C. Gaser

Temporal and Spatial Dynamics of Brain Structure Changes during Extensive Learning

The current view regarding human long-term memory as an active process of encoding and retrieval includes a highly specific learning-induced functional plasticity in a network of multiple memory systems. Voxel-based morphometry was used to detect possible structural brain changes associated with learning. Magnetic resonance images were obtained at three different time points while medical students learned for their medical examination. During the learning period, the gray matter increased significantly in the posterior and lateral parietal cortex bilaterally. These structural changes did not change significantly toward the third scan during the semester break 3 months after the exam. The posterior hippocampus showed a different pattern over time: the initial increase in gray matter during the learning period was even more pronounced toward the third time point. These results indicate that the acquisition of a great amount of highly abstract information may be related to a particular pattern of structural gray matter changes in particular brain areas.

Training-Induced Brain Structure Changes in the Elderly

It has been suggested that learning is associated with a transient and highly selective increase in brain gray matter in healthy young volunteers. It is not clear whether and to what extent the aging brain is still able to exhibit such structural plasticity. We built on our original study, now focusing on healthy senior citizens. We observed that elderly persons were able to learn three-ball cascade juggling, but with less proficiency compared with 20-year-old adolescents. Similar to the young group, gray-matter changes in the older brain related to skill acquisition were observed in area hMT/V5 (middle temporal area of the visual cortex). In addition, elderly volunteers who learned to juggle showed transient increases in gray matter in the hippocampus on the left side and in the nucleus accumbens bilaterally.

Changes in Gray Matter Induced by Learning—Revisited

Background Recently, activation-dependant structural brain plasticity in humans has been demonstrated in adults after three months of training a visio-motor skill. Learning three-ball cascade juggling was associated with a transient and highly selective increase in brain gray matter in the occipito-temporal cortex comprising the motion sensitive area hMT/V5 bilaterally. However, the exact time-scale of usage-dependant structural changes occur is still unknown. A better understanding of the temporal parameters may help to elucidate to what extent this type of cortical plasticity contributes to fast adapting cortical processes that may be relevant to learning. Principal Findings Using a 3 Tesla scanner and monitoring whole brain structure we repeated and extended our original study in 20 healthy adult volunteers, focussing on the temporal aspects of the structural changes and investigated whether these changes are performance or exercise dependant. The data confirmed our earlier observation using a mean effects analysis and in addition showed that learning to juggle can alter gray matter in the occipito-temporal cortex as early as after 7 days of training. Neither performance nor exercise alone could explain these changes. Conclusion We suggest that the qualitative change (i.e. learning of a new task) is more critical for the brain to change its structure than continued training of an already-learned task.

Template-O-Matic: a toolbox for creating customized pediatric templates.

Processing pediatric neuroimaging data is a challenge due to pervasive morphological changes that occur in the human brain during normal development. This is of special relevance when reference data is used as part of the processing approach, as in spatial normalization and tissue segmentation. Current approaches construct reference data (templates) by averaging brain images from a control group of subjects, or by creating custom templates from the group under study. In this technical note, we describe a new, and generalized method of constructing such appropriate reference data by statistically analyzing a large sample (n=404) of healthy children, as acquired during the NIH MRI study of normal brain development. After eliminating non-contributing demographic variables, we modeled the effects of age (first, second, and third-order terms) and gender, for each voxel in gray matter and white matter. By appropriate weighting with the parameter estimates from these analyses, complete tissue maps can be generated automatically from this database to match a pediatric population selected for study. The algorithm is implemented in the form of a toolbox for the SPM5 image data processing suite, which we term Template-O-Matic. We compare the performance of this approach with the current method of template generation and discuss the implications of our approach.

Gray Matter Increase Induced by Practice Correlates with Task-Specific Activation: A Combined Functional and Morphometric Magnetic Resonance Imaging Study

The neurophysiological basis of practice-induced gray matter increase is unclear. To study the relationship of practice-induced gray matter changes and neural activation, we conducted a combined longitudinal functional and morphometric (voxel-based morphometry) magnetic resonance imaging (MRI) study on mirror reading. Compared with normal reading, mirror reading resulted in an activation of the dorsolateral occipital cortex, medial occipital cortex, superior parietal cortex, medial and dorsolateral prefrontal cortex, as well as anterior insula and cerebellum. Daily practice of 15 min for 2 weeks resulted in an increased performance of mirror reading. After correction for pure performance effects, we found a practice-related decrease of activation at the right superior parietal cortex and increase of activation at the right dorsal occipital cortex. The longitudinal voxel-based morphometry analysis yielded an increase of gray matter in the right dorsolateral occipital cortex that corresponded to the peak of mirror-reading-specific activation. This confirms that short-term gray matter signal increase corresponds to task-specific processing. We speculate that practice-related gray matter signal changes in MRI are primarily related to synaptic remodeling within specific processing areas.

Magnetic resonance-based morphometry: a window into structural plasticity of the brain.

Purpose of reviewIn contrast to traditional anatomical and pathological methods, magnetic resonance morphometry of the brain allows the in-vivo study of temporal changes in brain morphology and the correlation of brain morphology with brain function. Magnetic resonance morphometry has thereby recently emerged as one of the most promising fields in clinical neuroscience. This review covers the last 3 years, which have witnessed remarkable progress in this alluring new field. Recent findingsNext to the detection of structural differences in grey and white matter in a number of brain diseases, a very important recent finding of magnetic resonance-based morphometry is the discovery of the brains ability to alter its shape within weeks, reflecting structural adaptation to physical and mental activity. Consequently, magnetic resonance morphometry promises to be a powerful method to study disease states of the brain and to track the effects of novel therapies. SummaryDespite these fascinating prospects, the results of morphometric studies are still dependent on the properties of the individual magnetic resonance scanner, which renders pooling of data almost impossible. It is also not known what the structural plasticity is based on at the histological or cellular level. Once these obstacles are overcome, magnetic resonance-based morphometry will become a powerful method for multicenter and therapeutic trials of several brain diseases.

A curvature-based approach to estimate local gyrification on the cortical surface

Using magnetic resonance imaging and a new method to analyze local surface shape, we examined the effects of gender on gyrification in a large and well-matched sample of healthy subjects. Unlike traditional 2D methods that produce whole-brain measurements of cortical complexity or more sophisticated 3D parametric mesh-based techniques that allow only different sections (lobes) of the cortex to be investigated, we employed a novel approach with increased spatial resolution. Although our method is sensitive to similar cortical features like the classic whole-brain gyrification index (depths of sulci and heights of gyri), we are now able to provide detailed and regionally specific estimates of cortical convolution at thousands of points across the cortical surface without introducing any bias through the rater or the selected orientation of the slices. We revealed pronounced gender differences, showing increased gyrification in frontal and parietal regions in females compared to males that agree with recent regions-of-interest findings. In addition, we detected higher female gyrification in temporal and occipital cortices that was not previously identified in studies using more global measures. No cortical area was significantly more convoluted in males compared to females. Our results demonstrate the sensitivity of this automated approach for identifying very local changes in gyrification. This technique may serve to isolate regionally specific changes in fissuration/gyrification in neurodevelopmental or neuropsychiatric disorders.

Structural correlates of psychopathological symptom dimensions in schizophrenia: A voxel-based morphometric study

Structural neuroimaging has substantially advanced the neurobiological research of schizophrenia by describing a range of focal brain alterations as possible neuroanatomical underpinnings of the disease. Despite this progress, a considerable heterogeneity of structural findings persists that may reflect the phenomenological diversity of schizophrenia. It is unclear whether the range of possible clinical disease manifestations relates to a core structural brain deficit or to distinct structural correlates. Therefore, gray matter density (GMD) differences between 175 schizophrenic patients (SZ) and 177 matched healthy control subjects (HC) were examined in a three-step approach using cross-sectional and conjunctional voxel-based morphometry (VBM): (1) analysis of structural alterations irrespective of symptomatology; (2) subdivision of the patient sample according to a three-dimensional factor model of the PANSS and investigation of structural differences between these subsamples and healthy controls; (3) analysis of a common pattern of structural alterations present in all patient subsamples compared to healthy controls. Significant GMD reductions in patients compared to controls were identified within the prefrontal, limbic, paralimbic, temporal and thalamic regions. The disorganized symptom dimension was associated with bilateral alterations in temporal, insular and medial prefrontal cortices. Positive symptoms were associated with left-pronounced alterations in perisylvian regions and extended thalamic GMD losses. Negative symptoms were linked to the most extended alterations within orbitofrontal, medial prefrontal, lateral prefrontal and temporal cortices as well as limbic and subcortical structures. Thus, structural heterogeneity in schizophrenia may relate to specific patterns of GMD reductions that possibly share a common prefrontal-perisylvian pattern of structural brain alterations.

Structural brain alterations in subjects at high-risk of psychosis: a voxel-based morphometric study.

Forty Untreated high-risk (HR) individuals for psychosis and 75 healthy control subjects (HC) matched for age, gender, handedness and educational level were investigated by structural MRI. HR subjects were recruited at the Early Detection and Intervention Centre for Mental Crises (FETZ) of the Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Germany. Measurements of gray matter volumes were performed by voxel-based morphometry using SPM5. The sample of HR subjects showed GM volume reductions in frontal, lateral temporal and medial temporal regions compared to the healthy control group. These regions are compatible with structural findings in the clinically apparent disease of schizophrenia.

Infant Brain Probability Templates for MRI Segmentation and Normalization

Spatial normalization and segmentation of infant brain MRI data based on adult or pediatric reference data may not be appropriate due to the developmental differences between the infant input data and the reference data. In this study we have constructed infant templates and a priori brain tissue probability maps based on the MR brain image data from 76 infants ranging in age from 9 to 15 months. We employed two processing strategies to construct the infant template and a priori data: one processed with and one without using a priori data in the segmentation step. Using the templates we constructed, comparisons between the adult templates and the new infant templates are presented. Tissue distribution differences are apparent between the infant and adult template, particularly in the gray matter (GM) maps. The infant a priori information classifies brain tissue as GM with higher probability than adult data, at the cost of white matter (WM), which presents with lower probability when compared to adult data. The differences are more pronounced in the frontal regions and in the cingulate gyrus. Similar differences are also observed when the infant data is compared to a pediatric (age 5 to 18) template. The two-pass segmentation approach taken here for infant T1W brain images has provided high quality tissue probability maps for GM, WM, and CSF, in infant brain images. These templates may be used as prior probability distributions for segmentation and normalization; a key to improving the accuracy of these procedures in special populations.