The role of kinematics in cortical regions for continuous human motion perception

The Role of Agentive and Physical Forces in the Neural Representation of Motion Events

How does the brain represent information about motion events in relation to agentive and physical forces? In this study, we investigated the neural activity patterns associated with observing animated actions of agents (e.g., an agent hitting a chair) in comparison to similar movements of inanimate objects that were either shaped solely by the physics of the scene (e.g., gravity causing an object to fall down a hill and hit a chair) or initiated by agents (e.g., a visible agent causing an object to hit a chair). Using an fMRI-based multivariate pattern analysis (MVPA), this design allowed testing where in the brain the neural activity patterns associated with motion events change as a function of, or are invariant to, agentive versus physical forces behind them. A total of 29 human participants (nine male) participated in the study. Cross-decoding revealed a shared neural representation of animate and inanimate motion events that is invariant to agentive or physical forces in regions spanning frontoparietal and posterior temporal cortices. In contrast, the right lateral occipitotemporal cortex showed a higher sensitivity to agentive events, while the left dorsal premotor cortex was more sensitive to information about inanimate object events that were solely shaped by the physics of the scene.

A computational neuroethology perspective on body and expression perception

Survival prompts organisms to prepare adaptive behavior in response to environmental and social threat. However, what are the specific features of the appearance of a conspecific that trigger such adaptive behaviors? For social species, the prime candidates for triggering defense systems are the visual features of the face and the body. We propose a novel approach for studying the ability of the brain to gather survival-relevant information from seeing conspecific body features. Specifically, we propose that behaviorally relevant information from bodies and body expressions is coded at the levels of midlevel features in the brain. These levels are relatively independent from higher-order cognitive and conscious perception of bodies and emotions. Instead, our approach is embedded in an ethological framework and mobilizes computational models for feature discovery.

Action Observation Responses Are Influenced by Movement Kinematics and Target Identity

In order to inform the debate whether cortical areas related to action observation provide a pragmatic or a semantic representation of goal-directed actions, we performed 2 functional magnetic resonance imaging (fMRI) experiments in humans. The first experiment, involving observation of aimless arm movements, resulted in activation of most of the components known to support action execution and action observation. Given the absence of a target/goal in this experiment and the activation of parieto-premotor cortical areas, which were associated in the past with direction, amplitude, and velocity of movement of biological effectors, our findings suggest that during action observation we could be monitoring movement kinematics. With the second, double dissociation fMRI experiment, we revealed the components of the observation-related cortical network affected by 1) actions that have the same target/goal but different reaching and grasping kinematics and 2) actions that have very similar kinematics but different targets/goals. We found that certain areas related to action observation, including the mirror neuron ones, are informed about movement kinematics and/or target identity, hence providing a pragmatic rather than a semantic representation of goal-directed actions. Overall, our findings support a process-driven simulation-like mechanism of action understanding, in agreement with the theory of motor cognition, and question motor theories of action concept processing.

Kinematic boundary cues modulate 12-month-old infants' segmentation of action sequences: An ERP study

Human infants can segment action sequences into their constituent actions already during the first year of life. However, work to date has almost exclusively examined the role of infants' conceptual knowledge of actions and their outcomes in driving this segmentation. The present study examined electrophysiological correlates of infants' processing of lower-level perceptual cues that signal a boundary between two actions of an action sequence. Specifically, we tested the effect of kinematic boundary cues (pre-boundary lengthening and pause) on 12-month-old infants' (N = 27) processing of a sequence of three arbitrary actions, performed by an animated figure. Using the Event-Related Potential (ERP) approach, evidence of a positivity following the onset of the boundary cues was found, in line with previous work that has found an ERP positivity (Closure Positive Shift, CPS) related to boundary processing in auditory stimuli and action sequences in adults. Moreover, an ERP negativity (Negative Central, Nc) indicated that infants' encoding of the post-boundary action was modulated by the presence or absence of prior boundary cues. We therefore conclude that 12-month-old infants are sensitive to lower-level perceptual kinematic boundary cues, which can support segmentation of a continuous stream of movement into individual action units.

Parallels in Processing Boundary Cues in Speech and Action

Speech and action sequences are continuous streams of information that can be segmented into sub-units. In both domains, this segmentation can be facilitated by perceptual cues contained within the information stream. In speech, prosodic cues (e.g., a pause, pre-boundary lengthening, and pitch rise) mark boundaries between words and phrases, while boundaries between actions of an action sequence can be marked by kinematic cues (e.g., a pause, pre-boundary deceleration). The processing of prosodic boundary cues evokes an Event-related Potentials (ERP) component known as the Closure Positive Shift (CPS), and it is possible that the CPS reflects domain-general cognitive processes involved in segmentation, given that the CPS is also evoked by boundaries between subunits of non-speech auditory stimuli. This study further probed the domain-generality of the CPS and its underlying processes by investigating electrophysiological correlates of the processing of boundary cues in sequences of spoken verbs (auditory stimuli; Experiment 1; N = 23 adults) and actions (visual stimuli; Experiment 2; N = 23 adults). The EEG data from both experiments revealed a CPS-like broadly distributed positivity during the 250 ms prior to the onset of the post-boundary word or action, indicating similar electrophysiological correlates of boundary processing across domains, suggesting that the cognitive processes underlying speech and action segmentation might also be shared.

Computational Feature Analysis of Body Movements Reveals Hierarchical Brain Organization

Social species spend considerable time observing the body movements of others to understand their actions, predict their emotions, watch their games, or enjoy their dance movements. Given the important information obtained from body movements, we still know surprisingly little about the details of brain mechanisms underlying movement perception. In this fMRI study, we investigated the relations between movement features obtained from automated computational analyses of video clips and the corresponding brain activity. Our results show that low-level computational features map to specific brain areas related to early visual- and motion-sensitive regions, while mid-level computational features are related to dynamic aspects of posture encoded in occipital–temporal cortex, posterior superior temporal sulcus and superior parietal lobe. Furthermore, behavioral features obtained from subjective ratings correlated with activity in higher action observation regions. Our computational feature-based analysis suggests that the neural mechanism of movement encoding is organized in the brain not so much by semantic categories than by feature statistics of the body movements.

Manifold Warp Segmentation of Human Action

Human action segmentation is important for human action analysis, which is a highly active research area. Most segmentation methods are based on clustering or numerical descriptors, which are only related to data, and consider no relationship between the data and physical characteristics of human actions. Physical characteristics of human motions are those that can be directly perceived by human beings, such as speed, acceleration, continuity, and so on, which are quite helpful in detecting human motion segment points. We propose a new physical-based descriptor of human action by curvature sequence warp space alignment (CSWSA) approach for sequence segmentation in this paper. Furthermore, time series-warp metric curvature segmentation method is constructed by the proposed descriptor and CSWSA. In our segmentation method, descriptor can express the changes of human actions, and CSWSA is an auxiliary method to give suggestions for segmentation. The experimental results show that our segmentation method is effective in both CMU human motion and video-based data sets.

Oscillations in the human brain during walking execution, imagination and observation

Gait is an essential human activity which organizes many functional and cognitive behaviors. The biomechanical constraints of bipedalism implicating a permanent control of balance during gait are taken into account by a complex dialog between the cortical, subcortical and spinal networks. This networking is largely based on oscillatory coding, including changes in spectral power and phase-locking of ongoing neural activity in theta, alpha, beta and gamma frequency bands. This coding is specifically modulated in actual gait execution and representation, as well as in contexts of gait observation or imagination. A main challenge in integrative neuroscience oscillatory activity analysis is to disentangle the brain oscillations devoted to gait control. In addition to neuroimaging approaches, which have highlighted the structural components of an extended network, dynamic high-density EEG gives non-invasive access to functioning of this network. Here we revisit the neurophysiological foundations of behavior-related EEG in the light of current neuropsychological theoretic frameworks. We review different EEG rhythms emerging in the most informative paradigms relating to human gait and implications for rehabilitation strategies.

From personal fear to mass panic: The neurological basis of crowd perception

Recent studies have investigated the neural correlates of how we perceive emotions of individuals or a group of individuals using images of individual bodily expressions. However, it is still largely unknown how we perceive the emotion of a dynamic crowd. This fMRI study used realistic videos of a large group of people expressing fearful, happy or neutral emotions. Furthermore, the emotions were expressed by either unrelated individuals in the group or by an interacting group. It was hypothesized that the dynamics between the people in a crowd is a more salient signal than merely the emotion of the crowd. Second, it was expected that the group interaction is of special importance in a fearful or "panic" situation, as opposed to a happy or neutral situation. Using a fast-event related design, it was revealed that observing interactive individuals, more so than independently expressive individuals, activated networks related to the perception, execution and integration of action and emotion. Most importantly, the interactive or panicked crowds, as opposed to the individually fearful crowds, triggered more anticipatory and action preparation activity, whereas the brain was less sensitive to the dynamics of individuals in a happy or neutral crowd. This is the first study to assess the effect of the dynamics between people and the collectively displayed emotion as an important aspect of emotional crowd perception.

Neural rhythmic symphony of human walking observation: Upside-down and Uncoordinated condition on cortical theta, alpha, beta and gamma oscillations

Biological motion observation has been recognized to produce dynamic change in sensorimotor activation according to the observed kinematics. Physical plausibility of the spatial-kinematic relationship of human movement may play a major role in the top-down processing of human motion recognition. Here, we investigated the time course of scalp activation during observation of human gait in order to extract and use it on future integrated brain-computer interface using virtual reality (VR). We analyzed event related potentials (ERP), the event related spectral perturbation (ERSP) and the inter-trial coherence (ITC) from high-density EEG recording during video display onset (−200–600 ms) and the steady state visual evoked potentials (SSVEP) inside the video of human walking 3D-animation in three conditions: Normal; Upside-down (inverted images); and Uncoordinated (pseudo-randomly mixed images). We found that early visual evoked response P120 was decreased in Upside-down condition. The N170 and P300b amplitudes were decreased in Uncoordinated condition. In Upside-down and Uncoordinated conditions, we found decreased alpha power and theta phase-locking. As regards gamma oscillation, power was increased during the Upside-down animation and decreased during the Uncoordinated animation. An SSVEP-like response oscillating at about 10 Hz was also described showing that the oscillating pattern is enhanced 300 ms after the heel strike event only in the Normal but not in the Upside-down condition. Our results are consistent with most of previous point-light display studies, further supporting possible use of virtual reality for neurofeedback applications.