Task allocation and partitioning of social insects

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https://en.wikipedia.org/wiki/Task_allocation_and_partitioning_of_social_insects

 

Task allocation and partitioning is the way that tasks are chosen, assigned, subdivided, and coordinated (here, within a single colony of social insects). Closely associated are issues of communication that enable these actions to occur. This entry focuses exclusively on social insects. For information on human task allocation and partitioning, see division of labour, task analysis, and workflow.

Definitions

• Task allocation "... is the process that results in specific workers being engaged in specific tasks, in numbers appropriate to the current situation. [It] operates without any central or hierarchical control..." The concept of task allocation is individual-centric. It focuses on decisions by individuals about what task to perform. However, different biomathematical models give different weights to inter-individual interactions vs. environmental stimuli.
• Task partitioning is the division of one task into sequential actions done by more than one individual. The focus here is on the task, and its division, rather than on the individuals performing it. For example, "hygienic behavior" is a task in which worker bees uncap and remove diseased brood cells that may be affected by American foulbrood (Paenibacillus larvae) or the parasitic mite Varroa destructor. In this case, individual bees often focus on either uncapping or removing diseased brood. Therefore, the task is partitioned, and performed by multiple individuals.

Introduction

Social living provides a multitude of advantages to its practitioners, including predation risk reduction, environmental buffering, food procurement, and possible mating advantages. The most advanced form of sociality is eusociality, characterized by overlapping generations, cooperative care of the young, and reproductive division of labor, which includes sterility or near-sterility of the overwhelming majority of colony members. With few exceptions, all the practitioners of eusociality are insects of the orders Hymenoptera (ants, bees, and wasps), Isoptera (termites), Thysanoptera (thrips), and Hemiptera (aphids). Social insects have been extraordinarily successful ecologically and evolutionarily. This success has at its most pronounced produced colonies 1) having a persistence many times the lifespan of most individuals of the colony, and 2) numbering thousands or even millions of individuals. Social insects can exhibit division of labor with respect to non-reproductive tasks, in addition to the aforementioned reproductive one. In some cases this takes the form of markedly different, alternative morphological development (polymorphism), as in the case of soldier castes in ants, termites, thrips, and aphids, while in other cases it is age-based (temporal polyethism), as with honey bee foragers, who are the oldest members of the colony (with the exception of the queen). Evolutionary biologists are still debating the fitness-advantage gained by social insects due to their advanced division of labor and task allocation, but hypotheses include: increased resilience against a fluctuating environment, reduced energy costs of continuously switching tasks, increased longevity of the colony as a whole, or reduced rate of pathogen transmission. Division of labor, large colony sizes, temporally-changing colony needs, and the value of adaptability and efficiency under Darwinian competition, all form a theoretical basis favoring the existence of evolved communication in social insects. Beyond the rationale, there is well-documented empirical evidence of communication related to tasks; examples include the waggle dance of honey bee foragers, trail marking by ant foragers such as the red harvester ants, and the propagation via pheromones of an alarm state in Africanized honey bees.

Worker Polymorphism

One of the most well known mechanisms of task allocation is worker polymorphism, where workers within a colony have morphological differences. This difference in size is determined by the amount of food workers are fed as larvae, and is set once workers emerge from their pupae. Workers may vary just in size (monomorphism) or size and bodily proportions (allometry). An excellent example of the monomorphism is in bumblebees (Bombus spp.). Bumblebee workers display a large amount of body size variation which is normally distributed. The largest workers may be ten times the mass of the smallest workers. Worker size is correlated with several tasks: larger workers tend to forage, while smaller workers tend to perform brood care and nest thermoregulation. Size also affects task efficiency. Larger workers are better at learning, have better vision, carry more weight, and fly at a greater range of temperatures. However, smaller workers are more resistant to starvation. In other eusocial insects as well, worker size can determine what polymorphic role they become. For instance, larger workers in Myrmecocystus mexicanus (a North America species of honeypot ant) tend to become repletes, or workers so engorged with food that they become immobile and act a living food storage for the rest of the colonies.

In many ants and termites, on the other hand, workers vary in both size and bodily proportions, which have a bimodal distribution. This is present in approximately one in six ant genera. In most of these there are two developmentally distinct pathways, or castes, into which workers can develop. Typically members of the smaller caste are called minors and members of the larger caste are called majors or soldiers. There is often variation in size within each caste. The term soldiers may be apt, as in Cephalotes, but in many species members of the larger caste act primarily as foragers or food processors. In a few ant species, such as certain Pheidole species, there is a third caste, called supersoldiers.

Temporal polyethism

Temporal polyethism is a mechanism of task allocation, and is ubiquitous among eusocial insect colonies. Tasks in a colony are allocated among workers based on their age. Newly emerged workers perform tasks within the nest, such as brood care and nest maintenance, and progress to tasks outside the nest, such as foraging, nest defense, and corpse removal as they age. In honeybees, the youngest workers exclusively clean cells, which is then followed by tasks related to brood care and nest maintenance from about 2–11 days of age. From 11– 20 days, they transition to receiving and storing food from foragers, and at about 20 days workers begin to forage. Similar temporal polyethism patterns can be seen in primitive species of wasps, such as Ropalidia marginata as well as the eusocial wasp Vespula germanica. Young workers feed larvae, and then transition to nest building tasks, followed by foraging. Many species of ants also display this pattern. This pattern is not rigid, though. Workers of certain ages have strong tendencies to perform certain tasks, but may perform other tasks if there is enough need. For instance, removing young workers from the nest will cause foragers, especially younger foragers, to revert to tasks such as caring for brood. These changes in task preference are caused by epigenetic changes over the life of the individual. Honeybee workers of different ages show substantial differences in DNA methylation, which causes differences in gene expression. Reverting foragers to nurses by removing younger workers causes changes in DNA methylation similar to younger workers. Temporal polyethism is not adaptive because of maximized efficiency; indeed older workers are actually more efficient at brood care than younger workers in some ant species. Rather it allows workers with the lowest remaining life expectancy to perform the most dangerous tasks. Older workers tend to perform riskier tasks, such as foraging, which has high risks of predation and parasitism, while younger workers perform less dangerous tasks, such as brood care. If workers experience injuries, which shortens their life expectancies, they will start foraging sooner than healthy workers of the same age.

Response-Threshold Model

A dominant theory of explaining the self-organized division of labor in social insect societies such as honey bee colonies is the Response-Threshold Model. It predicts that individual worker bees have inherent thresholds to stimuli associated with different tasks. Individuals with the lowest thresholds will preferentially perform that task. Stimuli could include the “search time” that elapses while a foraging bee waits to unload her nectar and pollen to a receiver bee at the hive, the smell of diseased brood cells, or any other combination of environmental inputs that an individual worker bee encounters. The Response-Threshold Model only provides for effective task allocation in the honey bee colony if thresholds are varied among individual workers. This variation originates from the considerable genetic diversity among worker daughters of a colony due to the queen’s multiple matings.

Network representation of information flow and task allocation

To explain how colony-level complexity arises from the interactions of several autonomous individuals, a network-based approach has emerged as a promising area of social insect research. Social insect colonies can be viewed as a self-organized network, in which interacting elements (i.e. nodes) communicate with each other. As decentralized networks, colonies are capable of distributing information rapidly which facilitates robust responsiveness to their dynamic environments. The efficiency of information flow is critical for colony-level flexibility because worker behavior is not controlled by a centralized leader but rather is based on local information. 

Social insect networks are often non-randomly distributed, wherein a few individuals act as ‘hubs,’ having disproportionately more connections to other nestmates than other workers in the colony. In harvester ants, the total interactions per ant during recruitment for outside work is right-skewed, meaning that some ants are more highly connected than others. Computer simulations of this particular interaction network demonstrated that inter-individual variation in connectivity patterns expedites information flow among nestmates. 

Task allocation within a social insect colony can be modeled using a network-based approach, in which workers are represented by nodes, which are connected by edges that signify inter-node interactions. Workers performing a common task form highly connected clusters, with weaker links across tasks. These weaker, cross-task connections are important for allowing task-switching to occur between clusters. This approach is potentially problematic because connections between workers are not permanent, and some information is broadcast globally, e.g. through pheromones, and therefore does not rely on interaction networks. One alternative approach to avoid this pitfall is to treat tasks as nodes and workers as fluid connections. 

To demonstrate how time and space constraints of individual-level interactions affect colony function, social insect network approaches can also incorporate spatiotemporal dynamics. These effects can impose upper bounds to information flow rate in the network. For example, the rate of information flow through Temnothorax rugatulus ant colonies is slower than would be predicted if time spent traveling and location within the nest were not considered. In Formica fusca L. ant colonies, a network analysis of spatial effects on feeding and the regulation of food storage revealed that food is distributed heterogeneously within colony, wherein heavily loaded workers are located centrally within the nest and those storing less food were located at the periphery.

Studies of inter-nest pheromone trail networks maintained by super-colonies of Argentine ants (Linepithema humile) have shown that different colonies establish networks with very similar topologies. Insights from these analyses revealed that these networks – which are used to guide workers transporting brood, workers and food between nests – are formed through a pruning process, in which individual ants initially create a complex network of trails, which are then refined to eliminate extraneous edges, resulting in a shorter, more efficient inter-nest network. 

Long-term stability of interaction networks has been demonstrated in Odontomachus hastatus ants, in which initially highly connected ants remain highly connected over an extended time period. Conversely, Temnothorax rugatulus ant workers are not persistent in their interactive role, which might suggest that social organization is regulated differently among different eusocial species.

A network is pictorially represented as a graph, but can equivalently be represented as an adjacency list or adjacency matrix. Traditionally, workers are the nodes of the graph, but Fewell prefers to make the tasks the nodes, with workers as the links. O'Donnell has coined the term "worker connectivity" to stand for "communicative interactions that link a colony's workers in a social network and affect task performance". He has pointed out that connectivity provides three adaptive advantages compared to individual direct perception of needs:

1. It increases both the physical and temporal reach of information. With connectivity, information can travel farther and faster, and additionally can persist longer, including both direct persistence (i.e. through pheromones), memory effects, and by initiating a sequence of events.
2. It can help overcome task inertia and burnout, and push workers into performing hazardous tasks. For reasons of indirect fitness, this latter stimulus should not be necessary if all workers in the colony are highly related genetically, but that is not always the case.
3. Key individuals may possess superior knowledge, or have catalytic roles. Examples, respectively, are a sentry who has detected an intruder, or the colony queen.

O'Donnell provides a comprehensive survey, with examples, of factors that have a large bearing on worker connectivity. They include:

• graph degree
• size of the interacting group, especially if the network has a modular structure
• sender distribution (i.e. a small number of controllers vs. numerous senders)
• strength of the interaction effect, which includes strength of the signal sent, recipient sensitivity, and signal persistence (i.e. pheromone signal vs. sound waves)
• recipient memory, and its decay function
• socially-transmitted inhibitory signals, as not all interactions provide positive stimulus
• specificity of both the signal and recipient response
• signal and sensory modalities, and activity and interaction rates

Task taxonomy and complexity

Anderson, Franks, and McShea have broken down insect tasks (and subtasks) into a hierarchical taxonomy; their focus is on task partitioning and its complexity implications. They classify tasks as individual, group, team, or partitioned; classification of a task depends on whether there are multiple vs. individual workers, whether there is division of labor, and whether subtasks are done concurrently or sequentially. Note that in their classification, in order for an action to be considered a task, it must contribute positively to inclusive fitness; if it must be combined with other actions to achieve that goal, it is considered to be a subtask. In their simple model, they award 1, 2, or 3 points to the different tasks and subtasks, depending on its above classification. Summing all tasks and subtasks point values down through all levels of nesting allows any task to be given a score that roughly ranks relative complexity of actions.

Note: model-building

All models are simplified abstractions of the real-life situation. There exists a basic tradeoff between model precision and parameter precision. A fixed amount of information collected, will, if split amongst the many parameters of an overly precise model, result in at least some of the parameters being represented by inadequate sample sizes. Because of the often limited quantities and limited precision of data from which to calculate parameters values in non-human behavior studies, such models should generally be kept simple. Therefore, we generally should not expect models for social insect task allocation or task partitioning to be as elaborate as human workflow ones, for example.

Metrics for division of labor

With increased data, more elaborate metrics for division of labor within the colony become possible. Gorelick and Bertram survey the applicability of metrics taken from a wide range of other fields. They argue that a single output statistic is desirable, to permit comparisons across different population sizes and different numbers of tasks. But they also argue that the input to the function should be a matrix representation (of time spent by each individual on each task), in order to provide the function with better data. They conclude that "... normalized matrix-input generalizations of Shannon's and Simpson's index ... should be the indices of choice when one wants to simultaneously examine division of labor amongst all individuals in a population". Note that these indexes, used as metrics of biodiversity, now find a place measuring division of labor.

Genetics of aggression

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https://en.wikipedia.org/wiki/Genetics_of_aggression

 

The field of psychology has been greatly influenced by the study of genetics. Decades of research have demonstrated that both genetic and environmental factors play a role in a variety of behaviors in humans and animals (e.g. Grigorenko & Sternberg, 2003). The genetic basis of aggression, however, remains poorly understood. Aggression is a multi-dimensional concept, but it can be generally defined as behavior that inflicts pain or harm on another.

Genetic-developmental theory states that individual differences in a continuous phenotype result from the action of a large number of genes, each exerting an effect that works with environmental factors to produce the trait. This type of trait is influenced by multiple factors making it more complex and difficult to study than a simple Mendelian trait (one gene for one phenotype).

History

Past thought on genetic factors influencing aggression tended to seek answers from chromosomal abnormalities. Specifically, four decades ago, the XYY genotype was (erroneously) believed by many to be correlated with aggression. In 1965 and 1966, researchers at the MRC Clinical & Population Cytogenetics Research Unit led by Dr. Court Brown at Western General Hospital in Edinburgh reported finding a much higher than expected nine XYY men (2.9%) averaging almost 6 ft. tall in a survey of 314 patients at the State Hospital for Scotland; seven of the nine XYY patients were mentally retarded. In their initial reports published before examining the XYY patients, the researchers suggested they might have been hospitalized because of aggressive behavior. When the XYY patients were examined, the researchers found their assumptions of aggressive behavior were incorrect. Unfortunately, many science and medicine textbooks quickly and uncritically incorporated the initial, incorrect assumptions about XYY and aggression—including psychology textbooks on aggression.

The XYY genotype first gained wide notoriety in 1968 when it was raised as a part of a defense in two murder trials in Australia and France. In the United States, five attempts to use the XYY genotype as a defense were unsuccessful—in only one case in 1969 was it allowed to go to a jury—which rejected it.

Results from several decades of long-term follow-up of scores of unselected XYY males identified in eight international newborn chromosome screening studies in the 1960s and 1970s have replaced pioneering but biased studies from the 1960s (that used only institutionalized XYY men), as the basis for current understanding of the XYY genotype and established that XYY males are characterized by increased height but are not characterized by aggressive behavior. Though the link currently between genetics and aggression has turned to an aspect of genetics different from chromosomal abnormalities, it is important to understand where the research started and the direction it is moving towards today.

Heritability

Aggression, as well as other behavioral traits, is studied genetically based on its heritability through generations. Heritability models of aggression are mainly based on animals due to the ethical concern in using humans for genetic study. Animals are first selectively bred and then placed in a variety of environmental conditions, allowing researchers to examine the differences of selection in the aggression of animals.

Research methods

As with other topics in behavioral genetics, aggression is studied in three main experimental ways to help identify what role genetics plays in the behavior:

• Heritability studies – studies focused to determine whether a trait, such as aggression, is heritable and how it is inherited from parent to offspring. These studies make use of genetic linkage maps to identify genes associated with certain behaviors such as aggression.
• Mechanism experiments – studies to determine the biological mechanisms that lead certain genes to influence types of behavior like aggression.
• Genetic behavior correlation studies – studies that use scientific data and attempt to correlate it with actual human behavior. Examples include twin studies and adoption studies.

These three main experimental types are used in animal studies, studies testing heritability and molecular genetics, and gene/environment interaction studies. Recently, important links between aggression and genetics have been studied and the results are allowing scientists to better understand the connections.

Selective breeding

The heritability of aggression has been observed in many animal strains after noting that some strains of birds, dogs, fish, and mice seem to be more aggressive than other strains. Selective breeding has demonstrated that it is possible to select for genes that lead to more aggressive behavior in animals. Selective breeding examples also allow researchers to understand the importance of developmental timing for genetic influences on aggressive behavior. A study done in 1983 (Cairns) produced both highly aggressive male and female strains of mice dependent on certain developmental periods to have this more aggressive behavior expressed. These mice were not observed to be more aggressive during the early and later stages of their lives, but during certain periods of time (in their middle-age period) were more violent and aggressive in their attacks on other mice. Selective breeding is a quick way to select for specific traits and see those selected traits within a few generations of breeding. These characteristics make selective breeding an important tool in the study of genetics and aggressive behavior.

Mouse studies

Mice are often used as a model for human genetic behavior since mice and humans have homologous genes coding for homologous proteins that are used for similar functions at some biological levels. Mice aggression studies have led to some interesting insight in human aggression. Using reverse genetics, the DNA of genes for the receptors of many neurotransmitters have been cloned and sequenced, and the role of neurotransmitters in rodent aggression has been investigated using pharmacological manipulations. Serotonin has been identified in the offensive attack by male mice against intruder male mice. Mutants were made by manipulating a receptor for serotonin by deleting a gene for the serotonin receptor. These mutant male mice with the knockout alleles exhibited normal behavior in everyday activities such as eating and exploration, but when prompted, attacked intruders with twice the intensity of normal male mice. In offense aggression in mice, males with the same or similar genotypes were more likely to fight than males that encountered males of other genotypes. Another interesting finding in mice dealt with mice reared alone. These mice showed a strong tendency to attack other male mice upon their first exposure to the other animals. The mice reared alone were not taught to be more aggressive; they simply exhibited the behavior. This implicates the natural tendency related to biological aggression in mice since the mice reared alone lacked a parent to model aggressive behavior.

Oxidative stress arises as a result of excess production of reactive oxygen species in relation to defense mechanisms, including the action of antioxidants such as superoxide dismutase 1 (SOD1). Knockout of the Sod1 gene was experimentally introduced in male mice leading to impaired antioxidant defense. These mice were designated (Sod1-/-). The Sod1-/- male mice proved to be more aggressive than both heterozygous knockout males (Sod1+/-) that were 50% deficient in SOD1, and wild-type males (Sod1+/+). The basis for the association of oxidative stress with increased aggression has not yet been determined.

Biological mechanisms

Experiments designed to study biological mechanisms are utilized when exploring how aggression is influenced by genetics. Molecular genetics studies allow many different types of behavioral traits to be examined by manipulating genes and studying the effect(s) of the manipulation.

Molecular genetics

A number of molecular genetics studies have focused on manipulating candidate aggression genes in mice and other animals to induce effects that can be possibly applied to humans. Most studies have focused on polymorphisms of serotonin receptors, dopamine receptors, and neurotransmitter metabolizing enzymes. Results of these studies have led to linkage analysis to map the serotonin-related genes and impulsive aggression, as well as dopamin-related genes and proactive aggression. In particular, the serotonin 5-HT seems to be an influence in inter-male aggression either directly or through other molecules that use the 5-HT pathway. 5-HT normally dampens aggression in animals and humans. Mice missing specific genes for 5-HT were observed to be more aggressive than normal mice and were more rapid and violent in their attacks. Other studies have been focused on neurotransmitters. Studies of a mutation in the neurotransmitter metabolizing enzyme monoamine oxidase A (MAO-A) have been shown to cause a syndrome that includes violence and impulsivity in humans. Studies of the molecular genetics pathways are leading to the production of pharmaceuticals to fix the pathway problems and hopefully show an observed change in aggressive behavior.

Human behavior genetics

In determining if a trait is related to genetic factors or environmental factors, twin studies and adoption studies are used. These studies examine correlations based on similarity of a trait and a person's genetic or environmental factors that could influence the trait. Aggression has been examined via both twin studies and adoption studies.

Twin studies

Twin studies manipulate the environmental factors of behavior by examining if identical twins raised apart are different from twins raised together. Before the advancement of molecular genetics, twin studies were almost the only mode of investigation of genetic influences on personality. Heritability was estimated as twice the difference between the correlation for identical, or monozygotic, twins and that for fraternal, or dizygotic, twins. Early studies indicated that personality was fifty percent genetic. Current thinking holds that each individual picks and chooses from a range of stimuli and events largely on the basis of his genotype creating a unique set of experiences; basically meaning that people create their own environments.

Social cognitive neuroscience

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https://en.wikipedia.org/wiki/Social_cognitive_neuroscience

 

Social cognitive neuroscience is the scientific study of the biological processes underpinning social cognition. Specifically, it uses the tools of neuroscience to study "the mental mechanisms that create, frame, regulate, and respond to our experience of the social world". Social cognitive neuroscience uses the epistemological foundations of cognitive neuroscience, and is closely related to social neuroscience. Social cognitive neuroscience employs human neuroimaging, typically using functional magnetic resonance imaging (fMRI). Human brain stimulation techniques such as transcranial magnetic stimulation and transcranial direct-current stimulation are also used. In nonhuman animals, direct electrophysiological recordings and electrical stimulation of single cells and neuronal populations are utilized for investigating lower-level social cognitive processes.

History and methods

The first scholarly works about the neural bases of social cognition can be traced back to Phineas Gage, a man who survived a traumatic brain injury in 1849 and was extensively studied for resultant changes in social functioning and personality. In 1924, esteemed psychologist Gordon Allport wrote a chapter on the neural bases of social phenomenon in his textbook of social psychology. However, these works did not generate much activity in the decades that followed. The beginning of modern social cognitive neuroscience can be traced to Michael Gazzaniga's book, Social Brain (1985), which attributed cerebral lateralization to the peculiarities of social psychological phenomenon. Isolated pockets of social cognitive neuroscience research emerged in the late 1980s to the mid-1990s, mostly using single-unit electrophysiological recordings in nonhuman primates or neuropsychological lesion studies in humans. During this time, the closely related field of social neuroscience emerged in parallel, however it mostly focused on how social factors influenced autonomic, neuroendocrine, and immune systems. In 1996, Giacomo Rizzolatti's group made one of the most seminal discoveries in social cognitive neuroscience: the existence of mirror neurons in macaque frontoparietal cortex. The mid-1990s saw the emergence of functional positron emission tomography (PET) for humans, which enabled the neuroscientific study of abstract (and perhaps uniquely human) social cognitive functions such as theory of mind and mentalizing. However, PET is prohibitively expensive and requires the ingestion of radioactive tracers, thus limiting its adoption.

In the year 2000, the term social cognitive neuroscience was coined by Matthew Lieberman and Kevin Oschner, who are from social and cognitive psychology backgrounds, respectively. This was done to integrate and brand the isolated labs doing research on the neural bases of social cognition. Also in the year 2000, Elizabeth Phelps and colleagues published the first fMRI study on social cognition, specifically on race evaluations. The adoption of fMRI, a less expensive and noninvasive neuroimaging modality, induced explosive growth in the field. In 2001, the first academic conference on social cognitive neuroscience was held at University of California, Los Angeles. The mid-2000s saw the emergence of academic societies related to the field (Social and Affective Neuroscience Society, Society for Social Neuroscience), as well as peer-reviewed journals specialized for the field (Social Cognitive and Affective Neuroscience, Social Neuroscience). In the 2000s and beyond, labs conducting social cognitive neuroscience research proliferated throughout Europe, North America, East Asia, Australasia, and South America.

Starting in the late 2000s, the field began expand its methodological repertoire by incorporating other neuroimaging modalities (e.g. electroencephalography, magnetoencephalography, functional near-infared spectroscopy), advanced computational methods (e.g. multivariate pattern analysis, causal modeling, graph theory), and brain stimulation techniques (e.g. transcranial magnetic stimulation, transcranial direct-current stimulation, deep brain stimulation). Due to the volume and rigor of research in the field, the 2010s saw social cognitive neuroscience achieving mainstream acceptance in the wider fields of neuroscience and psychology.

Functional anatomy

Much of social cognition is primarily subserved by two dissociable macro-scale brain networks: the mirror neuron system (MNS) and default mode network (DMN). MNS is thought to represent and identify observable actions (e.g. reaching for a cup) that are used by DMN to infer unobservable mental states, traits, and intentions (e.g. thirsty). Concordantly, the activation onset of MNS has been shown to precede DMN during social cognition. However, the extent of feedforward, feedback, and recurrent processing within and between MNS and DMN is not yet well-characterized, thus it is difficult to fully dissociate the exact functions of the two networks and their nodes.

Mirror neuron system (MNS)

Mirror neurons, first discovered in macaque frontoparietal cortex, fire when actions are either performed or observed. In humans, similar sensorimotor "mirroring" responses have been found in the brain regions listed below, which are collectively referred to as MNS. The MNS is has been found to identify and represent intentional actions such as facial expressions, body language, and grasping. MNS may encode the concept of an action, not just the sensory and motor information associated with an action. As such, MNS representations have been shown to be invariant of how an action is observed (e.g. sensory modality) and how an action is performed (e.g. left versus right hand, upwards or downwards). MNS has even been found to represent actions that are described in written language.

Mechanistic theories of MNS functioning fall broadly into two camps: motor and cognitive theories. Classical motor theories claim that abstract action representations arise from simulating actions within the motor system, while newer cognitive theories propose that abstract action representations arise from the integration of multiple domains of information: perceptual, motor, semantic, and conceptual. Aside from these competing theories, there are more fundamental controversies surrounding the human MNS – even the very existence of mirror neurons in this network is debated. As such, the term "MNS" is sometimes eschewed for more functionally defined names such as "action observation network", "action identification network", and "action representation network".

Premotor cortex

The macaque premotor cortex was the location of the first discoveries of mirror neurons. The premotor cortex is associated with a diverse array of functions, encompassing low-level motor control, motor planning, sensory guidance of movement, along with higher level cognitive functions such as language processing and action comprehension. The premotor cortex has been found to contain subregions with unique cytoarchitectural properties, the significance of which is not yet fully understood. In humans, sensorimotor mirroring responses are also found throughout premotor cortex and adjacent sections of inferior frontal gyrus and supplementary motor area.

Visuospatial information is more prevalent in ventral premotor cortex than dorsal premotor cortex. In humans, sensorimotor mirroring responses extend beyond ventral premotor cortex into adjacent regions of inferior frontal gyrus, including Broca's area, an area that is critical to language processing and speech production. Action representations in inferior frontal gyrus can be evoked by language, such as action verbs, in addition to the observed and performed actions typically used as stimuli in biological motion studies. The overlap between language and action understanding processes in inferior frontal gyrus has spurred some researchers to suggest overlapping neurocomputational mechanisms between the two. Dorsal premotor cortex is strongly associated with motor preparation and guidance, such as representing multiple motor choices and deciding the final selection of action.

Intraparietal sulcus

Classical studies of action observation have found mirror neurons in macaque intraparietal sulcus. In humans, sensorimotor mirroring responses are centered around the anterior intraperietal sulcus, with responses also seen in adjacent regions such as inferior parietal lobule and superior parietal lobule. Intraparietal sulcus has been shown to more sensitive to the motor features of biological motion, relative to semantic features. Intraparietal sulcus has been shown to encode magnitude in a domain-general manner, whether it be the magnitude of a motor movement, or the magnitude of a person's social status. Intraparietal sulcus is considered a part of the dorsal visual stream, but is also thought to receive inputs from non-dorsal stream regions such as lateral occipitotemporal cortex and posterior superior temporal sulcus.

Lateral occipitotemporal cortex (LOTC)

LOTC encompasses lateral regions of the visual cortex such as V5 and extrastriate body area. Though LOTC is typically associated with visual processing, sensorimotor mirroring responses and abstract action representations are reliably found in this region. LOTC includes cortical areas that are sensitive to motion, objects, body parts, kinematics, body postures, observed movements, and semantic content in verbs. LOTC is thought to encode the fine sensorimotor details of an observed action (e.g. local kinematic and perceptual features). LOTC is also thought to bind together the different means by which a specific action can be carried out.

Default mode network (DMN)

The default mode network (DMN) is thought to process and represent abstract social information, such as mental states, traits, and intentions. Social cognitive functions such as theory of mind, mentalizing, emotion recognition, empathy, moral cognition, and social working memory consistently recruit DMN regions in human neuroimaging studies. Though the functional anatomy of these functions can differ, they often include the core DMN hubs of medial prefrontal cortex, posterior cingulate, and temporoparietal junction. Aside from social cognition, the DMN is broadly associated with internally directed cognition. The DMN has been found to be involved in memory-related processing (semantic, episodic, prospection), self-related processing (e.g. introspection), and mindwandering. Unlike studies of the mirror neuron system, task-based DMN investigations almost always use human subjects, as DMN-related social cognitive functions are rudimentary or difficult to measure in nonhumans. However, much of DMN activity occurs during rest, as DMN activation and connectivity are quickly engaged and sustained during the absence of goal-directed cognition. As such, the DMN is widely thought the subserve the "default mode" of mammalian brain function.

The interrelations between social cognition, rest, and the diverse array of DMN-related functions are not yet well understood and is a topic of active research. Social, non-social, and spontaneous processes in the DMN are thought to share at least some underlying neurocomputational mechanisms with each other.

Medial prefrontal cortex (mPFC)

Medial prefrontal cortex (mPFC) is strongly associated with abstract social cognition such as mentalizing and theory of mind. Mentalizing about others activates much of the mPFC, but dorsal mPFC appears to be more selective for information about other people, while the middle mPFC may be more selective for information about the self.

Ventral regions of mPFC, such as ventromedial prefrontal cortex and medial orbitofrontal cortex, are thought to play a critical role in the affective components of social cognition. For example, ventromedial prefrontal cortex has been found to represent affective information about other people. Ventral mPFC has been shown to be critical in the computation and representation of valence and value for many types of stimuli, not just social stimuli.

The mPFC may subserve the most abstract components of social cognition, as it is one of the most domain general brain regions, sits at the top of the cortical hierarchy, and is last to activate during DMN-related tasks.

Posterior cingulate cortex (PCC)

Abstract social cognition recruits a large area of posteromedial cortex centered around posterior cingulate cortex (PCC), but also extending into precuneus and retrosplenial cortex. The specific function of PCC in social cognition is not yet well characterized, and its role may be generalized and tightly linked with medial prefrontal cortex. One view is that PCC may help represent some visuospatial and semantic components of social cognition. Additionally, PCC may track social dynamics by facilitating bottom-up attention to behaviorally relevant sources of information in the external environment and in memory. Dorsal PCC is also linked to monitoring behaviorally relevant changes in the environment, perhaps aiding in social navigation. Outside of the social domain, PCC is associated with a very diverse array of functions, such as attention, memory, semantics, visual processing, mindwandering, consciousness, cognitive flexibility, and mediating interactions between brain networks.

Temporoparietal junction (TPJ)

The temporoparietal junction (TPJ) is thought to be critical to distinguishing between multiple agents, such as the self and other. The right TPJ is robustly activated by false belief tasks, in which subjects have to distinguish between others' beliefs and their own beliefs in a given situation. The TPJ is also recruited by the wide variety of abstract social cognitive tasks associated with the DMN. Outside of the social domain, TPJ is associated with a diverse array of functions such as attentional reorienting, target detection, contextual updating, language processing, and episodic memory retrieval. The social and non-social functions of the TPJ may share common neurocomputational mechanisms. For example, the substrates of attentional reorientation in TPJ may be used for reorienting attention between the self and others, and for attributing attention between social agents. Moreover, a common neural encoding mechanism has been found to instantiate social, temporal, and spatial distance in TPJ.

Superior temporal sulcus (STS)

Social tasks recruit areas of lateral temporal cortex centered around superior temporal sulcus (STS), but also extending to superior temporal gyrus, middle temporal gyrus, and the temporal poles. During social cognition, the anterior STS and temporal poles are strongly associated with abstract social cognition and person information, while the posterior STS is most associated with social vision and biological motion processing. The posterior STS is also thought to provide perceptual inputs to the mirror neuron system.

Other regions

There are also several brain regions that fall outside the MNS and DMN which are strongly associated with certain social cognitive functions.

Ventrolateral prefrontal cortex (VLPFC)

The ventrolateral prefrontal cortex (VLPFC) is associated with emotional and inhibitory processing. It has been found to be involved in emotion recognition from facial expressions, body language, prosody, and more. Specifically, it is thought to access semantic representations of emotional constructs during emotion recognition. Moreover, VLPFC is often recruited in empathy, mentalizing, and theory of mind tasks. VLPFC is thought to support the inhibition of self-perspective when thinking about other people.

Insula

The insula is critical to emotional processing and interoception. It has been found to be involved in emotion recognition, empathy, morality, and social pain. The anterior insula is thought to facilitate feeling the emotions of others, especially negative emotions such as vicarious pain. Lesions of the insula are associated with decreased empathy capacity. Anterior insula also activates during social pain, such as the pain caused by social rejection.

Anterior cingulate cortex (ACC)

The anterior cingulate cortex (ACC) is associated with emotional processing and error monitoring. The dorsal ACC appears to share some social cognitive functions to the anterior insula, such as facilitating feeling the emotions of others, especially negative emotions. The dorsal ACC also robustly activates during social pain, like the pain caused by being the victim of an injustice. The dorsal ACC is also associated with social evaluation, such as the detection and appraisal of social exclusion. The subgenual ACC has been found to activate for vicarious reward, and may be involved in prosocial behavior.

Fusiform face area (FFA)

The fusiform face area (FFA) is strongly associated with face processing and perceptual expertise. The FFA has been shown to process the visuospatial features of faces, and may also encode some semantic features of faces.

Social behavior

From Wikipedia, the free encyclopedia

https://en.wikipedia.org/wiki/Social_behavior

 

Social behavior is behavior among two or more organisms within the same species, and encompasses any behavior in which one member affects the other. This is due to an interaction among those members. Social behavior can be seen as similar to an exchange of goods, with the expectation that when you give, you will receive the same. This behavior can be effected by both the qualities of the individual and the environmental (situational) factors. Therefore, social behavior arises as a result of an interaction between the two—the organism and its environment. This means that, in regards to humans, social behavior can be determined by both the individual characteristics of the person, and the situation they are in.

A group of women gathered around, talking. This is an example of social behavior.

 

A major aspect of social behavior is communication, which is the basis for survival and reproduction. Social behavior is said to be determined by two different processes, that can either work together or oppose one another. The dual-systems model of reflective and impulsive determinants of social behavior came out of the realization that behavior cannot just be determined by one single factor. Instead, behavior can arise by those consciously behaving (where there is an awareness and intent), or by pure impulse. These factors that determine behavior can work in different situations and moments, and can even oppose one another. While at times one can behave with a specific goal in mind, other times they can behave without rational control, and driven by impulse instead.

There are also distinctions between different types of social behavior, such as mundane versus defensive social behavior. Mundane social behavior is a result of interactions in day-to-day life, and are behaviors learned as one is exposed to those different situations. On the other hand, defensive behavior arises out of impulse, when one is faced with conflicting desires.

The Development of Social Behavior

Social behavior constantly changes as one continues to grow and develop, reaching different stages of life. The development of behavior is deeply tied with the biological and cognitive changes one is experiencing at any given time. This creates general patterns of social behavior development in humans. Just as social behavior is influenced by both the situation and an individual's characteristics, the development of behavior is due to the combination of the two as well—the temperament of the child along with the settings they are exposed to.

Culture (parents and individuals that influence socialization in children) play a large role in the development of a child's social behavior, as the parents or caregivers are typically those who decide the settings and situations that the child is exposed to. These various settings the child is placed in (for example, the playground and classroom) form habits of interaction and behavior insomuch as the child being exposed to certain settings more frequently than others. What takes particular precedence in the influence of the setting are the people that the child must interact with—their age, sex, and at times culture.

Emotions also play a large role in the development of social behavior, as they are intertwined with the way an individual behaves. Through social interactions, emotion is understood through various verbal and nonverbal displays, and thus plays a large role in communication. Many of the processes that occur in the brain and underlay emotion often greatly correlate with the processes that are needed for social behavior as well. A major aspect of interaction is understanding how the other person thinks and feels, and being able to detect emotional states becomes necessary for individuals to effectively interact with one another and behave socially.

As the child continues to gain social information, their behavior develops accordingly. One must learn how to behave according to the interactions and people relevant to a certain setting, and therefore begin to intuitively know the appropriate form of social interaction depending on the situation. Therefore, behavior is constantly changing as required, and maturity brings this on. A child must learn to balance their own desires with those of the people they interact with, and this ability to correctly respond to contextual cues and understand the intentions and desires of another person improves with age. That being said, the individual characteristics of the child (their temperament) is important to understanding how the individual learns social behaviors and cues given to them, and this learnability is not consistent across all children.

Patterns of Development Across the Lifespan

When studying patterns of biological development across the human lifespan, there are certain patterns that are well-maintained across humans. These patterns can often correspond with social development, and biological changes lead to respective changes in interactions.

In pre and post-natal infancy, the behavior of the infant is correlated with that of the caregiver. In infancy, there is already a development of the awareness of a stranger, in which case the individual is able to identify and distinguish between people.

Come childhood, the individual begins to attend more to their peers, and communication begins to take a verbal form. One also begins to classify themselves on the basis of their gender and other qualities salient about themselves, like race and age.

When the child reaches school age, one typically becomes more aware of the structure of society in regards to gender, and how their own gender plays a role in this. They become more and more reliant on verbal forms of communication, and more likely to form groups and become aware of their own role within the group.

An adult and infant

 

By puberty, general relations among same and opposite sex individuals are much more salient, and individuals begin to behave according to the norms of these situations. With increasing awareness of their sex and stereotypes that go along with it, the individual begins to choose how much they align with these stereotypes, and behaves either according to those stereotypes or not. This is also the time that individuals more often form sexual pairs.

Once the individual reaches childrearing age, one must begin to undergo changes within the own behavior in accordance to major life-changes of a developing family. The potential new child requires the parent to modify their behavior to accommodate a new member of the family.

Come senescence and retirement, behavior is more stable as the individual has often established their social circle (whatever it may be) and is more committed to their social structure.

Neural and Biological Correlates of Social Behavior

Neural Correlates

Rhesus monkey

 

Anatomical location of the amygdala

 

With the advent of the field social cognitive neuroscience came interest in studying social behavior's correlates within the brain, to see what is happening beneath the surface as organisms act in a social manner. Although there is debate on which particular regions of the brain are responsible for social behavior, some have claimed that the paracingulate cortex is activated when one person is thinking about the motives or aims of another, a means of understanding the social world and behaving accordingly. The medial prefrontal lobe has also been seen to have activation during social cognition  Research has discovered through studies on rhesus monkeys that the amygdala, a region known for expressing fear, was activated specifically when the monkeys were faced with a social situation they had never been in before. This region of the brain was shown to be sensitive to the fear that comes with a novel social situation, inhibiting social interaction.

Another form of studying the brain regions that may be responsible for social behavior has been through looking at patients with brain injuries who have an impairment in social behavior. Lesions in the prefrontal cortex that occurred in adulthood can effect the functioning of social behavior. When these lesions or a dysfunction in the prefrontal cortex occur in infancy/early on in life, the development of proper moral and social behavior is effected and thus atypical.

Biological Correlates

A prairie vole

 

Along with neural correlates, research has investigated what happens within the body (and potentially modulates) social behavior. Vasopressin is a posterior pituitary hormone that is seen to potentially play a role in affiliation for young rats. Along with young rats, vasopressin has also been associated with paternal behavior in prairie voles. Efforts have been made to connect animal research to humans, and found that vasopressin may play a role in the social responses of males in human research.

Oxytocin has also been seen to be correlated with positive social behavior, and elevated levels have been shown to potentially help improve social behavior that may have been suppressed due to stress. Thus, targeting levels of oxytocin may play a role in interventions of disorders that deal with atypical social behavior.

Along with vasopressin, serotonin has also been inspected in relation to social behavior in humans. It was found to be associated with human feelings of social connection, and we see a drop in serotonin when one is socially isolated or has feelings of social isolation. Serotonin has also been associated with social confidence.

Affect and Social Behavior

Positive affect (emotion) has been seen to have a large impact on social behavior, particularly by inducing more helping behavior, cooperation, and sociability. Studies have shown that even subtly inducing positive affect within individuals caused greater social behavior and helping. This phenomenon, however, is not one-directional. Just as positive affect can influence social behavior, social behavior can have an influence on positive affect.

Electronic Media and Social Behavior

Social behavior has typically been seen as a changing of behaviors relevant to the situation at hand, acting appropriately with the setting one is in. However, with the advent of electronic media, people began to find themselves in situations they may have not been exposed to in everyday life. Novel situations and information presented through electronic media has formed interactions that are completely new to people. While people typically behaved in line with their setting in face-to-face interaction, the lines have become blurred when it comes to electronic media. This has led to a cascade of results, as gender norms started to merge, and people were coming in contact with information they had never been exposed to through face-to-face interaction. A political leader could no longer tailor a speech to just one audience, for their speech would be translated and heard by anyone through the media. People can no longer play drastically different roles when put in different situations, because the situations overlap more as information is more readily available. Communication flows more quickly and fluidly through media, causing behavior to merge accordingly.

An example of helping behavior

 

Media has also been shown to have an impact on promoting different types of social behavior, such as prosocial and aggressive behavior. For example, violence shown through the media has been seen to lead to more aggressive behavior in its viewers. Research has also been done investigating how media portraying positive social acts, prosocial behavior, could lead to more helping behavior in its viewers. The general learning model was established to study how this process of translating media into behavior works, and why. This model suggests a link between positive media with prosocial behavior and violent media with aggressive behavior, and posits that this is mediated by the characteristics of the individual watching along with the situation they are in. This model also presents the notion that when one is exposed to the same type of media for long periods of time, this could even lead to changes within their personality traits, as they are forming different sets of knowledge and may be behaving accordingly.

In various studies looking specifically at how video games with prosocial content effect behavior, it was shown that exposure influenced subsequent helping behavior in the video-game player.^[23] The processes that underlay this effect point to prosocial thoughts being more readily available after playing a video game related to this, and thus the person playing the game is more likely to behave accordingly. These effects were not only found with video games, but also with music, as people listening to songs involving aggression and violence in the lyrics were more likely to act in an aggressive manner. Likewise, people listening to songs related to prosocial acts (relative to a song with neutral lyrics) were shown to express greater helping behaviors and more empathy afterwards. When these songs were played at restaurants, it even led to an increase in tips given (relative to those who heard neutral lyrics).

Aggressive and Violent Behavior

Aggression is an important social behavior that can have both negative consequences (in a social interaction) and adaptive consequences (adaptive in humans and other primates for survival). There are many differences in aggressive behavior, and a lot of these differences are sex-difference based.

Verbal, Coverbal, and Nonverbal Social Behavior

Verbal and Coverbal Behaviors

An example of hand gestures and facial expression accompanying speech.

 

Although most animals can communicate nonverbally, humans have the ability to communicate with both verbal and nonverbal behavior. Verbal behavior is the content one's spoken word. Verbal and nonverbal behavior intersect in what is known as coverbal behavior, which is nonverbal behavior that contribute to the meaning of verbal speech (i.e. hand gestures used to emphasize the importance of what someone is saying). Although the spoken words convey meaning in and of themselves, one cannot dismiss the coverbal behaviors that accompany the words, as they place great emphasis on the thought and importance contributing to the verbal speech. Therefore, the verbal behaviors and gestures that accompany it work together to make up a conversation. Although many have posited this idea that nonverbal behavior accompanying speech serves an important role in communication, it is important to note that not all researchers agree. However, in most literature on gestures, we see that unlike body language, gestures can accompany speech in ways that bring inner thoughts to life (often thoughts unable to be expressed verbally). Gestures (coverbal behaviors) and speech occur simultaneously, and develop along the same trajectory within children as well.

Nonverbal Behaviors

An example of a nonverbal behavior (facial expression, smile)

 

Behaviors that include any change in facial expression or body movement constitute the meaning of nonverbal behavior. Communicative nonverbal behavior include facial and body expressions that are intentionally meant to convey a message to those who are meant to receive it. Nonverbal behavior can serve a specific purpose (i.e. to convey a message), or can be more of an impulse/reflex. Paul Ekman, an influential psychologist, investigated both verbal and nonverbal behavior (and their role in communication) a great deal, emphasizing how difficult it is to empirically test such behaviors. Nonverbal cues can serve the function of conveying a message, thought, or emotion both to the person viewing the behavior and the person sending these cues.

Disorders Involving Impairments in Social Behavior

Social Anxiety Disorder

Social Anxiety Disorder is a phobic disorder characterized by a fear of being judged by others, which manifests itself as a fear of people in general. Due to this pervasive fear of embarrassing oneself in front of others, it causes those affected to avoid interactions with other people at all costs. People who classify as having Social Anxiety Disorder typically have low self-esteem due to being highly critical of themselves, and thus avoid contact for fear of being "exposed" as unlikable. Efforts to find the neural correlates associated with Social Anxiety Disorder have turned to functional neuroimaging, which has found that Social Anxiety Disorder is greatly associated with hyperactivity of the amygdala, the brain area activated during fear.

Attention Deficit Hyperactivity Disorder

ADHD is a neurodevelopmental disorder mainly identified by its symptoms of inattention, hyperactivity, and impulsivity. Hyperactivity-Impulsivity may lead to hampered social interactions, as one who displays these symptoms may be socially intrusive, unable to maintain personal space, and talk over others. The majority of children that display symptoms of ADHD also have problems with their social behavior. Although children may not identify these social problems within themselves, their caregivers, adults in their lives, and other children their age frequently report it. Children who have ADHD tend to be more frequently and quickly rejected by their peers, and their social skills tend to be less developed than those of the others in their age-group. Early social behavior difficulties within childhood can lead to further, more serious problems in adulthood (i.e. unruly behavior, problems with school, work, and potentially substance abuse). Studies have shown that while it seems as though those with ADHD have the information of social norms (according to their age) readily available, they have a hard time translating this knowledge to their own behavior.

Autism Spectrum

Autism Spectrum Disorder is a neurodevelopmental disorder that affects the functioning of social interaction and communication. People who fall on the autism spectrum scale may have difficulties in understanding social cues and the emotional states of others. Due to this, one may find it difficult to modulate behavior according to the situation, and act according to the setting's standards. Along the spectrum of autism includes Aspergers Syndrome, which contains the atypical functioning of social interaction and communication seen in autism, but without a clinically significant delay of cognitive and language abilities. Research is still being done to investigate which brain regions are involved in Autism Spectrum Disorder. In regards to abnormalities that often occur in Autism Spectrum Disorder, one who classifies as among the spectrum may have a series of symptoms, such as difficulty or inability to maintain eye-contact with another person, and communicate via face and body expression. One may have a hard time forming relationships with their peers, and have a difficult time forming mutual interests and sharing a common excitement with others. Language may be impaired to those on the low-end of the spectrum, which affects conversation and communication with others.

Learning Disability

Learning disabilities are often defined as a specific deficit in academic achievement; however, research has shown that with a learning disability can come social skill deficits as well. The National Joint Committee on Learning Disabilities now include delays in social interaction within the definition of learning disability. A growing body of research has studied the close connection between academic and social delays, and has seen that those with learning disabilities are at greater risk for experiencing social skill deficits than those who do not have an academic achievement delay. There is not enough evidence to claim that academic deficits are the cause of subsequent social delays, however, there is a strong correlation between the two.