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Conceptual pathways to HIV risk in Eastern and Southern Africa
Published in Kaymarlin Govender, Nana K. Poku, Preventing HIV Among Young People in Southern and Eastern Africa, 2020
Richard G. Cowden, Leigh A. Tucker, Kaymarlin Govender
Adolescence is one of the most sensitive periods for brain development (Steinberg, 2014). During this developmental phase, neuronal networks throughout the brain are optimised and fine-tuned (Arain et al., 2013). Structural changes to the prefrontal cortex, in particular, are linked to important advances in executive functions (Anderson, 2002), including planning, decision-making, and regulation of thought and action (Casey, Jones, & Hare, 2008). Over time, improvements in cognitive control lead to better decision-making processes and inhibition of impulsive behaviour (Blakemore & Choudhury, 2006). Developments in frontal-parietal lobe circuitry contribute to increasingly sophisticated social-cognitive processes that promote interpersonal functioning, including advances in adolescents’ proclivity to experience empathy and perspective-taking abilities (Blakemore & Mills, 2014; Dumontheil, Apperly, & Blakemore, 2010).
Substance misuse and young people: Reward mechanisms
Published in Ilana B. Crome, Richard Williams, Roger Bloor, Xenofon Sgouros, Substance Misuse and Young People, 2019
Cognitive control can be viewed as flexible goal-directed behaviour that requires an adaptive cognitive control system to organise and optimise processing pathways (Ridderinkhof et al., 2004). Emerging evidence from cognitive neuroscience is now beginning to converge on the different contributions of the PFC in the service of cognitive control. Furthermore, this convergence of evidence regarding the role of the PFC in cognitive control is well placed to explicate why certain processes may be compromised in adolescence, when a lack of cognitive control may be a central component for both initiating and continuing drug abuse (see Figure 10.1). Drug addiction is characterised by continued drug use and recurrent drug relapse, despite serious negative consequences, and may implicate decrements in cognitive inhibitory control functioning. Laboratory tests of cognitive inhibitory control usually involve a person withholding a habitual motor response or ignoring the presentation of irrelevant stimuli, during which a person must continually update information and monitor their performance. Importantly, the processes of cognitive inhibitory control and monitoring have consistently been shown to involve the lateral PFC and the ACC (Carter et al., 1998; Garavan et al., 1999; 2002; Ullsperger and von Cramon, 2001).
My, How Those Seedlings Have Grown: An Update on Mind/Body Interactions in the Exercise Domain
Published in James M. Rippe, Lifestyle Medicine, 2019
Steven J. Petruzzello, Allyson G. Box, Dakota G. Morales
The N2 waveform, another ERP component studied as an index of cognitive function, is a negative-going waveform that occurs approximately 200 ms following stimulus presentation. The N2 has been associated with detection of conflict, mismatch of stimuli, and cognitive control during response inhibition.5 The amplitude of the N2 is associated with cognitive control and the ability to filter or disengage from negative thoughts.6 In a study of individuals with major depressive disorder (MDD), for whom cognitive control is compromised, Olson et al.7 found that aerobic exercise resulted in increased N2 amplitude, reflecting enhanced cognitive control processes. That is, exercise reduced symptoms of depression and also “normalized” cognitive functioning.
Beyond weight: associations between 24-hour movement behaviors, cardiometabolic and cognitive health in adolescents with and without obesity
Published in Child and Adolescent Obesity, 2023
Erin K Howie, Connie Lamm, Marilou D. Shreve, Aaron R. Caldwell, Matthew S. Ganio
The AX-CPT task assesses two types of cognitive control: reactive control, the ability to change action strategies based on last minute information and proactive control, the ability to actively maintain information in the face of distraction (Braver et al. 2009). The task was administered according to previous procedures (Lamm et al. 2013). Outcome variables include reaction time on correct trials, accuracy (AY accuracy indicating more reactive control and BX accuracy indicating more proactive control), and BSI error. Based on the works of Braver and colleagues (Braver et al. 2009) (supporting information) a Behavioral Shift Index (BSI) was calculated (AY-BX)/(AY+BX) for correct probe reaction times and combined cue/probe error rates to show control style (i.e. more proactive or reactive control style). More positive values indicate a proactive style of responding, while less positive values indicate a more reactive style of responding.
An Evaluation of the Structure of Attention in Adolescence
Published in Developmental Neuropsychology, 2023
Paul T. Cirino, Abigail E. Farrell, Marcia A. Barnes, Greg J. Roberts
Second, executive function is confusable with attention, and these terms are often mixed (e.g., attentional control, executive, or controlled attention, cognitive control). There are numerous executive-focused factor analytic studies (e.g., Cirino et al., 2018; Miyake et al., 2000; see meta-analysis of Karr et al., 2018). However, such studies do not set out to evaluate the structure of attention along theoretical lines (there is typically no mention of the common theories noted above), and the tasks they employ have different and more complex demands (e.g., those requiring inhibition of a prepotent response; those requiring manipulation or simultaneous processing/storage; those requiring shifting between alternating demands). Working memory is the most widely studied “executive” process; in fact, it is discussed within the Chun et al. (2011) model as being situated at the juncture of internal and external attention. Because working memory necessarily deals with active processing, and because this processing can be internally or externally directed, one’s capacity for working memory can be used in the service of either internal or external attention. Therefore, the present study also includes working memory as a potentially discernable factor.
Differentiating brain function of punishment versus reward processing in conduct disorder with and without attention deficit hyperactivity disorder
Published in The World Journal of Biological Psychiatry, 2022
Sarah Baumann, Arne Hartz, Wolfgang Scharke, Stephane A. De Brito, Graeme Fairchild, Beate Herpertz-Dahlmann, Kerstin Konrad, Gregor Kohls
In an attempt to pinpoint particularly the distinct brain substrates of CD relative to ADHD, Rubia (2011) reviewed the relevant structural and functional magnetic resonance imaging (fMRI) studies and concluded that CD is associated with disorder-specific deficits in circuits known to regulate affective and motivational control processes (i.e. ‘hot’ executive functions), including regions such as orbitofrontal (OFC) and ventromedial prefrontal cortices (vmPFC), anterior cingulate cortex (ACC), striatum, and amygdala. The disorder-specific dysfunctions in ADHD, by contrast, appear in fronto-striato-parieto-cerebellar circuits that regulate motor, attentional, and cognitive control processes (i.e. ‘cool’ executive functions), most prominently the lateral inferior frontal cortex (for a more recent review, see also Puiu et al. 2018). Although both ‘hot’ and ‘cool’ control circuits are involved in the decision-making process (Ernst and Paulus 2005), the vast majority of fMRI studies reviewed by Rubia (2011) did not utilise experimental tasks that truly tap into reinforcement-based decision-making (Scholl and Klein-Flügge 2018). Thus, it still remains unclear to what extent the disorder-specific neural dysfunctions of CD versus ADHD, as highlighted by Rubia (2011), are linked to the differential decision-making deficits seen in both disorders.