Techniques of Neutralization: A Brain Network Perspective

Abstract

Sykes and Matza introduced neutralization theory in 1957 to explain how juvenile delinquents retain a positive self-image when engaging in delinquent acts. Since then, aspects of neutralization theory have been incorporated into sociological and criminological theories to explain socially deviant behavior. Functional brain mapping research utilizing advanced magnetic resonance imaging techniques has identified complex, intrinsically organized, large-scale brain networks. Higher order operations commonly attributed to three brain networks (default mode network [DMN], central executive network [CEN], salience network [SN]) align closely with neutralization theory. This article briefly discusses brain networks in general and the DMN, CEN, and SN specifically. It also discusses how these networks are involved when engaging in the use of techniques of neutralization and offers implications for future research.

Keywords

neutralization theory adolescence biocriminology biological theories criminality juvenile delinquency

In the early 1990s, researchers produced the first human functional magnetic resonance imaging (fMRI) results using a newly developed blood oxygenation level-dependent contrast method (Bandettini, 2012; Ogawa, 2012; Ugurbil, 2012). This marked the beginning of human brain research using magnetic resonance imaging (MRI) to map brain activation (Bandettini, 2012). The use of fMRI in research has led to the identification of a number of intrinsically organized, large-scale brain networks in humans (Bressler & Menon, 2010). Three of these networks (default mode network [DMN], central executive network [CEN], salience network [SN]) are believed to interact with each other and collectively control attention, working memory, decision-making, and other higher level cognitive operations (Chen et al., 2013). These networks are also thought to be involved in moral reasoning, moral decision-making, moral judgment, theory of mind, emotion regulation, and switching focus between internal and external events (Barrett & Satpute, 2013; Chiong et al., 2013; Greene, Hernandez, Bookheimer, & Dapretto, 2016; Harrison et al., 2008; Medford & Critchley, 2010; Menon & Uddin, 2010; Molenberghs et al., 2015; Palaniyappan & Liddle, 2012; Philippi & Koenigs, 2014; Seeley et al., 2007; Yoder, Harenski, Kiehl, & Decety, 2015).

Neutralization theory (Matza, 1964; Sykes & Matza, 1957) has long held that in advance of committing socially deviant acts, juvenile delinquents use techniques that neutralize social controls that would otherwise serve to check or inhibit following through with the acts. By using these techniques of neutralization, it is argued, juvenile delinquents avoid self-blame, the blame of others, and moral culpability for their acts; this allows them to retain a positive self-image. Higher order operations attributed to the DMN, CEN, and SN (e.g., moral cognition, judgment and decision-making in the context of goal-directed behavior, subjective salience, switching between internal and external events) align closely with the underpinnings of neutralization theory. Understanding the relationship between these intrinsically connected neural networks and the use of techniques of neutralization may offer new insight into neutralization theory and also guide future criminal brain network research. This article discusses brain networks in general, and the DMN, CEN, and SN specifically. It also discusses how these networks are involved when using techniques of neutralization and offer implications for future research.

Brain Networks

Recent researchers examining resting-state and task-evoked functional connectivity in the human brain have suggested that higher cognitive brain functions are not limited to individual, isolated brain areas as once believed. Instead, they appear to be the result of brain areas working jointly with one another to form organized large-scale structural networks that perform restricted roles (Bressler & Menon, 2010; Sporns, 2013). From these theorized large-scale structural networks, anatomical and functional interdependence inferences can be made about short- and long-range brain area interactions, activity flow patterns, and segregation or integration of network interactions (Bressler & Menon, 2010). From a structural framework, individual brain areas can be viewed as structurally connected subnetworks operating within a larger scale network. These subnetworks consist of groups of excitatory and inhibitory neurons (nodes) and interconnecting pathways (edges), and a number of methods (e.g., anatomical parcellation of the cerebral cortex) can be used to visualize large-scale structural network nodes (see Bressler & Menon, 2010). Edges consist of long-range uni- and bidirectional axonal-fiber pathways that allow brain areas to form unique interconnection sets to and from various brain areas within the large-scale structural networks (Bressler & Menon, 2010). There are a variety of different ways these pathways can be traced that allow for structural network edge delineation (e.g., magnetic resonance diffusion tensor imaging). Primarily through the use of fMRI methods, a number of intrinsically organized, distinct functional networks have been hypothesized. These include the DMN, CEN, and SN and are briefly described below.

DMN

The DMN, sometimes referred to as the mentalizing network, is believed to use memory and category knowledge to develop a mental model of the past, present, and future (Barrett & Satpute, 2013). The DMN is generally believed to include the following brain areas: ventral medial prefrontal cortex, dorsal medial prefrontal cortex, medial prefrontal cortex, ventral anterior cingulate cortex, posterior cingulate cortex, medial posterior parietal cortex, lateral parietal cortex, medial temporal cortex, angular gyrus, temporoparietal junction, hippocampal formation, and precuneus (Barrett & Satpute, 2013; Blakemore, 2012; Buckner, Andrews-Hanna, & Schacter, 2008; Fox et al., 2005; Fransson, 2005; Raichle et al., 2001; Sebastian, Burnett, & Blakemore, 2008; Shulman et al., 1997; Uddin, Kelly, Biswal, Castellanos, & Milham, 2009). The DMN includes a dorsal subnetwork (dorsal medial prefrontal cortex, temporoparietal junction, lateral temporal cortex, temporal pole) that has increased activity when abstract concepts involving others require judgment and a ventral subnetwork (ventral medial prefrontal cortex, posterior inferior parietal lobule, retrosplenial cortex, parahippocampal cortex, and hippocampal formation) that increases in activity when judgments involve first-person embodiment (Andrews-Hanna, 2012). The DMN, in general, displays increased metabolic activity and connectivity when an individual is at rest compared with when engaged in goal-oriented attention-demanding tasks or stimulus-driven cognitive processing (Buckner et al., 2008; Hamilton, Racer, & Newman, 2015; Menon, 2011; Raichle et al., 2001). This suggests that when individuals are allowed to direct their thoughts (i.e., choose what to think about) without the influence of external constraint (e.g., when performing an externally cued visual memory task), the DMN becomes more active as they engage in spontaneous, stimulus-independent, introspective, and adaptive mental activities (Andrews-Hanna, 2012). These activities include cognitions involving self-monitoring, self-awareness, self-processing, self-reflection, self-concept (how people perceive themselves), social self-concept (how people believe others perceive them), referencing information to the self, episodic memory (i.e., personal experiences), theory of mind/perspective-taking, emotional processing, moral decision-making, and thinking about the past, present, and future Andrews-Hanna, 2012; Barrett & Satpute, 2013; Blakemore, 2012; Buckner et al., 2008; Cavanna & Trimble, 2006; Greene, Sommerville, Nystrom, Darley, & Cohen, 2001; Gusnard, Akbudak, Shulman, & Raichle, 2001; Harrison et al., 2008; Johnson et al., 2006; Kiehl et al., 2001; Maddock, Garrett, & Buonocore, 2003; Philippi & Koenigs, 2014; Sebastian et al., 2008; Vollm et al., 2006). Researchers have suggested that the DMN develops as the individual matures, being sparsely connected under the age of 10 and strongly functionally connected by age 21 (Fair et al., 2008). Finally, the DMN can be collectively viewed as being most active when an individual is disengaged from the external world and thinking (mentalizing) about the self, especially when engaged in introspective, internal narrative involving judgments about self-worth and self-concept, and contemplations about past, present, and future behaviors.

CEN

Also referred to as the cognitive control network or executive control network, the CEN is thought to be linked to salience processing, control of attention, planning, decision-making in context of goal-directed behavior, rule-based problem solving, evaluating information, self-regulation, executive function, maintaining and manipulating information in working memory, and inhibition of irrelevant information patterns (Barrett & Satpute, 2013; Bressler & Menon, 2010; Francx et al., 2015; Heinonen et al., 2016; Menon, 2011; Niendam et al., 2012; Owen, Downes, Sahakian, Polkey, & Robbins, 1990). The CEN is generally thought to include the dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, lateral posterior parietal cortex, superior lateral parietal cortex, inferior parietal cortex, anterior insula, caudate, putamen, and cerebellum (Bellebaum & Daum, 2007; Liston et al., 2014; Niendam et al., 2012). It has been suggested that the CEN controls attention and includes a dorsal (dorsal parietal cortex, intraparietal sulcus, superior parietal lobule, dorsal frontal cortex along the precentral sulcus) and ventral (temporoparietal junction, posterior sector of the superior temporal sulcus and gyrus, the ventral part of the supramarginal gyrus, ventral frontal cortex, including parts of middle frontal gyrus, inferior frontal gyrus, frontal operculum, anterior insula, orbitofrontal cortex) subnetwork (Barrett & Satpute, 2013; Corbetta, Patel, & Shulman, 2008; Dong, Lin, Hu, Xie, & Du, 2015; Hamilton et al., 2015). The dorsal subnetwork shows increased activation during external goal- and task-focused cognitions and sensory processing of cues in the external environment. The ventral subnetwork shows increased activation when aspects of selective attention disrupt in-progress goal-directed activity and reorient attention toward other relevant stimuli. Researchers have shown that CEN brain structures also become active when making decisions about risky or dangerous social situations (Rodrigo, Padrón, De Vega, & Ferstl, 2014). Individuals with high impulsive-hyperactive traits have been shown to have decreased levels of CEN activity during resting-states when instructed to relax (Cohn et al., 2015), suggesting they have less externally directed attentional control, have less self-regulation, and engage in less evaluation of external task- or goal-focused information. In summary, the CEN can be viewed as being most active when regarding the worth and direct applicability of events in the external world and making decisions about attending to or acting upon these events.

SN

The SN includes the anterior insula, dorsal anterior cingulate cortex, ventral striatum, amygdala, substantia nigra, ventral tegmental area, and thalamus (Barrett & Satpute, 2013; Chong, Ng, Lee, & Zhou, 2016; Seeley et al., 2007; Yoder et al., 2015). The SN also shares the parts of the dorsal anterior cingulate cortex with the CEN, and areas of the bilateral insula involved in the SN are located just ventral to the areas of the anterior insula involved in the CEN (Hamilton et al., 2015). It is believed the SN is involved in consciously and unconsciously detecting personally or motivationally salient (rewarding, punishing) cognitive, biological, and emotional cues contained within internal and extrapersonal stimuli, helping the individual guide choices about actions, and selectively changing activity levels in other networks accordingly (Dosenbach et al., 2007; Green et al., 2016; Hamilton et al., 2015; Medford & Critchley, 2010; Seeley et al., 2007; Yoder et al., 2015). Similarly, the SN appears to direct the oscillation between internal focus and external task-processing (Medford & Critchley, 2010; Menon & Uddin, 2010; Palaniyappan & Liddle, 2012; Seeley et al., 2007). The SN is also believed to be involved in somatoviceral regulation (anger, disgust, fear, sadness, happiness), tracking feelings of pleasure, distress, and arousal, and switching between internal and external events (Barrett & Satpute, 2013). Furthermore, the SN appears to guide the CEN and the DMN, allowing flexibility in decision-making when adapting behaviorally (Bonnelle et al., 2012; Hamilton et al., 2015; Rilling, Dagenais, Goldsmith, Glenn, & Pagnoni, 2008; Sridharan, Levitin, & Menon, 2008). Researchers have found that activation in the SN is negatively correlated with activation in the DMN (Seeley et al., 2007). Researchers also suggest the SN activates the DMN during moral judgments and deactivates the DMN during nonmoral dilemmas (Chiong et al., 2013). In summary, the SN can be viewed as attending to salient cognitive, biological, and emotional cues and acting as a switching station that routes salient external cues for processing.

Brain Networks and Brain Structure Maturation

Researchers recognized in the late 1990s that human brain structures progress through significant maturational stages through the early 20s, during which white matter increases in a linear fashion and cortical gray matter follows an inverted U-shaped course, with greater regional variation than white matter (see Giedd, 2004; Giedd et al., 1999). In addition, recent researchers have shown that large-scale functional brain networks evolve early in life and become more distinct during childhood and adolescence (Gu et al., 2015; van den Heuvel et al., 2015). Refinement of these functional networks through childhood and adolescence increases connectivity within networks and decreases connectivity between networks, which leads to reductions in between-network interference and increased efficiency within networks (Baum et al., 2017). It is this reduced level of between-network interference that allows the CEN to suppress the DMN (Baum et al., 2017). Recently, Satterthwaite et al. (2013) noted that in a sample of 951 youth, ages 8 to 22, cognitive performance on a neurocognitive battery was more strongly associated with activation in the CEN and deactivation in the DMN than was chronological age. This discovery, combined with findings by Baum et al. (2017) that as brain structures mature they become more segregated (leading to better efficiency and global integration), may suggest that large-scale brain networks do not create more skills as the individual develops, rather existing functional skill sets become more efficient over time. Therefore, it is not that youth cannot make decisions, it is likely they just do not make decisions very efficiently. This might explain, for example, why youth do not consider outcomes of behaviors as much as immediate rewards (Reyna & Farley, 2006). This lack of efficiency might also explain why adolescents engage in risky behaviors. That is, interference from their SN, which includes limbic system structures (amygdala; thalamus) interferes with CEN decision-making, and this leads to poor decision-making (i.e., failing to consider risk, delaying gratification, disinhibition). How brain structure maturation affects an adolescent’s use of techniques of neutralization does not appear to have been explored, although doing so would be beneficial.

Brain Networks and Biosocial Factors

Relevant to the discussion of brain network development and function is the influence of biosocial factors. Although an in-depth review of this relationship is beyond the scope of this article, a brief discussion illustrates how damage to the brain, environmental factors, and neurodevelopmental disorders are associated with brain regions contained within the DMN, SN, and CEN.

Traumatic Brain Injury (TBI)

Due to the manner in which the brain is situated within the skull, the frontal and temporal lobes of the brain are highly susceptible to injury from inertial and contact forces (Bigler, 2007). The frontal lobe contains two relevant brain regions: the dorsolateral prefrontal cortex and the lateral orbitofrontal cortex. As noted above, these are believed to be strongly involved in CEN function. Another frontal lobe region is the dorsal anterior cingulate, which, as stated previously, is involved in the SN function. The temporal lobes are where the hippocampal formation and parahippocampal cortex are located and, as discussed earlier, these are involved in functions associated with the DMN.

Diagnosed TBI during childhood has been linked to a variety of adverse health and social outcomes later in life including disability pension, psychiatric visits and hospitalizations, premature mortality, low education, and welfare recipiency (Sariaslan, Sharp, D’Onofrio, Larsson, & Fazel, 2016). Self-reported early childhood TBI has also been linked to earlier and more significant self-reports of illicit drug use, higher rates of alcohol consumption, and higher levels of aggression (Fishbein, Dariotis, Ferguson, & Pickelsimer, 2016). Severe TBI in early childhood with damage to the dorsolateral prefrontal cortex, lateral orbitofrontal cortex, hippocampi, and corpus callosum has been associated with significant deficits in self-control and disinhibition (CEN), emotional lability and bouts of anxiety (DMN), inappropriate behaviors toward others and excessive irrational fear (SN), and unawareness (SN) and misjudgment of personal safety (DMN) during environmentally dangerous situations (Jantz & Bigler, 2014). Self-reported TBI by incarcerated adolescents has been found to be associated with short-term decreases in self-control and short-term increases in aggression and delinquency (Schwartz, Connolly, & Brauer, 2017).

Connectivity within the CEN and DMN display a positive correlation and are directed and anticorrelated with SN connectivity (Barrett & Satpute, 2013; Seeley et al., 2007). Moreover, the CEN has been linked to self-regulation while the DMN has been associated with self-awareness, emotional regulation, and moral development (Andrews-Hanna, 2012; Cavanna & Trimble, 2006; Chiong et al., 2013; Rodrigo et al., 2014). From a developmental viewpoint, injury to brain structures in any of these three networks, therefore, could lead to developmental abnormalities in the other two systems, which may result in impaired self-regulation and emotion as well as self-awareness and personal moral development. This impaired network interaction would not only lead to the inability to regulate behavior and feelings, but it also may affect the ability to reflect upon the moral implications of actions. When confronted with the negative outcomes of their violent behavior after the fact, individuals with network impairments would justify their actions as in accordance with neutralization theory as described below.

Environmental Factors

Research evidence suggests that brain abnormalities associated with violence and psychopathy often stem from environmental stimuli, namely childhood exposure to violence (Boxer et al., 2013; Dargis & Koenigs, 2017; Lewis et al., 1988; Lewis, Shanok, Pincus, & Glaser, 1979; McCord, 1991; Weiler & Wisdom, 1996). Specifically, childhood exposure to violence has been linked with self-reported and correctional staff–reported violent behavior (Lewis et al., 1979), the number of violent convictions among juveniles (Lewis et al., 1988), the number of violent offenses committed during adulthood (Debowska & Boduszek, 2017; McCord, 1991), higher ratings of psychopathy (Dargis & Koenigs, 2017; Weiler & Wisdom, 1996), and higher acceptance of rape myths that include denying a victim (Debowska, Boduszek, Dhingra, Kola, & Meller-Prunska, 2015). Moreover, one finding suggests that ethnopolitical violence increases violence and aggression (Boxer et al., 2013).

Cisler, Steele, Smitherman, Lenow, and Kilts (2013) found that in adolescent females with assaultive violence exposure and posttraumatic stress disorder (PTSD) symptoms, activation was increased in SN structures (anterior cingulate, anterior insula) when viewing fearful facial expressions and functional connectivity between structures of the CEN (perigenual anterior cingulate) and SN (amygdala) was mediated by severity of PTSD symptoms. Assaultive violence exposure and PTSD symptom severity were also found to mediate activity in DMN structures (parahippocampus, medial/lateral prefrontal cortex). In addition, Bertsch et al. (2013) found significant volumetric reductions in DMN structures (dorsal medial prefrontal cortex, posterior cingulate, precuneus) in offenders with high ratings on measures of psychopathy, while Bueso-Izquierdo, Verdejo-Roman, Contreras-Rodriguez, Carmona-Perera, and Hidalgo-Ruzzante (2016) found increased activation in the DMN structures (anterior/posterior cingulate cortex and medial prefrontal cortex) in males convicted of battery. When examining convicted and unconvicted psychopaths, Yang, Raine, Colletti, Toga, and Narr (2010) found reduced gray matter volume and thickness in structures associated with the SN (amygdala) and DMN (medial frontal cortex) in convicted psychopaths. Similarly, researchers have found that psychopathy is associated with abnormalities in structures associated with the DMN (Juarez, Kiehl, & Calhoun, 2013; Sheng, Gheytanchi, & Aziz-Zadeh, 2010; Thijssen et al., 2015), the SN (Krishnadas, Palaniyappan, Lang, McLean, & Cavanagh, 2014), and the CEN (Boccardi, 2013; Davidson, Putnam, & Larson, 2000; Mehta & Beer, 2010; Raine, 1993; Raine, Lencz, Bihrle, LaCasse, & Colletti, 2000).

Imaging studies have linked exposure to violence with abnormalities within the CEN, DMN, and SN (Cisler et al., 2013; Sripada et al., 2012; Steudte-Schmiedgen et al., 2014). That is, exposure to violence been shown to disrupt connectivity within the SN and connectivity between the SN and DMN (Cisler et al., 2013; Sripada et al., 2012). In addition, Thijssen et al. (2015) found evidence that suggests that SN and DMN abnormalities among violent children occur developmentally earlier than the CEN. These findings suggest that exposure to violence may affect the SN and DMN, leading to neuroplastic changes, and further disrupt the CEN, which may eventually result in developing psychopathy.

Neurodevelopmental Disorders

As Hughes (2015) noted, compared with the general youth population, there is a disproportionately higher prevalence of neurodevelopmental disorders among young offenders in custody including intellectual disability, prenatal alcohol exposure, communication disorders, attention-deficit hyperactivity disorder (ADHD), and autism spectrum disorder. Developmental abnormalities in the cortical layers of the CEN (orbitofrontal prefrontal cortex and insula) and DMN (medial prefrontal cortex, temporal cortex) have been found in individuals with intellectual disabilities (Zhang et al., 2010). Children with prenatal alcohol exposure have been found to have reduced resting-state functional connectivity in the DMN (postcentral gyrus) and SN (middle frontal gyrus; Fan et al., 2017). Silbert, Honey, Simony, Poeppel, and Hasson (2014) found activation in DMN structures (posterior cingulate cortex, medial prefrontal cortex, precuneus, medial and superior temporal gyrus, inferior frontal gyrus, temporoparietal junction) during spontaneous and rehearsed speech production. Researchers examining young children and adolescents with autism spectrum disorder diagnoses found reduced long-range functional connectivity between the posterior cingulate cortex and other DMN areas (precuneus, precentral gyrus, left frontal pole) as well as CEN areas (posterior cingulate cortex, medial prefrontal regions, anterior cingulate cortex; Schreiner et al., 2014; Yerys et al., 2015). Francx et al. (2015), examining persistent hyperactive/impulsive ADHD symptoms in adolescents, found decreased resting-state functional connectivity in CEN regions (anterior cingulate cortex, paracingulate gyrus).

As Hughes (2015) also pointed out, there is a wide range of biological factors that could explain antisocial and aggressive behavior, and likewise these neurodevelopmental disorders add another layer that may affect a juvenile delinquent’s use of neutralization techniques.

Neutralization Theory

For nearly 60 years, neutralization theory first introduced in the seminal article Techniques of Neutralization (Sykes & Matza, 1957) has been integrated into various sociological and criminological theories (Copes & Deitzer, 2016; Maruna & Copes, 2005). These include, control theory (Gottfredson & Hirschi, 1990; Williams & McShane, 2004), rational choice theory (Cornish & Clarke, 1987), life course theory (Sampson & Laub, 2005), and reintegrative shaming theory (Braithwaite, 1989). At its core, neutralization theory (Matza, 1964; Sykes & Matza, 1957) says that whereas society has legal defenses (e.g., self-defense, insanity) that remove criminal intent and allow individuals to avoid moral culpability for their behaviors, juvenile delinquents have a set of learned neutralization techniques (e.g., denial of injury; see below) that allow them to avoid moral culpability for their deviant acts. Where the two differ, however, is the point at which these are applied. That is, according to Sykes and Matza (1957), the legal system protects the individual from self-blame and the blame of others by rationalizing behavior after the act, and juvenile delinquents use what Sykes and Matza refer to as techniques of neutralization to protect themselves and justify deviant behavior in advance of the act. Furthermore, Sykes and Matza theorized that preemptively engaging in techniques of neutralization allows juveniles to engage in aberrant acts they know are principally against the rules of mainstream society, because techniques of neutralization remove morally based, preventive, social controls. Techniques of neutralization also allow juvenile delinquents to retain a positive moral self-image and view themselves as still being able to adhere to the social mores of society, thereby avoiding or reducing behavior-related shame or guilt. The use of techniques of neutralization allows juvenile delinquents to drift back and forth between socially acceptable and unacceptable behavior (Matza, 1964).

Sykes and Matza (1957) presented five techniques of neutralization that allow juvenile delinquents to maintain a perception that they are good moral beings: the denial of responsibility (there are extenuating circumstances), the denial of injury (no one really got hurt), the denial of the victim (the victim got what the victim deserved), the condemnation of the condemners (the condemners are hypocrites), and the appeal to higher loyalties (it is being done for the greater good).

Murray and Topalli (2014) have noted neutralization theory has been revised to explain criminal behavior in adults (e.g., assassination; assault on prostitutes, white-collar crime) and Maruna and Copes (2005) suggested neutralization theory could apply to anyone experiencing inconsistency between their actions and beliefs. Consequently, the past six decades has seen many more neutralization techniques added to a still growing list (i.e., defense of necessity, claim of normality, claim of entitlement, metaphor of the ledger, justification by comparison, postponement; Murray & Topalli, 2014). Recently, it has been suggested that individuals who wish to uphold a moral self-image that conforms to the greater morals of society will use techniques of neutralization to drift back and forth between criminal and noncriminal worlds, whereas, persistent, predatory criminals who wish to maintain a criminal self-image (the perception that being a bad person is good and being a good person is bad) use techniques of neutralization to create amoral excuses that create an illusion of drift and conformity with conventional morality standards (Jacobs & Copes, 2015).

DMN, CEN, SN, and Techniques of Neutralization

As noted above, researchers have suggested that the DMN is involved in internally focused cognitions that include moral reasoning, the SN and CEN are involved in external task- and goal-related cognitions that include deliberations, and the SN plays a general role in switching between the DMN and the CEN (Barrett & Satpute, 2013; Chiong et al., 2013; Hamilton et al., 2015; Medford & Critchley, 2010; Menon & Uddin, 2010; Palaniyappan & Liddle, 2012; Seeley et al., 2007). Researchers have also found that when the CEN is active during nonmoral reasoning (weighing actions that do not affect the interests of others) or impersonal moral reasoning (weighing actions that affect others, but do not violate personal rights), there is increased activation in the SN and decreased activation in the DMN (Chiong et al., 2013). Conversely, during decisions regarding personal moral dilemmas (e.g., weighing actions that violate someone’s personal rights), there is increased activation in the SN and decreased activation in the CEN and increased activation in the DMN (Chiong et al., 2013; Mendez & Shapira, 2009; Menon & Uddin, 2010).

According to Sykes and Matza (1957), the use of techniques of neutralization involves moral reasoning, moral decision-making, and moral judgment—various aspects of which are thought to involve the DMN, CEN, and SN (Chiong et al., 2013; Greene et al., 2001; Harrison et al., 2008; Philippi & Koenigs, 2014; Yoder et al., 2015). Yoder et al. (2015) found that when engaged in making dichotomous explicit moral judgments (right vs. wrong) and dichotomous implicit moral judgments when information regarding impersonal harm was task-irrelevant (answering a yes–no question about event location), incarcerated individuals who were rated high on a measure of psychopathy had significantly reduced activation in the SN, CEN, and DMN than did those with low ratings. This finding suggests that comparatively, these individuals paid less attention to salient moral cues, engaged in lower levels of cognitive deliberation about the worth and direct applicability of cues and events, and engaged in less moral reasoning.

The use of techniques of neutralization also requires the individual to be able to preempt emotions related to guilt or shame (e.g., anger, disgust, fear, sadness, happiness), track feelings of distress in others and the self, and switch focus between internal and external events. To be accomplished, this requires that the individual suspend empathy associated with the intended victim. The SN is believed to be involved in the regulation of these emotions and tasks (Barrett & Satpute, 2013; Medford & Critchley, 2010; Menon & Uddin, 2010; Palaniyappan & Liddle, 2012; Seeley et al., 2007). Yoder et al. (2015) found that when viewing implicit and explicit morally loaded events, incarcerated individuals who were rated high on a measure of psychopathy showed significantly reduced functional connectivity between a DMN node (right temporoparietal junction) and an SN node (right amygdala). These nodes are known to be involved in theory of mind, emotional salience, and moral cognition. These findings suggest that when viewing morally loaded events involving interpersonal harm or interpersonal assistance, there was a significant reduction in the amount of cognition devoted to the emotional or intentional cues of others.

According to neutralization theory, the use of techniques of neutralization preemptively neutralizes social controls that otherwise serve to check or inhibit following through on an act. In order for techniques of neutralization to be effective, individuals must devalue external salient information about the intended act when making decisions within the context of their goal-directed behavior (e.g., harm to the victim), regulate impulses to adhere to the rules of society, and inhibit irrelevant information (e.g., meeting personal goals at the expense of others). The CEN is believed to be involved in these cognitive activities (Fornito, Yoon, Zalesky, Bullmore, & Carter, 2011; Laird et al., 2005; Miller, 2000; Miller & Cohen, 2001; Niendam et al., 2012; Owen et al., 1990). It has been suggested that the CEN is deactivated when moral decisions involve violating someone’s personal rights and are activated during nonmoral practical dilemmas and impersonal dilemmas that require the weighting of harms and benefits (Chiong et al., 2013).

By using these techniques of neutralization, it is argued that juvenile delinquents are able to avoid self-blame and the blame of others, avoid moral culpability for their acts, and retain a positive self-image. Chiong et al. (2013) have shown that the DMN becomes activated when pondering personal moral dilemmas and that those with damage to the SN have been shown to give significantly more utilitarian responses (e.g., those that favor sacrificing a lesser number to preserve the interests of a greater number) than do healthy individuals. They have also suggested that abnormality in the function of the SN would result in an inability to attend to the personal dimensions of moral dilemmas and a subsequent inactivation in the DMN.

Application of DMN, CEN, and SN to Techniques of Neutralization

Current brain network research appears to apply to the use of techniques of neutralization. To illustrate, this section will compare nondelinquent juveniles with delinquent juveniles. As noted in Figure 1, it could be argued that when nondelinquent juveniles begin to contemplate engaging in unlawful acts, there is increased activation in the SN as they start to focus on information relevant to various aspects of the intended act. At this point, there would be activation in the dorsal subnetwork of the CEN as they begin processing information salience within the context of behavioral goals and outcomes. As they detect salient moral cues related to the act, there would be increased activation in the ventral subnetwork of the CEN and decreased activation in the dorsal subnetwork of the CEN. As these moral cues begin to be deliberated by the individuals in terms of theory of mind/perspective-taking, emotional processing, moral decision-making, and cognitions about the past, present, and future as these relate to the intended act, there would be increased activation in the SN, decreased activation in the CEN, and increased activation in the DMN. As the individuals judge the intended act to be in opposition to the rights of others, social mores, and/or personal beliefs, there would be decreased activation in the DMN and increased activation in the SN and the CEN, as the desire to follow through with the act is inhibited.

Figure 1.

Brain network activation in a nondelinquent juvenile contemplating engaging in an unlawful act.

When juvenile delinquents engage in the use techniques of neutralization, there would be significantly decreased activation in the DMN and the ventral subnetwork of the CEN and significantly increased activation in the SN and the dorsal subnetwork of the CEN (Figure 2). This hypothesis can be illustrated using the following example of techniques of neutralization in which a juvenile delinquent detained in a juvenile facility is contemplating physically assaulting a fellow detainee accused of rape:

This is juvie, I don’t make the rules, I just follow them (the denial of responsibility). I’m not going to kill him, I’m just going to kick his ass, (the denial of injury). He raped a helpless female, he deserves what he gets (the denial of the victim). Hey, I didn’t ask to be put in the same room with this guy . . . the guards know we don’t like rapists and they should never have put him in here (the condemnation of the condemners). I’d just be following the Juvenile Code of Honor and doing society a favor by making him pay for what he did to a helpless female (the appeal to higher loyalties).

In each of these techniques, activation in the DMN would be reduced as the juvenile delinquent is not contemplating theory of mind/perspective-taking, emotional processing, or moral decision-making and activation in the SN and dorsal subnetwork of the CEN would be increased as the juvenile delinquent is focused on the task and the goal-directed, rule-based behavior.

Figure 2.

Brain network activation in a delinquent juvenile using techniques of neutralization.

A brain network perspective, therefore, supports how this juvenile delinquent is able to maintain a positive moral self-image when using techniques of neutralization. That is, by focusing on the nonpersonal aspects of the act (i.e., the rules, fighting [kicking ass vs. killing], the crime [rape], housing error on the part of the guard, Juvenile Code of Honor), the SN and dorsal subnetwork of the CEN override the ventral subnetwork of the CEN. This override prevents the SN from shifting attention away from cognitions about goal-directed activity (physically assaulting a fellow detainee accused of rape) toward personal aspects of the act (e.g., moral prohibitions against violent acts) that would result in the increased activation of the network most associated with theory of mind/perspective-taking, moral reasoning, moral decision-making, and moral judgment, the DMN. As long as there is inhibited activity in the DMN (i.e., interference from the SN and CEN), the juvenile delinquent is not engaging in significant internally focused, morally driven theory of mind/perspective-taking cognitions. Therefore, negative emotions that would otherwise be associated with a negative moral self-image remain externally focused by the SN. This externalization of focus allows the juvenile delinquent to direct any negative emotions (e.g., anger) toward salient external, nonpersonal aspects of acts and complete tasks without remorse, guilt, shame, or degradation of a positive moral self-image.

Implications for Future Research

In as much as the brain is connected to behavior, it is also connected to theories about behavior. Over the years, theorists have proffered various explanations for deviant social behavior and continue to seek better understanding and refinement of their work. One such theory, neutralization theory (Matza, 1964; Sykes & Matza, 1957), has been integrated into various sociological and criminological theories for nearly 60 years. There has also been a plethora of research examining the core principals of neutralization theory and the application of techniques of neutralization, with mixed results (see Maruna & Copes, 2005, for a critical appraisal). Despite the lack of strong empirical support for neutralization theory, it has endured and been incorporated into criminal and sociological theory (Copes & Deitzer, 2016; Maruna & Copes, 2005).

Examining how the human brain functions is helpful in understanding and interpreting theory and behavior. Researchers using advanced MRI techniques to map brain activation, specifically fMRI, have identified intrinsically organized, large-scale brain networks in humans and suggested that three networks in particular (DMN, SN, CEN) are involved in collectively controlling attention, working memory, decision-making, and other higher level cognitive operations (Chen et al., 2013). It has also been suggested that these networks are involved in moral reasoning, moral decision-making, moral judgment, theory of mind, emotion regulation, and switching focus between internal and external events (Barrett & Satpute, 2013; Chiong et al., 2013; Greene et al., 2001; Harrison et al., 2008; Medford & Critchley, 2010; Menon & Uddin, 2010; Molenberghs et al., 2015; Palaniyappan & Liddle, 2012; Philippi & Koenigs, 2014; Seeley et al., 2007; Yoder et al., 2015). Clearly, there is overlap between cognitive processes believed to be related to the DMN, SN, and CEN and cognitive processes involved in the use of techniques of neutralization.

If the use of techniques of neutralization can be reliably linked to specific brain networks, and these same networks can be connected to core concepts associated with neutralization theory, then the involvement of these brain networks could increase the validity of neutralization theory and lead to a better understanding of the use of techniques of neutralization. Brain network research may also better link internal locus of control (DMN) and external locus of control (SN, CEN) to neutralization theory and the use of techniques of neutralization. Matza’s (1964) concept of drift suggests that individuals engage in the use of techniques of neutralization to regain a sense of control (internal locus, DMN) over situations into which they have been helplessly thrown (external locus, SN). Heatherton and Wagner (2011) discussed research findings that suggest environmental triggers (e.g., resource depletion, exposure to factors that elicited negative affect) can be linked to neurological dysfunction and trigger a self-regulation failure (CEN), which, can be considered a form of drift (i.e., a temporary period of irresponsibility). Examining the internal focus of the DMN, the external focus of the SN, and regulatory function of the CEN and SN may be helpful in better understanding self-regulation failures, the role that techniques of neutralization play in these failures, and the notion of drift.

Although fMRI has limitations (see Weinberger & Radulescu, 2016) and the existence of intrinsically organized, large-scale brain networks are theoretical, fMRI allows researchers to study the human brain in vivo. This has the potential to address one of the most common criticism of techniques of neutralization research: Individuals engage in the use of techniques of neutralization in advance of committing socially deviant acts and there is no reliable way to collect empirical evidence of this occurring.

How cognition and affective functioning is related to brain networks and the role that brain structure maturation and biosocial factors (e.g., damage to the brain, environmental factors, neurodevelopmental disorders) play in brain network interaction, efficiency, and function is not well understood. Building on research in these areas, this article has proffered an explanation of the relationship between three hypothesized intrinsically organized, distinct functional brain networks (DMN, SN, CEN) and an enduring core feature of neutralization theory believed to be utilized by juvenile delinquents to avoid self-blame, the blame of others, and moral culpability for their acts; techniques of neutralization.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Andrews-Hanna

J. R.

(2012). The brain’s default network and its adaptive role in internal mentation. The Neuroscientist, 18, 251-270. doi:10.1177/1073858411403316

Bandettini

P. A.

(2012). Twenty years of functional MRI: The science and the stories. NeuroImage, 62, 575-588. doi:10.1016/j.neuroimage.2012.04.026

Barrett

L. F.

Satpute

A. B.

(2013). Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain. Current Opinion in Neurobiology, 23, 361-372. doi:10.1016/j.conb.2012.12.012

Baum

G. L.

Ciric

Roalf

D. R.

Betzel

R. F.

Moore

T. M.

Shinohara

R. T.

. . . Satterthwaite

T. D.

(2017). Modular segregation of structural brain networks supports the development of executive function in youth. Current Biology, 27, 1561-1572. doi:10.1016/j.cub.2017.04.051

Bellebaum

Daum

(2007). Cerebellar involvement in executive control. Cerebellum, 6, 184-192. doi:10.1080/14734220601169707

Bertsch

Grothe

Prehn

Vohs

Berger

Hauenstein

. . . Herpertz

S. C.

(2013). Brain volumes differ between diagnostic groups of violent criminal offenders. European Archives of Psychiatry and Clinical Neuroscience, 263, 593-606. doi: 10.1007/s00406-013-0391-6

Bigler

E. D.

(2007). Anterior and middle cranial fossa in traumatic brain injury: Relevant neuroanatomy and neuropathology in the study of neuropsychological outcome. Neuropsychology, 21, 515-531. doi:10.1037/0894-4105.21.5.515

Blakemore

S. J.

(2012). Development of the social brain in adolescence. Journal of the Royal Society of Medicine, 105, 111-116. doi:10.1258/jrsm.2011.110221

Boccardi

(2013). Structural brain abnormalities and psychopathy. In Kiehl

K. A.

Sinnott-Armstrong

W. P.

(Eds.), Handbook on psychopathy and law (pp. 150-157). New York, NY: Oxford University Press.

10.

Bonnelle

Ham

T. E.

Leech

Kinnunen

K. M.

Mehta

M. A.

Greenwood

R. J.

Sharp

D. J.

(2012). Salience network integrity predicts default mode network function after traumatic brain injury. Proceedings of the National Academy of Sciences of the United States of America, 109, 4690-4695. doi:10.1073/pnas.1113455109

11.

Boxer

Rowell Huesmann

Dubow

E. F.

Landau

S. F.

Gvirsman

S. D.

Shikaki

Ginges

(2013). Exposure to violence across the social ecosystem and the development of aggression: A test of ecological theory in the Israeli-Palestinian conflict. Child Development, 84, 163-177. doi:10.1111/j.1467-8624.2012.01848.x

12.

Braithwaite

(1989). Crime, shame, and reintegration. Cambridge, UK: Cambridge University Press.

13.

Bressler

S. L.

Menon

(2010). Large-scale brain networks in cognition: Emerging methods and principles. Trends in Cognitive Sciences, 14, 277-290. doi:10.1016/j.tics.2010.04.004

14.

Buckner

R. L.

Andrews-Hanna

J. R.

Schacter

D. L.

(2008). The brain’s default network: Anatomy, function, and relevance to disease. Annuals of the New York Academy of Sciences, 1124, 1-38. doi:10.1196/annals.1440.011

15.

Bueso-Izquierdo

Verdejo-Roman

Contreras-Rodriguez

Carmona-Perera

Hidalgo-Ruzzante

(2016). Are batterers different from other criminals? An fMRI study. Social Cognitive and Affective Neuroscience, 11, 852-862. doi:10.1093/scan/nsw020

16.

Cavanna

A. E.

Trimble

M. R.

(2006). The precuneus: A review of its functional anatomy and behavioural correlates. Brain, 129, 564-583. doi:10.1093/brain/awl004

17.

Chen

A. C.

Oathes

D. J.

Chang

Bradley

Zhou

Williams

L. M.

. . . Etkin

(2013). Causal interactions between fronto-parietal central executive and default-mode networks in humans. Proceedings of the National Academy of Sciences of the United States of America, 110, 19944-19949. doi:10.1073/pnas.1311772110

18.

Chiong

Wilson

S. M.

D’Esposito

Kayser

A. S.

Grossman

S. N.

Poorzand

. . . Rankin

K. P.

(2013). The salience network causally influences default mode network activity during moral reasoning. Brain, 136, 1929-1941. doi:10.1093/brain/awt066

19.

Chong

J. S. X.

G. J. P.

Lee

S. C.

Zhou

(2016, August 29). Salience network connectivity in the insula is associated with individual differences in interoceptive accuracy. Brain Structure and Function, 1-10. Epub, doi:10.1007/s00429-016-1297-7

20.

Cisler

J. M.

Steele

J. S.

Smitherman

Lenow

J. K.

Kilts

C. D.

(2013). Neural processing correlates of assaultive violence exposure and PTSD symptoms during implicit threat processing: A network-level analysis among adolescent girls. Psychiatry Research: Neuroimaging, 214, 238-246. doi:10.1016/j.pscychresns.2013.06.003

21.

Cohn

M. D.

Pape

L. E.

Schmaal

van den Brink

van Wingen

Vermeiren

R. R.

. . . Popma

(2015). Differential relations between juvenile psychopathic traits and resting state network connectivity. Human Brain Mapping, 36, 2396-2405.

22.

Copes

Deitzer

(2016). Neutralization theory. In Jennings

W. G.

(Ed.), The encyclopedia of crime and punishment (1st ed., pp. 1-5). Hoboken, NJ: John Wiley.

23.

Corbetta

Patel

Shulman

G. L.

(2008). The reorienting system of the human brain: From environment to theory of mind. Neuron, 58, 306-324. doi:10.1016/j.neuron.2008.04.017

24.

Cornish

Clarke

(1987). Understanding crime displacement: An application of rational choice theory. Criminology, 25, 933-947. doi:10.1111/j.1745-9125.1987.tb00826.x

25.

Dargis

Koenigs

(2017). Witnessing domestic violence during childhood is associated with psychopathic traits in adult male criminal offenders. Law and Human Behavior, 41, 173-179. doi:10.1037/lhb0000226

26.

Davidson

R. J.

Putnam

K. M.

Larson

C. L.

(2000). Dysfunction in the neural circuitry of emotion regulation: A possible prelude to violence. Science, 289, 591-594. doi:10.1126/science.289.5479.591

27.

Debowska

Boduszek

(2017). Child abuse and neglect profiles and their psychosocial consequences in a large sample of incarcerated males. Child Abuse & Neglect, 65, 266-277. doi:10.1016/j.chiabu.2016.12.003

28.

Debowska

Boduszek

Dhingra

Kola

Meller-Prunska

(2015). The role of psychopathy and exposure to violence in rape myth acceptance. Journal of Interpersonal Violence, 30, 2751-2770. doi:10.1177/0886260514553635

29.

Dong

Lin

Xie

(2015). Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in internet gaming disorder. Scientific Reports, 5(9197), 1-6. doi:10.1038/srep09197

30.

Dosenbach

N. U.

Fair

D. A.

Miezin

F. M.

Cohen

A. L.

Wenger

K. K.

Dosenbach

R. A.

. . . Petersen

S. E.

(2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences of the United States of America, 104, 11073-11078. doi:10.1073/pnas.0704320104

31.

Fair

D. A.

Cohen

A. L.

Dosenbach

N. U.

Church

J. A.

Miezin

F. M.

Barch

D. M.

. . . Schlaggar

B. L.

(2008). The maturing architecture of the brain’s default network. Proceedings of the National Academy of Sciences of the United States of America, 105, 4028-4032. doi:10.1073/pnas.0800376105

32.

Fan

Taylor

P. A.

Jacobson

S. W.

Molteno

C. D.

Gohel

Biswal

B. B.

. . . Meintejes

E. M.

(2017). Localized reductions in resting-state functional connectivity in children with prenatal alcohol exposure. Human Brain Mapping. Retrieved from http://onlinelibrary.wiley.com/wol1/doi/10.1002/hbm.23726/abstract

33.

Fishbein

Dariotis

J. K.

Ferguson

P. L.

Pickelsimer

E. E.

(2016). Relationships between traumatic brain injury and illicit drug use and their association with aggression in inmates. International Journal of Offender Therapy and Comparative Criminology, 60, 575-597. doi:10.1177/0306624X14554778

34.

Fornito

Yoon

Zalesky

Bullmore

E. T.

Carter

C. S.

(2011). General and specific functional connectivity disturbances in first-episode schizophrenia during cognitive control performance. Biological Psychiatry, 70, 64-72. doi:10.1016/j.biopsych.2011.02.019

35.

Fox

M. D.

Snyder

A. Z.

Vincent

J. L.

Corbetta

Van Essen

D. C.

Raichle

M. E.

(2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. PNAS, 102, 9673-9678. Retrieved from http://www.pnas.org/content/102/27/9673.full

36.

Francx

Oldehinkel

Oosterlaan Heslenfeld

Hartmann

C. A.

Hoekstra

P. J.

Mennes

(2015). The executive control network and symptomatic improvement in attention-deficit/hyperactivity disorder. Cortex, 73, 62-72. doi:10.1016/j.cortex.2015.08.012

37.

Fransson

(2005). Spontaneous low-frequency BOLD signal fluctuations: An fMRI investigation of the resting-state default mode of brain function hypothesis. Human Brain Mapping, 26, 15-29. Retrieved from http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0193

38.

Giedd

J. N.

(2004). Structural magnetic resonance imaging of the adolescent brain. Annals of the New York Academy of Science, 1021, 77-85. doi:10.1196/annals.1308.009

39.

Giedd

J. N.

Blumenthal

Jeffries

N. O.

Castellanos

F. X.

Liu

Zijdenbos

. . . Rapoport

J. L.

(1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2, 861-863. doi:10.1038/13158

40.

Gottfredson

M. R.

Hirschi

(1990). A general theory of crime. Redwood City, CA: Stanford University Press.

41.

Green

S. A.

Hernandez

Bookheimer

S. Y.

Dapretto

(2016). Salience network connectivity in autism is related to brain and behavioral markers of sensory overresponsivity. Journal of the American Academy of Child & Adolescent Psychiatry, 55, 618-626. doi:10.1016/j.jaac.2016.04.013

42.

Greene

J. D.

Sommerville

R. B.

Nystrom

L. E.

Darley

J. M.

Cohen

J. D.

(2001). An fMRI investigation of emotional engagement in moral judgment. Science, 293, 2105-2108. doi:10.1126/science.1062872

43.

Satterthwaite

T. D.

Medaglia

J. D.

Yang

Gur

R. E.

Gur

R. C.

Bassett

D. S.

(2015). Emergence of system roles in normative neurodevelopment. Proceedings of the National Academy of Sciences of the United States of America, 112, 13681-13686. doi:10.1073/pnas.1502829112

44.

Gusnard

D. A.

Akbudak

Shulman

G. L.

Raichle

M. E.

(2001). Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98, 4259-4264. doi:10.1073/pnas.071043098

45.

Hamilton

R. K.

Racer

K. H.

Newman

J. P.

(2015). Impaired integration in psychopathy: A unified theory of psychopathic dysfunction. Psychological Review, 122, 770-791. doi:10.1037/a0039703

46.

Harrison

B. J.

Pujol

Lopez-Sola

Hernandez-Ribas

Deus

Ortiz

. . . Cardoner

(2008). Consistency and functional specialization in the default mode brain network. Proceedings of the National Academy of Sciences of the United States of America, 105, 9781-9786. doi:10.1073/pnas.0711791105

47.

Heatherton

T. F.

Wagner

D. D.

(2011). Cognitive neuroscience of self-regulation failure. Trends in Cognitive Sciences, 15, 132-139. doi:10.1016/j.tics.2010.12.005

48.

Heinonen

Numminen

Hlushchuk

Antell

Taatila

Suomala

(2016). Default mode and executive mode network areas: Association with the serial order in divergent thinking. PLoS ONE, 11(9), e0162234. doi:10.1371/journal.pone.0162234

49.

Hughes

(2015). Understanding the influence of neurodevelopmental disorders on offending: Utilizing developmental psychopathology in biosocial criminology, Criminal Justice Studies, 28(1), 39-60. Retireved from https://www-tandfonline-com.web.bisu.edu.cn/toc/gjup20/28/1?nav=tocList

50.

Jacobs

B. A.

Copes

(2015). Neurtralization without drift: Criminal commitment among persistent offenders. British Journal of Criminology, 55, 286-302. Retrieved from https://academic.oup.com/bjc/issue/55/2

51.

Jantz

P. B.

Bigler

E. D.

(2014). Neuroimaging and the school-based assessment of traumatic brain injury. NeuroRehabilitation, 34, 479-492. doi:10.3233/NRE-141058

52.

Johnson

M. K.

Raye

C. L.

Mitchell

K. J.

Touryan

S. R.

Greene

E. J.

Nolen-Hoeksema

(2006). Dissociating medial frontal and posterior cingulate activity during self-reflection. Social Cognitive and Affective Neuroscience, 1, 56-64. doi:10.1093/scan/nsl004

53.

Juarez

Kiehl

K. A.

Calhoun

V. D.

(2013). Intrinsic limbic and paralimbic networks are associated with criminal psychopathy. Human Brain Mapping, 34, 1921-1930. doi:10.1002/hbm.22037

54.

Kiehl

K. A.

Smith

A. M.

Hare

R. D.

Mendrek

Forster

B. B.

Brink

Liddle

P. F.

(2001). Limbic abnormalities in affective processing by criminal psychopaths as revealed by functional magnetic resonance imaging. Biological Psychiatry, 50, 677-684. doi:10.1016/S0006-3223(01)01222-7

55.

Krishnadas

Palaniyappan

Lang

McLean

Cavanagh

(2014). Psychoticism and salience network morphology. Personality and Individual Differences, 57, 37-42. doi:10.1016/j.paid.2013.09.016

56.

Laird

A. R.

Fox

P. M.

Price

C. J.

Glahn

D. C.

Uecker

A. M.

Lancaster

J. L.

. . . Fox

P. T.

(2005). ALE meta-analysis: Controlling the false discovery rate and performing statistical contrasts. Human Brain Mapping, 25, 155-164. doi:10.1002/hbm.20136

57.

Lewis

D.O.

Lovely

Yeager

Ferguson

Friedman

Sloane

. . . Friedman

(1988). Intrinsic and environmental characteristics of juvenile murderers. Journal of the American Academy of Child & Adolescent Psychiatry, 27(5), 582-587. https://dx-doi-org.web.bisu.edu.cn/10.1097/00004583-198809000-00011.

58.

Lewis

D. O.

Shanok

S. S.

Pincus

J. H.

Glaser

G. H.

(1979). Violent juvenile delinquents: Psychiatric, neurological, psychological, and abuse factors. Journal of the American Academy of Child Psychiatry, 18, 307-319. doi:10.1016/S0002-7138(09)61045-1

59.

Liston

Chen

A. C.

Zebley

B. D.

Drysdale

A. T.

Gordon

Leuchter

. . . Dubin

M. J.

(2014). Default mode network mechanisms of transcranial magnetic stimulation in depression. Biological Psychiatry, 76, 517-526. Retrieved from https://dx-doi-org.web.bisu.edu.cn/10.1016/j.biopsych.2014.01.023

60.

Maddock

R. J.

Garrett

A. S.

Buonocore

M. H.

(2003). Posterior cingulate cortex activation by emotional words: fMRI evidence from a valence decision task. Human Brain Mapping, 18, 30-41. doi:10.1002/hbm.10075

61.

Maruna

Copes

(2005). What have we learned from five decades of neutralization research? Crime and Justice, 32, 221-320. Retrieved from https://www-jstor-org.web.bisu.edu.cn/stable/3488361

62.

Matza

(1964). Delinquency and drift. New York, NY: John Wiley.

63.

McCord

(1991). The long reach of childhood. International Annals of Criminology, 29, 1-2, 89-96. Retrieved from http://idb.ub.uni-tuebingen.de/diglit/AIC_1991/0089/image?sid=74f2987fd30d1f7016e486c67ccacfb8

64.

Medford

Critchley

H. D.

(2010). Conjoint activity of anterior insular and anterior cingulate cortex: Awareness and response. Brain Structure & Function, 214, 535-549. doi:10.1007/s00429-010-0265-x

65.

Mehta

P. H.

Beer

(2010). Neural mechanisms of the testosterone-aggression relation: The role of orbitofrontal cortex. Journal of Cognitive Neuroscience, 22, 2357-2368. doi:10.1162/jocn.2009.21389

66.

Mendez

M. F.

Shapira

J. S.

(2009). Altered emotional morality in frontotemporal dementia. Cognitive Neuropsychiatry, 14, 165-179. doi:10.1080/13546800902924122

67.

Menon

(2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15, 483-506. doi:10.1016/j.tics.2011.08.003

68.

Menon

Uddin

(2010). Saliency, switching, attention and control: A network model of insula function. Brain Structure & Function, 214, 655-667. doi:10.1007/s00429-010-0262-0

69.

Miller

E. K.

(2000). The prefrontal cortex and cognitive control. Nature Reviews Neuroscience, 1, 59-65. doi:10.1038/35036228

70.

Miller

E. K.

Cohen

J. D.

(2001). An integrative theory of prefrontal cortex function. Annual Review of Neuroscience, 24, 167-202. doi:10.1146/annurev.neuro.24.1.167

71.

Molenberghs

Ogilvie

Louis

W. R.

Decety

Bagnall

Bain

P.G.

(2015). The neural correlates of justified and unjustified killing: An fMRI study. SCAN, 10, 1397-1404. doi:10.1093/scan/nsv027

72.

Murray

A. J.

Topalli

(2014). Delinquency and drift theory. In Miller

J. M.

(Ed.), The encyclopedia of theoretical criminology (1st ed.). Wiley Online Library. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/9781118517390.wbetc228/full

73.

Niendam

T. A.

Laird

A. R.

Ray

K. L.

Dean

Y. M.

Glahn

D. C.

Carter

C. S.

(2012). Meta-analytic evidence for a superordinate cognitive control network subserving diverse executive functions. Cognitive, Affective, & Behavioral Neuroscience, 12, 241-268. doi:10.3758/s13415-011-0083-5

74.

Ogawa

(2012). Finding the BOLD effect in brain images. NeuroImage, 62, 608-609. doi:10.1016/j.neuroimage.2012.01.091

75.

Owen

A. M.

Downes

J. J.

Sahakian

B. J.

Polkey

C. E.

Robbins

T. W.

(1990). Planning and spatial working memory following frontal lobe lesions in man. Neuropsychologia, 28, 1021-1034. doi:10.1016/0028-3932(90)90137-D

76.

Palaniyappan

Liddle

P. F.

(2012). Does the salience network play a cardinal role in psychosis? An emerging hypothesis of insular dysfunction. Journal of Psychiatry & Neuroscience, 37, 17-27. doi:10.1503/jpn.100176

77.

Philippi

C. L.

Koenigs

(2014). The neuropsychology of self-reflection in psychiatric illness. Journal of Psychiatric Research, 54, 55-63. doi:10.1016/j.jpsychires.2014.03.004

78.

Raichle

M. E.

MacLeod

A. M.

Snyder

A. Z.

Powers

W. J.

Gusnard

D. A.

Shulman

G. L.

(2001). A default mode of brain function. Proceedings of the National Academy of Sciences of the United States of America, 98, 676-682. doi:10.1073/pnas.98.2.676

79.

Raine

(1993). Violence and the brain. Psychological Review, 100, 674-701.

80.

Raine

Lencz

Bihrle

LaCasse

Colletti

(2000). Reduced prefrontal gray matter volume and reduced autonomic activity in antisocial personality disorder. Archives of General Psychiatry, 57, 119-127. doi:10.1001/archpsyc.57.2.11

81.

Reyna

V. F.

Farley

(2006). Risk and rationality in adolescent decision making: Implications for theory, practice, and public policy. Psychological Science in the Public Interest, 7, 1-44. Retrieved from https://journals-sagepub-com.web.bisu.edu.cn/doi/abs/10.1111/j.1529-1006.2006.00026.x

82.

Rilling

J. K.

Dagenais

J. E.

Goldsmith

D. R.

Glenn

A. L.

Pagnoni

(2008). Social cognitive neural networks during in-group and out-group interactions. NeuroImage, 41, 1447-1461. doi:10.1016/j.neuroimage.2008.03.044

83.

Rodrigo

M. J.

Padrón

De Vega

Ferstl

E. C.

(2014). Adolescents’ risky decision-making activates neural networks related to social cognition and cognitive control processes. Frontiers in Human Neuroscience, 8(60), 1-16. doi:10.3389/fnhum.2014.00060

84.

Sampson

R. L.

Laub

J. H.

(2005). A life-course view of the development of crime. The ANNALS of the American Academy of Political and Social Science, 602, 12-45. Retrieved from https://journals-sagepub-com.web.bisu.edu.cn/doi/abs/10.1177/0002716205280075

85.

Sariaslan

Sharp

D. J.

D’Onofrio

B. M.

Larsson

Fazel

(2016). Long-term outcomes associated with traumatic brain injury in childhood and adolescence: A nationwide Swedish cohort study of a wide range of medical and social outcomes. PLoS Medicine, 13(8), e1002103. doi:10.1371/journal.pmed.1002103

86.

Satterthwaite

T. D.

Wolf

D. H.

Erus

Ruparel

Elliott

M. A.

Gennatas

E. D.

. . . Gur

R. C.

(2013). Functional maturation of the executive system during adolescence. The Journal of Neuroscience, 33, 16249-16261. doi:10.1523/JNEUROSCI.2345-13.2013

87.

Schreiner

M. J.

Karlsgodt

K. H.

Uddin

L. Q.

Chow

Congdon

Jalbrzikowski

Bearden

C. E.

(2014). Default mode network connectivity and reciprocal social behavior in 22q11.2 deletion syndrome. Scan, 9, 1261-1267. doi:10.1093/scan/nst114

88.

Schwartz

J. A.

Connolly

E. J.

Brauer

J. R.

(2017). Head injuries and changes in delinquency from adolescence to emerging adulthood: The importance of self-control as a mediating influence. Journal of Research in Crime & Delinquency, 1-33, First Published June 7, 2017 Retrieved from https://journals-sagepub-com.web.bisu.edu.cn/doi/10.1177/0022427817710287. doi:10.1177/0022427817710287

89.

Sebastian

Burnett

Blakemore

S. J.

(2008). Development of the self-concept during adolescence. Trends in Cognitive Sciences, 12, 441-446. doi:10.1016/j.tics.2008.07.008

90.

Seeley

W. W.

Menon

Schatzberg

A. F.

Keller

Glover

G. H.

Kenna

. . . Greicius

M. D.

(2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27, 2349-2356. Retrieved from http://www.jneurosci.org/content/27/9/2349.full.pdf+html

91.

Sheng

Gheytanchi

Aziz-Zadeh

(2010). Default network deactivations are correlated with psychopathic personality traits. PLoS ONE, 5(9), e12611. doi:10.1371/journal.pone.0012611

92.

Shulman

G. L.

Fiez

J. A.

Corbetta

Buckner

R. L.

Miezin

F. M.

Raichle

M. E.

Peterson

S. E.

(1997). Common blood flow changes across visual tasks: II. Decreases in cerebral cortex. Journal of Cognitive Neuroscience, 9, 648-663. doi:10.1162/jocn.1997.9.5.648

93.

Silbert

L. J.

Honey

C. J.

Simony

Poeppel

Hasson

(2014). Coupled neural systems underlie the production and comprehension of naturalistic narrative speech. Proceedings of the National Academy of Sciences of the United States of America, 111, E4687-E4696. Retrieved from www.pnas.org/cgi/doi/10.1073/pnas.1323812111

94.

Sporns

(2013). Structure and function of complex brain networks. Dialogues in Clinical Neuroscience, 15, 247-262.

95.

Sridharan

Levitin

D. J.

Menon

(2008). A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proceedings of the National Academy of Sciences of the United States of America, 105, 12569-12574. doi:10.1073/pnas.0800005105

96.

Sripada

R. K.

King

A. P.

Welsh

R. C.

Garfinkel

S. N.

Wang

Sripada

C. S.

Liberzon

(2012). Neural dysregulation in posttraumatic stress disorder: Evidence for disrupted equilibrium between salience and default mode brain networks. Psychosomatic Medicine, 74, 904-911. doi:10.1097/PSY.0b013e318273bf33

97.

Steudte-Schmiedgen

Stalder

Kirschbaum

Weber

Hoyer

Plessow

(2014). Trauma exposure is associated with increased context-dependent adjustments of cognitive control in patients with posttraumatic stress disorder and healthy controls. Cognitive, Affective, & Behavioral Neuroscience, 14, 1310-1319. doi:10.3758/s13415-014-0299-2

98.

Sykes

G. M.

Matza

(1957). Techniques of neutralization: A theory of delinquency. American Sociological Review, 22, 664-670. Retrieved from https://www-jstor-org.web.bisu.edu.cn/stable/2089195

99.

Thijssen

Ringoot

A. P.

Wildeboer

Bakermans-Kranenburg

M. J.

El Marroun

Hofman

. . . White

(2015). Brain morphology of childhood aggressive behavior: A multi-informant study in school-age children. Cognitive, Affective, & Behavioral Neuroscience, 15, 564-577. doi:10.3758/s13415-015-0344-9

100.

Uddin

L. Q.

Kelly

A. M. C.

Biswal

B. B.

Castellanos

F. X.

Milham

M. P.

(2009). Functional connectivity of default mode network components: Correlation, anticorrelation, and causality. Human Brain Mapping, 30, 625-637. doi:10.1002/hbm.20531

101.

Ugurbil

(2012). Development of functional imaging in the human brain (fMRI): The University of Minnesota experience. NeuroImage, 62, 613-619. doi:10.1016/j.neuroimage.2012.01.135

102.

van den Heuvel

M. P.

Kersbergen

K. J.

de Reus

M. A.

Keunen

Kahn

R. S.

Groenendaal

Benders

M. J. N. L

. (2015). The neonatal connectome during preterm brain development. Cerebral Cortex, 25, 3000-3013. doi:10.1093/cercor/bhu095

103.

Vollm

B. A.

Taylor

A. N.

Richardson

Corcoran

Stirling

McKie

. . . Elliott

(2006). Neuronal correlates of theory of mind and empathy: A functional magnetic resonance imaging study in a nonverbal task. NeuroImage, 29, 90-98. doi:10.1016/j.neuroimage.2005.07.022

104.

Weiler

B. L.

Wisdom

C. S.

(1996). Psychopathy and violent behavior in abused and neglected young adults. Criminal Behavior and Mental Health, 6, 253-271.

105.

Weinberger

D. R.

Radulescu

(2016). Finding the elusive psychiatric “lesion” with 21st-century neuroanatomy: A note of caution. American Journal of Psychiatry, 173, 27-33. doi:10.1176/appi.ajp.2015.15060753

106.

Williams

F. P.

McShane

M. D.

(2004). Criminological theory (4th ed.). Saddle River, NJ: Prentice Hall.

107.

Yang

Raine

Colletti

Toga

A. W.

Narr

K. L.

(2010). Morphological alterations in the prefrontal cortex and the amygdala in unsuccessful psychopaths. Journal of Abnormal Pscyhology, 119, 546-554. doi: 10.1037/a0019611.

108.

Yerys

B. E.

Gordon

E. M. A.

Gordon

E. M.

Abrams

D. N.

Satterthwaite

T. D.

Weinblatt

. . . Vaidya

(2015). Defaultmode network segregation and social deficits in autism spectrum disorder: Evidence from non-medicated children DMN in children with ASD. NeuroImage, 9, 223-232. doi:10.1016/j.nicl.2015.07.018

109.

Yoder

K. J.

Harenski

Kiehl

K. A.

Decety

(2015). Neural networks underlying implicit and explicit moral evaluations in psychopathy. Translational Psychiatry, 5, e6251-e1628. doi:10.1038/tp.2015.117

110.

Zhang

Zhou

Lin

Jiang

(2010). Reduced cortical folding in mental retardation. American Journal of Neuroradiology, 31, 1063-1067. doi:10.3174/ajnr.A1984