Neurophysiological basis of contrast dependent BOLD orientation tuning.

Recent work in early visual cortex of humans has shown that the BOLD signal exhibits contrast dependent orientation tuning, with an inverse oblique effect (oblique > cardinal) at high contrast and a horizontal effect (vertical > horizontal) at low contrast. This finding is at odds with decades of neurophysiological research demonstrating contrast invariant orientation tuning in primate visual cortex, yet the source of this discrepancy is unclear. We hypothesized that contrast dependent BOLD orientation tuning may arise due to contrast dependent influences of feedforward (FF) and feedback (FB) synaptic activity, indexed through gamma and alpha rhythms, respectively. To quantify this, we acquired EEG and BOLD in healthy humans to generate and compare orientation tuning curves across all neural frequency bands with BOLD. As expected, BOLD orientation selectivity in V1 was contrast dependent, preferring oblique orientations at high contrast and vertical at low contrast. On the other hand, EEG orientation tuning was contrast invariant, though frequency-specific, with an inverse-oblique effect in the gamma band (FF) and a horizontal effect in the alpha band (FB). Therefore, high-contrast BOLD orientation tuning closely matched FF activity, while at low contrast, BOLD best resembled FB orientation tuning. These results suggest that contrast dependent BOLD orientation tuning arises due to the reduced contribution of FF input to overall neurophysiological activity at low contrast, shifting BOLD orientation tuning towards the orientation preferences of FB at low contrast.

Exploratory study of the effect of brain tumors on the default mode network.

Resting state functional magnetic resonance imaging (RS-fMRI) is a popular method of visualizing functional networks in the brain. One of these networks, the default mode network (DMN), has exhibited altered connectivity in a variety of pathological states, including brain tumors. However, very few studies have attempted to link the effect of tumor localization, type and size on DMN connectivity. We collected RS-fMRI data in 73 patients with various brain tumors and attempted to characterize the different effects these tumors had on DMN connectivity based on their location, type and size. This was done by comparing the tumor patients with healthy controls using independent component analysis (ICA) and seed based analysis. We also used a multi-seed approach described in the paper to account for anatomy distortion in the tumor patients. We found that tumors in the left hemisphere had the largest effect on DMN connectivity regardless of their size and type, while this effect was not observed for right hemispheric tumors. Tumors in the cerebellum also had statistically significant effects on DMN connectivity. These results suggest that DMN connectivity in the left side of the brain may be more fragile to insults by lesions.

Effects of transcranial magnetic stimulation on visual evoked potentials in a visual suppression task.

Transcranial magnetic stimulation (TMS) can non-invasively modify cortical neural activity by means of a time-varying magnetic field. For example, in cognitive neuroscience, it is applied to create reversible "virtual lesions" in healthy humans (usually assessed as diminished performance in a behavioral task), thereby helping to establish causal structure-function relationships. Despite its widespread use, it is still rather unclear how TMS acts on existing, task-related neural activity, potentially resulting in a measurable effect on the behavioral level. Here, we deliver TMS to early visual areas while recording EEG in order to directly characterize the interaction between TMS-evoked (TEPs) and visual-evoked potentials (VEPs). Simultaneously, the subjects' performance is assessed in a visual forced-choice task. This allows us to compare the TMS effects on the VEPs across different levels of behavioral impairment. By systematically varying the stimulation intensity, we demonstrate that TMS strongly enhances the overall visual stimulus-related activity (rather than disrupting it). This enhancement effect saturates when behavior is impaired. This might indicate that the neural coding of the visual stimulus is robust to noise within a certain dynamic range (as indexed by the enhancement). Strong disturbances might saturate this range, causing behavioral impairment. Variation of the timing between the visual stimulus and the magnetic pulse reveals a "constructive interference" between the TEPs and VEPs: The better the overlap between both evoked potentials, the stronger the interaction effect when TMS and visual stimulation are combined. Importantly, however, this effect is uncorrelated with the strength of behavioral impairment.

Visuomotor Prediction Errors Modulate EEG Activity Over Parietal Cortex.

The parietal cortex is thought to be involved in visuomotor adaptation, yet it remains unclear whether it is specifically modulated by visuomotor prediction errors (i.e. PEs; mismatch between the predicted and actual visual consequences of the movement). One reason for this is that PEs tend to be associated with task errors, as well as changes in motor output and visual input, making them difficult to isolate. Here this issue is addressed using electroencephalography. A strategy (STR) condition, in which participants were instructed on how to counter a 45° visuomotor rotation, was compared to a condition in which participants had adapted to the rotation (POST). Both conditions were matched for task errors and movement kinematics, with the only difference being the presence of PEs in STR. Results revealed strong parietal modulations in current source density and low theta (2-4 Hz) power shortly after movement onset in STR vs. POST, followed by increased alpha/low beta (8-18 Hz) power during much of the post-movement period. Given recent evidence showing that feedforward and feedback information is respectively carried by theta and alpha/beta oscillations, the observed power modulations may reflect the bottom-up propagation of PEs and the top-down revision of predictions.