A lower bound for the dimension of the base locus of the generalized theta divisor

We produce a lower bound for the dimension of the base locus of the generalized theta divisor on the moduli space SU_C(r) of semistable vector bundles of rank r and trivial determinant on a smooth curve C of genus g > 1.Comment: 4 page

Auditory white noise exposure results in intrinsic cortical excitability changes

Cortical excitability is commonly measured by applying magnetic stimulation in combination with measuring behavioral response. This measure has, however, some shortcomings including spatial limitation to the primary motor cortex and not accounting for intrinsic excitability fluctuations. Here, we use a measure for intrinsic excitability based on phase synchronization previously validated for epilepsy. We apply this measure in 30 healthy participants' magnetoencephalography (MEG) recordings during the exposure of auditory white noise, a stimulus that has been suggested to modify cortical excitability. Using cortical parcellation of the MEG source data, we could find a specific pattern of increased and decreased excitability while participants are exposed to white noise vs. silence. Specifically, excitability during white noise exposure decreases in the frontal lobe and increases in the temporal lobe. This study thus adds to the understanding of cortical excitability changes due to specific environmental stimuli as well as the spatial extent of these effects

Reliable measurement of auditory-driven gamma synchrony with a single EEG electrode: A simultaneous EEG-MEG study

Objective: Auditory-driven gamma synchrony (GS) is linked to the function of a specific cortical circuit based on a parvalbumin+ and pyramidal neuron loop. This loop is impaired in neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.) and its relevance in clinical practice is increasingly being recognized. Auditory stimulation at a typical gamma frequency of 40Hz can be applied as a 'stress test' for efficient excitation/inhibition (E/I) of the entire cerebral cortex to provoke GS and record it with magnetoencephalography (MEG) or high-density electroencephalography (EEG). However, these two techniques are costly and not widely available. Therefore, we assessed whether a single EEG electrode is sufficient to provide an accurate estimate of the auditory-driven GS level of the entire cortical surface while expecting the highest correspondence in the auditory and somatosensory cortices.Methods: We measured simultaneous EEG-MEG in 29 healthy subjects, utilizing 3 EEG electrodes (C4, F4, O2) and a full MEG setup. Recordings were performed during binaural exposure to auditory gamma stimulation and during silence. We compared GS measurement of each of the three EEG electrodes separately against full MEG mapping. Time-resolved phase locking value (PLVt) was computed between EEG signals and cortex reconstructed MEG signals.Results: During auditory stimulation, but not at rest, EEG captures a significant amount of GS, especially from both auditory cortices and motor-premotor regions. This was especially true for frontal (C4) and central electrodes (F4).Discussion and conclusions: While hd-EEG and MEG are necessary for accurate spatial mapping of GS at rest and during auditory stimulation, a single EEG channel is sufficient to detect the global level of GS. These results have great translational potential for mapping GS in standard clinical settings

MMP-2, MMP-9 and activin A blood levels in patients with breast cancer or prostate cancer metastatic to the bone.

Background: The clinical significance of the circulating levels of activin A and matrix metalloproteinase-2 (MMP-2) and -9 (MMP-9) was investigated in patients with breast cancer (BC) or prostate cancer (PC) with (M1) or without (M0) bone metastasis. Patients and Methods: MMP-2, MMP-9 and activin A blood concentrations were measured by enzyme immunoassays in 79 cancer patients and in 57 healthy blood donors (HS) who served as a control group. The diagnostic accuracy of these molecules to discriminate between M0 and M1 patients was evaluated by the receiver operating characteristic curve (ROC) and compared to that of tumor markers CA15.3 or prostate-specific antigen (PSA). Results: Activin A and MMP-2 were significantly increased in BC and PC patients as compared to sex-matched HS while MMP-9 levels were more elevated only in the PC patients. Interestingly, in the PC patients, activin A levels were significantly higher than those measured in the BC patients. In this latter group, activin A and CA15.3 but not MMP-2 or MMP-9 were increased in the M1 patients as compared to M0 patients. Furthermore, a significant relationship was also highlighted between activin A concentration and the number of bone metastases and tumor grade, between MMP-9 and tumor grade, and between MMP-2 and CA15.3. ROC curve analysis showed a good diagnostic accuracy for activin A and CA15.3 but a poor accuracy for MMP-2 and MMP-9 in discriminating between M0 and M1 patients. However, CA15.3 retained the best diagnostic accuracy in this respect. In the PC group, only activin A and PSA levels were significantly increased in the M1 patients as compared to the M0 patients. A similar although not statistically significant trend was noted for MMP-9. Interestingly, a significant correlation was observed between PSA and activin A and MMP-9, and between Activin A and Gleason score and the number of skeletal metastases. ROC curve analysis showed a good diagnostic accuracy for activin A, MMP-9 and PSA and a poor diagnostic accuracy for MMP-2 in detecting M1 patients. However, PSA showed the highest diagnostic accuracy. Conclusion: Activin A, MMP-2 and MMP-9 may be regarded as possible therapeutic targets in the treatment of metastatic bone disease. However, their usefulness as additional markers of bone metastasis remains to be better define

The impact of ROI extraction method for MEG connectivity estimation: practical recommendations for the study of resting state data

Magnetoencephalography and electroencephalography (MEEG) seed-based connectivity analysis requires the extraction of measures from regions of interest (ROI). MEEG ROI-derived source activity can be treated in different ways. It is possible, for instance, to average each ROI's time series prior to calculating connectivity measures. Alternatively, one can compute connectivity maps for each element of the ROI prior to dimensionality reduction to obtain a single map. The impact of these different strategies on connectivity results is still unclear. Here, we address this question within a large MEG resting state cohort (N=113) and within simulated data. We consider 68 ROIs (Desikan-Kiliany atlas), two measures of connectivity (phase locking value-PLV, and its imaginary counterpart- ciPLV), three frequency bands (theta 4-8 Hz, alpha 9-12 Hz, beta 15-30 Hz). We compare four extraction methods: (i) mean, or (ii) PCA of the activity within the seed or ROI before computing connectivity, map of the (iii) average, or (iv) maximum connectivity after computing connectivity for each element of the seed. Hierarchical clustering in then applied to compare connectivity outputs across multiple strategies, followed by direct contrasts across extraction methods. Finally, the results are validated by using a set of realistic simulations. We show that ROI-based connectivity maps vary remarkably across strategies in terms of connectivity magnitude and spatial distribution. Dimensionality reduction procedures conducted after computing connectivity are more similar to each-other, while PCA before approach is the most dissimilar to other approaches. Although differences across methods are consistent across frequency bands, they are influenced by the connectivity metric and ROI size. Greater differences were observed for ciPLV than PLV, and in larger ROIs. Realistic simulations confirmed that after aggregation procedures are generally more accurate but have lower specificity (higher rate of false positive connections).Though computationally demanding, after dimensionality reduction strategies should be preferred when higher sensitivity is desired. Given the remarkable differences across aggregation procedures, caution is warranted in comparing results across studies applying different methods