Family violence against children in the wake of COVID-19 pandemic: a review of current perspectives and risk factors

Child and Adolescent Psychiatry and Mental Health, Journal Year: 2020, Volume and Issue: 14(1)

Published: Oct. 20, 2020

Abstract The situation of crisis produced by the Coronavirus (COVID-19) pandemic poses major challenges to societies all over world. While efforts contain virus are vital protect global health, these same exposing children and adolescents an increased risk family violence. Various criminological theories explain causes this new danger. social isolation required measures taken in different countries, impact on jobs, economic instability, high levels tension fear virus, forms relationships have stress most vulnerable families and, therefore, In addition, mandatory lockdowns imposed curb spread disease trapped their homes, isolating them from people resources that could help them. general, restrictive many countries not been accompanied analysis access needed reduce risk. It is necessary take urgent intervene high-risk contexts so can develop prosper a society which likely undergo profound changes, but defense rights protection must remain priority.

Language: Английский

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Is There a ‘Social’ Brain? Implementations and Algorithms

Trends in Cognitive Sciences, Journal Year: 2020, Volume and Issue: 24(10), P. 802 - 813

Published: July 28, 2020

A central question in psychology and neuroscience is the extent to which social behaviour subserved by dedicated processes or systems that are 'socially specific' shared with other 'non-social' cognitive, perceptual, motor faculties.We suggest a process can be socially specific at different levels of explanation. This approach could help clarify role mirror neurons contexts whether learning uniquely 'social'. Experimental design should guided an appreciation specificity possible levels.Examining across species give unique clues about implementations algorithms. For example, converging evidence highlights anterior cingulate gyrus as crucial for processing implementations, 'theory mind' putative algorithm. fundamental cognitive neural specialised behaviour, faculties. Here we apply influential framework Marr (1982) research humans, monkeys, rodents propose information understood 'social' levels. We argue implementational and/or algorithmic level, changing goal also change specificity. provide important new insights into nature species, facilitate greater integration, inspire novel theoretical empirical approaches. Many behaviours occur context. Social behaviours, some form, exhibited surprisingly broad array from single-celled microorganisms [1.Crespi B.J. The evolution behavior microorganisms.Trends Ecol. Evol. 2001; 16: 178-183Abstract Full Text PDF PubMed Scopus (387) Google Scholar] [2.Chen P. Hong W. Neural circuit mechanisms behavior.Neuron. 2018; 98: 16-30Abstract (174) Scholar], fish [3.Bshary R. et al.Social cognition fishes.Trends Cogn. Sci. 2014; 18: 465-471Abstract (92) primates [4.Wittmann M.K. al.Neural primates.Annu. Rev. Neurosci. 41: 99-118Crossref (58) Scholar]. However, core there processes, brain areas, circuits, cells manner specific. That is, come online only situations way somehow what required motor, perceptual abilities? draw on pioneering idea Marr's (see Glossary) [5.Marr D. Vision. MIT Press, 1982Google understand test not. may considered level – it encodes algorithm rule being processed non-social domain same used, but area, circuit, cell. Moreover, information-processing system (computational level), such during cooperation competition, specialisation These description often overlooked when studying contexts. contend this lead inaccurate conclusions specialised, call more nuanced phrase 'the brain' beyond its simple connotation. argued that, system, consider multiple explanation computational, algorithmic, (Figure 1) [6.Krakauer J.W. al.Neuroscience needs behavior: correcting reductionist bias.Neuron. 2017; 93: 480-490Abstract (595) highest description, describes 'why' intends perform. if want bird flight cannot do so 'by feathers' first need know fly. second 'what' rules does particular operation? would bird's flapping wings. final implementational, 'how' achieves operation. bird, feathers. How behaviour? computational interactions dictated intentions agent, cooperating, affiliating, competing conspecifics. particular, formalised, model deployed engaging interaction. Lastly, region, cell realised. Although number their independence debated Scholar,7.Bickle J. reductionism.Top. 2015; 7: 299-311Crossref (25) theory provides organising suggesting delineated most point specific, must dissociation between either implemental levels, alternative, similar, domain-general ruled out. offers several debates neuroscience. two notable examples. Mirror 'common currency' accounts encoded based overlap implementation (the neuron fires similarly, fMRI blood oxygen level-dependent, BOLD, response) first- third-person events. Examples include pain self another [8.Lamm C. al.Meta-analytic common distinct networks associated directly experienced empathy pain.Neuroimage. 2011; 54: 2492-2502Crossref (1295) Scholar,9.Fan Y. al.Is network empathy? An quantitative meta-analysis.Neurosci. Biobehav. 35: 903-911Crossref (628) monetary reward [10.Ruff C.C. Fehr E. neurobiology rewards values decision making.Nat. 15: 549-562Crossref (404) Scholar,11.Munuera al.Shared coding hierarchy value primate amygdala.Nat. 21: 415-423Crossref (59) one's own another's action goals [12.Umilta M.A. al.I you doing: neurophysiological study.Neuron. 31: 155-165Abstract (796) Scholar,13.Chong T.T.-J. al.fMRI adaptation reveals human inferior parietal cortex.Curr. Biol. 2008; 1576-1580Abstract (256) interpreted coding' namely both understanding, empathy, has occurred mirroring drawn reference level. What used states another? Without manipulating controlling reflect total absence specificity, implementation, one Indeed, clear monitoring actions. not necessarily aiming reproduce actions ourselves, therefore even likely functional dissociation. measured using carefully controlled designs manipulate them anything means (Box 1).Box 1The Importance Non-Social Control ConditionsWhen designing experiment selective think appropriate control conditions. stems basic principles philosophy science necessity falsification [91.Popper K.R. logic scientific discovery. Basic Books, 1959Google find area responds smiling faces reward, conclude encoding something how rewarding stimulus is? have shown involved any process, share feature. studies monkeys included explicit conditions [21.Apps M.A.J. al.The cognition: tracking motivation others.Neuron. 2016; 90: 692-707Abstract (255) Scholar,42.Lockwood P.L. anatomy empathy: vicarious experience disorders cognition.Behav. Brain Res. 311: 255-266Crossref (124) Scholar,45.Chang S.W.C. al.Neuronal frames decisions frontal cortex.Nat. 2013; 243-250Crossref (203) Scholar,47.Rudebeck P.H. al.A macaque valuation.Science. 2006; 313: 1310-1312Crossref (242) Scholar,50.Carrillo M. al.Emotional rat's 2019; 29: 1301-1312Abstract (85) Scholar,51.Hernandez-Lallement al.Harm others acts negative reinforcer rats.Curr. 2020; 30: 949-961Abstract (33) In 'neither' condition been added, where seen delivered neither monkey nor conspecific [45.Chang Scholar,63.Dal Monte O. al.Specialized medial prefrontal–amygdala coordination other-regarding preference.Nat. 23: 565-574Crossref (46) rodent observational fear conditioning, typical classical conditioning condition, without context, employed try out response aversive mind processing, 'computer' physical object introduced show [65.Balsters J.H. al.Disrupted prediction errors index deficits autism spectrum disorder.Brain. 140: 235-246Crossref (48) Scholar,78.Rilling J.K. correlates within interpersonal interactions.Neuroimage. 2004; 22: 1694-1703Crossref (432) Scholar, 79.Gallagher H.L. Frith C.D. Functional imaging mind'.Trends 2003; 77-83Abstract (1597) 80.Apps al.Reinforcement signals cortex code others' false beliefs.NeuroImage. 64: 1-9Crossref (35) Scholar].However, these always part experimental design. Sometimes very difficult create equally matched shares all attributes except sociality person group. example computer people anthropomorphise still associate worth checking participants perceive condition. It well known geometric shapes moving implies interaction [92.Castelli F. al.Movement mind: study perception interpretation complex intentional movement patterns.Neuroimage. 2000; 12: 314-325Crossref (1006) Therefore, factor creating versus appears beliefs non-social, rather than observed behaviour. clearly Stanley colleagues [93.Stanley al.Effects agency interference observation dot stimulus.J. Exp. Psychol. Hum. Percept. Perform. 2007; 33: 915-926Crossref (115) who 2 × probe perceiving stimuli social. Participants dot-motion animations were instructed they prerecorded computer-generated. They manipulated display followed biologically plausible implausible velocity profiles. told reflected movement, regardless profiles supports inducing When Another major debate requires arises associative [14.Heyes What's learning?.J. Comp. 2012; 126: 193-202Crossref (252) 15.Cook al.Mirror neurons: origin function.Behav. 37: 177-192Crossref (314) 16.Catmur al.Associative sequence learning: development imitation system.Philos. Trans. Soc. B 2009; 364: 2369-2380Crossref (202) There growing algorithms indeed personal Scholar,17.Behrens T.E.J. value.Nature. 456: 245-249Crossref (637) 18.Lockwood Klein-Flügge Computational modelling reinforcement primer.Soc. Affect. (Published March 30, 2020. https://doi.org/10.1093/scan/nsaa040)Crossref (37) 19.Olsson A. learning.Nat. 197-212Crossref (78) 20.Lindström B. differentially mediates direct learning.NeuroImage. 167: 121-129Crossref (41) level? contrast increasing consensus circuits outcomes [17.Behrens Scholar,19.Olsson 21.Apps 22.Lockwood al.Neurocomputational prosocial links empathy.Proc. Natl. Acad. U. S. 113: 9763-9768Crossref (107) 23.Lockwood ownership.Nat. Commun. 9: 4747Crossref (40) 24.Apps al.Vicarious instructing others.J. 2904-2913Crossref (47) 25.Sul al.Spatial gradient representation along prefrontal reflects individual differences prosociality.Proc. 112: 7851-7856Crossref (88) Thus, though same. exemplars, highlight addressed considering addresses. Such inform basis. Key addressing empirically will use held constant, lesion stimulation approaches examine impact disrupting disrupt changed. At might algorithm, (RL) then implemented (learning others) self) Considering dissociate analysis generating aim address critical additional tested, identifying 1). following sections hypothesis key examples field non-human primates, rodents. ask why expect explanation? Evolutionarily, animal adapted environments, and, interact conspecifics, environments too [26.Gabay A.S. Apps Foraging optimally neuroscience: computations methodological considerations.Soc. https://doi.org/10.1093/scan/nsaa037)Crossref (9) argues abilities navigating through shaped large brains relative animals [27.Reader S.M. Laland K.N. intelligence, innovation, enhanced size primates.Proc. 2002; 99: 4436Crossref (783) 28.Dunbar R.I.M. Neocortex constraint group primates.J. 1992; 469-493Crossref (1372) 29.Dunbar hypothesis.Evol. Anthropol. Issues News 1998; 6: 178-190Crossref (1657) 30.Sawaguchi T. Kudo H. Neocortical structure primates.Primates. 1990; 283-289Crossref preceding intelligence structures evolutionary pressure drove emergence higher [31.Jolly survey order traces progressive life.Am. 1985; 73: 230-239Google Scholar,32.Humphrey N.K. function intellect.in: Bateson P.P.G. Hinde R.A. Growing Points Ethology. Cambridge University 1976: 303-318Google rodents, olfaction vocalisations strongly linked fitness [33.Matsuo al.Genetic dissection pheromone main olfactory system-mediated behaviors mice.Proc. E311-E320Crossref (63) Scholar,34.Asaba al.Sexual attractiveness male chemicals vocalizations mice.Front. 8: 231Crossref (53) follow specialised. although goes saying humans creatures, complexity boundaries particularly widely Scholar,4.Wittmann Scholar,35.Horschler D.J. al.Do really represent beliefs?.Trends June 24, https://doi.org/10.1016/j.tics.2020.05.009)Abstract (28) Scholar,36.Grimm al.Shedding light circuitry: (un)common blueprints rodents.Neuroscientist. 6, https://doi.org/10.1177/1073858420923552)Crossref (8) whereas many agree engage empathising mind, much controversia

Language: Английский

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A computational reward learning account of social media engagement

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: Feb. 26, 2021

Social media has become a modern arena for human life, with billions of daily users worldwide. The intense popularity social is often attributed to psychological need rewards (likes), portraying the online world as Skinner Box human. Yet despite such portrayals, empirical evidence engagement reward-based behavior remains scant. Here, we apply computational approach directly test whether reward learning mechanisms contribute behavior. We analyze over one million posts from 4000 individuals on multiple platforms, using models based reinforcement theory. Our results consistently show that conforms qualitatively and quantitatively principles learning. Specifically, spaced their maximize average rate accrued rewards, in manner subject both effort cost posting opportunity inaction. Results further reveal meaningful individual difference profiles media. Finally, an experiment (n = 176), mimicking key aspects media, verifies causally influence posited by our account. Together, these findings support account offer new insights into this emergent mode

Language: Английский

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Interbrain synchrony: on wavy ground

Trends in Neurosciences, Journal Year: 2022, Volume and Issue: 45(5), P. 346 - 357

Published: Feb. 28, 2022

Language: Английский

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The mnemonic basis of subjective experience

Nature Reviews Psychology, Journal Year: 2022, Volume and Issue: 1(8), P. 479 - 488

Published: June 1, 2022

Language: Английский

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Algorithm-mediated social learning in online social networks

Trends in Cognitive Sciences, Journal Year: 2023, Volume and Issue: 27(10), P. 947 - 960

Published: Aug. 3, 2023

Language: Английский

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A distinct cortical code for socially learned threat

Nature, Journal Year: 2024, Volume and Issue: 626(8001), P. 1066 - 1072

Published: Feb. 7, 2024

Language: Английский

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Using reinforcement learning models in social neuroscience: frameworks, pitfalls and suggestions of best practices

Social Cognitive and Affective Neuroscience, Journal Year: 2020, Volume and Issue: 15(6), P. 695 - 707

Published: June 1, 2020

Abstract The recent years have witnessed a dramatic increase in the use of reinforcement learning (RL) models social, cognitive and affective neuroscience. This approach, combination with neuroimaging techniques such as functional magnetic resonance imaging, enables quantitative investigations into latent mechanistic processes. However, increased relatively complex computational approaches has led to potential misconceptions imprecise interpretations. Here, we present comprehensive framework for examination (social) decision-making simple Rescorla–Wagner RL model. We discuss common pitfalls its application provide practical suggestions. First, simulation, unpack role rate pinpoint what could easily go wrong when interpreting differences rate. Then, inevitable collinearity between outcome prediction error suggestions how justify whether observed neural activation is related rather than valence. Finally, suggest posterior predictive check crucial step after model comparison, articulate employing hierarchical modeling parameter estimation. aim scalable explanations guidelines assist both beginners advanced users better implementing their model-based analyses.

Language: Английский

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A brain network supporting social influences in human decision-making

Science Advances, Journal Year: 2020, Volume and Issue: 6(34)

Published: Aug. 19, 2020

Social influence modulates choice and confidence in learning the interaction between brain’s reward hub social hub.

Language: Английский

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Computational modelling of social cognition and behaviour—a reinforcement learning primer

Social Cognitive and Affective Neuroscience, Journal Year: 2020, Volume and Issue: unknown

Published: March 25, 2020

Abstract Social neuroscience aims to describe the neural systems that underpin social cognition and behaviour. Over past decade, researchers have begun combine computational models with neuroimaging link computations brain. Inspired by approaches from reinforcement learning theory, which describes how decisions are driven unexpectedness of outcomes, accounts basis prosocial learning, observational mentalizing impression formation been developed. Here we provide an introduction for who wish use these in their studies. We consider both theoretical practical issues related implementation, a focus on specific examples field.

Language: Английский

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