Antonino Casile

Nonvisual Motor Training Influences Biological Motion Perception

Experimental evidence suggests a link between perception and the execution of actions . In particular, it has been proposed that motor programs might directly influence visual action perception . According to this hypothesis, the acquisition of novel motor behaviors should improve their visual recognition, even in the absence of visual learning. We tested this prediction by using a new experimental paradigm that dissociates visual and motor learning during the acquisition of novel motor patterns. The visual recognition of gait patterns from point-light stimuli was assessed before and after nonvisual motor training. During this training, subjects were blindfolded and learned a novel coordinated upper-body movement based only on verbal and haptic feedback. The learned movement matched one of the visual test patterns. Despite the absence of visual stimulation during training, we observed a selective improvement of the visual recognition performance for the learned movement. Furthermore, visual recognition performance after training correlated strongly with the accuracy of the execution of the learned motor pattern. These results prove, for the first time, that motor learning has a direct and highly selective influence on visual action recognition that is not mediated by visual learning.

Mirror Neurons Differentially Encode the Peripersonal and Extrapersonal Space of Monkeys

Actions performed by others may have different relevance for the observer, and thus lead to different behavioral responses, depending on the regions of space in which they are executed. We found that in rhesus monkeys, the premotor cortex neurons activated by both the execution and the observation of motor acts (mirror neurons) are differentially modulated by the location in space of the observed motor acts relative to the monkey, with about half of them preferring either the monkeys peripersonal or extrapersonal space. A portion of these spatially selective mirror neurons encode space according to a metric representation, whereas other neurons encode space in operational terms, changing their properties according to the possibility that the monkey will interact with the object. These results suggest that a set of mirror neurons encodes the observed motor acts not only for action understanding, but also to analyze such acts in terms of features that are relevant to generating appropriate behaviors.

Critical features for the recognition of biological motion

Humans can perceive the motion of living beings from very impoverished stimuli like point-light displays. How the visual system achieves the robust generalization from normal to point-light stimuli remains an unresolved question. We present evidence on multiple levels demonstrating that this generalization might be accomplished by an extraction of simple mid-level optic flow features within coarse spatial arrangement, potentially exploiting relatively simple neural circuits: (1) A statistical analysis of the most informative mid-level features reveals that normal and point-light walkers share very similar dominant local optic flow features. (2) We devise a novel point-light stimulus (critical features stimulus) that contains these features, and which is perceived as a human walker even though it is inconsistent with the skeleton of the human body. (3) A neural model that extracts only these critical features accounts for substantial recognition rates for strongly degraded stimuli. We conclude that recognition of biological motion might be accomplished by detecting mid-level optic flow features with relatively coarse spatial localization. The computationally challenging reconstruction of precise position information from degraded stimuli might not be required.

Predicting point-light actions in real-time

There is convincing evidence for a mirror system in humans which simulates actions of conspecifics. One possible purpose of such a simulation system is to support action prediction in real-time. Our goal was to study whether the prediction of actions involves a real-time simulation process. We motion-captured a number of human actions and rendered them as point-light action sequences. Observers perceived brief videos of these actions, followed by an occluder and a static test posture. We independently varied the occluder time and the movement gap (i.e., the time between the endpoint of the action and the test posture). Observers were required to judge whether the test stimulus depicted a continuation of the action in the same depth orientation. Prediction performance was best when occluder time and movement gap corresponded, i.e., when the test posture was a continuation of the sequence that matched the occluder duration (Experiments 1, 2 and 4). This pattern of results was destroyed when the sequences and test images were flipped around the horizontal axis (Experiment 3). Overall, our findings suggest that action prediction involves a simulation process that operates in real-time. This process can break down when the actions are presented under viewing conditions for which observers have little experience.

Neural representations of kinematic laws of motion: Evidence for action-perception coupling

Behavioral and modeling studies have established that curved and drawing human hand movements obey the 2/3 power law, which dictates a strong coupling between movement curvature and velocity. Human motion perception seems to reflect this constraint. The functional MRI study reported here demonstrates that the brains response to this law of motion is much stronger and more widespread than to other types of motion. Compliance with this law is reflected in the activation of a large network of brain areas subserving motor production, visual motion processing, and action observation functions. Hence, these results strongly support the notion of similar neural coding for motion perception and production. These findings suggest that cortical motion representations are optimally tuned to the kinematic and geometrical invariants characterizing biological actions.

The Mirror Neuron System A Fresh View

Mirror neurons are a class of visuomotor neurons in the monkey premotor and parietal cortices that discharge during the execution and observation of goal-directed motor acts. They are deemed to be at the basis of primates’ social abilities. In this review, the authors provide a fresh view about two still open questions about mirror neurons. The first question is their possible functional role. By reviewing recent neurophysiological data, the authors suggest that mirror neurons might represent a flexible system that encodes observed actions in terms of several behaviorally relevant features. The second question concerns the possible developmental mechanisms responsible for their initial emergence. To provide a possible answer to question, the authors review two different aspects of sensorimotor development: facial and hand movements, respectively. The authors suggest that possibly two different “mirror” systems might underlie the development of action understanding and imitative abilities in the two cases. More specifically, a possibly prewired system already present at birth but shaped by the social environment might underlie the early development of facial imitative abilities. On the contrary, an experience-dependent system might subserve perception-action couplings in the case of hand movements. The development of this latter system might be critically dependent on the observation of own movements.

Neuronal Encoding of Human Kinematic Invariants during Action Observation

Human movements, besides entailing the presence of a body shape, comply with characteristic kinematic laws of motion. Psychophysical studies show that low-level motion perception is biased toward stimuli complying with these laws. However, the neuronal structures that are sensitive to the kinematic laws of observed bodily movements are still largely unknown. We investigated this issue by dissociating, by means of computer-generated characters, form and motion information during the observation of human movements. In a functional imaging experiment, we compared the levels of blood oxygen level-dependent activity elicited by human actions complying with or violating the kinematic laws of human movements. Actions complying with normal kinematic laws of motion differentially activated the left dorsal premotor and dorsolateral prefrontal cortex as well as the medial frontal cortex. These findings suggest that the kinematic laws of human movements specifically modulate the responses of neuronal circuits also involved in action recognition and that are predominantly located in the left frontal lobe.

Mirror neurons encode the subjective value of an observed action

Objects grasped by an agent have a value not only for the acting agent, but also for an individual observing the grasping act. The value that the observer attributes to the object that is grasped can be pivotal for selecting a possible behavioral response. Mirror neurons in area F5 of the monkey premotor cortex have been suggested to play a crucial role in the understanding of action goals. However, it has not been addressed if these neurons are also involved in representing the value of the grasped object. Here we report that observation-related neuronal responses of F5 mirror neurons are indeed modulated by the value that the monkey associates with the grasped object. These findings suggest that during action observation F5 mirror neurons have access to key information needed to shape the behavioral responses of the observer.

Fixational instability and natural image statistics: Implications for early visual representations

Under natural viewing conditions, small movements of the eye, head and body prevent the maintenance of a steady direction of gaze. It is known that stimuli tend to fade when they are stabilized on the retina for several seconds. However, it is unclear whether the physiological motion of the retinal image serves a visual purpose during the brief periods of natural visual fixation. This study examines the impact of fixational instability on the statistics of the visual input to the retina and on the structure of neural activity in the early visual system. We show that fixational instability introduces a component in the retinal input signals that, in the presence of natural images, lacks spatial correlations. This component strongly influences neural activity in a model of the LGN. It decorrelates cell responses even if the contrast sensitivity functions of simulated cells are not perfectly tuned to counter-balance the power-law spectrum of natural images. A decorrelation of neural activity at the early stages of the visual system has been proposed to be beneficial for discarding statistical redundancies in the input signals. The results of this study suggest that fixational instability might contribute to the establishment of efficient representations of natural stimuli.

Decorrelation of neural activity during fixational instability: Possible implications for the refinement of V1 receptive fields

Early in life, visual experience appears to influence the refinement and maintenance of the orientation-selective responses of neurons in the primary visual cortex. After eye opening, the statistical structure of visually driven neural responses depends not only on the stimulus, but also on how the stimulus is scanned during behavior. Modulations of neural activity due to behavior may thus play a role in the experience-dependent refinement of cell response characteristics. To investigate the possible influences of eye movements on the maturation of thalamocortical connectivity, we have simulated the responses of neuronal populations in the lateral geniculate nucleus (LGN) and V1 of the cat while images of natural scenes were scanned in a way that replicated the cats oculomotor activity. In the model, fixational eye movements were essential to attenuate neural sensitivity to the broad correlational structure of natural visual input, decorrelate neural responses, and establish a regime of neural activity that was compatible with a Hebbian segregation of geniculate afferents to the cortex. We show that this result is highly robust and does not depend on the precise characteristics of the model.