Topographical Organization of Mu and Beta Band Activity Associated with Hand and Foot Movements in Patients with Perirolandic Lesions

To study the topographical organization of mu and beta band event-related desynchronization (ERD) associated with voluntary hand and foot movements, we used magnetoencephalographic (MEG) recordings from 19 patients with perirolandic lesions. Synthetic aperture magnetometry (SAM) was used to detect and localize changes in the mu (7 - 11 Hz) and beta (13 - 30 Hz) frequency bands associated with repetitive movements of the hand and foot and overlaid on individual coregistered magnetic resonance (MR) images. Hand movements showed homotopic and contralateral ERD at the sensorimotor (S/M) cortex in the majority of cases for mu and to a lesser extent for beta rhythms. Foot movements showed an increased heterotopic distribution with bilateral and ipsilateral ERD compared to hand movements. No systematic topographical segregation between mu and beta ERD could be observed. In patients with perirolandic lesions, the mu and beta band spatial characteristics associated with hand movements retain the expected functional-anatomical boundaries to a large extent. Foot movements have altered patterns of mu and beta band ERD, which may give more insight into the differential functional role of oscillatory activity in different voluntary movements

Magnetoencephalographic study of posterior tibial nerve stimulation in patients with intracranial lesions around the central sulcus

OBJECTIVE: To study interhemispheric differences of somatosensory evoked field (SEF) characteristics and the spatial distribution of equivalent current dipole sources in patients with unilateral hemispheric lesions around the central sulcus region. METHODS: In 17 patients with perirolandic lesions, averaged somatosensory responses after posterior tibial nerve stimulation at the ankle were recorded with magnetoencephalography. Dipole source solutions in the affected (AH) and unaffected (UH) hemispheres were analyzed and compared for latency, equivalent current dipole strength, root mean square, and spatial distribution in relation to clinical findings. RESULTS: Three main SEF components, P45m, N60m, and P75m, were identified in the hemisphere contralateral to the stimulated nerve. Dipole strength for the P45m component was significantly higher in the AH compared with the UH. SEF characteristics in the AH and UH showed no significant differences with respect to component latency or dipole strength of the N60m and P75m components. Interdipole location asymmetries exceeded 1.0 cm in 71% of the patients. Comparison of the posterior tibial nerve evoked responses (P45m and N60m) in patients with motor deficits and patients without deficits showed that these responses are enlarged in the AH when perirolandic lesions are present. Patients with motor deficits also showed an increased response for P45m in the UH. CONCLUSION: The results of posterior tibial nerve SEFs suggest spatial and functional changes in the somatosensory network as a result of perirolandic lesions with a possible relationship with clinical symptoms. The results can provide further basis for the evaluation of cortical changes in the presence of perirolandic lesion

The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex

<div><p>Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons’ receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex.</p></div

Localization of the microwires and retinotopy.

<p>(A) A schematic of the side-wire electrode. The body of the electrode was a hollow polyurethane tube. The gray-shaded regions depict the clinical macrocontacts used to measure intra-cranial EEG. The microwires were 40 μm diameter platinum-iridium wires situated between the macrocontacts. (B) Post-explantation fMRI measures of the retinotopic organization presented on an inflated representation of the patient’s left hemisphere. The left panel shows the eccentricity map and the right panel, the representation of polar angle. The solid lines indicate the representation of the vertical meridian and the dashed lines the representation of the horizontal meridian. The small blue patch outlined by a dashed line shows the estimated location of microwires E6 and E7 based on a spherical region-of-interest (diameter 5 mm) centered on the midpoint between macrocontacts M3 and M4 (see below). (C) (Left panel). The locations of the macrocontacts (turquoise regions) were obtained from a post-implantation CT scan, co-registered with a post-explantation structural MR image. The electrode track was clearly visible on the post-explantation scan as a region of signal dropout, depicted here in blue. The areas V1d–V3d are overlaid on the gray-white matter boundary. (Right panel) An inflated version of these areas and the estimated location of electrodes E6 and E7, which were situated very close to the representation of the horizontal meridian that marks the boundary between V2 and V3, and most likely within V3. Data is available from the Data Access Committee of the Netherlands Institute for Neuroscience: <a href="mailto:[email protected]" target="_blank">[email protected]</a>.</p

Contextual modulation of neuronal responses in human V2/V3.

<p>(A) The stimuli used to study contextual modulation. In the center-only condition, a 6° diameter grating was centered on the RF. We used two different orientations so that, on average, the orientation of the center was the same across conditions. In the Iso, Iso90, and Cross conditions, a full-screen surround was added. These conditions allowed extraction of signals related to two contextual effects: orientation-tuned surround suppression (upper panels) and figure-ground modulation (lower panels). (B) The MUA time courses averaged across E6 and E7. The inset shows responses during the early phase. These early responses were suppressed when the surround had the same orientation as the center (Iso, Iso90). Later activity depended on whether the central grating could be segmented from the background (Iso90, Cross) or not (Iso). (C) The average level of OTSS and FGM in an early (50–100 ms) and late (100–500 ms) time window for E6 and E7. Error bars represent 1 S.E.M. as estimated by a bootstrap procedure. Asterisks mark significant effects (** = <i>p</i> < 0.01, *** = <i>p</i> < 0.001, two-sample <i>t</i> test). (D) The time course of the modulatory effects. The black line illustrates OTSS (Cross-Iso90) averaged across E6 and E7. The gray line represents FGM (Iso90-Iso). The red lines show best-fitting Gaussian functions. Latencies were estimated as the point at which the Gaussians reached 50% of their maximum and are marked by the arrows. (E) Results of the latency analysis for OTSS and FGM. Error bars are 1 S.E.M. estimated by a bootstrap procedure. The black dashed line indicates the latency of the visual response estimated using the center-only condition. The latency was shorter than in <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002420#pbio.1002420.g002" target="_blank">Fig 2</a> because the effective contrast of the stimulus within the RF was higher. Data is available from doi:<a href="http://dx.doi.org/10.17605/OSF.IO/BRCZY" target="_blank">10.17605/OSF.IO/BRCZY</a></p

Receptive field location and size estimates from E6 and E7.

<p>(A) MUA receptive field (activity averaged between 50 and 300 ms after stimulus onset) from E6 to a 1° x 1° checkerboard briefly presented at each location of an 11 x 11 grid (left panel). The center of the RF was estimated by fitting a 2D Gaussian (right panel) to the data and the RF size as the width of the Gaussian at half of the maximum (FWHM), averaged across the <i>x</i> and <i>y</i> directions. (B) Responses from the 10% of locations closest to the center of the RF (red line) and the 10% of locations farthest from the center of the RF (blue line). The gray bars indicate samples with significant differences between these conditions (<i>t</i> test, <i>p</i> < 0.05). The latency of the response was estimated as the first significant sample that was followed by ten contiguous significant tests (arrow). (C) The change in gamma power (40–120 Hz) in a window from 100–250 ms after stimulus onset at each stimulus location relative to the average power across all locations (left panel). We also fit a 2D Gaussian to the spatial profile of the gamma power increase (right panel). (D) The relative increase in power when a flash was presented within the RF (10% closest locations, red line) compared to outside the RF (10% farthest locations, blue line). The shaded region depicts +/- 1 standard error of the mean (S.E.M) estimated by bootstrapping. (E–H) Data from electrode E7, same format as A–D. Data is available from doi:<a href="http://dx.doi.org/10.17605/OSF.IO/BRCZY" target="_blank">10.17605/OSF.IO/BRCZY</a></p

Orientation tuning in V2/V3.

<p>(A) Upper panel, MUA responses at electrode E7 to sine-wave gratings drifting in one of 24 directions. In this and subsequent figures, error-bars indicate +/- 1 S.E.M. The red line is the fit of a wrapped double Gaussian. The lower panel shows the same data in polar form, averaged across opposite movement directions with the same orientation and normalized to maximum response across orientations. The gray arrow is the preferred orientation (vector average). (B) Time course of MUA at E7 elicited by gratings of the preferred (averaged across 165° and 180°) and orthogonal (averaged across 75° and 90°) orientations. Orientation tuning arises very rapidly. (C) Upper panels: Gamma power (30–100 Hz) evoked by the 24 different directions at electrode E6 (green) and E7 (red) expressed as a percentage of the pre-stimulus baseline. The gamma power was significantly tuned for orientation but did not depend on direction. Lower panels: the same data in polar form, normalized to the maximum change in power across orientations. (D) The center frequency of the gamma peak at E6 and E7 at each of the 24 directions. (E) Change in power relative to pre-stimulus baseline in response to the preferred orientation (dark red) and the orthogonal orientation (pink) for E7. Note the presence of a clear peak in the power spectrum. The solid lines show a Gaussian fit, used to estimate the central frequency of the gamma peak. (F) Spatial frequency tuning of MUA at electrodes E6 (green) and E7 (red). (G) Gamma power (30–100 Hz) changes relative to the pre-stimulus baseline at different spatial frequencies. (H) Change in power relative to pre-stimulus baseline from E7 for each of the five spatial frequencies. Data is available from doi:<a href="http://dx.doi.org/10.17605/OSF.IO/BRCZY" target="_blank">10.17605/OSF.IO/BRCZY</a></p

Attentional modulation of spiking activity in human V2/V3.

<p>(A) Example stimulus of the curve-tracing experiment. The RF of MUA at E7 is also shown. There were two distractor curves, which were connected to two other circles near and far from the RF. The right panels illustrate the two alternative stimulus configurations. (B) The stimulus paradigm: The patient initially had to fixate for 300 ms. One of nine possible stimulus configurations was shown, the three curve configurations of stimulus set 1 are shown here. The patient had to mentally trace the target curve attached to the fixation point. After a delay of 500 ms the fixation point turned green and the patient was required to make a saccade towards the red target circle connected to the fixation dot. (C) The MUA response averaged across E6 and E7 when the RFs fell on the target curve (red line) or on one of the two distractor curves (blue line, averaged across near and far distractor). The attentional modulation is the difference between the two responses (gray shading). (D) The average response at E6 and E7 in a window from 200 to 500 ms elicited by the target curve (red bar) and the distractors (blue bars). The asterisks indicate the significance of the difference in MUA between the target and distractor conditions as assessed by a <i>t</i> test (* = <i>p</i> < 0.05, ** = <i>p</i> < 0.01). Error-bars indicate 1 S.E.M. Data is available from doi:<a href="http://dx.doi.org/10.17605/OSF.IO/BRCZY" target="_blank">10.17605/OSF.IO/BRCZY</a></p

Size tuning of MUA and LFP.

<p>(A) MUA responses at E7 evoked by drifting gratings of various sizes. The peak response increases up to sizes around 3°–4° and activity is suppressed at larger sizes. (B) The average response between 0–500 ms at each size for E6 and E7. Error-bars show +/- 1 S.E.M. The red line is the best fit of the ratio-of-Gaussians model. (C) The traces show the raw LFP from 20 trials from E7. The red vertical lines mark the onset and offset of the stimulus (a 10° diameter grating). Note the low-frequency oscillations before the appearance of the stimulus, which are replaced with high-frequency gamma oscillations after stimulus onset. (D) The relative increase in the amplitude spectrum in the gamma range as function of stimulus size averaged across E6 and E7 (compared to a pre-stimulus baseline). The non-normalized (log) amplitude spectra for E6 and E7 are shown on the right. (E) Center frequency of the gamma peak, as estimated by fitting a Gaussian function. The colors of the dots indicate the size of the grating; conventions as in panel D. (F) Increase in gamma-band amplitude as a function of the MUA response. Note the absence of a clear relationship. (G) Dependence of the change in gamma amplitude on stimulus size. There was a strong correlation (r = 0.98, <i>p</i> < 0.001). Data is available from doi:<a href="http://dx.doi.org/10.17605/OSF.IO/BRCZY" target="_blank">10.17605/OSF.IO/BRCZY</a></p