Kai Boelmans

Attention to features precedes attention to locations in visual search: evidence from electromagnetic brain responses in humans

Single-unit recordings in macaque extrastriate cortex have shown that attentional selection of nonspatial features can operate in a location-independent manner. Here, we investigated analogous neural correlates at the neural population level in human observers by using simultaneous event-related potential (ERP) and event-related magnetic field (ERMF) recordings. The goals were to determine (1) whether task-relevant features are selected before attention is allocated to the location of the target, and (2) whether this selection reflects the locations of the relevant features. A visual search task was used in which the spatial distribution of nontarget items with attended feature values was varied independently of the location of the target. The presence of task-relevant features in a given location led to a change in ERP/ERMF activity beginning ∼140 msec after stimulus onset, with a neural origin in the ventral occipito-temporal cortex. This effect was independent of the location of the actual target. This effect was followed by lateralized activity reflecting the allocation of attention to the location of the target (the well known N2pc component), which began at ∼170 msec poststimulus. Current source localization indicated that the allocation of attention to the location of the target originated in more anterior regions of occipito-temporal cortex anterior than the feature-related effects. These findings suggest that target detection in visual search begins with the detection of task-relevant features, which then allows spatial attention to be allocated to the location of a likely target, which in turn allows the target to be positively identified.

The Neural Site of Attention Matches the Spatial Scale of Perception

What is the neural locus of visual attention? Here we show that the locus is not fixed but instead changes rapidly to match the spatial scale of task-relevant information in the current scene. To accomplish this, we obtained electrical, magnetic, and hemodynamic measures of attention from human subjects while they detected large-scale or small-scale targets within multiscale stimulus patterns. Subjects did not know the scale of the target before stimulus onset, and yet the neural locus of attention-related activity between 250 and 300 ms varied according to the scale of the target. Specifically, maximal attention-related activity spread from a high-level, relatively anterior visual area (the lateral occipital complex) for large-scale targets to include a lower-level, more posterior area (visual area V4) for small-scale targets. This rapid change indicates that the neural locus of attention in visual cortex is not static but is instead determined rapidly and dynamically by means of an interaction between top-down task information and local information about the current visual input.

How does attention attenuate target-distractor interference in vision?. Evidence from magnetoencephalographic recordings.

This study used magnetoencephalographic and electroencephalographic recordings to investigate the neural mechanisms that underlie the attentional resolution of ambiguous feature coding in visual search. We addressed this issue by comparing neural activity related to target discrimination under conditions of more versus less feature overlap between the target and distractor items. The results show that increasing feature overlap leads to a focal enhancement of neural activity in ventral occipito-temporal areas, consistent with the larger need to attenuate distractor interference. Furthermore, the results suggest that distractor attenuation proceeds as a stepwise operation, with different spatial locations containing interfering features being suppressed successively. These findings support theories of visual search that emphasize location-based attentional selection as a key mechanism in resolving ambiguous feature coding in vision.

MicroRNA Profiling of CSF Reveals Potential Biomarkers to Detect Alzheimer`s Disease.

The miRBase-21 database currently lists 1881 microRNA (miRNA) precursors and 2585 unique mature human miRNAs. Since their discovery, miRNAs have proved to present a new level of epigenetic post-transcriptional control of protein synthesis. Initial results point to a possible involvement of miRNA in Alzheimer’s disease (AD). We applied OpenArray technology to profile the expression of 1178 unique miRNAs in cerebrospinal fluid (CSF) samples of AD patients (n = 22) and controls (n = 28). Using a Cq of 34 as cut-off, we identified positive signals for 441 miRNAs, while 729 miRNAs could not be detected, indicating that at least 37% of miRNAs are present in the brain. We found 74 miRNAs being down- and 74 miRNAs being up-regulated in AD using a 1.5 fold change threshold. By applying the new explorative “Measure of relevance” method, 6 reliable and 9 informative biomarkers were identified. Confirmatory MANCOVA revealed reliable miR-100, miR-146a and miR-1274a as differentially expressed in AD reaching Bonferroni corrected significance. MANCOVA also confirmed differential expression of informative miR-103, miR-375, miR-505#, miR-708, miR-4467, miR-219, miR-296, miR-766 and miR-3622b-3p. Discrimination analysis using a combination of miR-100, miR-103 and miR-375 was able to detect AD in CSF by positively classifying controls and AD cases with 96.4% and 95.5% accuracy, respectively. Referring to the Ingenuity database we could identify a set of AD associated genes that are targeted by these miRNAs. Highly predicted targets included genes involved in the regulation of tau and amyloid pathways in AD like MAPT, BACE1 and mTOR.

Diffusion tensor imaging of the corpus callosum differentiates corticobasal syndrome from Parkinson's disease

Differential diagnosis between patients with Corticobasal syndrome (CBS) and Parkinsons disease (PD) may be confusing, particularly in early disease stages. However, in contrast to PD, CBS shows a widespread cortical atrophy that suggests an involvement of the corpus callosum (CC). To test this hypothesis, we used diffusion tensor imaging (DTI) with a 1.5T scanner to compare 14 CBS patients, 14 PD patients, and an age-matched control group. The mean diffusivity (MD) and fractional anisotropy (FA) were determined in the whole CC and in five subdivisions. Group comparisons were performed using the Mann-Whitney U-test. We found a significantly increased MD and decreased FA in CBS patients compared to PD, particularly in the posterior truncus. No differences were found between PD patients and controls. A receiver-operating characteristics (ROC) analysis shows that the MD is particularly useful for discriminating between the two neurodegenerative diseases. Our data suggest that abnormal CC diffusivity in CBS reflects an atrophy and degraded transcallosal connectivity, making the CC a potential target to differentiate CBS from PD patients.

Involvement of motor pathways in corticobasal syndrome detected by diffusion tensor tractography.

Corticobasal syndrome (CBS) is a progressive parkinsonian disease characterized by cortical and subcortical neuronal loss. Although motor disabilities are a core feature of CBS, the involvement of motor pathways in this condition has not been completely clarified. We used magnetic resonance diffusion tensor imaging (DTI) to study corticospinal and transcallosal motor projections in CBS, and applied fiber tractography to analyze the axonal integrity of white matter projections. Ten patients with CBS were compared with 10 age‐matched healthy controls. Fiber tracts were computed using a Monte‐Carlo simulation approach. Tract‐specific mean values of the apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were determined. CBS patients showed a reduction of corticospinal tract (CST) fibers on the first affected side with significantly increased ADC and reduced FA values. In the corpus callosum (CC), particularly in the posterior trunk, patients also had significantly reduced fiber projections, with a higher ADC and lower FA than controls. This pattern indicates changes of the white matter integrity in both CST and CC. Thus, magnetic resonance DTI can be used to assess motor pathway involvement in CBS patients.

Parkinson's disease–related increase of T2*‐weighted hypointensity in substantia nigra pars compacta

Background: In PD, at the time of diagnosis, approximately 50% of melanized dopaminergic neurons in SNpc have died, yet ongoing neuronal death and neuromelanin release with associated neuroinflammation and microglial activation continue, as does local iron accumulation. Previous studies investigating nigral iron accumulation used T2/ T2* ‐weighted contrasts to define the regions of interest in the SN. Given that T2/ T2* ‐weighted contrasts lack sensitivity to neuromelanin and thereby SNpc, neuromelanin‐sensitive MRI provides better delineation of SNpc and allows the examination of increased iron deposition in SNpc more specifically and accurately.

Hirayama disease is a pure spinal motor neuron disorder—a combined DTI and transcranial magnetic stimulation study

Hirayama disease (HirD) is a juvenile spinal muscular atrophy predominantly affecting young men with an initially progressive course followed by a stable plateau within several years. It is a matter of debate whether HirD is a widespread motor neuron or more focal cervical cord disease. Whether the supraspinal pathways of the corticospinal tract (CST) are also affected has not been studied systematically. We analyzed CST integrity in seven HirD patients and 11 controls of similar age and gender using diffusion tensor imaging at a 1.5-T scanner and central motor conduction time (CMCT) using transcranial magnetic stimulation. The apparent diffusion coefficient, fractional anisotropy, and axial and radial diffusivity coefficients were determined bilaterally at four representative CST levels and along the whole CST using a probabilistic fiber tracking approach. There were no differences between the initially affected and the contralateral side in HirD patients and no difference between HirD patients and controls for both the ROI-based and the whole CST analyses. Radial diffusivity of the CST was positively correlated with years of disease progression in HirD patients. CMCT was normal in HirD patients. Combined anatomical and functional measurements established normal integrity of the supraspinal CST in HirD patients lending support to the notion that HirD is a pure spinal motor neuron disorder.

Diagnosis of Parkinson’s Disease—Transcranial Sonography in Relation to MRI

Displaying the echo pattern (echogenicity) of brain tissue transcranial sonography (TCS) may provide new and complementary information to other neuroimaging methods. In contrast to conventional magnetic resonance imaging (MRI), TCS is able to detect highly characteristic changes in signal brightness of the substantia nigra (SN) in patients with idiopathic Parkinsons disease. In this review, TCS findings are related to conventional and advanced high-field brain MRI findings. On the basis of the MRI findings, especially with T2-relaxometry, the possible role of trace metals in the genesis of altered echogenicity on TCS of brain parenchyma, especially of the SN, are discussed.

Widespread diffusion changes differentiate Parkinson's disease and progressive supranuclear palsy

Background Parkinsons disease (PD) and progressive supranuclear palsy – Richardsons syndrome (PSP-RS) are often represented by similar clinical symptoms, which may challenge diagnostic accuracy. The objective of this study was to investigate and compare regional cerebral diffusion properties in PD and PSP-RS subjects and evaluate the use of these metrics for an automatic classification framework. Material and methods Diffusion-tensor MRI datasets from 52 PD and 21 PSP-RS subjects were employed for this study. Using an atlas-based approach, regional median values of mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were measured and employed for feature selection using RELIEFF and subsequent classification using a support vector machine. Results According to RELIEFF, the top 17 diffusion values consisting of deep gray matter structures, the brainstem, and frontal cortex were found to be especially informative for an automatic classification. A MANCOVA analysis performed on these diffusion values as dependent variables revealed that PSP-RS and PD subjects differ significantly (p < .001). Generally, PSP-RS subjects exhibit reduced FA, and increased MD, RD, and AD values in nearly all brain structures analyzed compared to PD subjects. The leave-one-out cross-validation of the support vector machine classifier revealed that the classifier can differentiate PD and PSP-RS subjects with an accuracy of 87.7%. More precisely, six PD subjects were wrongly classified as PSP-RS and three PSP-RS subjects were wrongly classified as PD. Conclusion The results of this study demonstrate that PSP-RS subjects exhibit widespread and more severe diffusion alterations compared to PD patients, which appears valuable for an automatic computer-aided diagnosis approach.