| Age-Related Changes in Human Auditory Cortex |
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Although the age-related decline in the ability to understand and remember spoken messages reflects in part alterations in central auditory processing, relatively little is known about the effects of normal aging on the human auditory cortex (HAC). Here, we propose to undertake a comprehensive set of five experiments to evaluate age-related changes in speech perception and verbal memory in groups of young and older subjects, and correlate them with structural and functional changes in HAC visualized with a unique combination of magnetic resonance imaging (MRI) techniques. Exp. 1 will obtain baseline behavioral measures of two fundamental auditory abilities that show reliable age-related decline: speech reception thresholds in noise and auditory verbal short-term memory. Exp. 2 will investigate age-related changes in HAC surface structure using high-resolution T1-weighted MRI combined with cortical surface mapping techniques to analyze HAC thickness, area, and curvature. Exp. 3 will analyze age-related changes in HAC neuropil density and fiber connectivity using diffusion tensor imaging (DTI). DTI parameters in pericortical surface layers will be correlated with changes in cortical thickness and curvature to further elucidate age-related changes. Measures of HAC structure will be correlated with baseline behavioral measures to identify age-related anatomical changes associated with behavioral impairment. HAC functional organization will be examined in the final two experiments using functional MRI (fMRI). Exp. 4 will examine the automatic and attention-dependent processing of simple tone stimuli while Exp. 5 will use a similar design to analyze the processing of consonant-vowelconsonant (CVC) syllables. Comparison of tone- and CVC-related activations in the same subjects used in Exps. 1-3 will clarify the regions of auditory association cortex that show category-specific activations and clarify the neural circuits engaged in speech processing. fMRI activations from both experiments will be correlated with baseline behavioral measures and mapped to the cortical surface for correlation with changes in HAC structure, tissue properties, and connectivity. This unique combination of behavioral, structural and functional approaches will provide new insights into the structural and functional organization of HAC and will elucidate the effects of aging on this important structure. Understanding the consequences of normal aging is essential for evaluating the numerous age-related neurological and psychiatric disorders that affect HAC. In addition, the research techniques developed in this program can be extended to elucidate the basic organization of other cortical regions and the age-related changes they undergo. |
| PC-based Rehabilitation Of Auditory Function |
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More than 300,000 Veterans with sensorineural hearing loss (SNHL) are fitted with VA-issued hearing aids (HAs) each year with the primary goal of improving the patient's understanding of speech. Older veterans without hearing loss also experience a gradual decline in speech discrimination due to inevitable age-related changes in auditory function that compromise speech understanding in everyday environments. Neuroplastic reorganization within the central auditory system due to SNHL and aging contribute to these effects and compromise the subject's ability to process phonetic cues that are essential for understanding speech in noise. As a consequence, even when a HA restores high frequency signals to the cochlea in a patient with SNHL, speech understanding will remain suboptimal in the absence of rehabilitative perceptual learning. We have developed perceptual learning paradigms that drive this rehabilitative reorganization and significantly improve speech discrimination in new HA users. We now propose to test improved training paradigms in new and experienced HA users and older subjects with normal hearing. Exp. 1 will evaluate baseline speech discrimination in these populations using speech reception thresholds (SRTs) in sentences, consonant-vowel-consonant non-sense syllable tests (CVC-NST), tests of tone-pattern discrimination, and tests of auditory short-term verbal memory (ASTVM). An analysis of the correlations of these measures will provide information about basic processes underlying impaired word and sentence identification. Exp. 2 will investigate the effects of CVC-identification training using performance-adapted masking noise. Based on our previous results, we anticipate that training will significantly improve CVC-NST scores. In addition, we will examine the extent to which training also improves SRTs, tone pattern processing, and ASTVM. Exp. 3 will train subjects in a tone-pattern identification task to evaluate the extent to which non-phonetic factors (e.g., familiarity with the computerized hearing tests, placebo effects of training, improvements in auditory attention, etc.) may contribute to training benefit. Exp. 4 will compare the benefits of training with single-consonant syllables with the benefits of two-consonant syllable training studied in Exp. 2. Finally, Exp. 5 will study the benefits of CVC training using consonant-specific noise level adjusted to compensate for intrinsic differences in the discriminability of different consonants with the results compared to the benefits of global adaptive training obtained in Exp. 2. The experiments will clarify fundamental mechanisms underlying deficits in speech discrimination and ASTVM, provide insight into the nature of training-related improvements, and elucidate the parameters needed to optimize hearing rehabilitation. |
| Quantitative Automated Lesion Detection of TBI |
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Traumatic brain injury (TBI) afflicts 6 million Americans at an annual cost that exceeds $75 billion. TBI can produce debilitating cognitive deficits in attention, memory, and executive function due to diffuse axonal injury (DAI) and widely disseminated neuronal loss. Because of their non-focal nature, TBI-related brain lesions are difficult to detect and quantify with traditional MRI. In the current research program we propose to develop quantitative automated lesion detection (QALD) procedures to (1) clarify the nature and distribution of tissue damage following mild, moderate and severe TBI (2) improve the capability of detecting, quantifying, and localizing TBI brain damage in individual patients and (3) correlate quantitative measures of brain damage in individual TBI patients with neuropsychological deficits in attention, memory, and executive function.
QALD detects abnormal tissue parameters in the diseased brain through statistical comparisons with a normative database. Preliminary results show that QALD is capable of detecting highly significant abnormalities in the brains of TBI patients with normal clinical MRI scans. QALD will be further enhanced and tested with a larger database and including brain images acquired with four different imaging sequences (T1, T2, DTI and fluid-attenuated inversion recovery or FLAIR) from 100 control subjects. Data analysis will incorporate advanced cortical surface mapping techniques to quantify gray matter tissue parameters and thickness in 34 distinct cortical regions in each hemisphere. In addition, cortical fiber projections will be quantified with DTI and FLAIR analysis of white matter lying below the cortical surface. Subcortical fiber tracts critical for complex cognitive operations will be analyzed with voxel-based morphometry and with improved region of interest algorithms to define fiber tract boundaries. Tissue properties in critical subcortical structures (e.g., the hippocampus) will be quantified after automatic parcellation of these brain regions. We will also test the control subjects on a battery of neuropsychological tests (NPTs) and correlate variations in the size, myelination, and tissue properties of normal cortical and subcortical structures with cognitive performance. Then, we will gather identical imaging data in 99 TBI patients divided into three groups (mild, moderate and severe TBI) in order to characterize the average pattern of damage caused by TBIs of different severity. Next, we will quantify lesions in individual TBI patients and describe the variability of lesion patterns in the different severity groups. In parallel, we will develop further multimodal analysis techniques to combine statistical information from different imaging sequences to improve lesion-detection sensitivity to co-localized abnormalities evident with different imaging protocols. In addition, we will test patients with NPTs and analyze the relationship between brain damage, cognitive performance and self-assessments of outcome in order to improve the prognostic value of neuroradiological studies of TBI.
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| PC-Based Cognitive Rehabilitation For TBI |
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Traumatic brain injury (TBI) is the signature illness of military conflicts in Iraq and Afghanistan, potentially affecting as many as 70,000 veterans in the combat theater. For many of these veterans, TBI will produce disabling cognitive impairments of attention, memory, and executive function contributing to long-term disability and social isolation. Their long-term prognosis is worsened by the fact that there are currently no accepted treatments for rehabilitating TBI-related cognitive deficits.
Here we propose two randomized clinical trials to determine if at-home PC-based adaptive training can improve cognitive function in chronic TBI patients. Both trials will use protocols designed to drive beneficial neuroplastic changes using paradigms similar to those that have shown promising results in smaller scale studies. The first experiment will investigate the effects of training of short-term verbal and spatial memory. 36 patients with chronic mild, moderate and severe TBI will be evaluated with an extensive battery of neuropsychological tests (NPTs) and subjective rating scale measures at study entry. NPT and rating scale data will be compared to those obtained from 100 matched control subjects to characterize the cognitive deficits following mild, moderate and severe TBI. Patients will then be randomly assigned to immediate training (IT) or delayed training (DT) groups in a longitudinal crossover design. IT patients will begin training for 20 min/day on each of three different memory tasks for a period of three months. Training data will be automatically uploaded to monitor daily compliance and learning rate. NPT and rating scale assessments will be obtained midway through the study. Comparisons of changes in trained (IT) and untrained (DT) groups will be used to evaluate training efficacy. Then, during the second phase of the study, the DT group will undergo identical training. Repeat testing at the end of the study will quantify the effects of training on the DT group, and evaluate retention of training benefit in the IT group.
The second experiment will evaluate the effects of training on attention and executive function using a similar randomized trial with a separate group of 36 chronic TBI patents. A comparison of the magnitude of training-related improvements in the two experiments will be used to evaluate specific- and non-specific factors that contribute to training benefit and identify the patient characteristics that are most critical for successful cognitive rehabilitation.
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