Introduction to Abnormal Child and Adolescent Psychology. Robert Weis

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СКАЧАТЬ give off slightly different signals. In the brain, neurons (i.e., gray matter), myelin (i.e., white matter), and cerebrospinal fluid give different signals. A computer can use these different signals to generate a digital image of the brain. MRI machines generate two-dimensional images of brain tissue that can be integrated by the computer (i.e., “stacked” on top of one another) to create a three-dimensional picture (Picon, Volpe, Sterzer, & Heinz, 2016).

      MRI has a number of advantages over CT and most other imaging techniques. First, MRI does not subject individuals to radiation; it is believed to be safe and has even been used to obtain images of the brains of developing fetuses. Second, because it is safe, MRI can be used with healthy children and administered repeatedly over time. Consequently, MRI technology allows us to study the same children’s brains across development. Third, MRI yields clearer and more precise pictures of the brain than older neuroimaging methods (Giedd & Denker, 2015).

      MRI can allow us to detect structural abnormalities in the brains of youths with mental disorders. In a typical MRI study, researchers scan the brains of youths with and without a specific disorder. For example, Castellanos and colleagues (2002) scanned the brains of children with and without ADHD. The researchers compared the volumes of the frontal cortex of children in the two groups. They found that children with ADHD showed an average 4% reduction in volume of the frontal cortex compared to children without ADHD. These results are important because underactivity in portions of the frontal cortex is believed to account for some ADHD symptoms.

      Functional magnetic resonance imaging (fMRI) is used to measure brain activity. The fMRI machine measures changes in oxygenated hemoglobin concentrations in the brain. When the individual engages in mental activity, oxygenated hemoglobin concentrations increase in brain regions that become active. Consequently, fMRI yields a picture of the individual’s brain showing regions most active during certain mental activities (Sadock & Sadock, 2015).

      To perform fMRI, researchers typically obtain an image of the individual’s brain, using traditional MRI. Then, researchers ask the individual to perform a series of mental activities while they collect fMRI data. For example, researchers might ask adolescents with autism to describe the emotional expression on pictures of people’s faces or ask children with learning disabilities to read or solve math problems. These fMRI images are then superimposed over the traditional MRI to show brain regions that are most active during the mental tasks.

      Tamm, Menon, and Reiss (2006) used fMRI to determine which brain regions might be responsible for the deficits in attention shown by youths with ADHD. They asked adolescents with and without ADHD to perform a test of attention while they collected fMRI data. Specifically, youths were presented with a series of either circles or triangles. They were asked to press one button when they saw a circle and a different button when they saw a triangle. As expected, youths with ADHD made significantly more errors than youths without ADHD. Furthermore, youths with ADHD showed significantly less activity in certain brain areas compared to their healthy peers. The researchers concluded that these brain regions may play a role in people’s ability to direct and regulate attention.

      Sometimes, children show abnormalities in the connections between brain regions. Scientists can study the fibers that connect these regions using a technique called diffusion tensor imaging (DTI). DTI is similar to fMRI but it measures the diffusion of water molecules in brain tissue. DTI provides a high-resolution image of the density and volume of white matter, myelinated axons that connect brain regions (Image 3.3). By measuring the structural integrity of this tissue, scientists can estimate the connectivity between brain regions (Baribeau & Anagnostou, 2015; Emsell, Van Hecke, & Tournier, 2016).

      For example, Wu and colleagues (2019) used DTI to compare the brains of school-age children with and without ADHD. The researchers were especially interested in white matter tracts that connect the frontal lobes of the brain to other regions responsible for attention and behavioral control. They found that children with ADHD showed lower cell density and volume in the white matter that connects these brain regions, especially in the right hemisphere. Their finding is important because reduced connectivity could underlie many ADHD symptoms.

      Thomas Schultz

      Neuroimaging studies involving children and adolescents often yield inconsistent results. One reason for these inconsistent findings is that studies differ in their recruitment of participants, methods of data collection, and resolution of neuroimaging. Subtle differences in the studies’ methods can yield divergent results. For example, Bouziane and colleagues (2019) also used DTI to compare the brains of children with and without ADHD. Surprisingly, they found no differences in connectivity between youths with and without the disorder. Unlike other studies, none of the children with ADHD in their study had used medication in the past. The researchers suggested that medication, rather than ADHD, might partially explain the reduced connectivity seen in children with ADHD in other research.

      Another reason for inconsistent results is that children show enormous variability in their brain volumes and rates of brain development. For example, total brain volume can differ by as much as 20% based on factors such as children’s age and gender. Researchers wishing to identify structural abnormalities in the brains of children with specific disorders need to carefully control for these factors (Sadock & Sadock, 2015).

      Perhaps the most important reason for the inconsistent findings is that disorders in children and adolescents rarely have single causes that can be traced to specific brain regions. For example, ADHD appears to be caused by a complex relationship between biological, psychological, and social–cultural factors. It would be a mistake to think that a specific brain abnormality would account for all (or even most) cases of ADHD or any other disorder. Instead, it is likely that early differences in brain structure interact with environmental experiences to produce symptoms (Nusslock, 2018).

       Review

       A case study provides a detailed description of a person, small group, or phenomenon. Case studies focus on idiographic assessment, that is, unique abilities, behaviors, or experiences. Case studies are especially useful to describe new disorders or treatments.

       A survey is used to describe larger groups of individuals. Surveys focus on nomothetic assessment, that is, how people generally think, feel, or act. Surveys that rely on random selection reflect the larger population.

       Commonly used neuroimaging techniques include MRI, fMRI, and DTI. These techniques provide images of the brain’s structure, functioning, and connectivity, respectively.

      How Do Psychologists Predict Behavior?

      Correlational Research

      Surveys can also be used to predict children’s behavior or developmental outcomes. Some researchers are interested in identifying possible risk factors for ADHD. For example, the genes that children inherit from their parents, complications during pregnancy or delivery, and exposure to illnesses or toxins in early childhood can increase the likelihood that children will develop the disorder. Other researchers focus on protective factors that might lower a child’s likelihood of developing symptoms. For example, mothers who receive prenatal medical care, who avoid alcohol and other drugs during pregnancy, and who manage stress after delivery may lower their child’s risk for ADHD. Still other researchers explore children’s prognosis or developmental outcomes. For example, some children with ADHD may develop academic problems, depression, or substance use disorders later in life. Correlational studies allow researchers to explore possible relationships between variables like these (Kazdin, 2017).

      Researchers СКАЧАТЬ