi, R. and Pelli, D. G. (2008). What role does contour integration play in crowding? Talk presented at the 8th annual meeting of Vision Sciences Society, Naples, FL.
- Rosen, S., Chakravarthi, R., and Pelli, D. G. (2008). Nasotemporal asymmetry in crowding. Talk presented at the 8th annual meeting of Vision Sciences Society, Naples, FL.
- Vickery, T. J., Shim, W. M., Jiang, Y. V., Chakravarthi, R., and Luedeman, R. (2008). Supercrowding: Weakly masking a target greatly enhances crowding. Talk presented at the 8th annual meeting of Vision Sciences Society, Naples, FL.
- Chatterjee, G. and Chakravarthi, R. (2008). Characterization of flickering-flanker induced blindness phenomenon. Poster presented at ECVP 2008, Utrecht, Netherlands.
- Chakravarthi R., Rajagopal, A.K., and Usha Devi, A. R. (2008). Quantum mechanical basis of vision. Talk presented at India-US workshop on Science and Technology at the Nano-Bio Interface, Bhubaneshawar, India.
- Chakravarthi, R. and Cavanagh, P. (2007). The effect of distracters on enumeration in the periphery. Poster presented at the 7th annual meeting of Vision Sciences Society, Sarasota, FL.
- Chakravarthi, R. and Cavanagh, P. (2006). Hemifield independence in visual crowding. Talk presented at the 6th annual meeting of Vision Sciences Society, Sarasota, FL.
- Chakravarthi, R. and Cavanagh, P. (2005). Temporal properties of the polarity advantage effect in crowding. Poster presented at the 5th annual meeting of Vision Sciences Society, Sarasota, FL.
§ Preregistered/Presubmitted Study
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Education and Employment
|2012 – Present:||Lecturer, School of Psychology
University of Aberdeen, Scotland UK
|2009 – 2012:||Post Doctoral Fellow; Advisor: Dr. Rufin VanRullen
Centre de Recherche Cerveau et Cognition CNRS, Toulouse, France,
|2007 – 2009:||Post Doctoral Fellow in Psychology and Neural Science; Advisor: Prof. Denis Pelli
New York University, New York NY
|2002 – 2007:||PhD in Psychology: Cognition, Brain and Behavior; Advisor: Prof. Patrick Cavanagh
Harvard University, Cambridge MA
|1999 – 2001:||M.S. in Consciousness Studies; Advisor: Dr Shantanu Nagarkatti
Birla Institute of Technology and Science, Pilani, India
|1993 – 1999:||M.B., B.S. (Bachelor of Medicine, Bachelor of Surgery)
Manipal Academy of Higher Education, Manipal, India
Grants and Funding
|2014 – :||Exploring the neural basis of visual crowding, Eastbio BBSRC Doctoral Training Programme awarded to Ms. Leili Soo, ~£92,000|
|2014 – :||Neural correlates of Blindsight, Elphinstone PhD Scholarship awarded to Mr Nicholas Hall, ~£15,000|
|2013 – :||Mechanisms of Visual Crowding, Anderson Postgraduate (PhD) Scholarship awarded to Ms Josephine Reuther, ~£50,000|
|2014:||Developing Scientists Summer Placement awarded to Mr. Robert Ainsley Henriksen, £1000|
|2012:||Developing Scientists Summer Placement awarded to Mr. Sindre Henriksen, £1000|
|2006 – 2007:||Graduate Society Dissertation Completion Fellowship, Harvard University, $18,000|
|2007:||Stimson travel grant for presenting at VSS conference, 2007, $500|
|2006:||McMasters travel grant for presenting at VSS conference, 2006, $500|
|2005:||Graduate Society Fellowship Summer Award, Harvard University, $3,000|
|2004:||Mind, Brain and Behavior Graduate Student Award, Harvard University, $5,000|
|2003 – 2004:||Harvard University Graduate Summer Awards, $3,000/year|
|2002 – 2004:||Harvard University GSAS Merit Fellowship, $70,000|
|2000 – 2001:||Sir Ratan Tata Trust Scholarship for the M.S. Program, INR 15,000|
|Level 3:||Methodology B: Semester long research projects (5-6 students each semester)|
|Masters:||Professional research skills I: Web design and maintenance in academia|
|2003 – 2005:||Teaching Fellow, The Evolution of Human Nature. Taught by Professors Marc Hauser and Richard Wrangham, Harvard University, 2 semesters|
|2004 – 2006:||Teaching Fellow, The Human Mind. Taught by Professor Steven Pinker, Harvard University, 2 semesters|
- Level 3 Methods B Course Coordinator
- Member of Ethics Committee
- Equality and Diversity Committee
- Psychology Webpage maintenance
- Social media outreach
- Organising Perception and Attention group meetings
- Society for Neuroscience
- Vision Sciences Society
- European Conference on Visual Perception
- Scottish Vision Group
- Karnataka Medical Council, India
- Attention, Perception, and Psychophysics
- Journal of Cognitive Neuroscience
- Journal of Experimental Psychology: Human Perception and Performance
- Journal of Vision
- Vision Research
- Frontiers in Psychology
- Review Editor: Frontiers of Consciousness Research
|2014:||The role of neural oscillations in visual processing. Presented at the University of Bangor, Wales|
|2013:||When one's company, two's a crowd in object recognition. Presented at Workshop on crowding, EPFL, Lausanne, Switzerland.|
|2012:||One rule to bind them all. Presented at the British Science Festival, Aberdeen UK|
|2010:||Object recognition and visual attention. Presented at the Center for Brain and Cognitive Sciences, University of Allahabad, India.|
|2006:||The Resolution of Visual Consciousness. Presented at Mind, Brain, and Behavior Graduate Seminar Series, Harvard University.|
Critical resolution: a superior measure of crowding'
Soo, L., Chakravarthi, R. and Andersen, S. K. (2018)
Visual object recognition is essential for adaptive interactions with the environment. It is fundamentally limited by crowding, a breakdown of object recognition in clutter. The spatial extent over which crowding occurs is proportional to the eccentricity of the target object, but nevertheless varies substantially depending on various stimulus factors (e.g. viewing time, contrast). However, a lack of studies jointly manipulating such factors precludes predictions of crowding in more heterogeneous scenes, such as the majority of real life situations. To establish how such co-occurring variations affect crowding, we manipulated combinations of 1) flanker contrast and backward masking, 2) flanker contrast and presentation duration, and 3) flanker preview and pop-out while measuring participants’ ability to correctly report the orientation of a target stimulus. In all three experiments, combining two manipulations consistently modulated the spatial extent of crowding in a way that could not be predicted from an additive combination. However, a simple transformation of the measurement scale completely abolished these interactions and all effects became additive. Precise quantitative predictions of the magnitude of crowding when combining multiple manipulations are thus possible when it is expressed in terms of what we label the ‘critical resolution’. Critical resolution is proportional to the inverse of the smallest flanker free area surrounding the target object necessary for its unimpaired identification. It offers a more parsimonious description of crowding than the traditionally used critical spacing and may thus constitute a measure of fundamental importance for understanding object recognition.Close window
Does self-prioritization affect perceptual processes?'
Reuther, J. and Chakravarthi, R. (2017)
The tendency to prioritize information related to the self (or socially salient information) has been established for several cognitive tasks. However, earlier studies on this question suffered from confounds such as familiarity and intimacy. Recently, a series of studies overcame this limitation using newly learnt associations between geometric shapes and identities. Results from these studies have been argued to show that self-prioritization affects perceptual processing. In two studies, we replicated and extended the original shape-identity association paradigm to test an alternative hypothesis that self-prioritization does not affect perceptual processes but arises from potential memory differences introduced during the formation of associations. We found that induced memory differences lead to response patterns similar to those that have been attributed to changes in the perceptual domain. However, even extended learning undertaken to equate memory for various identity-based associations did not eliminate the effects of self-prioritization, leaving the question open if the differences are cognitive or perceptual in nature. The current evidence can be explained both in terms of memory differences and perceptual effects. Hence, we strongly recommend that the existence of perceptual effects of self-prioritization should be investigated directly rather than through changes in reaction times in match–non-match tasks.Close window
Combining S-cone and luminance signals adversely affects discrimination of objects within backgrounds
Jennings, B. J., Tsattalios, K., Chakravarthi, R., and Martinovic, J. (2016)
The visual system processes objects embedded in complex scenes that vary in both luminance and colour. In such scenes, colour contributes to the segmentation of objects from backgrounds, but does it also a ect perceptual organisation of object contours which are already de ned by luminance signals, or are these processes una ected by colour’s presence? We investigated if luminance and chromatic signals comparably sustain processing of objects embedded in backgrounds, by varying contrast along the luminance dimension and along the two cone-opponent colour directions. In the rst experiment thresholds for object/non-object discrimination of Gaborised shapes were obtained in the presence and absence of background clutter. Contrast of the component Gabors was modulated along single colour/luminance dimensions or co-modulated along multiple dimensions simultaneously. Background clutter elevated discrimination thresholds only for combined S-(L + M) and L + M signals. The second experiment replicated and extended this nding by demonstrating that the e ect was dependent on the presence of relatively high S-(L + M) contrast. These results indicate that S-(L + M) signals impair spatial vision when combined with luminance. Since S-(L + M) signals are characterised by relatively large receptive elds, this is likely to be due to an increase in the size of the integration eld over which contour-de ning information is summed.Close window
The temporal dynamics of visual processing in multiple sclerosis
Costa, S. L., Gonçalves, O. F., DeLuca, J. Chiaravalloti, N., Chakravarthi, R., and Almeida, J. (2015)
Although the integrity of the visual system is often affected in multiple sclerosis (MS), the potential relationship between the temporal dynamics of visual processing and performance on neuropsychological tests assessing processing speed (PS) remains relatively unexplored. Here, we test if a PS deficit is related to abnormalities within the visual system, rather than impaired higher-level cognitive function. Two groups of participants with MS (1 group with PS deficits and another without) and a healthy control group, matched for age and education, were included. To explore the temporal dynamics of visual processing, we used 2 psychophysical paradigms: attention enhancement/prioritization and rapid serial visual presentation. Visual PS deficits were associated with a decreased capability to detect visual stimuli and a higher limitation in visual temporal-processing capacity. These results suggest that a latent sensorial temporal limitation of the visual system is significantly associated to PS deficits in MS.Close window
The Bouma law of crowding, revised: Critical spacing is equal across parts, not objects
Rosen, S., Chakravarthi, R. and Pelli, D. G. (2014)
Crowding is the inability to identify an object among flankers in the periphery. It is due to inappropriate incorporation of features from flanking objects in perception of the target. Crowding is characterized by measuring critical spacing, the minimum distance needed between a target and flankers to allow recognition. The existing Bouma law states that, at a given point and direction in the visual field, critical spacing, measured from the center of a target object to the center of a similar flanking object, is the same for all objects (Pelli & Tillman, 2008). Because flipping an object about its center preserves its center-to-center spacing to other objects, according to the Bouma law, crowding should be unaffected. However, because crowding is a result of feature combination, the location of features within an object might matter. In a series of experiments, we find that critical spacing is affected by the location of features within the flanker. For some flankers, a flip greatly reduces crowding even though it maintains target–flanker spacing and similarity. Our results suggest that the existing Bouma law applies to simple one-part objects, such as a single roman letter or a Gabor patch. Many objects consist of multiple parts; for example, a word is composed of multiple letters that crowd each other. To cope with such complex objects, we revise the Bouma law to say that critical spacing is equal across parts, rather than objects. This accounts for old and new findings.Close window
The temporal evolution of coarse location coding of objects: Evidence for feedback
Chakravarthi, R., Carlson, T. A., Chaffin, J., Turret, J., and VanRullen, R. (2014)
Objects occupy space. How does the brain represent the spatial location of objects? Retinotopic early visual cortex has precise location information but can only segment simple objects. On the other hand, higher visual areas can resolve complex objects but only have coarse location information. Thus coarse location of complex objects might be represented by either (a) feedback from higher areas to early retinotopic areas or (b) coarse position encoding in higher areas. We tested these alternatives by presenting various kinds of first- (edge- defined) and second-order (texture) objects. We applied multi- variate classifiers to the pattern of EEG amplitudes across the scalp at a range of time points to trace the temporal dynamics of coarse location representation. For edge-defined objects, peak classification performance was high and early and thus attributable to the retinotopic layout of early visual cortex. For texture objects, it was low and late. Crucially, despite these differences in peak performance and timing, training a classifier on one object and testing it on others revealed that the topography at peak performance was the same for both first- and second-order objects. That is, the same location in- formation, encoded by early visual areas, was available for both edge-defined and texture objects at different time points. These results indicate that locations of complex objects such as textures, although not represented in the bottom–up sweep, are encoded later by neural patterns resembling the bottom–up ones. We conclude that feedback mechanisms play an important role in coarse location representation of complex objects.Close window
Categorical membership modulates crowding: Evidence from characters
Reuther, J. and Chakravarthi, R. (2014)
Visual crowding is generally thought to affect recognition mostly or only at the level of feature combination. Calling this assertion into question, recent studies have shown that if a target object and its flankers belong to different categories crowding is weaker than if they belong to the same category. Nevertheless, these results can be explained in terms of featural differences between categories. The current study tests if category- level (i.e., high-level) interference in crowding occurs when featural differences are controlled for. First, replicating previous results, we found lower critical spacing for targets and flankers belonging to different categories. Second, we observed the same, albeit weaker, category-specific effect when objects in both categories had the exact same feature set, suggesting that category-specific effects persist even when featural differences are fully controlled for. Third, we manipulated the semantic content of the flankers while keeping their feature set constant, by using upright or rotated objects, and found that meaning modulated crowding. An exclusively feature-based account of crowding would predict no differences due to such changes in meaning. We conclude that crowding results from not only the well-documented feature-level interactions but also additional interactions at a level where objects are grouped by meaning.Close window
For whom the bell tolls: periodic reactivation of sensory cortex in the gamma band as a substrate of visual working memory maintenanc
Van Vugt, M. K., Chakravarthi, R. and Lachaux, J. P. (2014)
Working memory (WM) is central to human cognition as it allows information to be kept online over brief periods of time and facilitates its usage in cognitive operations (Luck and Vogel, 2013). How this information maintenance actually is implemented is still a matter of debate. Several independent theories of WM, derived, respectively, from behavioral studies and neural considerations, advance the idea that items in WM decay over time and must be periodically reactivated. In this proposal, we show how recent data from intracranial EEG and attention research naturally leads to a simple model of such reactivation in the case of sensory memories. Specifically, in our model the amplitude of high-frequency activity (>50 Hz, in the gamma-band) underlies the representation of items in high-level visual areas. This activity decreases to noise-levels within 500 ms, unless it is reactivated. We propose that top-down attention, which targets multiple sensory items in a cyclical or rhythmic fashion at around 6–10 Hz, reactivates these decaying gamma-band representations. Therefore, working memory capacity is essentially the number of representations that can simultaneously be kept active by a rhythmically sampling attentional spotlight given the known decay rate. Since attention samples at 6–10 Hz, the predicted WM capacity is 3–5 items, in agreement with empirical findings.Close window
Conscious updating is a rhythmic process
Chakravarthi, R. and VanRullen, R. (2012)
As the visual world changes, its representation in our consciousness must be constantly updated. Given that the external changes are continuous, it appears plausible that conscious updating is continuous as well. Alternatively, this updating could be periodic, if, for example, its implementation at the neural level relies on oscillatory activity. The flash-lag illusion, where a briefly presented flash in the vicinity of a moving object is misperceived to lag behind the moving object, is a useful tool for studying the dynamics of conscious up- dating. Here, we show that the trial-by-trial variability in updating, measured by the flash-lag effect (FLE), is highly correlated with the phase of spontaneous EEG oscillations in occipital (5–10 Hz) and frontocentral (12–20 Hz) cortices just around the reference event (flash onset). Further, the periodicity in each region independently influences the updating process, suggesting a two-stage periodic mechanism. We conclude that conscious updating is not continuous; rather, it follows a rhythmic pattern.Close window
Substitution and pooling in crowding
Freeman, J., Chakravarthi, R., and Pelli, D. G. (2012)
Unless we fixate directly on it, it is hard to see an object among other objects. This breakdown in object recognition, called crowding, severely limits peripheral vision. The effect is more severe when objects are more similar. When observers mistake the identity of a target among flanker objects, they often report a flanker. Many have taken these flanker reports as evidence of internal substitution of the target by a flanker. Here, we ask observers to identify a target presented in between one similar and one dissimilar flanker. (Simple) substitution takes only one letter, which is often the target but, by unwitting mistake, is sometimes a flanker. The opposite of substitution is pooling, which takes in more than one letter. Having taken only one letter, the substitution process knows only its identity, not its similarity to the target. Thus, it must report similar and dissimilar flankers equally often. Contrary to this prediction, the similar flanker is reported much more often than the dissimilar flanker, showing that rampant flanker substitution cannot account for most flanker reports. Mixture modeling shows that simple substitution can account for, at most, about half the trials. Pooling and nonpooling (simple substitution) together include all possible models of crowding. When observers are asked to identify a crowded object, at least half of their reports are pooled, on the basis of a combination of information from target and flankers, rather than being based on a single letter.Close window
The same binding in contour integration and crowding
Chakravarthi, R. and Pelli, D. G. (2011)
Binding of features helps object recognition in contour integration, but hinders it in crowding. In contour integration, aligned adjacent objects group together to form a path. In crowding, flanking objects make the target unidentifiable. But, to date, the two tasks have only been studied separately. May and Hess (2007) suggested that the same binding mediates both tasks. To test this idea, we ask observers to perform two different tasks with the same stimulus. We present oriented grating patches that form a “snake letter” in the periphery. Observers report either the identity of the whole letter (contour integration task) or the phase of one of the grating patches (crowding task). We manipulate the strength of binding between gratings by varying the alignment between them, i.e. the Gestalt goodness of continuation, measured as “wiggle”. We find that better alignment strengthens binding, which improves contour integration and worsens crowding. Observers show equal sensitivity to alignment in these two very different tasks, suggesting that the same binding mechanism underlies both phenomena. It has been claimed that grouping among flankers reduces their crowding of the target. Instead, we find that these published cases of weak crowding are due to weak binding resulting from target-flanker misalignment. We conclude that crowding is mediated solely by the grouping of flankers with the target and is independent of grouping among flankers.Close window
Bullet trains and steam engines: Exogenous attention zips but endogenous attention chugs along
Chakravarthi, R. and VanRullen, R. (2011)
Analyzing a scene requires shifting attention from object to object. Although several studies have attempted to determine the speed of these attentional shifts, there are large discrepancies in their estimates. Here, we adapt a method pioneered by Carlson et al (2006) that directly measures pure attentional shift times. We also test if attentional shifts can be handled in parallel by the independent resources available in the two cortical hemispheres. We present 10 ‘clocks’, with single revolving hands, in a ring around fixation. Observers are asked to report the hand position on one of the clocks at the onset of a transient cue. The delay between the reported time and the veridical time at cue onset can be used to infer processing and attentional shift times. With this setup, we use a novel subtraction method that utilizes different combinations of exogenous and endogenous cues to determine shift times for both types of attention. In one experiment, subjects shift attention to an exogenously cued clock (baseline condition) in one block and in other blocks perform one further endogenous shift to a nearby clock (test condition). In another experiment, attention is endogenously cued to one clock (baseline condition) and on other trials an exogenous cue further shifts attention to a nearby clock (test condition). Subtracting report delays in the baseline condition from those obtained in the test condition allows us to isolate genuine attentional shift times. In agreement with previous studies, our results reveal that endogenous attention is much slower than exogenous attention (endogenous: 250ms; exogenous: 100 ms). Surprisingly, the dependence of shift time on distance is minimal for exogenous attention, whereas it is steep for endogenous attention. In the final experiment we find that endogenous shifts are faster across hemifields than within a hemifield suggesting that the two hemispheres can simultaneously process at least parts of these shifts.Close window
Recovery of a crowded object by masking the distracters: Determining the locus of feature integration
Chakravarthi, R. and Cavanagh, P. (2009)
Object recognition is a central function of the visual system. As a first step, the features of an object are registered; these independently encoded features are then bound together to form a single representation. Here we investigate the locus of this ‘feature integration’ by examining crowding, a striking breakdown of this process. Crowding, an inability to identify a peripheral target surrounded by flankers, results from ‘excessive integration’ of target and flanker features. We presented a standard crowding display with a target C flanked by four flanker C’s in the periphery. We then masked only the flankers (but not the target) with one of three kinds of masks – noise, metacontrast, and object substitution – each of which interferes at progressively higher levels of visual processing. With noise and metacontrast masks (low-level masking), the crowded target was recovered, whereas with object substitution masks (high-level masking), it was not. This places a clear upper bound on the locus of interference in crowding suggesting that crowding is not a low-level phenomenon. We conclude that feature integration, which underlies crowding, occurs prior to the locus of object substitution masking. Further, our results indicate that the integrity of the flankers, but not their identification, is crucial for crowding to occur.Close window
Bilateral field advantage in visual crowding
Chakravarthi, R. and Cavanagh, P. (2009)
Thirty randomly oriented T’s were presented in a circle around fixation at an eccentricity of 11 degrees such that each T was crowded by its neighbors. Two locations within the same hemifield (unilateral condition) or one location in each hemifield (bilateral condition) were precued for subsequent probing. Observers were then asked to report the orientation of a target T at one of these locations. A bilateral field advantage was found: target identification was better when the two precued targets were in different hemifields than when they were within the same hemifield. This bilateral advantage was absent when only targets were presented, without any distracters. Further controls showed that this advantage could not be attributed to differences between horizontal and vertical target alignments or to visual field anisotropies. A similar bilateral advantage has been reported for multiple object tracking (Alvarez & Cavanagh, 2005) and other attentional tasks. Our results suggest that crowding also demonstrates separate attentional resources in the left and right hemifields. There was a cost to attending to two targets presented unilaterally over attending to a single target. However, this cost was reduced when the two crowded targets were in separate hemifields.Close window
Supercrowding: Weakly masking a target expands the range of crowding
Vickery, T. J., Shim, W. M., Chakravarthi, R., Jiang, Y. V., and Luedeman, R. (2009)
Crowding is the impairment of peripheral object identiﬁcation by nearby objects. Critical spacing (the minimum target-ﬂanker distance that does not produce crowding) scales with target eccentricity and is consistently reported as roughly equal to or less than 50% of target eccentricity (0.5e). This study demonstrates that crowding occurs far beyond the typical critical spacing when the target is weakly masked by a surrounding contour or backwards pattern mask. A target was presented at a peripheral location on every trial and participants reported its orientation. Flankers appeared at target-ﬂanker distances of 0.3–0.7e, or were absent. The target was presented with or without a mask. When ﬂankers were absent, the masks only mildly impaired performance. When ﬂankers were present but the mask was absent, target identiﬁcation was nearly perfect at wide target-ﬂanker distances (0.5e–0.7e). However, when ﬂankers were present and the target was masked, performance dropped signiﬁcantly, even when target-ﬂanker distances far exceeded the typical crowding range. This phenomenon (“supercrowding”) shares critical features with standard crowding: ﬂankers similar to the target impair performance more than dissimilar ﬂankers, and the characteristic anisotropic proﬁle of crowding is preserved. Supercrowding may reﬂect a general interaction between crowding and other forms of masking.Close window
Temporal properties of the polarity advantage effect in crowding
Chakravarthi, R. and Cavanagh, P. (2007)
If the target in a crowding display differs from the distracters in its contrast polarity, the extent of crowding is reduced compared to the condition where all the elements in the display have the same polarity. In experiment 1 we test the temporal properties of this polarity advantage by reversing the contrast of the target and flankers at 4 frequencies between 2 and 15 Hz. In the same-polarity condition, target and distracters were all white in one frame but all black in the next. In the opposite-polarity condition, the target was white and distracters black in one frame and all reversed in the next frame. Less crowding was seen for the opposite polarity condition at lower frequencies but this advantage disappeared at 7.5 Hz and higher frequencies. In experiment 2, we test whether this result can be explained by lateral masking, using a display that matched the crowding configuration. Lateral masking did not exhibit a polarity advantage at any frequency. Hence, the polarity advantage in crowding, and its loss at 6 to 8 Hz, cannot be attributed to lateral masking. It is known that attention has a coarse temporal resolution (6 – 8 Hz). The findings of this study suggest a role for attention in crowding, as opposed to low-level mechanisms like lateral masking.Close window