From visual to motor strategies: Training in mental rotation of hands.

Functional imaging studies on mental rotation of hands have consistently pointed to the importance of the motor network implying the use of motor simulations for task solving. There is some evidence that the putamen may be a critical modulator of processing egocentric spatial orientation in mental rotation of hands and implicit motor imagery strategies have been described involving hand motor areas. This recruitment of resources processing representations of the own body is used in therapeutic mental rotation training. However, studies are lacking that investigate training-induced changes on the neuronal level. We used functional MRI to study the effects of long-term training on the neuro-functional correlates of mental rotation of hands in healthy volunteers and compared the training group to a passive control group. From pre- to post training, we found a transition of activation from the anterior putamen in unskilled performance to the posterior putamen in skilled performance. We also found an increase in activation in motor cortices and the supramarginal gyrus after learning. By contrast, members of the control group showed no improvements in performance and no pre/post-test differences in cortical activity. In conclusion, these findings suggest that increased neural efficiency after training in mental rotation of hands manifests as a decrease in visual imagery in conjunction with increased recruitment of motor-related regions. This is consistent with the obtained behavioral effects depicting motor imagery mediating expertise in mental rotation of hands.

MRI Biomarkers for Hand-Motor Outcome Prediction and Therapy Monitoring following Stroke.

Several biomarkers have been identified which enable a considerable prediction of hand-motor outcome after cerebral damage already in the subacute stage after stroke. We here review the value of MRI biomarkers in the evaluation of corticospinal integrity and functional recruitment of motor resources. Many of the functional imaging parameters are not feasible early after stroke or for patients with high impairment and low compliance. Whereas functional connectivity parameters have demonstrated varying results on their predictive value for hand-motor outcome, corticospinal integrity evaluation using structural imaging showed robust and high predictive power for patients with different levels of impairment. Although this is indicative of an overall higher value of structural imaging for prediction, we suggest that this variation be explained by structure and function relationships. To gain more insight into the recovering brain, not only one biomarker is needed. We rather argue for a combination of different measures in an algorithm to classify fine-graded subgroups of patients. Approaches to determining biomarkers have to take into account the established markers to provide further information on certain subgroups. Assessing the best therapy approaches for individual patients will become more feasible as these subgroups become specified in more detail. This procedure will help to considerably save resources and optimize neurorehabilitative therapy.

Association of basal forebrain volumes and cognition in normal aging.

The basal forebrain cholinergic system (BFCS) is known to undergo moderate neurodegenerative alterations during normal aging and severe atrophy in Alzheimer's disease (AD). It has been suggested that functional and structural alterations of the BFCS mediate cognitive performance in normal aging and AD. But, it is still unclear to what extend age-associated cognitive decline can be related to BFCS in normal aging. We analyzed the relationship between BFCS volume and cognition using MRI and a comprehensive neuropsychological test battery in a cohort of 43 healthy elderly subjects spanning the age range from 60 to 85 years. Most notably, we found significant associations between general intelligence and BFCS volumes, specifically within areas corresponding to posterior nuclei of the nucleus basalis of Meynert (Ch4p) and the nucleus subputaminalis (NSP). Associations between specific cognitive domains and BFCS volumes were less pronounced. Supplementary analyses demonstrated that especially the volume of NSP but also the volume of Ch4p was related to the volume of widespread temporal, frontal, and parietal gray and white matter regions. Volumes of these gray and white matter regions were also related to general intelligence. Higher volumes of Ch4p and NSP may enhance the effectiveness of acetylcholine supply in related gray and white matter regions underlying general intelligence and hence explain the observed association between the volume of Ch4p as well as NSP and general intelligence. Since general intelligence is known to attenuate the degree of age-associated cognitive decline and the risk of developing late-onset AD, the BFCS might, besides the specific contribution to the pathophysiology in AD, constitute a mechanism of brain resilience in normal aging.

A novel MRI-biomarker candidate for Alzheimer's disease composed of regional brain volume and perfusion variables.

BACKGROUND: Earlier evidence indicates that regional cerebral volume (rVOL) and blood flow (rCBF) variables carry independent information on incipient and early Alzheimer's disease (AD) and combining these modalities may increase discriminant performance. We compared single variables and combinations regarding their power for optimizing diagnostic accuracy. METHODS: Twelve cognitively normal elderly controls (CN), 30 subjects with mild cognitive impairment (MCI) and 15 with mild AD were examined by structural and perfusion-weighted magnetic resonance imaging (MRI) in single sessions at 1.5 Tesla. rVOLs were measured by manual volumetry, and rCBFs were calculated with a ROI-based co-localization technique. RESULTS: Applying single MRI variables for the differentiation of AD versus CN, the area under curve (AUC) of receiver operating characteristic curves (ROCCs) was highest for rVOL variables (maximum of 0.972 for right amygdala). A composite marker selected and weighted by logistic regression containing left amygdalar rCBF, left hippocampal and right amygdalar rVOLs gave a diagnostic accuracy for AD versus CN of 100%. Internal cross-validation revealed a reliability of 88.9%. CONCLUSIONS: Whilst external revalidation is mandatory employing a naturalistic sample containing disease controls, our phase I/II findings demonstrate that deducing composite markers from multimodal MRI acquisitions can optimize diagnostic accuracy for AD.