Correspondence between retinotopic cortical mapping and conventional functional and morphological assessment of retinal disease.

PURPOSE: The present study describes retinotopic mapping of the primary visual cortex using functional MRI (fMRI) in patients with retinal disease. It addresses the relationship between fMRI data and data obtained by conventional assessment including microperimetry (MP) and structural imaging. METHODS: Initial testing involved eight patients with central retinal disease (Stargardt disease, STGD) and eight with peripheral retinal disease (retinitis pigmentosa, RP), who were examined using fMRI and MP (Nidek MP-1). All had a secure clinical diagnosis supported by electrophysiological data. fMRI used population-receptive field (pRF) mapping to provide retinotopic data that were then compared with the results of MP, optical coherence tomography and fundus autofluorescence imaging. RESULTS: Full analysis, following assessment of fMRI data reliability criteria, was performed in five patients with STGD and seven patients with RP; unstable fixation was responsible for unreliable pRF measurements in three patients excluded from final analysis. The macular regions in patients with STGD with central visual field defects and outer retinal atrophy (ORA) at the macula correlated well with pRF coverage maps showing reduced density of activated voxels at the occipital pole. Patients with RP exhibited peripheral ORA and concentric visual field defects both on MP and pRF mapping. Anterior V1 voxels, corresponding to peripheral regions, showed no significant activation. Correspondence between MP and pRF mapping was quantified by calculating the simple matching coefficient. CONCLUSION: Retinotopic maps acquired by fMRI provide a valuable adjunct in the assessment of retinal dysfunction. The addition of microperimetric data to pRF maps allowed better assessment of macular function than MP alone. Unlike MP, pRF mapping provides objective data independent of psychophysical perception from the patient.

Individual diversity of functional brain network economy.

On average, brain network economy represents a trade-off between communication efficiency, robustness, and connection cost, although an analogous understanding on an individual level is largely missing. Evaluating resting-state networks of 42 healthy participants with seven Tesla functional magnetic resonance imaging and graph theory revealed that not even half of all possible connections were common across subjects. The strongest similarities among individuals were observed for interhemispheric and/or short-range connections, which may relate to the essential feature of the human brain to develop specialized systems within each hemisphere. Despite this marked variability in individual network architecture, all subjects exhibited equal small-world properties. Furthermore, interdependency between four major network economy metrics was observed across healthy individuals. The characteristic path length was associated with the clustering coefficient (peak correlation r=0.93), the response to network attacks (r=-0.97), and the physical connection cost in three-dimensional space (r=-0.62). On the other hand, clustering was negatively related to attack response (r=-0.75) and connection cost (r=-0.59). Finally, increased connection cost was associated with better response to attacks (r=0.65). This indicates that functional brain networks with high global information transfer also exhibit strong network resilience. However, it seems that these advantages come at the cost of decreased local communication efficiency and increased physical connection cost. Except for wiring length, the results were replicated on a subsample at three Tesla (n=20). These findings highlight the finely tuned interrelationships between different parameters of brain network economy. Moreover, the understanding of the individual diversity of functional brain network economy may provide further insights in the vulnerability to mental and neurological disorders.

Bone homogeneity factor: an advanced tool for the assessment of osteoporotic bone structure in high-resolution magnetic resonance images.

RATIONALE AND OBJECTIVES: Osteoporosis is characterized by low bone mass and inferior structural competence. In this study we introduce the bone homogeneity factor (BHF) as a quantitative measurement of bone structure, which could be equally important as bone mineral density. METHODS: BHF represents an advanced texture analysis tool based on the spatial autocorrelation function calculated in 9 different directions. These calculations were performed on high-resolution magnetic resonance images of the calcaneus at 3.0 T and compared with dual-energy x-ray absorptiometry measurements of the femoral neck. RESULTS: The quality and resolution of the high-resolution magnetic resonance images is sufficient for reliably calculating BHF. The mean BHF of the control group (n = 5, mean BHF = 525,0) with normal bone is significantly (P = 0.009, Mann-Whitney U test) higher than in the osteoporotic group (n = 7, mean BHF = 137,8). The BHF correlates with the DXA measurements of the femoral neck (correlation coefficient = 0.75). CONCLUSIONS: By calculating the BHF, it was possible to distinguish between osteoporotic and nonosteoporotic bone structure. Hence, BHF could be a possible candidate for noninvasive assessment of osteoporotic bone structure giving additional information to routinely used bone mineral densitometry.

Consistency of inter-trial activation using single-trial fMRI: assessment of regional differences.

Recently, the technique of single-trial fMRI was introduced, which allows the assessment of hemodynamic responses to single task executions (e.g. sensory, motor, or cognitive). In this study, single-trial fMRI was used to examine regional differences in the inter-trial consistency (ITC) of brain activity related to the processing of a dynamic visuo-spatial imagery task. For every single trial, a t-statistic assessing task-related activation was calculated and thresholded at a p-value of P < or =l0.05 (uncorrected). The percentage of trials with t-values above the threshold was used to assess differences in the consistency of brain activity in occipital, parietal, premotor and prefrontal regions of interest. While most of these regions showed activation which was highly consistent across trials, the consistency of activation was significantly reduced in the dorsolateral prefrontal cortex. We hypothesize that the consistency of activation across trials may be interpreted as an indicator of the functional relevance of a brain region for processing and solving a cognitive task. Thus, the analysis concept presented here has the potential to provide new insights into the neuro-cognitive mechanisms of human information processing. In addition, the results of this study confirm that averaging across trials might result in a significant loss of information about functional neuroanatomy. Regions which are active in some trials only, which show only weak activity increases, or whose activity is not constant and time-locked, might not show up in averaged activation maps and could thus erroneously be interpreted as irrelevant for task processing.