Editing Loss aversion (section)

== Neural aspect ==
In earlier studies, both bidirectional [[Mesolimbic pathway|mesolimbic]] responses of activation for gains and deactivation for losses (or vice versa) and gain or loss-specific responses have been seen. While reward anticipation is associated with ventral [[striatum]] activation,<ref>{{Cite journal|title=Explicit neural signals reflecting reward uncertainty|last=N. Tobler|first=Philippe|journal=Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences|date=1 October 2008|volume=363|issue=1511|pages=3801–11|doi=10.1098/rstb.2008.0152|pmid=18829433|pmc=2581779}}</ref><ref>{{Cite journal|url=https://web.stanford.edu/group/spanlab/Publications/bk05jn.pdf|title=Distributed Neural Representation of Expected Value|last=Knutson|first=Brian|journal=The Journal of Neuroscience|date=2005|volume=25|issue=19|pages=4806–12|doi=10.1523/JNEUROSCI.0642-05.2005|pmid=15888656|pmc=6724773}}</ref> negative outcome anticipation engages the [[amygdala]]. Only some studies have shown involvement of amygdala during negative outcome anticipation but not others,<ref>{{Cite journal|title=Differential Encoding of Losses and Gains in the Human Striatum |date=2007-05-02 |pmc=2630024|pmid=17475790|doi=10.1523/JNEUROSCI.0400-07.2007|volume=27|issue=18 |journal=J Neurosci|pages=4826–31 | last1 = Seymour | first1 = B | last2 = Daw | first2 = N | last3 = Dayan | first3 = P | last4 = Singer | first4 = T | last5 = Dolan | first5 = R}}</ref><ref>{{Cite journal|title=Correspondence of the brain's functional architecture during activation and rest|journal=Proceedings of the National Academy of Sciences|volume=106|issue=31|pages=13040–13045|last=M Smith|first=Stephen|bibcode=2009PNAS..10613040S|year=2009|doi=10.1073/pnas.0905267106|pmid=19620724|pmc=2722273|doi-access=free}}</ref> which has led to some inconsistencies. It has later been proven that inconsistencies may only have been due to methodological issues including the utilisation of different tasks and stimuli, coupled with ranges of potential gains or losses sampled from either payoff matrices rather than parametric designs, and most of the data are reported in groups, therefore ignoring the variability amongst individuals. Rather than focusing on subjects in groups, later studies focus more on individual differences in the neural bases by jointly looking at behavioural analyses and neuroimaging <ref>{{Cite journal|url=http://www.cresa.eu/wp-content/uploads/2013/09/Canessa-Motterlini-et-al.-2013-The-Functional-and-Structural-Neural-Basis-of-Individual-Differences-in-Loss-Aversion.pdf|title=The Functional and Structural Neural Basis of Individual Differences in Loss Aversion|last=Canessa|first=Nicola|journal=The Journal of Neuroscience|date=September 4, 2013|volume=33|issue=36|pages=14307–17|doi=10.1523/JNEUROSCI.0497-13.2013|pmid=24005284|pmc=6618376}}</ref> 

[[Neuroimaging]] studies on loss aversion involves measuring brain activity with [[functional magnetic resonance imaging]] (fMRI) to investigate whether individual variability in loss aversion were reflected in differences in brain activity through bidirectional or gain or loss specific responses, as well as multivariate source-based morphometry (SBM) to investigate a structural network of loss aversion and univariate [[voxel-based morphometry]] (VBM) to identify specific functional regions within this network.<ref>{{Cite journal|title=Joint source based morphometry identifies linked gray and white matter group differences|doi=10.1016/j.neuroimage.2008.09.051|pmid=18992825|volume=44|issue=3|journal=NeuroImage|pages=777–789|pmc=2669793|year=2008|last1=Xu|first1=L.|last2=Pearlson|first2=G.|last3=Calhoun|first3=V. D.}}</ref>

Brain activity in a right ventral striatum cluster increases particularly when anticipating gains. This involves the ventral [[caudate nucleus]], [[Pallium (neuroanatomy)|pallidum]], [[putamen]], bilateral [[orbitofrontal cortex]], superior frontal and middle [[Gyrus|gyri]], [[Posterior cingulate|posterior cingulate cortex]], dorsal [[anterior cingulate cortex]], and parts of the dorsomedial [[thalamus]] connecting to temporal and [[prefrontal cortex]]. There is a significant correlation between degree of loss aversion and strength of activity in both the frontomedial cortex and the ventral striatum. This is shown by the slope of brain activity deactivation for increasing losses being significantly greater than the slope of activation for increasing gains in the appetitive system involving the ventral striatum in the network of reward-based behavioural learning. On the other hand, when anticipating loss, the central and basal nuclei of amygdala, right posterior [[Insular cortex|insula]] extending into the [[supramarginal gyrus]] mediate the output to other structures involved in the expression of fear and anxiety, such as the right [[Operculum (brain)|parietal operculum]] and supramarginal gyrus. Consistent with gain anticipation, the slope of the activation for increasing losses was significantly greater than the slope of the deactivation for increasing gains.

Multiple neural mechanisms are recruited while making choices, showing functional and structural individual variability. Biased anticipation of negative outcomes leading to loss aversion involves specific [[Somatosensory system|somatosensory]] and [[Limbic system|limbic]] structures. fMRI test measuring neural responses in striatal, limbic and somatosensory brain regions help track individual differences in loss aversion. Its limbic component involved the amygdala (associated with [[negative emotion]] and plays a role in the expression of fear) and [[putamen]] in the [[right hemisphere]]. The somatosensory component included the middle [[cingulate cortex]], as well as the posterior insula and [[rolandic operculum]] bilaterally. The latter cluster partially overlaps with the right hemispheric one displaying the loss-oriented bidirectional response previously described, but, unlike that region, it mostly involved the posterior insula bilaterally. All these structures play a critical role in detecting threats and prepare the organism for appropriate action, with the connections between amygdala nuclei and the striatum controlling the avoidance of aversive events. There are functional differences between the right and left amygdala. Overall, the role of amygdala in loss anticipation suggested that loss aversion may reflect a [[Classical conditioning|Pavlovian]] conditioned approach-avoidance response. Hence, there is a direct link between individual differences in the structural properties of this network and the actual consequences of its associated behavioral defense responses. The neural activity involved in the processing of aversive experience and stimuli is not just a result of a temporary fearful overreaction prompted by choice-related information, but rather a stable component of one's own preference function, reflecting a specific pattern of neural activity encoded in the functional and structural construction of a limbic-somatosensory neural system anticipating heightened aversive state of the brain. Even when no choice is required, individual differences in the intrinsic responsiveness of this interoceptive system reflect the impact of anticipated negative effects on evaluative processes, leading preference for avoiding losses rather than acquiring greater but riskier gains.<ref>{{Cite journal|url=https://www.researchgate.net/publication/310649386|title=Neural markers of loss aversion in resting-state brain activity|journal=NeuroImage|volume=146|pages=257–265|last=Canessa|first=Nicole|s2cid=3396784|date=19 November 2016|doi=10.1016/j.neuroimage.2016.11.050|pmid=27884798}}</ref> 

Individual differences in loss aversion are related to variables such as age,<ref>{{Cite journal|title=Behavioral and neural correlates of loss aversion and risk avoidance in adolescents and adults|doi=10.1016/j.dcn.2012.09.007|pmid=23245222|pmc=6987718|volume=3|journal=Dev Cogn Neurosci|pages=72–83 | last1 = Barkley-Levenson | first1 = EE | last2 = Van Leijenhorst | first2 = L | last3 = Galván | first3 = A|year=2013}}</ref> gender, and genetic factors,<ref>{{Cite book|url=https://books.google.com/books?id=nW65CgAAQBAJ&pg=PA49|title=Society Organizations and the Brain: Building towards a UnifiedCognitive Neuroscience Perspective|date=2015-07-02|isbn=9782889195800|last1=Senior|first1=Carl|last2=Lee|first2=Nick|last3=Braeutigam|first3=Sven|publisher=Frontiers Media SA }}</ref> all of which affect thalamic norepinephrine transmission, as well as neural structure and activities. Outcome anticipation and ensuing loss aversion involve multiple neural systems, showing functional and structural individual variability directly related to the actual outcomes of choices. In a study, adolescents and adults are found to be similarly loss-averse on behavioural level but they demonstrated different underlying neural responses to the process of rejecting gambles. Although adolescents rejected the same proportion of trials as adults, adolescents displayed greater caudate and frontal pole activation than adults to achieve this. These findings suggest a difference in neural development during the avoidance of risk. It is possible that adding affectively arousing factors (e.g. peer influences) may overwhelm the reward-sensitive regions of the adolescent decision making system leading to risk-seeking behaviour. On the other hand, although men and women did not differ on their behavioural task performance, men showed greater neural activation than women in various areas during the task. Loss of striatal dopamine neurons is associated with reduced risk-taking behaviour. Acute administration of D2 dopamine agonists may cause an increase in risky choices in humans. This suggests dopamine acting on stratum and possibly other mesolimbic structures can modulate loss aversion by reducing loss prediction signalling.<ref>{{Cite journal|last=Barkley-Levenson|first=Emily|date=1 January 2013|title=Behavioral and neural correlates of loss aversion and risk avoidance in adolescents and adults.|journal= Developmental Cognitive Neuroscience|volume=3|pages=72–83|doi=10.1016/j.dcn.2012.09.007|pmid=23245222|pmc=6987718}}</ref>