Progress in brain research
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The developing normal brain shows a remarkable capacity for plastic change in response to a wide range of experiences including sensory and motor experience, psychoactive drugs, parent-child relationships, peer relationships, stress, gonadal hormones, intestinal flora, diet, and injury. The effects of injury vary with the precise age-at-injury, with the general result being that injury during cell migration and neuronal maturation has a poor functional outcome, whereas similar injury during synaptogenesis has a far better outcome. A variety of factors influence functional outcome including the nature of the behavior in question and the age at behavioral assessment as well as pre- and postinjury experiences. Here, we review the phases of brain development, how factors influence brain, and behavioral development in both the normal and perturbed brain, and propose mechanisms that may underlie these effects.
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The purpose of this review is to summarize how our perspective about the neuroscience of brain plasticity, informed by perceptual, experimental, and cognitive psychology, has led to the designs of a new class of therapeutic tools developed to drive functionally distorted and damaged brains in corrective directions. How does neuroplasticity science inform us about optimal therapeutic program designs? How do we apply that science, using modern technology, to drive neurological changes that address both the neurobehavioral distortions and the resulting behavioral deficits that are expressed in specific neurological and psychiatric disorders? By what strategies can we achieve the strongest and most complete rehabilitative corrections? These are questions that we have extensively explored in our efforts to establish new medical applications of neuroplasticity-based therapeutics. Here, we summarize the state of this rapidly emerging area of translational neuroscience, beginning with an explanation of the scientific premises and strategies, then describing their implementation in therapeutic software to address two human illnesses: the treatment of social cognition deficits in chronic schizophrenia and in autism; and the amelioration of age-related functional decline using strategies designed to delay the onset of--and potentially prevent--Alzheimer's Disease and related causes of dementia in aging.
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We constantly need to make decisions that can result in rewards of different amounts with different probabilities and at different timing. To characterize the neural coding of such computational factors affecting value-based decision making, we have investigated how reward information processing is influenced by parameters such as reward magnitude, probability, delay, effort, and uncertainty using either fMRI in healthy humans or intracranial recordings in patients with epilepsy. ⋯ Moreover, separate valuation systems were engaged for delay and effort costs when deciding between options. Finally, genetic variations in dopamine-related genes influenced the response of the reward system and may contribute to individual differences in reward-seeking behavior and in predisposition to neuropsychiatric disorders.
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Emotion plays a major role in influencing our everyday cognitive and behavioral functions, including decision making. We introduce different ways in which emotions are characterized in terms of the way they influence or elicited by decision making. ⋯ We present and discuss results from a study with emotional pictures presented prior to decision making and how that influences both decision processes and postdecision experience as a function of uncertainty. We conclude with a summary of the work on emotions and decision making in the context of decision-making theories and our work on incidental emotions.
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Cognitive control and decision making are two important research areas in the realm of higher-order cognition. Control processes such as interference control and monitoring in cognitive and affective contexts have been found to influence the process of decision making. Development of control processes follows a gradual growth pattern associated with the prolonged maturation of underlying neural circuits including the lateral prefrontal cortex, anterior cingulate, and the medial prefrontal cortex. ⋯ Neuroimaging studies have shown the involvement of separable neural networks for cognitive (medial prefrontal cortex and anterior cingulate) and affective control (amygdala, ventral medial prefrontal cortex) shows that one system can affect the other also at the neural level. Hence, an understanding of the interaction and balance between the cognitive and affective brain networks may be crucial for self-regulation and decision making during the developmental period, particularly late childhood and adolescence. The chapter highlights the need for empirical investigation on the interaction between the different aspects of cognitive control and decision making from a developmental perspective.