definition of mafia hypothesis

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Meet the Cuckoo Mafia

Are you intimidated by this bird? Would you be if it destroyed all your unborn children? Some species of cuckoo and other birds are "brood parasites." This means that instead of raising their own young, they sneak their eggs into other birds' nests and let the adoptive parents do all the work. If you watch these parents taking care of hulking nestlings that are clearly a different species from their own young (and sometimes bully their adoptive siblings out of the nest), it's hard not to see the parents as suckers. But there's evidence for another possibility: that adoptive parents accept baby cuckoos into their nests because they fear violent retaliation if they don't. The "mafia hypothesis" is based on scientists' observations that great spotted cuckoos (above) and brown-headed cowbirds (another brood parasite) can retaliate against birds that oust their eggs. If a host parent tosses a cuckoo or cowbird egg of out its nest, the cuckoo or cowbird parent may return and destroy every other egg that bird has laid. "Mafia" might imply more organization than is really involved—but the idea is that host parents adopt new eggs because they know there's a threat if they don't. To find out whether the controversial mafia hypothesis might be true, Maria Abou Chakra and her colleagues in the Evolutionary Theory Group at Germany's Max Planck Institute ran a series of mathematical simulations. It all comes down to game theory—if murdering baby birds were a game. In the simple version of their model, researchers assumed that each cuckoo (or other brood parasite) can lay only one egg per nest. They assumed two types of cuckoos: "mafia" birds, which after being rejected will destroy a host's entire nest, then return to lay a new egg; and non-mafia birds, which just move on to a new host if their egg is kicked out. And the researchers assumed three types of host birds: accepters, who always take the cuckoo egg; conditional accepters, who only accept an egg if they've already experience retaliation; and rejecters. Every action has a cost. For a host bird, raising a cuckoo baby along with its own young is expensive. But kicking out the cuckoo egg risks getting its whole nest killed, then having to lay all new eggs. For the cuckoo, losing an egg is costly—but so is spending time and energy to monitor the host nest and retaliate if necessary. In this model, the authors saw a cyclical pattern emerge. When most cuckoos are non-mafia, it makes sense for hosts to be conditional accepters: they're probably safe kicking out the first cuckoo egg, but if the cuckoo retaliates they'll take the hint. This creates a fitness advantage for mafia birds, who always retaliate. But as mafia birds become more and more common, it becomes safest for host birds to accept every egg. And once most host birds become accepters, it no longer makes sense for cuckoos to spend the energy on retaliation. So mafia birds will become less common—making it safe for hosts to start booting their eggs again. The cycle starts over. For real birds, things aren't quite this simple. Cuckoos may lay more than one egg per host nest, for example. Hosts can choose between kicking out a cuckoo egg and abandoning their nest to start a new one. And hosts can change their behavior depending on how many cuckoo eggs they find in their nest. The researchers put all these factors into a computer model and ran a large number of simulations to see how evolution would play out. Once again, a cyclical pattern emerged . When hosts wait for mafia-style retaliation before accepting a cuckoo egg, mafia birds have an advantage. Then, as the threat becomes more convincing and host birds begin to accept all eggs, cuckoos no longer benefit from their mafia activities. The frequencies of mafia and non-mafia birds, blind accepters and conditional accepters, swung back and forth in an endless cycle. And although they could lay any number of eggs, cuckoos in the simulations usually evolved to lay only one egg per host nest—just as they usually do in the wild. The computer model doesn't prove that mafia behavior is driving the interactions between cuckoos and their hosts in real life. But it fits with scientists' observations that mafia-style retaliations can happen. The model also shows that the existence of mafia birds could be enough to create the balance we see in the wild, where neither bird has a true upper hand over the other. If birds are flexible enough to change their behavior with the circumstances, they'll do what they can to avoid getting on the wrong side of the mob.

Image: Great spotted cuckoo by Isidro Vila Verde (via Flickr)

Abou Chakra M, Hilbe C, & Traulsen A (2014). Plastic behaviors in hosts promote the emergence of retaliatory parasites. Scientific reports, 4 PMID: 24589512

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April 17, 2014

Fear of the cuckoo mafia

by Max Planck Society

If a restaurant owner fails to pay the protection money demanded of him, he can expect his premises to be trashed. Warnings like these are seldom required, however, as fear of the consequences is enough to make restaurant owners pay up. Similarly, mafia-like behaviour is observed in parasitic birds, which lay their eggs in other birds' nests. If the host birds throw the cuckoo's egg out, the brood parasites take their revenge by destroying the entire nest. Consequently, it is beneficial for hosts to be capable of learning and to cooperate. Previously seen only in field observations, scientists at the Max Planck Institute for Evolutionary Biology in Plön have now modelled this behaviour mathematically to confirm it as an effective strategy.

Some parasitic birds, such as the North American brown-headed cowbird ( Molothrus ater ), are observed to punish host birds by destroying their clutches if their eggs are rejected. Consequently, the hosts accept a certain degree of parasitism as long as they can raise their own offspring alongside the parasitic chicks. "We tested and confirmed the mafia hypothesis, which was controversial among scientists," explains Maria Abou Chakra, lead author of the study. The parasitic birds use their behaviour to extort the hosts, forcing them to cooperate. "They give the hosts no choice. If they wish to avoid retaliation, they need to keep the foreign egg."

For the theory to work, two points are absolutely crucial: the host birds must be capable of learning, and the parasites must approach the same nests more than once. Only then does the mafia-like behaviour have the desired effect. "For the hosts, the best thing is to remove the foreign egg from their own nests. But if they encounter a retaliatory parasite that destroys their nest, it's best to adapt and accept the parasitic egg," says Abou Chakra.

Maria Abou Chakra works in the Evolutionary Theory Department at the Max Planck Institute for Evolutionary Biology. In collaboration with Christian Hilbe, now at Harvard University, and Arne Traulsen, she developed mathematical models to test the mafia hypothesis. The underlying principle in their minimalistic model was that each parasite lays no more than one egg in another bird's nest, which the host may accept or eject. A more complex model allowed the parasites to lay several eggs, each of which could be destroyed or accepted individually.

"Biologists prefer the complex model, because it is closer to reality. But we came to the same conclusion with both models: the dynamics of the interaction between host and parasite is cyclical." An equilibrium is never established; instead, there are regular cycles in terms of the frequency of mafia and non-mafia parasites and hosts that accept an egg immediately or only after they have suffered retaliation. If the number of non-mafia brood parasites is high, the advantage lies with conditional accepters, hosts that leave the parasite's egg in their nest only after their nest has been destroyed. After all, there is little chance the parasite is a retaliator. This behaviour therefore increases among host birds. And this, in turn, improves the survival rate of the mafia-like brood parasites . As soon as the latter are in the majority, it makes sense for the hosts to accept unconditionally, which, in turn, renders the mafia-like behaviour unnecessary. The cycle begins anew.

Evolutionary biologist Amotz Zahavi postulated the mafia hypothesis back in 1979. It has been contentious ever since. Critics argue that the retaliation gives the parasites no advantage, carrying high costs instead. However, the future nestlings benefit from the hot-headed behaviour if the host parents do indeed keep and hatch the next cuckoo's egg for fear of having their nest destroyed again.

Instead of retaliating, the parasites could attempt to mimic the eggs of the host birds. This makes it more difficult for hosts to identify and destroy the foreign egg. There are some birds which do in fact apply this strategy. But Abou Chakra sees an advantage in the mafia-like behaviour itself: "We believe it helps the parasites to avoid specialisation." Birds that do not adapt the size and colour of their eggs to any particular host can foist their offspring on nearly any species of bird and use their behaviour to force the foster parents to raise it. "The question is, what are the conditions under which it's better for parasites to specialise and when does mafia-like behaviour pay off?" This is what the scientists intend on testing next.

Journal information: Scientific Reports

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In This Article Expand or collapse the "in this article" section Organized Crime

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Organized Crime by Jay S. Albanese LAST REVIEWED: 14 December 2009 LAST MODIFIED: 14 December 2009 DOI: 10.1093/obo/9780195396607-0021

Organized crime is a continuing criminal enterprise that works to profit from illicit activities that are often in great public demand. Organized crimes can be grouped into three broad categories: provision of illicit goods, illicit services, and infiltration of business and government. Organized crimes are distinct from traditional crimes (such as larceny and assault) because they involve planning, multiple participants, and require corrupt measures such as threats to maintain and protect their ongoing criminal activities.

There are a number of texts that provide general overviews of transnational crime. Albanese 2007 offers a systematic typology of organized crimes, together with an explanation of causation and investigation, prosecution, defense, and sentencing issues. Other texts by Abadinsky 2009 , Grennan and Britz 2005 , Lyman and Potter 2006 , and Mallory 2007 approach organized crime by the type of group involved, or geographic region, and focus more on descriptions of different groups and their activities than on investigative response. Nearly all these books offer at least one chapter applying criminological theory to organized crime and on transnational organized crime, and all are directed toward the undergraduate or beginning graduate-level reader.

Abadinsky, Howard. 2009. Organized crime . 9th ed. Belmont, CA: Thomson Wadsworth.

A mainstream organized crime text with more than half the book discussing the histories of specific groups, plus three chapters on historical summaries of different types and past incidents of organized crimes.

Albanese, Jay S. 2007. Organized crime in our times . 5th ed. Newark, NJ: LexisNexis.

A book designed as a textbook overview of organized crime with significant attention to a distinct typology of organized crimes, investigative, prosecution, defense, and sentencing tools. Unique chapters are included on the role of conspiracy in organized crime and on paradigms of organized crime.

Grennan, Sean, and Marjie T. Britz. 2005. Organized crime: A worldwide perspective . Upper Saddle River, NJ: Pearson Prentice Hall.

A book focused exclusively on different types of organized crime groups with unique chapters on supremacist groups and Hispanic gangs.

Lyman, Michael D., and Gary W. Potter. 2006. Organized crime . 4th ed. Upper Saddle River, NJ: Pearson Prentice Hall.

A textbook treatment of organized crime is provided, with unique chapters on organized crime in the American South; also included is the relationship between organized crime and political/corporate connections.

Mallory, Stephen. 2007. Understanding organized crime . Sudbury, MA: Jones and Bartlett.

An introductory textbook on organized crime with the majority of chapters focusing on specific organized crime groups with two separate chapters on Colombian and Mexican drug cartels.

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Italian Mafia

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Italian organized crime

Different ways of conceptualizing the mafia have been proposed over the time, emphasizing either the cultural or the organizational factors. The former describes the mafia as a subculture typical of certain areas of Southern Italy, whereas the latter focuses on its internal configuration. The mafia has also been conceptualized as a business enterprise, although its political dimension has also been emphasized by delineating it as an industry of private protection. Indeed, Italian mafias differ from other criminal organizations for their will to political dominion in the areas of their traditional presence. Another peculiarity of mafia groups in Italy is their internal configuration and the resort to symbols and rituals that promote the creation of strong ties among the affiliates.

Italian mafia organizations include Cosa Nostra (Our Thing) in Sicily, the ‘Ndrangheta (Society of the Men of Honor) in Calabria, and the Camorra in Campania....

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Recommended Reading and References

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• Published: 22 May 2020

Pathological risk-propensity typifies Mafia members’ cognitive profile

• Gerardo Salvato 1 , 2 , 3 ,
• Maria Laura Fiorina 1 , 4 ,
• Gabriele De Maio 1 ,
• Elisa Francescon 1 ,
• Daniela Ovadia 1 , 3 ,
• Luisa Bernardinelli 1 ,
• Amedeo Santosuosso 4 ,
• Eraldo Paulesu 5 , 6 &
• Gabriella Bottini 1 , 2 , 3  

Scientific Reports volume  10 , Article number:  8559 ( 2020 ) Cite this article

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• Cognitive neuroscience
• Human behaviour

Since the recruitment process, Italian Mafias impose on their members a strict code of conduct. These rigid rules regulate their private and public behavior, implying a total adhesion to the group’s values. Such juridical and social aspects substantially distinguish organized crime (OC) from ordinary crime. It is still unknown whether these two categories of offenders also show distinctive cognitive traits. Here we investigated the frontal lobe cognitive functions of 50 OC prisoners from the Mafia and 50 non-OC prisoners based on the performance of 50 non-prisoner controls. We found that OC members were more likely to show pathological risk-propensity than non-OC prisoners. We interpret this finding as the result of the internal dynamics of Mafia groups. OC is a worldwide threat, and the identification of cognitive traits behind criminal behavior will help in devising focused prevention policies.

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Introduction.

Organized crime (OC) groups are very stable organizations governed by a complex hierarchical structure and bounded by rigorous norms 1 , 2 . OC recruits specific individuals on whom they impose a veritable status contract 3 . In the case of archetypical organizations such as the Italian Mafias, through the ritual initiation, novices are required to assume a new permanent identity as “men of honor” 3 , 4 , 5 . As such, OC members regulate their behavior according to canons of masculinity, respect, and secrecy, to increase their reputation and preserve their position within their group 3 , 6 . Their criminal activities, as well as their private lives, are regulated by codes of conduct known as commandments 1 , which are shared norms that build a strong collective identity, enhancing the group’s cohesion. Indeed, OC activities implicate a close interaction between co-offenders and firm adherence to the group’s values. These peculiar features substantially distinguish OC from ordinary crime (non-OC) from both a juridical and social perspective, leaving an open question concerning possible distinctions between offender types, including at the behavioral level. One might suppose that distinctive features of OC members’ behavioral profiles emerge from cognitive variations in frontal lobe executive functions, i.e., high-order goal-oriented processes controlling flexible behaviors to support a proficient interaction with the environment 7 , 8 . Previous studies have shown that executive dysfunctions are predictive of specific criminal behaviors 9 , 10 . So far, cognitive neuroscience has provided evidence for selective executive deficits in non-OC offenders, which include planning strategies 11 and working memory 12 . However, it is currently unknown whether there is also a pattern of executive (dys)functioning that is characteristic of OC members. Clear-cut experimental evidence on this topic is scarce. Here, we were able to test these hypotheses and assessed 50 Mafia-type OC prisoners to explore as comprehensively as possible the various facets of executive functions. On the basis of the most recent neurocognitive models of frontal lobe functioning 7 , 8 , we used a series of computerized cognitive tasks investigating planning, working memory, risk-taking behavior, flexibility, inhibition, and sustained attention. By comparison, the same tests were administered to 50 ordinary non-OC prisoners, and 50 age-gender matched non-prisoners. We hypothesized that OC members, as part of an organized and pervasive group with its specific group dynamics, may show distinctive cognitive traits compared to non-OC prisoners. For instance, it is increasingly recognized that self-identification with a group modulates frontal lobe functions 13 , 14 , 15 . More specifically, the affiliation to a group that endangers the lives of its affiliated “men of honor” could boost risk-taking behavior.

As a first step, we compared the socio-demographic and psychological variables between the two groups of prisoners to detect possible differences, and eventually to adjust subsequent analysis for the observed effect. The OC and non-OC groups did not differ in age ( t (98) = −0.87; p  = 0.382), education ( t (98) = 0.38; p  = 0.706), global cognitive functioning ( t (98) = −1.26; p  = 0.212), fluid intelligence ( t (98) = 0.08; p  = 0.940), anxiety ( t (98) = −0.47; p  = 0.642), depression ( t (98) = −1.03; p  = 0.307), psychopathy personality traits ( t (98) = 0.20; p  = 0.844), and number of incarcerations ( t (98) = −0.38; p  = 0.704). Nevertheless, at the time of testing, they differed in periods of detention ( t (98) = −5.58; p  < 0.001): OC offenders had been staying in prison on average for 12.7 years ( SD  = 9.2), while non-OC prisoners were incarcerated on average for 4.9 years ( SD  = 3.5) (Table  1 ). Such a difference was expected because of the Italian Law System: for the same crime committed, OC members received a harsher sentence than non-OC individuals, because they are also convicted of Mafia association. We considered this variable as a covariate in the subsequent analyses.

As a second step, we standardized the OC and non-OC participants’ test scores based on the non-prisoner control group’s values. Scores from the two groups of prisoners were transformed in z-scores according to the mean and standard deviation calculated for each test using the control group scores. This procedure allowed us to compare different tests and gauge possible cognitive deficits (scores < or > 2 standard deviations 16 , 17 ). As each test provided different outcome variables (e.g., reaction times, false alarms, error percentage, and others), we applied a data-driven approach. To select one variable of interest for each executive function subcomponent, we used multiple Partial Least Square Regressions. Lastly, we performed a Binary Logistic Regression to determine domains associated with group membership. This model included Group (OC, non-OC) as a dependent variable, and we inserted the scores from the Stockings of Cambridge test (planning), Spatial Working Memory task (working memory), Balloon Analogue Risk Task (BART) and the Body Analogue Risk Task (BoART) (risk-taking behavior associated with non-biological and biological stimuli), Multitasking Test (flexibility and inhibition), and Rapid Visual Information Processing test (sustained attention) as predictors (see the methods section for a detailed description of the tests of each specific function). The final model was significant (omnibus test χ2 (2df) = 36.1; p  < 0.001; Hosmer and Lemeshow χ2 (8df) = 4.5; p  = 0.805)), and it explained 40.7% of Nagelkerke’s pseudo-variance 18 . We found that the odds of an OC prisoner presenting with impaired risk-taking behavior (elevated risk-taking behavior, e.g., scores >2 standard deviations of the controls’ mean) were 6.4 times greater than the odds of a non-OC prisoner (Wald χ2 (1) = 5.5; p  = 0.019; OR  = 6.44; CI  = 1.36–30.5); the other variables were removed from the model (all ps  > 0.05) (Table  2 ). A Receiver Operating Characteristic (ROC) curve was calculated to test whether the predicted probability of the model successfully discriminated OC from non-OC. The results showed an accuracy (area under the curve) of 0.80 ( CI : 0.71, 0.89; p  < 0.001). Lastly, as it has been shown that risk-taking behavior may be associated with personality traits 19 , we ran an additional analysis correlating the risk index scores of the two prisoners’ groups with the psychopathic personality traits test scores (Psychopathic Personality Inventory-Revised (PPI-R)) 20 . We found no evidence for a correlation between risk-taking behavior and the eight PPI-R subscales (α level = 0.006; Bonferroni corrected).

Discussions

These findings demonstrate that affiliation to pervasive groups such as the Mafias influences their members’ behavior. This is consistent with social psychology studies showing that group dynamics modulate individual behavior in a pervasive way. People with a strong identification to the group they belong to behave differently from people who perceive themselves as isolated individuals. Interestingly, the main cognitive dysfunction characterizing OC members is a pathological risk-taking behavior, whereas the other predictors were not significant. Such a cognitive feature did not correlate with psychopathy traits.

Typically, the group pushes the individuals towards more risky behavior, a tendency labeled as “risk-shift phenomenon” 15 . In a seminal study, Wallach and colleagues 21 showed that when group interaction occurs, people tend to make riskier decisions compared to those made individually. In their study, two groups of subjects were asked to individually decide on 12 everyday life situations with increasing risk/reward trade-offs (choice dilemma procedure). Furthermore, the experimental group was asked to discuss to reach a consensual decision. In this case, subjects showed an overall general shift towards riskier decisions that persisted for quite a long period (2 to 6 weeks). These results have been replicated several times with different paradigm variations 22 , 23 , 24 . Two hypotheses have been proposed to explain this phenomenon: i) shared/spreading of responsibility in the group, so that risky decisions are perceived as more affordable, ii) persuasion exerted by the most influential individuals, usually high-risk takers, and perceived as holders of greater forcefulness by the group. Reframing these hypotheses into the OC background, OC offenders may show higher propensity towards risky behavior as they share responsibility with the other members of the group. Furthermore, OC members may feel protected by their criminal network, whereas non-OC offenders act as lone wolves. Nevertheless, we cannot exclude the second hypothesis as, in our study, we exclusively tested individuals with a low hierarchical standing, merely crime executors, and typically, Mafia bosses are considered untouchable, highly influential leaders whose decisions are not to be disputed. However, the risky-leader theory has been criticized by Hoyt and Stoner 24 as they replicated the risk-shift effect while neutralizing any leadership effects of highly risk-prone persons. In this case, group discussion to consensus still produced decisions that were riskier than the mean of the individual decisions of group members. Furthermore, the risk-shift phenomenon does not exclusively occur when the group can discuss the decisions to be taken consensually, as it has been demonstrated that this effect is also obtained in the absence of this interaction 25 . We also propose a third hypothesis that concerns the “man of honor” status, which is a crucial and symbolic dimension of Mafia organizations. To maintain this status, OC members should continuously demonstrate their willingness to do anything, including criminal acts. Such a philosophy of life inevitably leads to pathological risk-taking behavior that paradoxically protects OC members from unwanted changes of status within the group. Interestingly, contrary to previous experimental paradigms, the test that was used to evaluate risk-taking behavior, the Balloon Analogue Risk Task (BART) 26 , models real-world risk behavior through the conceptual frame of balancing the potential for reward versus loss. In brief, during the BART, participants are offered the chance to virtually earn money by pumping the balloon up by clicking a keyboard button. Each click causes the balloon to incrementally inflate and virtual money to be added to a counter up until some threshold, at which point the balloon is overinflated and explodes. Each pump entails greater risk, but also greater potential reward. If the participants choose to cash-out before the balloon explodes, then they virtually collect the money earned for that trial, but in case the balloon explodes, earnings for that trial are lost. Importantly, this test provides a highly generalizable outcome as it correlates with several real-world risky behaviors, for example, drug abuse 27 , gambling, risky sexual behavior 28 , smoking 29 , and substance abuse with coexisting conduct problems in adolescent patients 30 .

In conclusion, the current study shows that OC members are more likely to show pathological risk propensity compared to non-OC offenders. Group membership appears to be an important dimension of this pathological attitude. This executive dysfunction should be taken into account together with innate and environmental components, both of which are required for a cognitive trait to develop 31 , 32 . More information concerning the etiology of the OC-membership might be useful in future studies to better understand the risk-taking behavior of those individuals who were born into the OC-family compared to those who came from outside the OC structures. OC is a worldwide threat, and understanding the dynamic interplay between all these components could help devise effective prevention policies. So far, several prevention programs have been devised to foster the development of emotional and social skills already in childhood and adolescence in case of dysfunctional behaviors. In particular, the Social and Emotional Learning (SEL) programs proved effective in promoting such skills 36 , 37 , 38 . The Collaborative to Advance Social and Emotional Learning (CASEL) 39 has developed a framework of key SEL skills, including self-awareness, self-management, social awareness, relational skills, and responsible decision-making. The latter, is particularly relevant to the case of OC as it fosters the ability to make decisions based on consideration of ethical standards, safety concerns, appropriate standards of conduct, respect for others, and likely consequences of various actions. These conclusions underpin the rationale for the adoption of educational and social intervention programs (e.g., the SEL) that may be particularly effective in specific “at-risk areas” in which mafia and other forms of organized crime are present 40 , 41 . We anticipate that the promotion of more controlled decision-making skills in young adults may reduce their future recruitment into the local OC group. As it is well known, the translation of a proof of principle into educational policies and programs requires a long and laborious process and vast resources ( http://www.oecd.org/education/implementing-policies/ ).

Limitations

This study has some limitations. For instance, we used a control matched non-prisoners control group to determine normative scores for each computerized test. We acknowledge that a group of 50 individuals could not be an adequate proxy for norms in the general population. It is also important to bear in mind that although risk-taking behavior was the only pathological trait distinguishing between the two groups of prisoners, this result did not imply that the two groups were different with respect to other/different cognitive functions. Thus, it is possible that the two prisoners’ groups showed equal cognitive functioning (or dysfunctioning) at planning, spatial working memory, flexibility and inhibition, and sustained attention. According to our experimental question, our statistical approach explored the hypothesis of a pathological cognitive function predicting the OC membership. Nonetheless, future studies may be specifically conceived to test differences in the cognitive functioning of OC members compared to other types of prisoners. So far, only one study has explored the neuropsychological profile of OC prisoners, who were, in that case, all affiliated to a drug trafficking Mexican cartel 33 . Ostrosky and collaborators 33 have compared this type of OC offenders with a group of non-prisoner healthy individuals on executive functions. They have found differences in several cognitive functions, including planning, working memory, and inhibition. Unfortunately, the provided results are hardly generalizable because the only comparison between prisoners and non-prisoners left open the possibility that those differences may be the result of the condition of detention per se , rather than belonging to the drug trafficking OC. Moreover, in the same study, the inmate group was divided into five subcategories (kingpins, money launderers, protectors, enforcers, and distributors/producers). Such categories were strongly unbalanced by sample size and compared with each other, possibly affecting the statistical power and the Type I error rates.

Materials and methods

Participants.

According to a priori power analysis (see below), one hundred male inmates were randomly selected from two lists provided by two Italian Penitentiaries comprising respectively 1125 and 1253 prisoners. To be included in the organized crime (OC) group, prisoners had to have committed a Mafia-related crime (article 416 bis of the Italian Penal Code). We tested 50 OC prisoners and 50 non-organized crime prisoners (non-OC). The OC and non-OC groups were balanced according to the nature of the crime committed (25 violent and 25 nonviolent prisoners per group). We also recruited a matched control group, including 50 non-prisoner participants, which allowed us to determine the performance at the experimental computerized tasks in a non-incarcerated population. The three groups of participants were matched for age, gender, and years of education. All participants were native Italian speakers and had a normal or corrected-to-normal vision. Participants had no history of neurological or psychiatric disorders. Informed consent was obtained before participation in the experiment using a form purposely developed for this project within the framework of the Charter of Fundamental Rights of the European Union and the principles of the Office for Human Research Protection of the US Department of Health and Human Services for research on prisoners. In accordance with the Declaration of Helsinki (BMJ 1991; 302: 1194), all the experimental procedures were approved by the Ethical Committee of the Department of Brain and Behavioral Sciences, University of Pavia (protocol No. 010).

Sample size calculation

Studies investigating cognitive functions in OC compared to non-OC prisoners are absent. For this reason, we estimated the group size needed to show a between-group difference in executive functioning by using a study in which frontal lobe functions had been tested in a group of non-OC prisoners. Dolan and colleagues 34 tested memory and executive functions comparing prisoners convicted for violent crimes to healthy controls. The group of prisoners showed a mean Executive Function Index score of 2.16 ( SD  = 3.9), whereas the healthy controls had a mean of 5.57 ( SD  = 2.3). Based on these data, we hypothesized that one of the groups in our study would show an executive functions deficit with an alpha  = 0.05 on an independent means two-tailed t -test. Using a freely available sample-size calculating tool ( G*Power ), we determined a suggested sample size of 25 participants per group. Although in our study we were not interested in differences between violent and non-violent offenders, we nevertheless balanced the two groups (OC, non-OC) of prisoners for the type of crime committed to deal with a possible confounding due to the differences between violent and nonviolent prisoners on the executive function tests that we used here (see for instance 35 ). More precisely, we tested 50 criminals per group (OC, non-OC), considering in each group 25 violent and 25 nonviolent prisoners.

Neuropsychological assessment

Cognitive screening.

To exclude that possible general cognitive impairment or intelligence deficit could influence the performance in the other tests, we administered two neuropsychological tests assessing the integrity of their global cognitive functioning and intelligence: the Addenbrooke’s Cognitive Examination-Revised (ACE-R) 36 and the Raven’s Colored Progressive Matrices (CPM) 37 . ACE-R is a brief battery that provides an evaluation of six cognitive domains (orientation, attention, memory, verbal fluency, language, and visuospatial ability). The total score indicated the global cognitive functioning clinical status. CPM is a culture-free test for nonverbal intelligence. It consists of 36 nonrepresentational colored design patterns incomplete in the bottom right corner. Participants were required to select the best completion pattern from among six alternatives. The available normative scores for the Italian population 37 , 38 were used to diagnose possible neuropsychological deficits. All the participants showed preserved global cognitive functioning and fluid intelligence.

We also tested anxiety and depression using the State-Trait Anxiety Inventory (STAI) 39 and the Beck Depression Inventory (BDI) 40 . The STAI is a psychological inventory based on a 4-point Likert scale and consists of 40 questions on a self-report basis. The STAI measures two types of anxiety – state anxiety, or anxiety about an event, and trait anxiety, or anxiety level as a personal characteristic. The BDI is a 21-question multiple-choice self-report inventory, one of the most widely used psychometric tests for measuring the severity of depression.

Psychopathy

Lastly, we assessed psychopathic personality traits using the Psychopathic Personality Inventory-Revised (PPI-R) 20 . The PPI-R is a personality test for traits associated with psychopathy in adults. It consists of a series of statements to which subjects respond, indicating how accurately the statement describes them using a 4-point Likert scale (“False,” “Mostly False,” “Mostly True,” “True”). The PPI-R scores are grouped into eight subscales, seven of which can be organized into two higher-order factors: Fearless Dominance, including the subscales Stress Immunity, Social Influence, and Fearlessness; and Self- Centered Impulsivity, including the subscales Rebellious Nonconformity, Blame Externalization, Machiavellian Egocentricity, and Carefree Nonplanfulness.

Experimental tasks

Following the neuropsychological screening, seven tests from the Cambridge Automated Neuropsychological Test Battery (CANTAB; Cambridge Cognition 2006; 2008) were used to assess the frontal lobe profile of our participants. Extensive descriptions and interactive demonstrations of the tasks are available on the website of the manufacturer ( www.cambridgecognition.com ). The tests were administered using a 12.1-in. touch-screen tablet (screen resolution of 1280 × 800). We also used a newly developed paradigm to assess risk-taking behavior with biological and non-biological stimuli. The following tasks were administered:

Cognitive flexibility and inhibition

The Multitasking Test explored the participant’s ability to manage conflicting information provided by the direction of an arrow and its location on the screen and to ignore task-irrelevant information. The test displayed an arrow, which could appear on either side of the screen (right or left) and could point in either horizontal direction (to the right or the left). Each trial displayed a cue at the top of the screen that indicated to the participants whether they had to select the right or left button according to the “side on which the arrow appeared” or the “direction in which the arrow was pointing.” In some sections of the task, this rule was consistent across trials (single task), while in others, the rule was allowed to change from trial to trial in a randomized fashion (multitasking). Flexibly using both rules places a higher demand on cognition than using a single rule. Some trials displayed congruent stimuli (e.g., an arrow on the right side pointing to the right). In contrast, other trials displayed incongruent stimuli (e.g., an arrow on the right side of the screen pointing to the left), which required a higher cognitive demand. As outcome variables, we used the following:

Multitasking incongruency cost (median): The difference between the median latency of response (from stimulus appearance to button press) on the trials that were congruent versus the incongruent trials. This was calculated by subtracting the median congruent-trial latency (in ms) from the median incongruent-trial latency. A positive score indicates that the subject was faster on congruent trials, and a negative score indicates that the subject was faster on incongruent trials. A higher incongruency cost indicates that the subject took longer to process conflicting information.

Multitasking cost (median): The difference between the median latency of response (from stimulus appearance to button press) during assessed blocks in which both rules were used versus assessed blocks in which only a single rule was used. Calculated by subtracting the median latency of response during single-task blocks from the median latency of response during multitasking blocks. A positive score indicates that the subject responded more slowly during multitasking blocks and indicates a higher cost of managing multiple sources of information.

Reaction latency (median): The median latency of response (from stimulus appearance to button press). Calculated across all correct trials.

Total incorrect: The number of trials for which the outcome was an incorrect response (subject pressed the wrong button within the response window). Calculated across all assessed trials.

The Stockings of Cambridge (SOC) is a computerized modified version of the Tower of London test and assessed the participants’ ability to engage in planning and spatial problem-solving. Participants were presented with a horizontally split screen, and verbally instructed to move the colored balls in the lower half to copy the pattern of colored balls in the upper half. Difficulty slowly increased from requiring a minimum of two moves to requiring a minimum of five moves. As outcome variables, we used the following:

Median Latency to First Choice: The median latency, measured from the appearance of the stocking balls until the first box choice was made by the subject. Calculated across all assessed trials where the subject’s first response was correct.

Problems solved on the first choice: The total number of assessed trials where the subject chose the correct answer on their first attempt. Calculated across all assessed trials.

Sustained attention

The Rapid Visual Information Processing (RVP) test was used to measure sustained attention. In this task, participants were required to detect target sequences of digits displayed on the side of the screen (for example, 2-4-6, 3-5-7, 4-6-8). A white box was shown in the center of the screen, inside of which digits from 2 to 9 appeared in a pseudo-random order, at the rate of 100 digits per minute. When the participant saw the target sequence, they responded by selecting the button in the center of the screen as quickly as possible. The level of difficulty varied, with the participant having to watch for either one- or three-target sequences at the same time. As outcome variables, we used the following:

A′ (A prime) is the signal detection measure of a subject’s sensitivity to the target sequence (a string of three numbers), regardless of response tendency (the expected range is 0.00 to 1.00; bad to good). In essence, this metric is a measure of how good the subject is at detecting target sequences.

Median response latency: The median response latency on trials where the subject responded correctly, calculated across all assessed trials.

Probability of false alarm: The number of sequence presentations that were false alarms divided by the number of sequence presentations that were false alarms plus the number of sequence presentations that were correct rejections: (false alarms ÷ (false alarms + correct rejections)).

Working memory

The Spatial Working Memory task (SWM) was used to measure working memory. This task assesses the participants’ ability to retain spatial information and to manipulate remembered items in working memory. In the SWM, participants were presented with several closed colored boxes and were instructed to search for a small blue token that was hidden in one of the closed boxes. All closed boxes contained a blue token only once; that is, participants had to remember in which boxes they had already found a blue token and in which they had not. Looking inside a closed box that had previously contained a blue token was considered an error (a “between error”). Looking inside a closed box twice within the same search was also considered an error (a “within error”). As outcome variables, we used the following:

Between errors 12 boxes: The number of times the subject revisited a box in which a token had previously been found. Calculated across all trials with 12 tokens only.

Between errors four boxes: The number of times a subject revisited a box in which a token had previously been found. Calculated across all trials with four tokens only.

Between errors six boxes: The number of times the subject revisited a box in which a token had previously been found. Calculated across all trials with six tokens only.

Between errors eight boxes: The number of times the subject revisited a box in which a token had previously been found. Calculated across all trials with eight tokens only.

Between Errors: The number of times the subject incorrectly revisited a box in which a token had previously been found. Calculated across all assessed four-, six- and eight-token trials.

Strategy (six and eight boxes): The number of times a subject began a new search pattern from the same box they had started with previously. If they always began a search from the same starting point, we inferred that the subject was employing a planned strategy for finding the tokens. Therefore, a low score indicated high strategy use (1 = they always began the search from the same box); a high score indicated that they began their searches from many different boxes. Calculated across assessed trials with six tokens or eight tokens.

Risk-taking behavior

We assessed risk-taking behavior associated with biological and non-biological stimuli using two tasks. Participants were administered with a well-known computerized test investigating risk propensity associated with non-biological stimuli, the Balloon Analogue Risk Task (BART) 26 . They were also tested with a recently modified version of it developed in our lab 41 , the Body Analogue Risk Task (BoART), investigating risk propensity associated with biological stimuli. In the original BART, a balloon was placed at the center of the screen, along with a balloon pump, a button labeled “Collect $$$,” a permanent display labeled “Total Earned” indicating the money earned and a second display listing the money earned on the last balloon, labeled the “Last Balloon.” The participant was asked to click on the pump. Each pump caused a size increase in the balloon (about 0.125 in. [0.3 cm] in all directions), accompanied by a pump sound effect. Additionally, 5 cents were banked in a temporary reserve (not indicated to the subject). When a balloon was pumped to its explosion point, a “pop” sound effect was generated, causing the loss of all banked money. The subjects were instructed that they could stop pumping and click the “Collect $$$” button at any time, transferring all temporary money to the permanent bank. A slot machine payoff sound effect played as the subject clicked on the “Collect $$$” button. After the explosion or the money collection, the balloon disappeared, and a new balloon appeared until a total of 90 balloons had been used/shown. The maximum number of pumps allowed for a single trial was pseudo-randomly chosen within a range that was determined by the balloon’s color (orange life range = 1–8 pumps, yellow life range = 1–32 pumps, blue life range = 1–128 pumps). The three different colors had the purpose of generating an experience-based risk-taking task. Stimuli were presented over three experimental blocks: Block 1 contained the three balloon variants, Block 2 contained the orange and yellow balloons, and Block 3 contained the yellow and blue balloons. Participants were not instructed regarding this difference. Rather, they learned during the task that stimuli had different chances of explosion depending on their colors. Such a learning effect would lead participants to increase their risk-taking behavior over the three blocks linearly. Typically, participants pumped more during the last experimental block when only blue balloons were present, having learned that those had the lowest probability of exploding compared to other balloon colors.

In the modified version of the BART, we replaced the balloon with a body silhouette. As in the case of balloons, each pump increased the stimulus size (about 0.125 in. [0.3 cm] in all directions), and was accompanied by a pump sound effect. Importantly, the human configuration of the silhouette remained plausible throughout inflation. The experimental design was identical to that of the original BART for both the balloon and body tasks. Importantly, we have previously demonstrated that although scores from the two versions of the task were highly correlated, the body task also correlated with core aspects of bodily self-awareness, such as interoception 41 . Each participant performed the two tasks in a randomized order within the group. As outcome variables, we used the following:

Adjusted value: defined as the average number of pumps on the blue stimuli excluding those that exploded (i.e., the average number of pumps on each balloon or body prior to money collection). This exclusion was because the number of pumps was necessarily constrained on the stimuli that exploded, thereby limiting between-subject variability in the absolute averages 26 . As the blue stimuli allowed the widest range in the possible number of pumps and therefore were likely to capture the highest amount of individual variability in task performance, the adjusted number of pumps on these stimuli across blocks served as our primary dependent measure ( risk index 26 , 29 ).

Reaction times calculated across all unexploded blue stimuli.

Statistical analyses

Data preprocessing.

As a first step, we standardized the OC and non-OC participants’ test scores based on the control group’s performance. Values from the two groups of prisoners were transformed in z -score according to the mean and standard deviation calculated for each test using the control group’s scores. This allowed us to compare different tests and to gauge cognitive deficits (scores above or below two standard deviations from the control group’s mean) 16 , 17 .

Feature selection and data analyses

According to the experimental design, each test had several outcome variables (e.g., reaction times, accuracy, percentages). For this reason, on each test, we applied a data-driven feature selection technique, which is widely used in neuroscience 42 , 43 , 44 , to produce a small number of features for efficient classification or regression and to reduce overfitting and increase the generalization performance of the model. Data were analyzed with SPSS 20 (Statistical Package for Social Science, Windows version, Chicago, Illinois). We used a partial least squares regression (PLS) method to select a subset of key informative behavioral features (one for a cognitive test) based on the resulting variable importance in the projection (VIP) value, to be included in the final regression model. PLS selects the key informative variables by optimizing the model’s performance and has therefore been used to explore possible biomarkers in medicine 45 , 46 . Furthermore, this data-driven selection of one predictor for cognitive test reduced the risk of multicollinearity that could have occurred if several measures of the same test had been introduced as predictors in the subsequent regression model. However, for the sake of completeness, we have also provided the univariate test results for each variable in the Supplementary Table  S1 .

Lastly, we used binary logistic regression to determine domains associated with group membership (OC, non-OC) from a set of six predictor variables. Multivariable methods have become routine in statistical analyses appearing in medical literature. A regression model serves two purposes: (i) it can predict the outcome variable for new values of the predictor variables, and (ii) it can help answer questions about the most important predictors of the OC cognitive profile, because the coefficient of each predictor variable explicitly describes the relative contribution of that variable to the outcome variable, automatically controlling for the influences of the other predictor variables. As the two groups of prisoners differed in their duration of detention, we also inserted it as a covariate in the regression model. As we had no a priori hypothesis on the role that different variables play in the prediction of the OC membership, we used a forward stepwise (likelihood ratio) method. To deal with potential outliers influencing the regression model, we also performed a case-wise diagnostic on Studentized residuals (i.e., the quotients resulting from the division of a residual by an estimate of its standard deviation), and cases with Studentized residuals >2 were excluded. We found one influential case within the non-OC group that was excluded from the subsequent analyses.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N° 699824 for the project: PROTON “Modelling the Process leading to Organised crime and TerrOrist Networks.” The Authors declare that the publication reflects only the Authors’ view, and the Agency is not responsible for any use that may be made of the information it contains.

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Gerardo Salvato, Maria Laura Fiorina, Gabriele De Maio, Elisa Francescon, Daniela Ovadia, Luisa Bernardinelli & Gabriella Bottini

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G.S., D.O., and G.B. designed the experiment and wrote the manuscript. M.L.F., G.D.M., and E.F. collected the data and wrote the manuscript. G.S. and L.B. analyzed the data. G.B., A.S., and E.P. wrote the manuscript giving a critical revision of it. All Authors gave the final approval of the version to be published.

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Salvato, G., Fiorina, M.L., De Maio, G. et al. Pathological risk-propensity typifies Mafia members’ cognitive profile. Sci Rep 10 , 8559 (2020). https://doi.org/10.1038/s41598-020-65486-z

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Received : 16 September 2019

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DOI : https://doi.org/10.1038/s41598-020-65486-z

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5 Mafia, State, and Society

• Published: June 2008
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The development and existence of mafia associations in Sicily and Calabria over the last hundred and fifty years cannot be explained without mentioning the longstanding incapacity of state institutions to guarantee order and public security over wide areas of the Mezzogiorno through the monopoly of force, and thus to gain full legitimacy in the eyes of the local population. Mafia cosche long enjoyed the consensus—or at least, the tolerance—of large strata of the local population, whose cultural codes they repeated and manipulated. Unlike the state, at least up to the 1950s, mafia power thus succeeded in transforming itself into authority. Empowered by popular consensus and the benign neglect of law-enforcement agencies, members of Cosa Nostra and the 'Ndrangheta met with little difficulty in accomplishing their roles as brokers and pursuing their own goals of power and wealth. The deterioration of relations between the mafia and politics is the result of a slow process of delegitimation that has invested mafia power during the whole post-war period, but has recorded a sharp acceleration from the early 1980s onward.

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The paradoxes of organized crime

2002, Crime Law and Social Change

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Djordje Ignjatović

Organized crime in the 21 st century-controversies and dilemmas SUMMARY This paper presents a review of the controversies and dilemmas – especially of the way in which criminologists and subjects of criminal politics operationalize the concept of " organized crime " , and how the latter ones come to control it. The question of how the process of globalization influenced the creation of the category " transnational organized crime " and the consequences of adopting a concept that ties it to criminal organizations, while neglecting its entrepreneurial nature, are also included in this analysis. Even though the analysis is mostly criminological in nature, reviewing the legal side of the problem, as well as, a number of other questions that a thorough study of organized crime entails, which are ethical, racial, ethnical, and political and other in nature, couldn't be avoided. In the conclusion, the author points out that the criminological notion of organized crime must encompass, most notably, criminal entrepreneurship, but without neglecting the characteristics of the perpetrators and the way they are organized. In addition to that, the author also gives his own explanation of why the creators of criminal politics, government officials and justice departments prefer the concept of organized crime which focuses on the organizational aspect of it. Finally, the author concludes that very little is known about organized crime and encourages young people and other researchers to study it further.

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This paper provides an insight into the phenomenology of organised crime as a historical and contemporary experience, and discusses issues related to understanding and definitions. Since the social environment determines significance of organised crime in society, the paper highlights influence of political context in normative design of organised crime acts through the presentation of the genesis of criminal organisation. The paper also offers an analysis of the essential conceptual connections between various understanding of organised crime, primarily in the sense in which it is reflected in the norms, given that normative definitions of organised crime are typically influenced by the understanding of how organised crime generates social danger. By offering historical and anthropological overview of organised crime normative regulation, the authors seek to contribute to a deeper understanding of this socially destructive phenomenon and related challenges in social control state o...

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The authors of this article focus on the term and the meaning of ‘organised crime’.Following their approach, it seems to be impossible to give an exact definition, because it has meant different things over time. There is a historical dimension but also a geopolitical dimension: South American, European and Russian historical developments have created different forms. Sometimes and somewhere organised crime is more or less ‘disorganised’, deregulated and connected with local frameworks. With regard to the organisation structures the authors distinguish five main ideal types: criminal networks with, firstly, ‘no social support structure in the milieu of operation’; those ‘rooted in marginalised subcultures’; those ‘rooted in mainstream society’; those with links ‘in power elites’; ‘criminal alliances between underworld and upper world or mafia-like organisations’.Moreover, the authors offer a versatile and complex picture of what organised crime means today. The contribution offers s...

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mafia hypothesis

Proper noun.

the mafia hypothesis

• ( biology ) A hypothesis attempting to explain why most hosts of brood parasites care for the parasite's nestlings . Since the host's nest is attacked if the parasite's egg is detected and rejected, this indirectly enhances selective pressures favouring aggressive parasite behaviour that may result in positive feedback between mafia-like parasites and compliant hosts.

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Definition of hypothesis

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

• proposition
• supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of hypothesis in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do

1641, in the meaning defined at sense 1a

Phrases Containing hypothesis

• counter - hypothesis
• nebular hypothesis
• null hypothesis
• planetesimal hypothesis
• Whorfian hypothesis

Articles Related to hypothesis

This is the Difference Between a...

This is the Difference Between a Hypothesis and a Theory

In scientific reasoning, they're two completely different things

Dictionary Entries Near hypothesis

hypothermia

hypothesize

Cite this Entry

“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 5 Sep. 2024.

Kids Definition

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Towards a Computational Theory of the Brain: The Simplest Neural Models, and a Hypothesis for Language

Mitropolsky, Daniel

Obtaining a computational understanding of the brain is one of the most important problems in basic science. However, the brain is an incredibly complex organ, and neurobiological research has uncovered enormous amounts of detail at almost every level of analysis (the synapse, the neuron, other brain cells, brain circuits, areas, and so on); it is unclear which of these details are conceptually significant to the basic way in which the brain computes. An essential approach to the eventual resolution of this problem is the definition and study of theoretical computational models, based on varying abstractions and inclusions of such details. This thesis defines and studies a family of models, called NEMO, based on a particular set of well-established facts or well-founded assumptions in neuroscience: atomic neural firing, random connectivity, inhibition as a local dynamic firing threshold, and fully local plasticity. This thesis asks: what sort of algorithms are possible in these computational models? To the extent possible, what seem to be the simplest assumptions where interesting computation becomes possible? Additionally, can we find algorithms for cognitive phenomena that, in addition to serving as a "proof of capacity" of the computational model, otherwise reflect what is known about these processes in the brain? The major contributions of this thesis include: 1. The formal definition of the basic-NEMO and NEMO models, with an explication of their neurobiological underpinnings (that is, realism as abstractions of the brain). 2. Algorithms for the creation of neural \emph{assemblies}, or highly dense interconnected subsets of neurons, and various operations manipulating such assemblies, including reciprocal projection, merge, association, disassociation, and pattern completion, all in the basic-NEMO model. Using these operations, we show the Turing-completeness of the NEMO model (with some specific additional assumptions). 3. An algorithm for parsing a small but non-trivial subset of English and Russian (and more generally any regular language) in the NEMO model, with meta-features of the algorithm broadly in line with what is known about language in the brain. 4. An algorithm for parsing a much larger subset of English (and other languages), in particular handling dependent (embedded) clauses, in the NEMO model with some additional memory assumptions. We prove that an abstraction of this algorithm yields a new characterization of the context-free languages. 5. Algorithms for the blocks-world planning task, which involves outputting a sequence of steps to rearrange a stack of cubes in one order into another target order, in the NEMO model. A side consequence of this work is an algorithm for a chaining operation in basic-NEMO. 6. Algorithms for several of the most basic and initial steps in language acquisition in the baby brain. This includes an algorithm for the learning of the simplest, concrete nouns and action verbs (words like "cat" and "jump") from whole sentences in basic-NEMO with a novel representation of word and contextual inputs. Extending the same model, we present an algorithm for an elementary component of syntax, namely learning the word order of 2-constituent intransitive and 3-constituent transitive sentences. These algorithms are very broadly in line with what is known about language in the brain.

• Computer science
• Neurosciences
• Brain--Physiology
• Language acquisition
• Computational linguistics
• Computational neuroscience
• English language
• Russian language

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