The Human Factor: Behavioral and Neural Correlates of Humanized Perception in Moral Decision Making

The extent to which people regard others as full-blown individuals with mental states (“humanization”) seems crucial for their prosocial motivation towards them. Previous research has shown that decisions about moral dilemmas in which one person can be sacrificed to save multiple others do not consistently follow utilitarian principles. We hypothesized that this behavior can be explained by the potential victim’s perceived humanness and an ensuing increase in vicarious emotions and emotional conflict during decision making. Using fMRI, we assessed neural activity underlying moral decisions that affected fictitious persons that had or had not been experimentally humanized. In implicit priming trials, participants either engaged in mentalizing about these persons (Humanized condition) or not (Neutral condition). In subsequent moral dilemmas, participants had to decide about sacrificing these persons’ lives in order to save the lives of numerous others. Humanized persons were sacrificed less often, and the activation pattern during decisions about them indicated increased negative affect, emotional conflict, vicarious emotions, and behavioral control (pgACC/mOFC, anterior insula/IFG, aMCC and precuneus/PCC). Besides, we found enhanced effective connectivity between aMCC and anterior insula, which suggests increased emotion regulation during decisions affecting humanized victims. These findings highlight the importance of others’ perceived humanness for prosocial behavior - with aversive affect and other-related concern when imagining harming more “human-like” persons acting against purely utilitarian decisions.     

The shaping of social perception by stimulus and knowledge cues to human animacy

Although robots are becoming an ever-growing presence in society, we do not hold the same expectations for robots as we do for humans, nor do we treat them the same. As such, the ability to recognize cues to human animacy is fundamental for guiding social interactions. We review literature that demonstrates cortical networks associated with person perception, action observation and mentalizing are sensitive to human animacy information. In addition, we show that most prior research has explored stimulus properties of artificial agents (humanness of appearance or motion), with less investigation into knowledge cues (whether an agent is believed to have human or artificial origins). Therefore, currently little is known about the relationship between stimulus and knowledge cues to human animacy in terms of cognitive and brain mechanisms. Using fMRI, an elaborate belief manipulation, and human and robot avatars, we found that knowledge cues to human animacy modulate engagement of person perception and mentalizing networks, while stimulus cues to human animacy had less impact on social brain networks. These findings demonstrate that self–other similarities are not only grounded in physical features but are also shaped by prior knowledge. More broadly, as artificial agents fulfil increasingly social roles, a challenge for roboticists will be to manage the impact of pre-conceived beliefs while optimizing human-like design.     

Trying to See Red Through Stickleback Photoreceptors: Functional Substitution of Receptor Sensitivities

A key to understanding animal behavior is knowledge of the sensory information animals extract from their environment. For visually motivated tasks, the information animals obtain through their eyes is often assumed to be essentially the same as that perceived by humans. However, known differences in structure and processing among the visual systems of different animals clearly indicate that the world seen by each is different. A well‐characterized difference between human and other animal visual systems is the number of types and spectral sensitivities of their photoreceptors. We are developing a technique, functional substitution, that exploits knowledge of these differences to portray for human subjects, colors as they would appear through the photoreceptors of another animal. In a specific application, we ask human subjects to rank hues of male threespine stickleback (Gasterosteus aculeatus) throats viewed through stickleback photopigments. We compare these ranks to ranks of the same throat hues viewed through normal human photoreceptors. We find essentially no difference between the two sets of rankings. This suggests that any differences in human and stickleback rankings of such hues would result from differences in post‐receptoral neural processing. Using a previously developed model of stickleback neural processing, we established another ranking of the hues which was again essentially the same as the rankings produced by the human subjects. A growing literature indicates that stickleback do rank such hues in the evaluation of males as potential mates or threats. Although our results do not demonstrate that humans and stickleback use the same mechanisms to assess color, our experiments significantly failed to show that stickleback and human rankings of throat hues should be different. Nevertheless, a comparison of all these rankings to ranks derived from subjective color scoring by human observers suggests that color scoring may utilize other cues and should thus be used cautiously.     

Ovulatory shifts in human female ornamentation: near ovulation, women dress to impress

Humans differ from many other primates in the apparent absence of obvious advertisements of fertility within the ovulatory cycle. However, recent studies demonstrate increases in women's sexual motivation near ovulation, raising the question of whether human ovulation could be marked by observable changes in overt behavior. Using a sample of 30 partnered women photographed at high and low fertility cycle phases, we show that readily-observable behaviors - self-grooming and ornamentation through attractive choice of dress - increase during the fertile phase of the ovulatory cycle. At above-chance levels, 42 judges selected photographs of women in their fertile (59.5%) rather than luteal phase (40.5%) as "trying to look more attractive." Moreover, the closer women were to ovulation when photographed in the fertile window, the more frequently their fertile photograph was chosen. Although an emerging literature indicates a variety of changes in women across the cycle, the ornamentation effect is striking in both its magnitude and its status as an overt behavioral difference that can be easily observed by others. It may help explain the previously documented finding that men's mate retention efforts increase as their partners approach ovulation.     

Of bonds and boundaries: what is the modern role of anthropomorphism in primatological studies?

Anthropomorphism (and its obverse, zoomorphism) continues to shift and propel us toward changing perspectives on ourselves and other animals. Discussions of anthropomorphism in primate behavior are ostensibly about our use and definition of terms, but ultimately reflect our views of what is unique to humans or unknowable in other animals. Primatologists doing long-term fieldwork report on the bonds that are inevitably formed through familiarity with their study subjects and how anecdotes and anthropomorphism help them to gain a contextualized view of animal lives. This fuller view of animal society serves as an aid to understanding different rationalities and provides a more effective modern role for anthropomorphism than does seeking to demonstrate isomorphic capacities in alloprimates. Although most ordinary language terms are accepted among primatologists, "primate culture" serves as an example of a term and a concept that overreached acceptable anthropomorphic limits when defined to accord with definitions of modern human culture. Comparing similar behavioral forms as the product of similar selective pressures acting on specific early traits, producing homoplasies through convergent evolution, provides a nonanthropomorphic basis for seeking similarities in human and alloprimate behavior.     

Analyzing the "degree of humanness" of antibody sequences

Genetically engineered mouse antibodies are now commonly in clinical use. However, their development is limited because the human immune system tends to regard them as foreign and this triggers an immune response. The solution is to make engineered antibodies appear more human. Here, we propose a method to assess the "degree of humanness" of antibody sequences providing a tool that may contribute to predictions of antigenicity. We analyzed sequences of antibodies belonging to various chains/classes in human and mouse. Our analysis of metrics based on percentage sequence identity between antibody sequences shows distinct differences between human and mouse sequences. Based on mean sequence identity and standard deviation, we calculated Z-scores for data sets of antibody sequences extracted from the Kabat database. We applied the analysis to a set of humanized and chimeric antibodies and to human germline sequences. We conclude that this approach may aid in the selection of more suitable mouse variable domains for antibody engineering to render them more human but in general, we find that typicality of a sequence compared with the expressed human repertoire is not well correlated with antigenicity. We have provided a Web server allowing humanness to be assigned for a sequence.     

Oxytocin shapes the neural circuitry of trust and trust adaptation in humans

Trust and betrayal of trust are ubiquitous in human societies. Recent behavioral evidence shows that the neuropeptide oxytocin increases trust among humans, thus offering a unique chance of gaining a deeper understanding of the neural mechanisms underlying trust and the adaptation to breach of trust. We examined the neural circuitry of trusting behavior by combining the intranasal, double-blind, administration of oxytocin with fMRI. We find that subjects in the oxytocin group show no change in their trusting behavior after they learned that their trust had been breached several times while subjects receiving placebo decrease their trust. This difference in trust adaptation is associated with a specific reduction in activation in the amygdala, the midbrain regions, and the dorsal striatum in subjects receiving oxytocin, suggesting that neural systems mediating fear processing (amygdala and midbrain regions) and behavioral adaptations to feedback information (dorsal striatum) modulate oxytocin's effect on trust. These findings may help to develop deeper insights into mental disorders such as social phobia and autism, which are characterized by persistent fear or avoidance of social interactions.     

Can Machines Think? Interaction and Perspective Taking with Robots Investigated via fMRI

Background

When our PC goes on strike again we tend to curse it as if it were a human being. Why and under which circumstances do we attribute human-like properties to machines? Although humans increasingly interact directly with machines it remains unclear whether humans implicitly attribute intentions to them and, if so, whether such interactions resemble human-human interactions on a neural level. In social cognitive neuroscience the ability to attribute intentions and desires to others is being referred to as having a Theory of Mind (ToM). With the present study we investigated whether an increase of human-likeness of interaction partners modulates the participants'' ToM associated cortical activity.

Methodology/Principal Findings

By means of functional magnetic resonance imaging (subjects n = 20) we investigated cortical activity modulation during highly interactive human-robot game. Increasing degrees of human-likeness for the game partner were introduced by means of a computer partner, a functional robot, an anthropomorphic robot and a human partner. The classical iterated prisoner''s dilemma game was applied as experimental task which allowed for an implicit detection of ToM associated cortical activity. During the experiment participants always played against a random sequence unknowingly to them. Irrespective of the surmised interaction partners'' responses participants indicated having experienced more fun and competition in the interaction with increasing human-like features of their partners. Parametric modulation of the functional imaging data revealed a highly significant linear increase of cortical activity in the medial frontal cortex as well as in the right temporo-parietal junction in correspondence with the increase of human-likeness of the interaction partner (computerConclusions/SignificanceBoth regions correlating with the degree of human-likeness, the medial frontal cortex and the right temporo-parietal junction, have been associated with Theory-of-Mind. The results demonstrate that the tendency to build a model of another''s mind linearly increases with its perceived human-likeness. Moreover, the present data provides first evidence of a contribution of higher human cognitive functions such as ToM in direct interactions with artificial robots. Our results shed light on the long-lasting psychological and philosophical debate regarding human-machine interaction and the question of what makes humans being perceived as human.     

Evolution of life history and behavior in Hominidae: Towards phylogenetic reconstruction of the chimpanzee–human last common ancestor

The origin of the fundamental behavioral differences between humans and our closest living relatives is one of the central issues of evolutionary anthropology. The prominent, chimpanzee-based referential model of early hominin behavior has recently been challenged on the basis of broad multispecies comparisons and newly discovered fossil evidence. Here, we argue that while behavioral data on extant great apes are extremely relevant for reconstruction of ancestral behaviors, these behaviors should be reconstructed trait by trait using formal phylogenetic methods. Using the widely accepted hominoid phylogenetic tree, we perform a series of character optimization analyses using 65 selected life-history and behavioral characters for all extant hominid species. This analysis allows us to reconstruct the character states of the last common ancestors of Hominoidea, Hominidae, and the chimpanzee–human last common ancestor. Our analyses demonstrate that many fundamental behavioral and life-history attributes of hominids (including humans) are evidently ancient and likely inherited from the common ancestor of all hominids. However, numerous behaviors present in extant great apes represent their own terminal autapomorphies (both uniquely derived and homoplastic). Any evolutionary model that uses a single extant species to explain behavioral evolution of early hominins is therefore of limited use. In contrast, phylogenetic reconstruction of ancestral states is able to provide a detailed suite of behavioral, ecological and life-history characters for each hypothetical ancestor. The living great apes therefore play an important role for the confident identification of the traits found in the chimpanzee–human last common ancestor, some of which are likely to represent behaviors of the fossil hominins.     

Discrimination of Complex Human Behavior by Pigeons (Columba livia) and Humans

The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors (“martial arts” vs. “Indian dance”). Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species.     

Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates

Reaching and grasping in primates depend on the coordination of neural activity in large frontoparietal ensembles. Here we demonstrate that primates can learn to reach and grasp virtual objects by controlling a robot arm through a closed-loop brain–machine interface (BMIc) that uses multiple mathematical models to extract several motor parameters (i.e., hand position, velocity, gripping force, and the EMGs of multiple arm muscles) from the electrical activity of frontoparietal neuronal ensembles. As single neurons typically contribute to the encoding of several motor parameters, we observed that high BMIc accuracy required recording from large neuronal ensembles. Continuous BMIc operation by monkeys led to significant improvements in both model predictions and behavioral performance. Using visual feedback, monkeys succeeded in producing robot reach-and-grasp movements even when their arms did not move. Learning to operate the BMIc was paralleled by functional reorganization in multiple cortical areas, suggesting that the dynamic properties of the BMIc were incorporated into motor and sensory cortical representations.     

Learning to control a brain-machine interface for reaching and grasping by primates

Reaching and grasping in primates depend on the coordination of neural activity in large frontoparietal ensembles. Here we demonstrate that primates can learn to reach and grasp virtual objects by controlling a robot arm through a closed-loop brain–machine interface (BMIc) that uses multiple mathematical models to extract several motor parameters (i.e., hand position, velocity, gripping force, and the EMGs of multiple arm muscles) from the electrical activity of frontoparietal neuronal ensembles. As single neurons typically contribute to the encoding of several motor parameters, we observed that high BMIc accuracy required recording from large neuronal ensembles. Continuous BMIc operation by monkeys led to significant improvements in both model predictions and behavioral performance. Using visual feedback, monkeys succeeded in producing robot reach-and-grasp movements even when their arms did not move. Learning to operate the BMIc was paralleled by functional reorganization in multiple cortical areas, suggesting that the dynamic properties of the BMIc were incorporated into motor and sensory cortical representations.     

Mapping connectivity damage in the case of Phineas Gage

White matter (WM) mapping of the human brain using neuroimaging techniques has gained considerable interest in the neuroscience community. Using diffusion weighted (DWI) and magnetic resonance imaging (MRI), WM fiber pathways between brain regions may be systematically assessed to make inferences concerning their role in normal brain function, influence on behavior, as well as concerning the consequences of network-level brain damage. In this paper, we investigate the detailed connectomics in a noted example of severe traumatic brain injury (TBI) which has proved important to and controversial in the history of neuroscience. We model the WM damage in the notable case of Phineas P. Gage, in whom a "tamping iron" was accidentally shot through his skull and brain, resulting in profound behavioral changes. The specific effects of this injury on Mr. Gage's WM connectivity have not previously been considered in detail. Using computed tomography (CT) image data of the Gage skull in conjunction with modern anatomical MRI and diffusion imaging data obtained in contemporary right handed male subjects (aged 25-36), we computationally simulate the passage of the iron through the skull on the basis of reported and observed skull fiducial landmarks and assess the extent of cortical gray matter (GM) and WM damage. Specifically, we find that while considerable damage was, indeed, localized to the left frontal cortex, the impact on measures of network connectedness between directly affected and other brain areas was profound, widespread, and a probable contributor to both the reported acute as well as long-term behavioral changes. Yet, while significantly affecting several likely network hubs, damage to Mr. Gage's WM network may not have been more severe than expected from that of a similarly sized "average" brain lesion. These results provide new insight into the remarkable brain injury experienced by this noteworthy patient.     

Biosensor approach to psychopathology classification

We used a multi-round, two-party exchange game in which a healthy subject played a subject diagnosed with a DSM-IV (Diagnostic and Statistics Manual-IV) disorder, and applied a Bayesian clustering approach to the behavior exhibited by the healthy subject. The goal was to characterize quantitatively the style of play elicited in the healthy subject (the proposer) by their DSM-diagnosed partner (the responder). The approach exploits the dynamics of the behavior elicited in the healthy proposer as a biosensor for cognitive features that characterize the psychopathology group at the other side of the interaction. Using a large cohort of subjects (n = 574), we found statistically significant clustering of proposers' behavior overlapping with a range of DSM-IV disorders including autism spectrum disorder, borderline personality disorder, attention deficit hyperactivity disorder, and major depressive disorder. To further validate these results, we developed a computer agent to replace the human subject in the proposer role (the biosensor) and show that it can also detect these same four DSM-defined disorders. These results suggest that the highly developed social sensitivities that humans bring to a two-party social exchange can be exploited and automated to detect important psychopathologies, using an interpersonal behavioral probe not directly related to the defining diagnostic criteria.     

Variation in the large-scale organization of gene expression levels in the hippocampus relates to stable epigenetic variability in behavior

Background

Despite sharing the same genes, identical twins demonstrate substantial variability in behavioral traits and in their risk for disease. Epigenetic factors–DNA and chromatin modifications that affect levels of gene expression without affecting the DNA sequence–are thought to be important in establishing this variability. Epigenetically-mediated differences in the levels of gene expression that are associated with individual variability traditionally are thought to occur only in a gene-specific manner. We challenge this idea by exploring the large-scale organizational patterns of gene expression in an epigenetic model of behavioral variability.

Methodology/Findings

To study the effects of epigenetic influences on behavioral variability, we examine gene expression in genetically identical mice. Using a novel approach to microarray analysis, we show that variability in the large-scale organization of gene expression levels, rather than differences in the expression levels of specific genes, is associated with individual differences in behavior. Specifically, increased activity in the open field is associated with increased variance of log-transformed measures of gene expression in the hippocampus, a brain region involved in open field activity. Early life experience that increases adult activity in the open field also similarly modifies the variance of gene expression levels. The same association of the variance of gene expression levels with behavioral variability is found with levels of gene expression in the hippocampus of genetically heterogeneous outbred populations of mice, suggesting that variation in the large-scale organization of gene expression levels may also be relevant to phenotypic differences in outbred populations such as humans. We find that the increased variance in gene expression levels is attributable to an increasing separation of several large, log-normally distributed families of gene expression levels. We also show that the presence of these multiple log-normal distributions of gene expression levels is a universal characteristic of gene expression in eurkaryotes. We use data from the MicroArray Quality Control Project (MAQC) to demonstrate that our method is robust and that it reliably detects biological differences in the large-scale organization of gene expression levels.

Conclusions

Our results contrast with the traditional belief that epigenetic effects on gene expression occur only at the level of specific genes and suggest instead that the large-scale organization of gene expression levels provides important insights into the relationship of gene expression with behavioral variability. Understanding the epigenetic, genetic, and environmental factors that regulate the large-scale organization of gene expression levels, and how changes in this large-scale organization influences brain development and behavior will be a major future challenge in the field of behavioral genomics.     

Visualizing adenosine-to-inosine RNA editing in the Drosophila nervous system

Informational recoding by adenosine-to-inosine RNA editing diversifies neuronal proteomes by chemically modifying structured mRNAs. However, techniques for analyzing editing activity on substrates in defined neurons in vivo are lacking. Guided by comparative genomics, here we reverse-engineered a fluorescent reporter sensitive to Drosophila melanogaster adenosine deaminase that acts on RNA (dADAR) activity and alterations in dADAR autoregulation. Using this artificial dADAR substrate, we visualized variable patterns of RNA-editing activity in the Drosophila nervous system between individuals. Our results demonstrate the feasibility of structurally mimicking ADAR substrates as a method to regulate protein expression and, potentially, therapeutically repair mutant mRNAs. Our data suggest variable RNA editing as a credible molecular mechanism for mediating individual-to-individual variation in neuronal physiology and behavior.     

Being Barbie: the size of one's own body determines the perceived size of the world

A classical question in philosophy and psychology is if the sense of one's body influences how one visually perceives the world. Several theoreticians have suggested that our own body serves as a fundamental reference in visual perception of sizes and distances, although compelling experimental evidence for this hypothesis is lacking. In contrast, modern textbooks typically explain the perception of object size and distance by the combination of information from different visual cues. Here, we describe full body illusions in which subjects experience the ownership of a doll's body (80 cm or 30 cm) and a giant's body (400 cm) and use these as tools to demonstrate that the size of one's sensed own body directly influences the perception of object size and distance. These effects were quantified in ten separate experiments with complementary verbal, questionnaire, manual, walking, and physiological measures. When participants experienced the tiny body as their own, they perceived objects to be larger and farther away, and when they experienced the large-body illusion, they perceived objects to be smaller and nearer. Importantly, despite identical retinal input, this "body size effect" was greater when the participants experienced a sense of ownership of the artificial bodies compared to a control condition in which ownership was disrupted. These findings are fundamentally important as they suggest a causal relationship between the representations of body space and external space. Thus, our own body size affects how we perceive the world.     

A complex experimental assessment for objective description of hierarchical psychophysiological behavior as human regulatory phenotype

For the objective and valid identification of different human regulatory phenotypes it should be useful to analyze the behavior of different regulatory subsystems (Anochin 1976) in one multivariate design. Therefore in a DARA supported project a fully computerized and reliable laboratory assessment was developed and tested. We used a set of electrophysiological parameters that should indicate the activity of different functional regulation systems on different "behavioral levels". Skin conductance, skin temperature and voice pitch were used as indicators of sympathico-parasympathical activity. Breathing, heart rate variability and bloodpressure should indicate cardiovascular activity and electromyogram and mimic variablity were thought as indicators of locomotional external behavioral activity. To identify physiological reactions which are influenced by emotional stress we used voice stress measures. Even in the field of aviation and space medicine there exist data about the correlation of voice pitch with emotional excitation (Hecker et. al. 1968, Williams et.al. 1969, Friedrich, Vaic 1978, Vaic et.al. 1981,1982, Griffin, Williams 1987). In our former study (MOSAIC-study, Johannes 1990) the voice pitch and its variation range correlated with perceived emotional excitation but were independent of real bloodpressure variations. Two different types of pitch reaction to this experimental design were correlated to psychological personality scales and assigned subjects to "sensitizers" and "suppressors".