Action observation and robotic agents: learning and anthropomorphism

The ‘action observation network’ (AON), which is thought to translate observed actions into motor codes required for their execution, is biologically tuned: it responds more to observation of human, than non-human, movement. This biological specificity has been taken to support the hypothesis that the AON underlies various social functions, such as theory of mind and action understanding, and that, when it is active during observation of non-human agents like humanoid robots, it is a sign of ascription of human mental states to these agents. This review will outline evidence for biological tuning in the AON, examining the features which generate it, and concluding that there is evidence for tuning to both the form and kinematic profile of observed movements, and little evidence for tuning to belief about stimulus identity. It will propose that a likely reason for biological tuning is that human actions, relative to non-biological movements, have been observed more frequently while executing corresponding actions. If the associative hypothesis of the AON is correct, and the network indeed supports social functioning, sensorimotor experience with non-human agents may help us to predict, and therefore interpret, their movements.

Effects of action observation on corticospinal excitability: muscle specificity, direction, and timing of the mirror response

Many human behaviours and pathologies have been attributed to the putative mirror neuron system, a neural system that is active during both the observation and execution of actions. While there are now a very large number of papers on the mirror neuron system, variations in the methods and analyses employed by researchers mean that the basic characteristics of the mirror response are not clear. This review focuses on three important aspects of the mirror response, as measured by modulations in corticospinal excitability: (1) muscle specificity, (2) direction, and (3) timing of modulation. We focus mainly on electromyographic (EMG) data gathered following single-pulse transcranial magnetic stimulation (TMS), because this method provides precise information regarding these three aspects of the response. Data from paired-pulse TMS paradigms and peripheral nerve stimulation (PNS) are also considered when we discuss the possible mechanisms underlying the mirror response. In this systematic review of the literature, we examine the findings of 85 TMS and PNS studies of the human mirror response, and consider the limitations and advantages of the different methodological approaches these have adopted in relation to discrepancies between their findings. We conclude by proposing a testable model of how action observation modulates corticospinal excitability in humans. Specifically, we propose that action observation elicits an early, non-specific facilitation of corticospinal excitability (at around 90 ms from action onset), followed by a later modulation of activity specific to the muscles involved in the observed action (from around 200 ms). Testing this model will greatly advance our understanding of the mirror mechanism and provide a more stable grounding on which to base inferences about its role in human behaviour.

Measuring the effects of manipulating stimulus presentation time on sensorimotor alpha and low beta reactivity during hand movement observation

The present study addresses three methodological questions that have been ignored in previous research on EEG indices of the human mirror neuron system (hMNS), particularly in regard to autistic individuals. The first question regards how to elicit the EEG indexed hMNS during movement observation: Is hMNS activation best elicited using long stimulus presentations or multiple short repetitions? The second question regards what EEG sensorimotor frequency bands reflect sensorimotor reactivity during hand movement observation? The third question regards how widespread is the EEG reactivity over the sensorimotor cortex during movement observation? The present study explored sensorimotor alpha and low beta reactivity during hand movement versus static hand or bouncing balls observation and compared two experimental protocols (long exposure vs. multiple repetitions) in the same participants. Results using the multiple repetitions protocol indicated a greater low beta desynchronisation over the sensorimotor cortex during hand movement compared to static hand and bouncing balls observation. This result was not achieved using the long exposure protocol. Therefore, the present study suggests that the multiple repetitions protocol is a more robust protocol to use when exploring the sensorimotor reactivity induced by hand action observation. In addition, sensorimotor low beta desynchronisation was differently modulated during hand movement, static hand and bouncing balls observation (non-biological motion) while it was not the case for sensorimotor alpha and that suggest that low beta may be a more sensitive index of hMNS activation during biological motion observation. In conclusion the present study indicates that sensorimotor reactivity of low beta during hand movement observation was found to be more widespread over the sensorimotor cortex than previously thought.

Dynamic modulation of human motor activity when observing actions

Previous studies have demonstrated that when we observe somebody else executing an action many areas of our own motor systems are active. It has been argued that these motor activations are evidence that we motorically simulate observed actions; this motoric simulation may support various functions such as imitation and action understanding. However, whether motoric simulation is indeed the function of motor activations during action observation is controversial, due to inconsistency in findings. Previous studies have demonstrated dynamic modulations in motor activity when we execute actions. Therefore, if we do motorically simulate observed actions, our motor systems should also be modulated dynamically, and in a corresponding fashion, during action observation. Using magnetoencephalography (MEG), we recorded the cortical activity of human participants while they observed actions performed by another person. Here, we show that activity in the human motor system is indeed modulated dynamically during action observation. The finding that activity in the motor system is modulated dynamically when observing actions can explain why studies of action observation using functional magnetic resonance imaging (fMRI) have reported conflicting results, and is consistent with the hypothesis that we motorically simulate observed actions.

EEG activation differences in the pre-motor cortex and supplementary motor area between normal individuals with high and low traits of autism

The human mirror neuron system (hMNS) is believed to provide a basic mechanism for social cognition. Event-related desynchronization (ERD) in alpha (8–12 Hz) and low beta band (12–20 Hz) over sensori-motor cortex has been suggested to index mirror neurons' activity. We tested whether autistic traits revealed by high and low scores on the Autistic Quotient (AQ) in the normal population are linked to variations in the electroencephalogram (EEG) over motor, pre-motor cortex and supplementary motor area (SMA) during action observation. Results revealed that in the low AQ group, the pre-motor cortex and SMA were more active during hand action than static hand observation whereas in the high AQ group the same areas were active both during static and hand action observation. In fact participants with high traits of autism showed greater low beta ERD while observing the static hand than those with low traits and this low beta ERD was not significantly different when they watched hand actions. Over primary motor cortex, the classical alpha and low beta ERD during hand actions relative to static hand observation was found across all participants. These findings suggest that the observation–execution matching system works differently according to the degree of autism traits in the normal population and that this is differentiated in terms of the EEG according to scalp site and bandwidth.

Reduced cortico-motor facilitation in a normal sample with high traits of autism

Recent research in social neuroscience proposes a link between mirror neuron system (MNS) and social cognition. The MNS has been proposed to be the neural mechanism underlying action recognition and intention understanding and more broadly social cognition. Pre-motor MNS has been suggested to modulate the motor cortex during action observation. This modulation results in an enhanced cortico-motor excitability reflected in increased motor evoked potentials (MEPs) at the muscle of interest during action observation. Anomalous MNS activity has been reported in the autistic population whose social skills are notably impaired. It is still an open question whether traits of autism in the normal population are linked to the MNS functioning. We measured TMS-induced MEPs in normal individuals with high and low traits of autism as measured by the autistic quotient (AQ), while observing videos of hand or mouth actions, static images of a hand or mouth or a blank screen. No differences were observed between the two while they observed a blank screen. However participants with low traits of autism showed significantly greater MEP amplitudes during observation of hand/mouth actions relative to static hand/mouth stimuli. In contrast, participants with high traits of autism did not show such a MEP amplitude difference between observation of actions and static stimuli. These results are discussed with reference to MNS functioning.

Identifying and understanding factors influencing the uptake of new technologies on dairy farms in SW England using the theory of reasoned action

Whilst much is known of new technology adopters, little research has addressed the role of their attitudes in adoption decisions; particularly, for technologies with evident economic potential that have not been taken up by farmers. This paper presents recent research that has used a new approach which examines the role that adopters' attitudes play in identifying the drivers of and barriers to adoption. The study was concerned with technologies for livestock farming systems in SW England, specifically oestrus detection, nitrogen supply management, and, inclusion of white clover. The adoption behaviour is analysed using the social-psychology theory of reasoned action to identify factors that affect the adoption of technologies, which are confirmed using principal components analysis. The results presented here relate to the specific adoption behaviour regarding the Milk Development Council's recommended observation times for heat detection. The factors that affect the adoption of this technology are: cost effectiveness, improved detection and conception rates as the main drivers, whilst the threat to demean the personal knowledge and skills of a farmer in 'knowing' their cows is a barrier. This research shows clearly that promotion of a technology and transfer of knowledge for a farming system need to take account of the beliefs and attitudes of potential adopters. (C) 2006 Elsevier Ltd. All rights reserved.

Action following the discovery of a global association between the whole genome and adverse event risk in a clinical drug-development programme

Observation of adverse drug reactions during drug development can cause closure of the whole programme. However, if association between the genotype and the risk of an adverse event is discovered, then it might suffice to exclude patients of certain genotypes from future recruitment. Various sequential and non-sequential procedures are available to identify an association between the whole genome, or at least a portion of it, and the incidence of adverse events. In this paper we start with a suspected association between the genotype and the risk of an adverse event and suppose that the genetic subgroups with elevated risk can be identified. Our focus is determination of whether the patients identified as being at risk should be excluded from further studies of the drug. We propose using a utility function to? determine the appropriate action, taking into account the relative costs of suffering an adverse reaction and of failing to alleviate the patient's disease. Two illustrative examples are presented, one comparing patients who suffer from an adverse event with contemporary patients who do not, and the other making use of a reference control group. We also illustrate two classification methods, LASSO and CART, for identifying patients at risk, but we stress that any appropriate classification method could be used in conjunction with the proposed utility function. Our emphasis is on determining the action to take rather than on providing definitive evidence of an association. Copyright (C) 2008 John Wiley & Sons, Ltd.

Sensorimotor experience enhances automatic imitation of robotic action

Recent research in cognitive neuroscience has found that observation of human actions activates the ‘mirror system’ and provokes automatic imitation to a greater extent than observation of non-biological movements. The present study investigated whether this human bias depends primarily on phylogenetic or ontogenetic factors by examining the effects of sensorimotor experience on automatic imitation of non-biological robotic, stimuli. Automatic imitation of human and robotic action stimuli was assessed before and after training. During these test sessions, participants were required to execute a pre-specified response (e.g. to open their hand) while observing a human or robotic hand making a compatible (opening) or incompatible (closing) movement. During training, participants executed opening and closing hand actions while observing compatible (group CT) or incompatible movements (group IT) of a robotic hand. Compatible, but not incompatible, training increased automatic imitation of robotic stimuli (speed of responding on compatible trials, compared with incompatible trials) and abolished the human bias observed at pre-test. These findings suggest that the development of the mirror system depends on sensorimotor experience, and that, in our species, it is biased in favour of human action stimuli because these are more abundant than non-biological action stimuli in typical developmental environments.

Measures of observation impact in non-Gaussian data assimilation

ABSTRACT Non-Gaussian/non-linear data assimilation is becoming an increasingly important area of research in the Geosciences as the resolution and non-linearity of models are increased and more and more non-linear observation operators are being used. In this study, we look at the effect of relaxing the assumption of a Gaussian prior on the impact of observations within the data assimilation system. Three different measures of observation impact are studied: the sensitivity of the posterior mean to the observations, mutual information and relative entropy. The sensitivity of the posterior mean is derived analytically when the prior is modelled by a simplified Gaussian mixture and the observation errors are Gaussian. It is found that the sensitivity is a strong function of the value of the observation and proportional to the posterior variance. Similarly, relative entropy is found to be a strong function of the value of the observation. However, the errors in estimating these two measures using a Gaussian approximation to the prior can differ significantly. This hampers conclusions about the effect of the non-Gaussian prior on observation impact. Mutual information does not depend on the value of the observation and is seen to be close to its Gaussian approximation. These findings are illustrated with the particle filter applied to the Lorenz ’63 system. This article is concluded with a discussion of the appropriateness of these measures of observation impact for different situations.

Adjuvant chemotherapy in older women (ACTION) study - what did we learn from the pilot phase?

Despite widespread support at several public meetings, input from patient groups including representation on the Trial Management Group, the trial failed to recruit due to the inability to convince patients to accept randomisation. It would therefore seem that randomising the patients to receive chemotherapy vs observation is not a viable design in the current era for this patient population.

CLSM method for the dynamic observation of pH change within polymer matrices for oral delivery

If acid-sensitive drugs or cells are administered orally, there is often a reduction in efficacy associated with gastric passage. Formulation into a polymer matrix is a potential method to improve their stability. The visualization of pH within these materials may help better understand the action of these polymer systems and allow comparison of different formulations. We herein describe the development of a novel confocal laser-scanning microscopy (CLSM) method for visualizing pH changes within polymer matrices and demonstrate its applicability to an enteric formulation based on chitosan-coated alginate gels. The system in question is first shown to protect an acid-sensitive bacterial strain to low pH, before being studied by our technique. Prior to this study, it has been claimed that protection by these materials is a result of buffering, but this has not been demonstrated. The visualization of pH within these matrices during exposure to a pH 2.0 simulated gastric solution showed an encroachment of acid from the periphery of the capsule, and a persistence of pHs above 2.0 within the matrix. This implies that the protective effect of the alginate-chitosan matrices is most likely due to a combination of buffering of acid as it enters the polymer matrix and the slowing of acid penetration.

Data assimilation with correlated observation errors: experiments with a 1-D shallow water model

Remote sensing observations often have correlated errors, but the correlations are typically ignored in data assimilation for numerical weather prediction. The assumption of zero correlations is often used with data thinning methods, resulting in a loss of information. As operational centres move towards higher-resolution forecasting, there is a requirement to retain data providing detail on appropriate scales. Thus an alternative approach to dealing with observation error correlations is needed. In this article, we consider several approaches to approximating observation error correlation matrices: diagonal approximations, eigendecomposition approximations and Markov matrices. These approximations are applied in incremental variational assimilation experiments with a 1-D shallow water model using synthetic observations. Our experiments quantify analysis accuracy in comparison with a reference or ‘truth’ trajectory, as well as with analyses using the ‘true’ observation error covariance matrix. We show that it is often better to include an approximate correlation structure in the observation error covariance matrix than to incorrectly assume error independence. Furthermore, by choosing a suitable matrix approximation, it is feasible and computationally cheap to include error correlation structure in a variational data assimilation algorithm.

Observation impact in data assimilation: the effect of non-Gaussian observation error.

Data assimilation methods which avoid the assumption of Gaussian error statistics are being developed for geoscience applications. We investigate how the relaxation of the Gaussian assumption affects the impact observations have within the assimilation process. The effect of non-Gaussian observation error (described by the likelihood) is compared to previously published work studying the effect of a non-Gaussian prior. The observation impact is measured in three ways: the sensitivity of the analysis to the observations, the mutual information, and the relative entropy. These three measures have all been studied in the case of Gaussian data assimilation and, in this case, have a known analytical form. It is shown that the analysis sensitivity can also be derived analytically when at least one of the prior or likelihood is Gaussian. This derivation shows an interesting asymmetry in the relationship between analysis sensitivity and analysis error covariance when the two different sources of non-Gaussian structure are considered (likelihood vs. prior). This is illustrated for a simple scalar case and used to infer the effect of the non-Gaussian structure on mutual information and relative entropy, which are more natural choices of metric in non-Gaussian data assimilation. It is concluded that approximating non-Gaussian error distributions as Gaussian can give significantly erroneous estimates of observation impact. The degree of the error depends not only on the nature of the non-Gaussian structure, but also on the metric used to measure the observation impact and the source of the non-Gaussian structure.