mystery of yawning
Le bâillement, du réflexe à la pathologie
Le bâillement : de l'éthologie à la médecine clinique
Le bâillement : phylogenèse, éthologie, nosogénie
 Le bâillement : un comportement universel
La parakinésie brachiale oscitante
Yawning: its cycle, its role
Warum gähnen wir ?
 
Fetal yawning assessed by 3D and 4D sonography
Le bâillement foetal
Le bâillement, du réflexe à la pathologie
Le bâillement : de l'éthologie à la médecine clinique
Le bâillement : phylogenèse, éthologie, nosogénie
 Le bâillement : un comportement universel
La parakinésie brachiale oscitante
Yawning: its cycle, its role
Warum gähnen wir ?
 
Fetal yawning assessed by 3D and 4D sonography
Le bâillement foetal
http://www.baillement.com
resolutionmini

mise à jour du
26 décembre 2010
TICS
2009;13(10):420-428
Herding in humans
 
Ramsey M. Raafat, Nick Chater, Chris Frith
 
Cognitive, Perceptual and Brain Sciences research department
University College London, UK

Chat-logomini

 
Herding is a form of convergent social behaviour that can be broadly defined as the alignment of the thoughts or behaviours of individuals in a group (herd) through local interaction and without centralized coordination. We suggest that herding has a broad application, from intellectual fashion to mob violence; and that understanding herding is particularly pertinent in an increasingly interconnected world. An integrated approach to herding is proposed, describing two key issues: mechanisms of transmission of thoughts or behaviour between agents, and patterns of connections between agents. We show how bringing together the diverse, often disconnected, theoretical and methodological approaches illuminates the applicability of herding to many domains of cognition and suggest that cognitive neuroscience offers a novel approach to its study.
 
Introduction
 
Cognitive psychology generally focuses on the individual as the fundamental unit of analysis [1]. Nevertheless, we are all embedded in a complex system of social structures, which ground and organize much of our behaviour [2], ranging from national identity to religious affiliation. Here, we consider one of the many bridges that link agents and the social structures in which they are embedded: a form of convergent social behaviour termed 'herding'. Herding can be broadly defined as the alignment of thoughts or behaviours of individuals in a group (herd) through local interactions rather than centralized coordination. In other words, the apparent central coordination of the herd is an emergent property of local interactions. Herding is an influential and well-documented feature of human behaviour in a number of domains, particularly economics and finance [3&endash;5]. Although the current economic turmoil has revealed the depth of herding among financial institutions and individual investors [6,7] (and by implication the agents responsible for their decisions), this concept also has much broader relevance beyond the economic arena. Examples of phenomena that have been described as involving herd behaviour are diverse and varied, ranging from stock market bubbles and financial speculation to zealotry (e. g. the 2002 Gujarat mob violence [8]), political choice [9] and consumer preferences [10,11]. The concept is well known in ethology, where for example the biologist William Hamilton illustrated how herd behaviour can emerge from the uncoordinated behaviour of individuals engaged in predator avoidance [12]. The process has also been investigated in social psychology and terms such as Fad, Fashion, Mass Hysteria, Bandwagon Effect, Groupthink and Herd Instinct have entered common parlance. Whereas the concepts behind herd mentality and herd behaviour have a rich history (Table 1), the methods, techniques and approaches currently used to elucidate them are relatively recent. In this article we review the extensive range of theoretical frameworks for describing herding. Similar ideas and explanations have emerged in many fields, albeit with different emphases, demonstrating the interdisciplinary nature of the concept. Wepropose a framework with which to organize these diverse approaches, which is based on a distinction between the mechanisms of transmission of a particular thought between individuals and the patterns of connections between individuals. We also distinguish between two main types of transmission: automatic contagion and rational deliberation. We suggest that cognitive neuroscience can reveal the mechanisms underlying the transmission of information, which can in turn help elucidate patterns of herd behaviour.
 
Models of herding
 
As indicated above, herding among individuals has been studied within a number of diverse domains. As a result, a number of different mechanisms and approaches have emerged across these domains in order to explain herding behaviour. It is therefore important to develop a conceptual framework within which the different approaches and models can be described, one that also permits the highlighting of common features. We propose that understanding how members of a group become aligned by 'local' interactions requires determining: (i) the mechanism of transmission that propagates a particular thought or behaviour from one agent to another and (ii) the pattern of interactions between agents. Conceptualizing herding as representing these two separate, though interconnected, perspectives addresses these requirements. Experimental approaches and modelling typically focus nearly exclusively on one issue or the other and this division between mechanisms of transmission vs. pattern of interactions between agents can be considered as a local vs. global division. This framework brings two primary questions into focus: (i) How do various types of information transmission, conscious vs. automatic, rational vs. emotional, affect the emergent architecture? (ii) What are the emergent effects of the pattern of connections?
 
Cognitive psychology and neuroscience generally focus on the individual, or on parts of the herd (Figure la), yet herding also arises from the organizing relations of those parts, that is, by how the individuals are configured (Figure lb). The pattern-based approach, adopted widely in fields such as Traffic Jam and Crowd analysis, financial markets, and social network analysis, emphasizes the static structure of the system and its relationships. It shows the dependencies among these components and takes the relationships between individuals as the primary unit for herding research and for the development of theory. However, a full understanding of herding behaviour requires the ability to 'shift' between the two levels represented in our framework. This distinction aids in the identification of contextual effects, that is, herding behaviour that is not apparent at the individual level. Moreover, the proposed framework indicates at which level different research questions could be appropriately addressed. For instance, there are some enquiries, such as whether herding is linear (that is, whether we can use conventional 'reductionist' approaches that look at the parts and employ superposition to investigate how they work together), which can only be addressed at the pattern level. In contrast, focusing on the affective and cognitive mental states of individuals, specifying the common and differential neural mechanisms of 'self and 'other', or interpersonal face-to-face interactions [131 may reveal quite different aspects of herding from the insights arising out of the pattern-based level. These two levels are not mutually exclusive; both levels can cross-fertilize each other. Moreover we consider that increasing knowledge of the brain areas involved in social cognition (the capacity to understand people's behavioural intentions, social beliefs, and personality traits) [141 can inform patternbased herding analyses and constrain the vast space of relations that can potentially exist between actors.
 
Pattern-based theories/models of herding behaviour: structure sets the herd?
 
Pattern-based explanations treat individuals as units with certain simple, well-defined properties and modes of interaction (Figure 2, left branch). The terminology used in this class of models, such as 'critical mass', 'self-organized criticality' and 'epidemics', is inspired by models in either particle physics or epidemiology and shares a similar structure. Such models often come under the rubric of econophysics models of herding and are prevalent in finance [151.
 
Pattern-based approaches view herding (and social phenomena in general) in terms of the patterns of interaction among the agents, modelled as simple imitators, or as following basic heuristics. In other words, people are treated as units or atoms with certain simple, well-defined properties and modes of interaction that yield herding: the focus is patterns, not people [161. The models generally rely on physical laws, distances and velocities rather than the emotional states of the herd. These approaches to multiagent phenomena are applied to many areas, naturally lending themselves to the explanation of phenomena, such as queuing, crowd and traffic interactions [171. Cellular Automata models [18,191 and Ising models [201 are the most extreme examples of this abstract approach. Closely related are models of 'flocking' in animal behaviour (for excellent reviews see [21,221), widely exhibited in biology by living creatures ranging from bacteria to birds. These models have been used to simulate human crowd behaviour [17,231, social behaviour such as language emergence and evolution [241, as well as in attempts to elucidate the general concept of emergent phenomena [251.
 
The most intuitively understandable pattern-based perspective is social network analysis - this perspective employs the simplest of structures in which each node (a person) is attached via some tie to others. This approach has had an important influence in modern sociology (Box 1). Such studies have shown that happiness and obesity tend to spread through social networks in a manner analogous to a contagious disease [26,271 (Figure Tin Box 1). Thinking in social network terms has progressed from being an evocative allegory [28-301 and has been extended to agent-based modelling approaches [311. Social network analysis focuses on how the structure of other relationships affects individuals [321 rather than treating individuals as the fundamental unit, and allows epidemiological methods to be employed.
 
Transmission mechanisms in herding: how do we broadcast?
 
In contrast to the focus on patterns of interaction, the complementary transmission perspective seeks to unify and identify mechanisms of transfer of information in herding (as illustrated in the split within the right branch of Figure 2) by concentrating on the role of cognitive and affective components, particularly the effortless human capacity known as 'mentalizing' (the ability to explain and predict the behaviour of others by attributing to them independent mental states) [331. A number of important theoretical distinctions can be used to classify different transmission mechanisms in human herding, including rational vs. emotional, automatic vs. controlled and conscious vs. unconscious. However, herding is a social tendency; an essential component of this behaviour is that it can incorporate beliefs about the herd. Individuals often converge by modelling behaviours and beliefs of the larger group within which they are embedded. Indeed most economic models are based on the assumption that single agents are able to view another agent's perspective [341.
 
People often explicitly attempt to infer others' beliefs, attitudes or preferences; and draw on these to help determine their own perspective [351. As such, our sub-division reflects this key mentalizing facet. In Figure 2, the left subbranch under transmission-based approaches includes approaches that do not postulate mentalizing as a critical aspect of transmission. These approaches range from emotional contagion through to social contagion and priming. The right 'mentalizing' sub-branch encompasses social conformity and influence, culminating with rational processes through which the agent consciously and deliberately considers the information in the signals of others. Although the importance of the presence of others has been a mainstay of social psychology, since Le Bon's [361 claim that collective influence can almost mesmerize the individual, when herding is viewed from a rational stance it is generally considered in two flavours: informational and reputational (that is, peer pressure) [371. Economists, in particular, have observed how groups of individually rational agents, each drawing on information about the choices of others can fall into collectively irrational 'informational cascades', which do not properly reflect the group's preferences. This assumes a utility-maximizing behaviour on the part of each agent [381 (Box 2).
 
There are, of course, other explicit drivers that may induce the alignment of the thoughts or behaviours of individuals in a group (herd), through local interaction and without centralized coordination. Social psychological accounts, such as those of Sherif [391, Asch [401 or Latané [411, indicate mechanisms that are consistent with herding and contagion under a variety of conditions. Social influence, real or imagined, of others can have a measurable impact, ranging from obedience and compliance through to conformity (for a useful review [421), but generally the latter imply some awareness of the act of alignment. This boundary between self and other is where social neuroscience can perhaps make a valuable contribution to the investigation of how the individual's perception [431 and the borders of self are affected by the group (Box 3). Social psychologists in particular have studied this as the process of de-individuation, and have addressed how the loss of a person's sense of individuality can reduce normal constraints against deviant behaviour. De-individuation is generally conceived of as a collective phenomenon, where anonymity and reduced feelings of individual responsibility provide a mechanism for situational forces to collectively drive behaviour [441 immersing the individual into the coup or herd.
 
Although herding and its consequences may arise from active choice, responses often occur without awareness, hence the key role of mentality in herding. Presumably, these and other Theory of mind factors can be manipulated in the laboratory.
 
The most researched example of the non-mentalizing approach in describing transmission in human herding is that of emotional contagion. Emotional contagion involves an involuntary spread of feeling without any conscious awareness of where the feeling initially originated [451 and without necessarily requiring interpersonal empathy. For example, a child's emotion, be it excitement or a tantrum, can rapidly influence the emotion of others, generating a group of rowdy and energetic children. Adults too can experience such contagion, as when one can automatically pick up the excitement in a crowd or audience. However, unlike empathy, emotional contagion does not require understanding another's emotion and is largely involuntary, a less conscious and more 'infectious' effect, relying principally on non-verbal communication (although the 'online world' of emails and instant messaging can also be susceptible to emotional contagion, where emotion can be transmitted without non-verbal cues [461). It is not yet clear how this domain is related to other contagious behaviours in humans such as laughter [471 and yawning [481 or to what extent these contagious behaviours arise through cultural or innate processes [491.
 
Given the importance of implicit processes in social cognition and the possibility that emotions play an adaptive role in the social environment [501, it follows that fast, automatic and perhaps unconscious routines [351 provide a signalling channel to transmit messages to all members of the group. The analogy with animal herding of this ripple effect [511, where moods can ripple out, influencing group members' emotions, their group dynamics and individual cognitions, provides an evolutionary perspective into these behaviours and suggests that they are crucial for the maintenance of societal norms. Thus, the notion of emotional contagion can be extended to the broader concept of social contagion: the tendency to automatically mimic and synchronize expressions, vocalizations, postures and movements with those of another person leading to behavioural convergence [521.
 
A strong form of contagion is termed hysterical contagion (also termed mass hysteria, collective hysteria or even mass psychogenic illness). A common manifestation of mass hysteria occurs when a group of people (falsely) believe that they are suffering from a similar disease or ailment [53-561. Such manifestations have been reported as far back as 1374 (with dancing mania reaching such an extreme that it caused deaths) [571. Other manifestations of the dark side of social contagion are displayed in mobs, riots and hooliganism [581. These latter phenomena highlight the importance of a framework in organizing different approaches, as they indicate examples of behaviour which most likely draw upon both mentalizing and non-mentalizing drivers.
 
There is, of course, another example of an implicit effect, well researched by psychologists, which has applications for herding, namely priming: another example of a nonmentalizing phenomenon. People can be primed into certain forms of similar behaviour, with primes ranging from smells [591, everyday objects [601, the surroundings [611, to the performance of activities such as marching or dancing in unison which increase loyalty to the group [62,631. More worryingly, on a larger scale, the news media [64,651 implicitly influence the public, creating mass movements of the herd that are invisible to the individual.
 
What can social neuroscience say?
 
A point of interaction between these two levels concerns the biological mechanisms that underlie herding. Social neuroscience is ideally positioned to connect these levels. Social structures may be emergent organizations beyond the individual, yet these emergent organizations require biological systems in the individual to create them [66,671. Furthermore, there is a large body of work on imitation [681. Mirror neurons (nerve cells that fire when we carry out an action, or watch someone else carry out a similar action) may also play a role in this interaction between the individual and the herd. Neural evidence seems to support this idea as a promising line of research. There are, as yet, few studies investigating the neurobiological correlates of herding mentality, conformity [43,691 and emotional contagion [70,711. However, the evidence so far is promising; for example, it demarcates how emotion circuitry diverges in the adolescent male and female brain under peer approval [721 and rejection [731.
 
There are many areas in which the cognitive neuroscience 'toolbox' can be applied to research in herding. For example, neuroimaging could provide evidence for reinforcement models of information cascades [741. There may also be analogies of quorum sensing (from ethology) in human herding. The communication of chemosensory signals between conspecifics has been well documented in many vertebrates and invertebrates, and as such provides a transmission mechanism for the non-mentalizing approaches to herding. Indeed, in a recent study, pre-exam sweat had a specific effect on brain activity, correlating with areas involved in empathy and those that process social and emotional signals [751.
 
Combining the methods of neuroscience and the diverse approaches presented in Figure 2 can generate powerful tools for studying the brain processes behind human herding. Novel neuroimaging techniques (scanning many individuals at a time) could be used to capture brain-based
 
correlates of herding [761, whereas the emerging field of neuroeconomics [77,781 offers the possibility of characterizing and building biological models of herding (such as the recent imaging study based on a model from economics the 'beauty contest' game - which permits the investigation of how a player's mental processing incorporates the thinking process of others in strategic reasoning [791).
 
Concluding remarks and future directions
 
The concept of herding has been evoked in many different contexts, ranging from mass hysteria in neurology [561 to the diffusion of innovations in economics and to the propagation of ideas [801. These appeals to collective behaviour all imply that certain forms of behaviour go beyond the individual, but different disciplines yield somewhat dissimilar accounts of the mechanisms of herding. To discern structure within this array of approaches requires a broad integrative viewpoint. The framework presented here, similar to other integrative approaches in cognitive psychology [811, has heuristic as well as integrative potential. It presents scaffolding for organizing the questions that can be addressed about herding and the common and diverse mechanisms that underlie it across domains. The proposed classification invites specific interdisciplinary questions to be addressed (see also Box 3). For instance, a pertinent case would be the boundary specification problem of a herd. Dunbar has suggested that the typical size of a social network is restricted to around 150 people due to possible limits in the capacity of the human communication channel [821. How do pattern models integrate this with the limits of cognitive capacity?
 
In the group environment we are exposed to ever shifting emotional messages and are influenced by the social situation and other agents. The convergence upon a single mood or emotion can elicit herd behaviour in which the agents are connected and process stimuli in a similar manner. How stable this contagion is, its neural mechanisms and the role of rational 'top-down' factors remain unclear.
 
Diffusion theory explores social networks and their role in influencing the spread of new ideas and practices. How do authority figures or 'hubs' transmit their information in the more spatial-based transmission models, and can knowledge of cognitive biases or biological limitations in processing influence or provide more accurate parameters for these descriptions?
 
Allying the methods of cognitive neuroscience with the pattern-based and transmission-based perspectives on herding creates both interesting hypotheses and predictions concerning areas of activation associated with selfand other-processing and how the individual transmits (and encodes) information from/to the herd. Interesting herding patterns can be expected to arise within biological constraints that neuroimaging can elucidate, which in turn could provide insight into factors ranging from the rationality of herds [831 to the role of mentalizing and proximity [841.
 
One wonders, in this internet age with the increasing ease of sharing information and ideas [851, and with ever proliferating points of contact between people, whether we will be more susceptible to herding. However, with modern experimental data tracking techniques permitting the analysis of individuals in a top-down manner [86] and neuroscientific methods such as imaging in a bottom-up manner [71], more than ever the fields of social cognition and social neuroscience can play an important role in exploring the ubiquitous yet sometimes disquieting, interaction between the individual and the herd.