Brain

This study analyzed the relationship between brain dominance, gender, and improvement in creative thinking skills. The creative skills studied were fluency, originality, abstractness of titles, elaboration, resistance to closure and the creativity index. In addition to investigating the possible relationships between brain dominance, gender, and improvement in creative thinking skills, the question of whether or not improvement occurred was also examined. Brain dominance was determined by a self-report instrument. This instrument was based upon brain dominance research. The subjects were 63 high school students in grades 9 through 12. These subjects were enrolled in three separate classes. The subjects' ages ranged from 14 to 19 years of age. Subjects were administered the Human Information Processing Survey, a self-report learning style instrument, and the Torrance Test of Creative Thinking, a test of creative thinking skills. The scores on the Human Information Processing Survey were used to determine the subjects' brain dominance. The Torrance Test of Creative Thinking was used in a pretest and posttest design as a measure of improvement of the creative thinking skills. The results of this study indicated a significant improvement for selective creative thinking skills following a four week series of special activities. Significant relationships with brain dominance and gender were found between specific creative thinking skills.

Experimental and computational investigations addressing how various neural functions are achieved in the brain converged in recent years to a unified idea that the neural activity underlying most of the cognitive functions is distributed over large scale networks comprising various cortical and subcortical areas. Modeling approaches represent these areas and their connections using diverse models of neurocomputational units engaged in graph-like or neural field-like structures. Regardless of the manner of network implementation, simulations of large scale networks have encountered significant difficulties mainly due to the time delay introduced by the long range connections. To decrease the computational effort, it is common to assume severe approximations to simplify the descriptions of the neural dynamics associated with the system's units. In this dissertation we propose an alternative framework allowing the prevention of such strong assumptions while efficiently representing th e dynamics of a complex neural network. First, we consider the dynamics of small scale networks of globally coupled non-identical excitatory and inhibitory neurons, which could realistically instantiate a neurocomputational unit. We identify the most significant dynamical features the neural population exhibits in different parametric configuration, including multi-cluster dynamics, multi-scale synchronization and oscillator death. Then, using mode decomposition techniques, we construct analytically low dimensional representations of the network dynamics and show that these reduced systems capture the dynamical features of the entire neural population. The cases of linear and synaptic coupling are discussed in detail. In chapter 5, we extend this approach for spatially extended neural networks.

Traumatic Brain Injury (TBI) is a disability resulting in functional impairments and heightened dependence on others. Family members of persons with TBI can assume added responsibilities during the adjustment to the disability and rehabilitation process, placing strain on the family system. Community re-integration is a primary goal of the rehabilitation process for persons with TBI as this is a step in developing autonomy and promoting independence and productive activity throughout different areas of the person's life (e.g., work, social networks, and home life). This study was designed to examine predictors of community re-integration outcomes of TBI survivors and empirically test the resiliency model of family stress, adjustment, and adaptation while incorporating family needs by surveying caregiving family members. Specific aims of the study include validating relationships of the resiliency model with individual and family outcomes in adaptation and supporting future recommendations for healthcare providers working with families with members with TBI.

Contemporary understanding of human visual spatial attention rests on the hypothesis of a top-down control sending from cortical regions carrying higher-level functions to sensory regions. Evidence has been gathered through functional Magnetic Resonance Imaging (fMRI) experiments. The Frontal Eye Field (FEF) and IntraParietal Sulcus (IPS) are candidates proposed to form the frontoparietal attention network for top-down control. In this work we examined the influence patterns between frontoparietal network and Visual Occipital Cortex (VOC) using a statistical measure, Granger Causality (GC), with fMRI data acquired from subjects participated in a covert attention task. We found a directional asymmetry in GC between FEF/IPS and VOC, and further identified retinotopically specific control patterns in top-down GC. This work may lead to deeper understanding of goal-directed attention, as well as the application of GC to analyzing higher-level cognitive functions in healthy functioning human brain.

3,4-methlenedioxymethamphetamine (MDMA), the main constituent of Ecstasy, is a ring-substituted amphetamine commonly abused in recreational users. High doses of MDMA determined by allometric scaling produce serotonin (5-HT) axon deneveration. Studies suggest that this interspecies scaling does not reflect human use. An 'effects' scale comparing similar behavioral and physiological effects between species has been postulated as more accurate for translational studies. Experiment 1 examined the effects of MDMA on serotonergic forebrain innervation using immunohistochemical labeling targeting the serotonin transporter protein (SERT). Experiments 2 and 3 examined low and high doses of MDMA on spatial memory, prefrontal functioning, and serotonergic neurotoxicity using 'effects' scaling. Long Evans rats were given MDMA regimens of: chronic low dose (daily injections of 1.5 mg/kg for 10 days); binge low dose (2 days of 4 x 1.5 mg/kg spaced 2 hours apart), binge high dose (2 x 7.5 mg/kg sp aced 2 hours apart). Acquisition, retention, and spatial reversal (SR) were measured in a water maze task. A 2.0 mg/kg MDMA drug challenge was then given prior to a serial spatial reversal (SSR) task to assess performance while under the effect of the drug. Attentional set shifting and behavioral flexibility were assessed in an intradimensional extradimensionl (IED) task using odor/texture discriminations. MDMA chronic and binge low doses did not impair water maze or IED performance and produced no reductions in SERT expression. MDMA binge high dose resulted in significant reductions of SERT density in the prefrontal cortex, striatum, cortical mantle, hippocampus, amygdala, and many thalamic nuclei. Despite prominent 5-HT denervation, water maze performance was unaffected. Selective impairment in behavioral flexibility on the IED test was found.

The human prefrontal cortex (PFC) is associated with complex cognitive behaviors such as planning for the future, memory for serial order, social information processing and language. Understanding how the PFC has changed through time is central to the study of human neural evolution. Here we investigate the expansion of the PFC by measuring relative surface area of the PFC in Pan troglodytes and Homo sapiens. Magnetic resonance images (MRI's) from 8 preserved chimpanzee brains (3 male and 5 female adults) were segmented and measured. The results of this study indicate that there are gross anatomical differences between the chimpanzee and human prefrontal cortex beyond absolute size. The lower surface area to volume ratio in PFC of the chimpanzee when compared to a human indicates less gyral white matter in this region and thus, less associative connectivity. This anatomical evidence of a difference corresponds with the lesser cognitive complexity observed in chimpanzees.

Mild traumatic brain injuries (MTBI) are the leading type of head injuries with appreciable risque of sequelae leading to functional and psychological deficits. Although mild traumatic brain injuries are frequently underdiagnosed by conventional imaging modalities, rapidly evolving techniques such as diffusion tensor imaging (DTI) reveal subtle changes in white matter integrity as a result of head trauma and play an important role in refining diagnosis, therapeutic interventions and management of MTBI. In this dissertation we use diffusion tensor imaging to detect the microstructural changes induced by axonal injuries and to monitor their evolution during the recovery process. DTI data were previously acquired from 11 subjects, football players of age 19-23 years (median age 20 years). Three players had suffered a mild traumatic brain injury during the season and underwent scanning within 24 hours after the injury with follow-ups after one and two weeks. A set of diffusion indices, such as fractional anisotropy, axial, radial and mean diffusivity were derived from the diffusion tensor. Changes in diffusion indices in concussed subjects were analyzed based on two different approaches: whole brain analysis, using tract-based spatial statistics (TBSS) and region of interest analysis (ROI). In both approaches we use a voxelwise analysis to examine group differences in diffusion indices between five controls and three concussed subjects for all DTI scans. Additional statistical analysis was performed between control groups consisting of five and three non-injured players. Both analyses demonstrated that the MTBI group reveals increase in fractional anisotropy and decreases in transversal and mean diffusivity in cortical and subcortical areas within 24 hours after the injury.