Publications by authors named "Matej Hoffmann"

Predictive coding, currently a highly influential theory in neuroscience, has not been widely adopted in machine learning yet. In this work, we transform the seminal model of Rao and Ballard (1999) into a modern deep learning framework while remaining maximally faithful to the original schema. The resulting network we propose (PreCNet) is tested on a widely used next-frame video prediction benchmark, which consists of images from an urban environment recorded from a car-mounted camera, and achieves state-of-the-art performance.

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This longitudinal study investigated the effect of experience with tactile stimulation on infants' ability to reach to targets on the body, an important adaptive skill. Infants were provided weekly tactile stimulation on eight body locations from 4 to 8 months of age (N = 11), comparing their ability to reach to the body to infants in a control group who did not receive stimulation (N = 10). Infants who received stimulation were more likely to successfully reach targets on the body than controls by 7 months of age.

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Accurately predicting contact between our bodies and environmental objects is paramount to our evolutionary survival. It has been hypothesized that multisensory neurons responding both to touch on the body, and to auditory or visual stimuli occurring near them-thus delineating our peripersonal space (PPS)-may be a critical player in this computation. However, we lack a normative account (i.

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Infant development of reaching to tactile targets on the skin has been studied little, despite its daily use during adaptive behaviors such as removing foreign stimuli or scratching an itch. We longitudinally examined the development of infant reaching strategies (from just under 2 to 11 months) approximately every other week with a vibrotactile stimulus applied to eight different locations on the face (left/right/center temple, left/right ear, left/right mouth corners, and chin). Successful reaching for the stimulus uses tactile input and proprioception to localize the target and move the hand to it.

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This study focuses on how the body schema develops during the first months of life, by investigating infants' motor responses to localized vibrotactile stimulation on their limbs. Vibrotactile stimulation was provided by small buzzers that were attached to the infants' four limbs one at a time. Four age groups were compared cross-sectionally (3-, 4-, 5-, and 6-month-olds).

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The contribution of the body to cognition and control in natural and artificial agents is increasingly described as "offloading computation from the brain to the body," where the body is said to perform "morphological computation." Our investigation of four characteristic cases of morphological computation in animals and robots shows that the "offloading" perspective is misleading. Actually, the contribution of body morphology to cognition and control is rarely computational, in any useful sense of the word.

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This paper investigates a biologically motivated model of peripersonal space through its implementation on a humanoid robot. Guided by the present understanding of the neurophysiology of the fronto-parietal system, we developed a computational model inspired by the receptive fields of polymodal neurons identified, for example, in brain areas F4 and VIP. The experiments on the iCub humanoid robot show that the peripersonal space representation i) can be learned efficiently and in real-time via a simple interaction with the robot, ii) can lead to the generation of behaviors like avoidance and reaching, and iii) can contribute to the understanding the biological principle of motor equivalence.

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