Spatiotemporal dynamics in understanding hand-object interactions

Photographs of Actions: What Makes Them Special Cues to Social Perception

I have reviewed studies on neural responses to pictured actions in the action observation network (AON) and the cognitive functions of these responses. Based on this review, I have analyzed the specific representational characteristics of action photographs. There has been consensus that AON responses provide viewers with knowledge of observed or pictured actions, but there has been controversy about the properties of this knowledge. Is this knowledge causally provided by AON activities or is it dependent on conceptual processing? What elements of actions does it refer to, and how generalized or specific is it? The answers to these questions have come from studies that used transcranial magnetic stimulation (TMS) to stimulate motor or somatosensory cortices. In conjunction with electromyography (EMG), TMS allows researchers to examine changes of the excitability in the corticospinal tract and muscles of people viewing pictured actions. The timing of these changes and muscle specificity enable inferences to be drawn about the cognitive products of processing pictured actions in the AON. Based on a review of studies using TMS and other neuroscience methods, I have proposed a novel hypothetical account that describes the characteristics of action photographs that make them effective cues to social perception. This account includes predictions that can be tested experimentally.

Perspective-dependent activation of frontoparietal circuits during the observation of a static body effector

The perspective from which body-related stimuli are observed plays a fundamental role in modulating cerebral activity during the processing of others' bodies and actions. Previous research has shown perspective-dependent cerebral responses during the observation of both ongoing actions and static images of an acting body with implied motion information, with an advantage for the egocentric viewpoint. The present high-density EEG study assessed event-related potentials triggered by the presentation of a forearm at rest before reach-to-grasp actions, shown from four different viewpoints. Through a spatiotemporal analysis of the scalp electric field and the localization of cortical generators, our study revealed overall different processing for the third-person perspective relative to other viewpoints, mainly due to a later activation of motor-premotor regions. Since observing a static body effector often precedes action observation, our results integrate previous evidence of perspective-dependent encoding, with cascade implications on the design of neurorehabilitative or motor learning interventions based on action observation.

Neural dynamics of grip and goal integration during the processing of others' actions with objects: An ERP study

Recent behavioural evidence suggests that when processing others’ actions, motor acts and goal-related information both contribute to action recognition. Yet the neuronal mechanisms underlying the dynamic integration of the two action dimensions remain unclear. This study aims to elucidate the ERP components underlying the processing and integration of grip and goal-related information. The electrophysiological activity of 28 adults was recorded during the processing of object-directed action photographs (e.g., writing with pencil) containing either grip violations (e.g. upright pencil grasped with atypical-grip), goal violations (e.g., upside-down pencil grasped with typical-grip), both grip and goal violations (e.g., upside-down pencil grasped with atypical-grip), or no violations. Participants judged whether actions were overall typical or not according to object typical use. Brain activity was sensitive to the congruency between grip and goal information on the N400, reflecting the semantic integration between the two dimensions. On earlier components, brain activity was affected by grip and goal typicality independently. Critically, goal typicality but not grip typicality affected brain activity on the N300, supporting an earlier role of goal-related representations in action recognition. Findings provide new insights on the neural temporal dynamics of the integration of motor acts and goal-related information during the processing of others’ actions.

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.

Fish do not feel pain and its implications for understanding phenomenal consciousness

Phenomenal consciousness or the subjective experience of feeling sensory stimuli is fundamental to human existence. Because of the ubiquity of their subjective experiences, humans seem to readily accept the anthropomorphic extension of these mental states to other animals. Humans will typically extrapolate feelings of pain to animals if they respond physiologically and behaviourally to noxious stimuli. The alternative view that fish instead respond to noxious stimuli reflexly and with a limited behavioural repertoire is defended within the context of our current understanding of the neuroanatomy and neurophysiology of mental states. Consequently, a set of fundamental properties of neural tissue necessary for feeling pain or experiencing affective states in vertebrates is proposed. While mammals and birds possess the prerequisite neural architecture for phenomenal consciousness, it is concluded that fish lack these essential characteristics and hence do not feel pain.

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.

Head model and electrical source imaging: a study of 38 epileptic patients

Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from scalp EEG. When applied to interictal epileptiform discharges (IEDs), this technique is of great use for identifying the irritative zone in focal epilepsies. Inaccuracies in the modeling of electro-magnetic field propagation in the head (forward model) may strongly influence ESI and lead to mislocalization of IED generators. However, a systematic study on the influence of the selected head model on the localization precision of IED in a large number of patients with known focus localization has not yet been performed. We here present such a performance evaluation of different head models in a dataset of 38 epileptic patients who have undergone high-density scalp EEG, intracranial EEG and, for the majority, subsequent surgery. We compared ESI accuracy resulting from three head models: a Locally Spherical Model with Anatomical Constraints (LSMAC), a Boundary Element Model (BEM) and a Finite Element Model (FEM). All of them were computed from the individual MRI of the patient and ESI was performed on averaged IED. We found that all head models provided very similar source locations. In patients having a positive post-operative outcome, at least 74% of the source maxima were within the resection. The median distance from the source maximum to the nearest intracranial electrode showing IED was 13.2, 15.6 and 15.6 mm for LSMAC, BEM and FEM, respectively. The study demonstrates that in clinical applications, the use of highly sophisticated and difficult to implement head models is not a crucial factor for an accurate ESI.