The newly sighted fail to match seen with felt

Held, Richard; Ostrovsky, Yuri; Gelder, Béatrice de; Gandhi, Tapan Kumar; Ganesh, Suma; Mathur, Umang; Sinha, Pawan

doi:10.1038/nn.2795

Cited by 196 publications

(147 citation statements)

References 12 publications

(8 reference statements)

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“…However, actively generating (retrieving) sensorimotor experiences does require training and generalization capabilities. Similar findings have been reported recently for humans (Held et al, 2011). Previously blind subjects, regaining sight after a surgical procedure, were able to visually discriminate different objects right away.…”

Section: Discussionsupporting

confidence: 91%

WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot

Kleesiek¹,

Badde²,

Wermter³

et al. 2012

Proceedings of the 4th International Conference on Agents and Artificial Intelligence

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Abstract:We present a recurrent neural architecture with parametric bias for actively perceiving objects. A humanoid robot learns to extract sensorimotor laws and based on those to classify eight objects by exploring their multimodal sensory characteristics. The network is either trained with prototype sequences for all objects or just two objects. In both cases the network is able to self-organize the parametric bias space into clusters representing individual objects and due to that, discriminates all eight categories with a very low error rate. We show that the network is able to retrieve stored sensory sequences with a high accuracy. Furthermore, trained with only two objects it is still able to generate fairly accurate sensory predictions for unseen objects. In addition, the approach proves to be very robust against noise.

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Section: Discussionsupporting

confidence: 91%

WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot

Kleesiek¹,

Badde²,

Wermter³

et al. 2012

Proceedings of the 4th International Conference on Agents and Artificial Intelligence

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“…This suggests that the association of shape-related features may be 'hardwired', in accord with the observation that 29-day-old human infants are already able to visually recognise the shape of a pacifier after exploring it orally (Meltzoff and Borton, 1979). However the results obtained by Meltzoff and Borton (1979) have not been replicable (Maurer et al, 1999), which coupled with the demonstration that adults newly treated for congenital blindness fail to immediately visually recognise previously handled objects (Held et al, 2011), suggests that the association of shape-related cues may actually be learnt, at least in humans. Further research is needed to clarify the basis of this form of correspondence, and to determine whether shape based associations can be related to the perception of communicative cues.…”

Section: Redundant Feature Correspondencessupporting

confidence: 59%

Cross-Modal Correspondences in Non-human Mammal Communication

2016

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For both humans and other animals, the ability to combine information obtained through different senses is fundamental to the perception of the environment. It is well established that humans form systematic cross-modal correspondences between stimulus features that can facilitate the accurate combination of sensory percepts. However, the evolutionary origins of the perceptual and cognitive mechanisms involved in these cross-modal associations remain surprisingly under-explored. In this review we outline recent comparative studies investigating how non-human mammals naturally combine information encoded in different sensory modalities during communication. The results of these behavioural studies demonstrate that various mammalian species are able to combine signals from different sensory channels when they are perceived to share the same basic features, either because they can be redundantly sensed and/or because they are processed in the same way.Moreover, evidence that a wide range of mammals form complex cognitive representations about signallers, both within and across species, suggests that animals also learn to associate different sensory features which regularly co-occur. Further research is now necessary to determine how multisensory representations are formed in individual animals, including the relative importance of low-level feature-related correspondences. Such investigations will generate important insights into how animals perceive and categorise their environment, as well as provide an essential basis for understanding the evolution of multisensory perception in humans.

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“…been probed through studies of controlled-reared animals [54], newborn human infants [55] and older children with a delayed onset of pattern vision [56,57]. Converging findings from all these strands of research provide evidence that animals from insects to humans recognize objects primarily on the basis of their shapes, regardless of task demands [58].…”

Section: Recognizing the Shapes Of Visual Formsmentioning

confidence: 99%

Core systems of geometry in animal minds

Spelke

Lee

2012

Phil. Trans. R. Soc. B

110

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Research on humans from birth to maturity converges with research on diverse animals to reveal foundational cognitive systems in human and animal minds. The present article focuses on two such systems of geometry. One system represents places in the navigable environment by recording the distance and direction of the navigator from surrounding, extended surfaces. The other system represents objects by detecting the shapes of small-scale forms. These two systems show common signatures across animals, suggesting that they evolved in distant ancestral species. As children master symbolic systems such as maps and language, they come productively to combine representations from the two core systems of geometry in uniquely human ways; these combinations may give rise to abstract geometric intuitions. Studies of the ontogenetic and phylogenetic sources of abstract geometry therefore are illuminating of both human and animal cognition. Research on animals brings simpler model systems and richer empirical methods to bear on the analysis of abstract concepts in human minds. In return, research on humans, relating core cognitive capacities to symbolic abilities, sheds light on the content of representations in animal minds.Keywords: cognitive development; animal cognition; navigation; geometry CORE COGNITIVE SYSTEMS IN ANIMAL MINDSFor well over 2000 years, studies of higher cognition have focused primarily on capacities that are unique to humans, such as language and geometrical intuitions. Debates about the nature and sources of these capacities continue to the present day, however, and progress in resolving them pales by contrast with the progress achieved in understanding the perceptual capacities that humans share with other animals. This contrast highlights problems faced by attempts to study higher cognition in any species, and it hints at a solution to those problems.The modern study of perception began with research on humans, who experimented on themselves to probe the physical events that evoke conscious experiences of colour, tone or motion. The power of these 'psychophysical experiments' was greatly enhanced, however, by parallel research on animals. Studies of perception in humans and in other animals were mutually illuminating: while human psychophysical findings guided research on animal perceptual systems, animal research shed light on the development and architecture of those systems, using methods of controlled rearing, neurophysiology and (more recently) genetics. Research from evolutionary biology and computer science enriched both sets of insights, by shedding light on the computational problems that visual systems evolved to solve.The study of higher cognition has not experienced the same synergies. Indeed, attempts to use human conscious experience as a guide to animal research often lead to blind alleys, because human intuition is a poor source of insights into animal minds. This failure stems, we suggest, from three prominent differences between perceptual systems, on one hand, and higher cognitive...

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The newly sighted fail to match seen with felt

Cited by 196 publications

References 12 publications

WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot

WHAT DO OBJECTS FEEL LIKE? - Active Perception for a Humanoid Robot

Cross-Modal Correspondences in Non-human Mammal Communication

Core systems of geometry in animal minds

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