PreCNet: Next-Frame Video Prediction Based on Predictive Coding.

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. Performance on all measures (MSE, PSNR, and SSIM) was further improved when a larger training set (2M images from BDD100k) pointed to the limitations of the KITTI training set. This work demonstrates that an architecture carefully based on a neuroscience model, without being explicitly tailored to the task at hand, can exhibit exceptional performance.

Tactile training facilitates infants' ability to reach to targets on the body.

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. These findings indicate that tactile stimulation facilitates the development of reaching to the body by allowing infants to explore the sensorimotor correlations emerging from the stimulation.

A normative model of peripersonal space encoding as performing impact prediction.

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.e., a model specifying how we ought to compute) linking impact prediction and PPS encoding. Here, we leverage Bayesian Decision Theory to develop such a model and show that it recapitulates many of the characteristics of PPS. Namely, a normative model of impact prediction (i) delineates a graded boundary between near and far space, (ii) demonstrates an enlargement of PPS as the speed of incoming stimuli increases, (iii) shows stronger contact prediction for looming than receding stimuli-but critically is still present for receding stimuli when observation uncertainty is non-zero-, (iv) scales with the value we attribute to environmental objects, and finally (v) can account for the differing sizes of PPS for different body parts. Together, these modeling results support the conjecture that PPS reflects the computation of impact prediction, and make a number of testable predictions for future empirical studies.

Development of Infant Reaching Strategies to Tactile Targets on the Face.

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. We studied the developmental progression of reaching and grasping strategies. As infants became older the likelihood of using the hand to reach to the target - versus touching the target with another body part or surface such as the upper arm or chair - increased. For trials where infants reached to the target with the hand, infants also refined their hand postures with age. As infants became older, they made fewer contacts with a closed fist or the dorsal part of the hand and more touches/grasps with the fingers or palm. Results suggest that during the first year infants become able to act more precisely on tactile targets on the face.

Which limb is it? Responses to vibrotactile stimulation in early infancy.

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). We show that before they actually reach for the buzzer, which, according to previous studies, occurs around 7-8 months of age, infants demonstrate emerging knowledge about their body's configuration by producing specific movement patterns associated with the stimulated body area. At 3 months, infants responded with an increase in general activity when the buzzer was placed on the body, independently of the vibrator's location. Differentiated topographical awareness of the body seemed to appear around 5 months, with specific responses resulting from stimulation of the hands emerging first, followed by the differentiation of movement patterns associated with the stimulation of the feet. Qualitative analyses revealed specific movement types reliably associated with each stimulated location by 6 months of age, possibly preparing infants' ability to actually reach for the vibrating target. We discuss this result in relation to newborns' ability to learn specific movement patterns through intersensory contingency. Statement of contribution what is already known on infants' sensorimotor knowledge about their own bodies 3-month-olds readily learn to produce specific limb movements to obtain a desired effect (movement of a mobile). infants detect temporal and spatial correspondences between events involving their own body and visual events. what the present study adds until 4-5 months of age, infants mostly produce general motor responses to localized touch. this is because in the present study, infants could not rely on immediate contingent feedback. we propose a cephalocaudal developmental trend of topographic differentiation of body areas.

What Is Morphological Computation? On How the Body Contributes to Cognition and Control.

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. We thus distinguish (1) morphology that facilitates control, (2) morphology that facilitates perception, and the rare cases of (3) morphological computation proper, such as reservoir computing, where the body is actually used for computation. This result contributes to the understanding of the relation between embodiment and computation: The question for robot design and cognitive science is not whether computation is offloaded to the body, but to what extent the body facilitates cognition and control-how it contributes to the overall orchestration of intelligent behavior.

Peripersonal Space and Margin of Safety around the Body: Learning Visuo-Tactile Associations in a Humanoid Robot with Artificial Skin.

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. More specifically, with respect to i) the present model contributes to hypothesizing a learning mechanisms for peripersonal space. In relation to point ii) we show how a relatively simple controller can exploit the learned receptive fields to generate either avoidance or reaching of an incoming stimulus and for iii) we show how the robot can select arbitrary body parts as the controlled end-point of an avoidance or reaching movement.