Decoding intention: a neuroergonomic perspective

Configuration of the action observation network depends on the goals of the observer

Observing the actions of others engages a core action observation network (AON) that includes the bilateral inferior frontal cortex (IFC), posterior superior temporal sulcus (pSTS) and inferior parietal lobule (IPL) (Caspers et al., 2010). Each region in the AON has functional properties that are heterogeneous and include representing the perceptual properties of action, predicting action outcomes and making inferences as to the goals of the actor. Critically, recent evidence shows that neural representations within the pSTS are sharpened when attending to the kinematics of the actor, such that the top-down guided attention reshapes underlying neural representations. In this study we evaluate how attention alters network connectivity within the AON as a system. Cues directed participant's attention to the goal, kinematics, or identity depicted in short action animations while brain responses were measured by fMRI. We identified those parcels within the AON with functional connectivity modulated by task. Results show that connectivity between the right pSTS and right IFC, and bilateral extended STS (STS+) were modulated during action observation such that connections were strengthened when the participant was attending to the action than goal. This finding is contrasted by the univariate results, which no univariate modulations in these brain regions except for right IFC. Using the functional networks defined by Yeo et al. (2011), we identified the parcels that are modulated by the attention to consist mainly of the fronto-parietal control network and default mode networks. These results are consistent with models of top-down feedback from executive system in the IFC to pSTS and implicates a right lateralized dual pathway model for action observation when focused on whole-body kinematics.

Body Form Modulates the Prediction of Human and Artificial Behaviour from Gaze Observation

The future of human–robot collaboration relies on people’s ability to understand and predict robots' actions. The machine-like appearance of robots, as well as contextual information, may influence people’s ability to anticipate the behaviour of robots. We conducted six separate experiments to investigate how spatial cues and task instructions modulate people’s ability to understand what a robot is doing. Participants observed goal-directed and non-goal directed gaze shifts made by human and robot agents, as well as directional cues displayed by a triangle. We report that biasing an observer's attention, by showing just one object an agent can interact with, can improve people’s ability to understand what humanoid robots will do. Crucially, this cue had no impact on people’s ability to predict the upcoming behaviour of the triangle. Moreover, task instructions that focus on the visual and motor consequences of the observed gaze were found to influence mentalising abilities. We suggest that the human-like shape of an agent and its physical capabilities facilitate the prediction of an upcoming action. The reported findings expand current models of gaze perception and may have important implications for human–human and human–robot collaboration.

Neuroergonomy: An Engagement between Work Psychology and Neurosciences

This article aims to identify the importance of markers at the neurophysiological, physiological, and behavioral levels of mental states linked to the performance of workers as an influence in the field of neuroscience and psychology at work. The author discusses the emergence of neuroergonomy as an area of neuroscience principles and cognitive psychology related to human factors for fundamentals of analysis in brain dynamics, mainly through the use of noninvasive tools, such as the use of electroencephalography for physiological aspects of mental exhaustion of the worker. Neuroergonomics is seen as fundamental for the investigation of complex relationships of organizations, especially when interacting with technology. Future research should involve more complex team-building scenarios and enrich the different neuroergonomic solutions.

Age-congruency and contact effects in body expression recognition from point-light displays (PLD)

Recognition of older people’s body expressions is a crucial social skill. We here investigate how age, not just of the observer, but also of the observed individual, affects this skill. Age may influence the ability to recognize other people’s body expressions by changes in one’s own ability to perform certain action over the life-span (i.e., an own-age bias may occur, with best recognition for one’s own age). Whole body point light displays of children, young adults and older adults (>70 years) expressing six different emotions were presented to observers of the same three age-groups. Across two variations of the paradigm, no evidence for the predicted own-age bias (a cross-over interaction between one’s own age and the observed person’s age) was found. Instead, experience effects were found with children better recognizing older actors’ expressions of ‘active emotions,’ such as anger and happiness with greater exposure in daily life. Together, the findings suggest that age-related changes in one own’s mobility only influences body expression categorization in young children who interact frequently with older adults.

Body language in the brain: constructing meaning from expressive movement

This fMRI study investigated neural systems that interpret body language-the meaningful emotive expressions conveyed by body movement. Participants watched videos of performers engaged in modern dance or pantomime that conveyed specific themes such as hope, agony, lust, or exhaustion. We tested whether the meaning of an affectively laden performance was decoded in localized brain substrates as a distinct property of action separable from other superficial features, such as choreography, kinematics, performer, and low-level visual stimuli. A repetition suppression (RS) procedure was used to identify brain regions that decoded the meaningful affective state of a performer, as evidenced by decreased activity when emotive themes were repeated in successive performances. Because the theme was the only feature repeated across video clips that were otherwise entirely different, the occurrence of RS identified brain substrates that differentially coded the specific meaning of expressive performances. RS was observed bilaterally, extending anteriorly along middle and superior temporal gyri into temporal pole, medially into insula, rostrally into inferior orbitofrontal cortex, and caudally into hippocampus and amygdala. Behavioral data on a separate task indicated that interpreting themes from modern dance was more difficult than interpreting pantomime; a result that was also reflected in the fMRI data. There was greater RS in left hemisphere, suggesting that the more abstract metaphors used to express themes in dance compared to pantomime posed a greater challenge to brain substrates directly involved in decoding those themes. We propose that the meaning-sensitive temporal-orbitofrontal regions observed here comprise a superordinate functional module of a known hierarchical action observation network (AON), which is critical to the construction of meaning from expressive movement. The findings are discussed with respect to a predictive coding model of action understanding.

The contribution of brain sub-cortical loops in the expression and acquisition of action understanding abilities

•

Focusing on cortical areas is too restrictive to explain action understanding ability.

•

We propose that sub-cortical areas support action understanding ability.

•

Cortical and sub-cortical processes allow acquisition of action understanding ability.

Research on action understanding in cognitive neuroscience has led to the identification of a wide “action understanding network” mainly encompassing parietal and premotor cortical areas. Within this cortical network mirror neurons are critically involved implementing a neural mechanism according to which, during action understanding, observed actions are reflected in the motor patterns for the same actions of the observer. We suggest that focusing only on cortical areas and processes could be too restrictive to explain important facets of action understanding regarding, for example, the influence of the observer's motor experience, the multiple levels at which an observed action can be understood, and the acquisition of action understanding ability. In this respect, we propose that aside from the cortical action understanding network, sub-cortical processes pivoting on cerebellar and basal ganglia cortical loops could crucially support both the expression and the acquisition of action understanding abilities. Within the paper we will discuss how this extended view can overcome some limitations of the “pure” cortical perspective, supporting new theoretical predictions on the brain mechanisms underlying action understanding that could be tested by future empirical investigations.

Sensing, assessing, and augmenting threat detection: behavioral, neuroimaging, and brain stimulation evidence for the critical role of attention

Rapidly identifying the potentially threatening movements of other people and objects—biological motion perception and action understanding—is critical to maintaining security in many civilian and military settings. A key approach to improving threat detection in these environments is to sense when less than ideal conditions exist for the human observer, assess that condition relative to an expected standard, and if necessary use tools to augment human performance. Action perception is typically viewed as a relatively “primitive,” automatic function immune to top-down effects. However, recent research shows that attention is a top-down factor that has a critical influence on the identification of threat-related targets. In this paper we show that detection of motion-based threats is attention sensitive when surveillance images are obscured by other movements, when they are visually degraded, when other stimuli or tasks compete for attention, or when low-probability threats must be watched for over long periods of time—all features typical of operational security settings. Neuroimaging studies reveal that action understanding recruits a distributed network of brain regions, including the superior temporal cortex, intraparietal cortex, and inferior frontal cortex. Within this network, attention modulates activation of the superior temporal sulcus (STS) and middle temporal gyrus. The dorsal frontoparietal network may provide the source of attention-modulation signals to action representation areas. Stimulation of this attention network should therefore enhance threat detection. We show that transcranial Direct Current Stimulation (tDCS) at 2 mA accelerates perceptual learning of participants performing a challenging threat-detection task. Together, cognitive, neuroimaging, and brain stimulation studies provide converging evidence for the critical role of attention in the detection and understanding of threat-related intentional actions.

Controlling Assistive Machines in Paralysis Using Brain Waves and Other Biosignals

The extent to which humans can interact with machines significantly enhanced through inclusion of speech, gestures, and eye movements. However, these communication channels depend on a functional motor system. As many people suffer from severe damage of the motor system resulting in paralysis and inability to communicate, the development of brain-machine interfaces (BMI) that translate electric or metabolic brain activity into control signals of external devices promises to overcome this dependence. People with complete paralysis can learn to use their brain waves to control prosthetic devices or exoskeletons. However, information transfer rates of currently available noninvasive BMI systems are still very limited and do not allow versatile control and interaction with assistive machines. Thus, using brain waves in combination with other biosignals might significantly enhance the ability of people with a compromised motor system to interact with assistive machines. Here, we give an overview of the current state of assistive, noninvasive BMI research and propose to integrate brain waves and other biosignals for improved control and applicability of assistive machines in paralysis. Beside introducing an example of such a system, potential future developments are being discussed.