Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements

Understanding the neural mechanisms responsible for human social interactions is difficult, since the brain activities of two or more individuals have to be examined simultaneously and correlated with the observed social patterns. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Graph analysis of hyper-brain networks constructed from the EEG scanning of 26 couples of individuals playing the Iterated Prisoner's Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two-defector couples have significantly less inter-brain links and overall higher modularity--i.e., the tendency to form two separate subgraphs--than couples playing cooperative or tit-for-tat strategies. The decision to defect can be "read" in advance by evaluating the changes of connectivity pattern in the hyper-brain network.     

Cooperation prevails when individuals adjust their social ties

Conventional evolutionary game theory predicts that natural selection favours the selfish and strong even though cooperative interactions thrive at all levels of organization in living systems. Recent investigations demonstrated that a limiting factor for the evolution of cooperative interactions is the way in which they are organized, cooperators becoming evolutionarily competitive whenever individuals are constrained to interact with few others along the edges of networks with low average connectivity. Despite this insight, the conundrum of cooperation remains since recent empirical data shows that real networks exhibit typically high average connectivity and associated single-to-broad–scale heterogeneity. Here, a computational model is constructed in which individuals are able to self-organize both their strategy and their social ties throughout evolution, based exclusively on their self-interest. We show that the entangled evolution of individual strategy and network structure constitutes a key mechanism for the sustainability of cooperation in social networks. For a given average connectivity of the population, there is a critical value for the ratio W between the time scales associated with the evolution of strategy and of structure above which cooperators wipe out defectors. Moreover, the emerging social networks exhibit an overall heterogeneity that accounts very well for the diversity of patterns recently found in acquired data on social networks. Finally, heterogeneity is found to become maximal when W reaches its critical value. These results show that simple topological dynamics reflecting the individual capacity for self-organization of social ties can produce realistic networks of high average connectivity with associated single-to-broad–scale heterogeneity. On the other hand, they show that cooperation cannot evolve as a result of “social viscosity” alone in heterogeneous networks with high average connectivity, requiring the additional mechanism of topological co-evolution to ensure the survival of cooperative behaviour.     

Working together may be better: activation of reward centers during a cooperative maze task

Humans use theory of mind when predicting the thoughts and feelings and actions of others. There is accumulating evidence that cooperation with a computerized game correlates with a unique pattern of brain activation. To investigate the neural correlates of cooperation in real-time we conducted an fMRI hyperscanning study. We hypothesized that real-time cooperation to complete a maze task, using a blind-driving paradigm, would activate substrates implicated in theory of mind. We also hypothesized that cooperation would activate neural reward centers more than when participants completed the maze themselves. Of interest and in support of our hypothesis we found left caudate and putamen activation when participants worked together to complete the maze. This suggests that cooperation during task completion is inherently rewarding. This finding represents one of the first discoveries of a proximate neural mechanism for group based interactions in real-time, which indirectly supports the social brain hypothesis.     

基于功能性近红外光谱技术的双人同步交互测量研究

多人同步交互式记录是认知神经科学的一种新的研究范式,它可以揭示两个或多个个体的大脑间在社交情境下神经活动的耦合。这一目标仅靠单个大脑活动的记录与测量是无法实现的。功能性近红外光谱成像在进行多人同步交互记录研究中有独特的优势。该方面的研究已经涵盖了社会认知神经科学的多个领域。本研究使用近红外光谱成像对社交情境下自我表露的双人大脑前额皮层的活动进行交互式测量,并使用小波相关来分析双人大脑互动时的神经同步性。研究结果表明在进行社交对话时,被试对的大脑间左侧额中回、右侧眶额皮层和右侧额下回下部的活动同步性显著增强。共情能力与社交情境下脑间同步性的强度呈正相关,这种关系主要体现在右侧额下回。本研究支持了采用近红外光谱成像技术研究多人同步交互记录大脑间神经耦合的可行性和有效性。     

On the further integration of cooperative breeding and cooperation theory

We present a synopsis about the commentaries to the target article "Integrating cooperative breeding into theoretical concepts of cooperation", in which we attempted to integrate general mechanisms to explain cooperative behaviour among unrelated individuals with classic concepts to explain helping behaviour in cooperative breeders that do not invoke kin-based benefits. Here we (1) summarize the positions of the commentators concerning the main issues we raised in the target article and discuss important criticisms and extensions. (2) We relate our target article to some recent reviews on the evolution of cooperation and, (3) clarify how we use terminology with regard to cooperation and cooperative behaviour. (4) We discuss several aspects that were raised with respect to cooperative interactions including by-product mutualism, generalised reciprocity and multi-level selection and, (5) examine the alternatives to our classification scheme as proposed by some commentaries. (6) Finally, we highlight several aspects that might hinder the application of game theoretical mechanisms of cooperation in cooperatively breeding systems. Although there is broad agreement that cooperative breeding theory should be integrated within the more general concepts of cooperation, there is some debate about how this may be achieved. We conclude that the contributions in this special issue provide a fruitful first step and ample suggestions for future directions with regard to a more unified framework of cooperation in cooperative breeders.     

Heart Rate and Respiration Responses to Real Traffic Pattern Flight

The purpose of this study was to observe heart rate and respiration responses to real traffic pattern flight. Nine experienced and nine less-experienced military pilots on active flying status participated in four uninterrupted traffic patterns flight missions with F-7 jet trainer. The heart rates and respiration waves were continuously recorded using a small recording device strapped around the chest. As compared with baseline values, significant increases in heart rates of the two groups (for experienced pilots group, F (11, 88) = 4.636, p = 0.000; for less-experienced, F (11, 88) = 4.437, p = 0.000) and mean respiration rates of less-experienced group (F (11, 88) = 4.488, p = 0.000) were obtained during the phases of take-off, final approach and landing. Heart rates of less-experienced pilots were significant higher than those of experienced pilots during the take-off phase (p < 0.05). There were no significant differences in respiration rates between the two groups at each phase of the whole flight. The results show that take-off, final approach and landing are the most mental workload phases in-flight, and less-experienced pilots show more mental workload than experienced pilots in take-off phase in-flight.     

Do Short International Layovers Allow Sufficient Opportunity for Pilots to Recover?

For Australian pilots, short layovers (<40 h) are a feature of many international patterns. However, anecdotal reports suggest that flight crew members find patterns with short slips more fatiguing than those with a longer international layover, as they restrict the opportunity to obtain sufficient sleep. The current study aimed to determine whether pilots operating international patterns with short layovers have sufficient opportunity to recover prior to the inbound flight. Nineteen international pilots (ten captains, nine first officers) operating a direct return pattern from Australia to Los Angeles (LAX) with a short (n=9) 9±0.8 h (mean±S.D) or long (n=10) 62.2±0.9 h LAX layover wore an activity monitor and kept a sleep/duty diary during the pattern. Immediately before and after each flight, pilots completed a 5 min PalmPilot‐based psychomotor vigilance task (Palm‐PVT). Flights were of comparable duration outbound (3.5±0.6 h) and inbound (14.3±0.6 h) and timing. The amount of sleep obtained in‐flight did not significantly vary as a function of layover length. However, pilots obtained significantly more sleep during the inbound (3.7±0.8 h) than the outbound flight (2.2±0.8 h). Pilots with the shorter layover obtained significantly less sleep in total during layover (14.0±2.7 h vs. 19.6±2.5), due to significantly fewer sleep periods (3.0±0.7 vs. 4.0±0.9). However, neither mean sleep duration nor the sleep obtained in the 24 h prior to the inbound flight significantly differed as a function of layover length. Response speed significantly varied across the pattern, and a significant interaction was also observed. For pilots with a short layover, response speed was significantly slower at the end of both the outbound and inbound flight, and prior to the inbound flight (i.e., at the end of layover), relative to response speed at the start of the pattern (pre‐trip). Similarly, response speed for the longer layover was slower at the end of the outbound flight compared to pre‐trip (approaching significance, p=0.073). However, response speed at the beginning of the inbound flight was significantly faster than pre‐trip and did not significantly differ from pre‐trip at the end of the inbound flight. The data suggest that short slips (<40 h) do not allow pilots the opportunity to obtain sufficient sleep to reverse the effects of fatigue accumulated during the outbound flight. As a result, their response speed prior to the inbound flight is substantially slower than the response speed of flight crew with a longer layover.     

Dynamic effective connectivity of inter-areal brain circuits

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities.     

Do short international layovers allow sufficient opportunity for pilots to recover?

For Australian pilots, short layovers (<40 h) are a feature of many international patterns. However, anecdotal reports suggest that flight crew members find patterns with short slips more fatiguing than those with a longer international layover, as they restrict the opportunity to obtain sufficient sleep. The current study aimed to determine whether pilots operating international patterns with short layovers have sufficient opportunity to recover prior to the inbound flight. Nineteen international pilots (ten captains, nine first officers) operating a direct return pattern from Australia to Los Angeles (LAX) with a short (n = 9) 9+/-0.8 h (mean+/-S.D) or long (n = 10) 62.2+/-0.9 h LAX layover wore an activity monitor and kept a sleep/duty diary during the pattern. Immediately before and after each flight, pilots completed a 5 min PalmPilot-based psychomotor vigilance task (Palm-PVT). Flights were of comparable duration outbound (3.5+/-0.6 h) and inbound (14.3+/-0.6 h) and timing. The amount of sleep obtained in-flight did not significantly vary as a function of layover length. However, pilots obtained significantly more sleep during the inbound (3.7+/-0.8 h) than the outbound flight (2.2+/-0.8 h). Pilots with the shorter layover obtained significantly less sleep in total during layover (14.0+/-2.7 h vs. 19.6+/-2.5), due to significantly fewer sleep periods (3.0+/-0.7 vs. 4.0+/-0.9). However, neither mean sleep duration nor the sleep obtained in the 24 h prior to the inbound flight significantly differed as a function of layover length. Response speed significantly varied across the pattern, and a significant interaction was also observed. For pilots with a short layover, response speed was significantly slower at the end of both the outbound and inbound flight, and prior to the inbound flight (i.e., at the end of layover), relative to response speed at the start of the pattern (pre-trip). Similarly, response speed for the longer layover was slower at the end of the outbound flight compared to pre-trip (approaching significance, p = 0.073). However, response speed at the beginning of the inbound flight was significantly faster than pre-trip and did not significantly differ from pre-trip at the end of the inbound flight. The data suggest that short slips (<40 h) do not allow pilots the opportunity to obtain sufficient sleep to reverse the effects of fatigue accumulated during the outbound flight. As a result, their response speed prior to the inbound flight is substantially slower than the response speed of flight crew with a longer layover.     

Role of structural inhomogeneities in resting-state brain dynamics

Brain imaging methods allow a non-invasive assessment of both structural and functional connectivity. However, the mechanism of how functional connectivity arises in a structured network of interacting neural populations is as yet poorly understood. Here we use a modeling approach to explore the way in which functional correlations arise from underlying structural connections taking into account inhomogeneities in the interactions between the brain regions of interest. The local dynamics of a neural population is assumed to be of phase-oscillator type. The considered structural connectivity patterns describe long-range anatomical connections between interacting neural elements. We find a dependence of the simulated functional connectivity patterns on the parameters governing the dynamics. We calculate graph-theoretic measures of the functional network topology obtained from numerical simulations. The effect of structural inhomogeneities in the coupling term on the observed network state is quantified by examining the relation between simulated and empirical functional connectivity. Importantly, we show that simulated and empirical functional connectivity agree for a narrow range of coupling strengths. We conclude that identification of functional connectivity during rest requires an analysis of the network dynamics.     

Human connectomics

Recent advances in non-invasive neuroimaging have enabled the measurement of connections between distant regions in the living human brain, thus opening up a new field of research: Human connectomics. Different imaging modalities allow the mapping of structural connections (axonal fibre tracts) as well as functional connections (correlations in time series), and individual variations in these connections may be related to individual variations in behaviour and cognition. Connectivity analysis has already led to a number of new insights about brain organization. For example, segregated brain regions may be identified by their unique patterns of connectivity, structural and functional connectivity may be compared to elucidate how dynamic interactions arise from the anatomical substrate, and the architecture of large-scale networks connecting sets of brain regions may be analysed in detail. The combined analysis of structural and functional networks has begun to reveal components or modules with distinct patterns of connections that become engaged in different cognitive tasks. Collectively, advances in human connectomics open up the possibility of studying how brain connections mediate regional brain function and thence behaviour.     

Intelligence quotients of pilots in civil aviation with atherosclerotic changes in the brain vessels

Intelligence quotients (IQs) in pilots of civil aviation were studied. A total of 73 healthy pilots (control group) and 70 pilots with atherosclerosis of the brain vessels, including 23 persons with atherosclerotic plaques, were studied. The study of intellectual indices was performed using the classical Eysenck??s tests and their modifications by Gorbov in a computer variant developed by Sobchik. In pilots with atherosclerosis of the brain vessels, a tendency towards an insignificant decrease in the indices of average values of IQ as compared to those of healthy pilots was recorded. The IQs of the examined pilots indicated their occupational fitness. Despite the presence of atherosclerotic plaques in the group of pilots examined by us, the results of numerical (IQ2) and verbal (IQ3) tests were not reduced. The presence of hemodynamically insignificant stable atherosclerotic plaques in pilots examined by us did not lead to a change in the cognitive functions; the intellectual capacities of pilots were preserved, which allowed them to continue flight work.     

Inter-Brain Synchronization during Social Interaction

During social interaction, both participants are continuously active, each modifying their own actions in response to the continuously changing actions of the partner. This continuous mutual adaptation results in interactional synchrony to which both members contribute. Freely exchanging the role of imitator and model is a well-framed example of interactional synchrony resulting from a mutual behavioral negotiation. How the participants'' brain activity underlies this process is currently a question that hyperscanning recordings allow us to explore. In particular, it remains largely unknown to what extent oscillatory synchronization could emerge between two brains during social interaction. To explore this issue, 18 participants paired as 9 dyads were recorded with dual-video and dual-EEG setups while they were engaged in spontaneous imitation of hand movements. We measured interactional synchrony and the turn-taking between model and imitator. We discovered by the use of nonlinear techniques that states of interactional synchrony correlate with the emergence of an interbrain synchronizing network in the alpha-mu band between the right centroparietal regions. These regions have been suggested to play a pivotal role in social interaction. Here, they acted symmetrically as key functional hubs in the interindividual brainweb. Additionally, neural synchronization became asymmetrical in the higher frequency bands possibly reflecting a top-down modulation of the roles of model and imitator in the ongoing interaction.     

LIMITED DISPERSAL, BUDDING DISPERSAL, AND COOPERATION: AN EXPERIMENTAL STUDY

Numerous theoretical studies have investigated how limited dispersal may provide an explanation for the evolution of cooperation, by leading to interactions between relatives. However, despite considerable theoretical attention, there has been a lack of empirical tests. In this article, we test how patterns of dispersal influence the evolution of cooperation, using iron-scavenging in the bacterium Pseudomonas aeruginosa as our cooperative trait. We found that relatively limited dispersal does not favor cooperation. The reason for this is that although limited dispersal increases the relatedness between interacting individuals, it also leads to increased local competition for resources between relatives. This result supports Taylor's prediction that in the simplest possible scenario, the effects of increased relatedness and local competition exactly cancel out. In contrast, we show that one way for cooperation to be favored is if individuals disperse in groups (budding dispersal), because this maintains high relatedness while reducing local competition between relatives (relatively global competition).     

Movement patterns, social dynamics, and the evolution of cooperation

The structure of social interactions influences many aspects of social life, including the spread of information and behavior, and the evolution of social phenotypes. After dispersal, organisms move around throughout their lives, and the patterns of their movement influence their social encounters over the course of their lifespan. Though both space and mobility are known to influence social evolution, there is little analysis of the influence of specific movement patterns on evolutionary dynamics. We explored the effects of random movement strategies on the evolution of cooperation using an agent-based prisoner’s dilemma model with mobile agents. This is the first systematic analysis of a model in which cooperators and defectors can use different random movement strategies, which we chose to fall on a spectrum between highly exploratory and highly restricted in their search tendencies. Because limited dispersal and restrictions to local neighborhood size are known to influence the ability of cooperators to effectively assort, we also assessed the robustness of our findings with respect to dispersal and local capacity constraints. We show that differences in patterns of movement can dramatically influence the likelihood of cooperator success, and that the effects of different movement patterns are sensitive to environmental assumptions about offspring dispersal and local space constraints. Since local interactions implicitly generate dynamic social interaction networks, we also measured the average number of unique and total interactions over a lifetime and considered how these emergent network dynamics helped explain the results. This work extends what is known about mobility and the evolution of cooperation, and also has general implications for social models with randomly moving agents.     

Changes in Task-Related Functional Connectivity across Multiple Spatial Scales Are Related to Reading Performance

Reading requires the interaction of a distributed set of cortical areas whose distinct patterns give rise to a wide range of individual skill. However, the nature of these neural interactions and their relation to reading performance are still poorly understood. Functional connectivity analyses of fMRI data can be used to characterize the nature of interactivity of distributed brain networks, yet most previous studies have focused on connectivity during task-free (i.e., “resting state”) conditions. Here, we report new methods for assessing task-related functional connectivity using data-driven graph theoretical methods and describe how large-scale patterns of connectivity relate to individual variability in reading performance among children. We found that connectivity patterns of subjects performing a reading task could be decomposed hierarchically into multiple sub-networks, and we observed stronger long-range interaction between sub-networks in subjects with higher task accuracy. Additionally, we found a network of hub regions known to be critical to reading that displays increased short-range synchronization in higher accuracy subjects. These individual differences in task-related functional connectivity reveal that increased interaction between distant regions, coupled with selective local integration within key regions, is associated with better reading performance. Importantly, we show that task-related neuroimaging data contains far more information than usually extracted via standard univariate analyses – information that can meaningfully relate neural connectivity patterns to cognition and task.     

Cooperation between referees and authors increases peer review accuracy

Peer review is fundamentally a cooperative process between scientists in a community who agree to review each other''s work in an unbiased fashion. Peer review is the foundation for decisions concerning publication in journals, awarding of grants, and academic promotion. Here we perform a laboratory study of open and closed peer review based on an online game. We show that when reviewer behavior was made public under open review, reviewers were rewarded for refereeing and formed significantly more cooperative interactions (13% increase in cooperation, P = 0.018). We also show that referees and authors who participated in cooperative interactions had an 11% higher reviewing accuracy rate (P = 0.016). Our results suggest that increasing cooperation in the peer review process can lead to a decreased risk of reviewing errors.     

Cooperation and deception recruit different subsets of the theory-of-mind network

The term "theory of mind" (ToM) describes an evolved psychological mechanism that is necessary to represent intentions and expectations in social interaction. It is thus involved in determining the proclivity of others to cooperate or defect. While in cooperative settings between two parties the intentions and expectations of the protagonists match, they diverge in deceptive scenarios, in which one protagonist is intentionally manipulated to hold a false belief about the intention of the other. In a functional magnetic resonance imaging paradigm using cartoons showing social interactions (including the outcome of the interaction) between two or three story characters, respectively, we sought to determine those brain areas of the ToM network involved in reasoning about cooperative versus deceptive interactions. Healthy volunteers were asked to reflect upon the protagonists' intentions and expectations in cartoons depicting cooperation, deception or a combination of both, where two characters cooperated to deceive a third. Reasoning about the mental states of the story characters yielded substantial differences in activation patterns: both deception and cooperation activated bilateral temporoparietal junction, parietal and cingulate regions, while deception alone additionally recruited orbitofrontal and medial prefrontal regions. These results indicate an important role for prefrontal cortex in processing a mismatch between a character's intention and another's expectations as required in complex social interactions.     

Cooperation can promote rescue or lead to evolutionary suicide during environmental change

The adaptation of populations to changing conditions may be affected by interactions between individuals. For example, when cooperative interactions increase fecundity, they may allow populations to maintain high densities and thus keep track of moving environmental optima. Simultaneously, changes in population density alter the marginal benefits of cooperative investments, creating a feedback loop between population dynamics and the evolution of cooperation. Here we model how the evolution of cooperation interacts with adaptation to changing environments. We hypothesize that environmental change lowers population size and thus promotes the evolution of cooperation, and that this, in turn, helps the population keep up with the moving optimum. However, we find that the evolution of cooperation can have qualitatively different effects, depending on which fitness component is reduced by the costs of cooperation. If the costs decrease fecundity, cooperation indeed speeds adaptation by increasing population density; if, in contrast, the costs decrease viability, cooperation may instead slow adaptation by lowering the effective population size, leading to evolutionary suicide. Thus, cooperation can either promote or—counterintuitively—hinder adaptation to a changing environment. Finally, we show that our model can also be generalized to other social interactions by discussing the evolution of competition during environmental change.     

Structure-Function Discrepancy: Inhomogeneity and Delays in Synchronized Neural Networks

The discrepancy between structural and functional connectivity in neural systems forms the challenge in understanding general brain functioning. To pinpoint a mapping between structure and function, we investigated the effects of (in)homogeneity in coupling structure and delays on synchronization behavior in networks of oscillatory neural masses by deriving the phase dynamics of these generic networks. For homogeneous delays, the structural coupling matrix is largely preserved in the coupling between phases, resulting in clustered stationary phase distributions. Accordingly, we found only a small number of synchronized groups in the network. Distributed delays, by contrast, introduce inhomogeneity in the phase coupling so that clustered stationary phase distributions no longer exist. The effect of distributed delays mimicked that of structural inhomogeneity. Hence, we argue that phase (de-)synchronization patterns caused by inhomogeneous coupling cannot be distinguished from those caused by distributed delays, at least not by the naked eye. The here-derived analytical expression for the effective coupling between phases as a function of structural coupling constitutes a direct relationship between structural and functional connectivity. Structural connectivity constrains synchronizability that may be modified by the delay distribution. This explains why structural and functional connectivity bear much resemblance albeit not a one-to-one correspondence. We illustrate this in the context of resting-state activity, using the anatomical connectivity structure reported by Hagmann and others.