Decoding the direction of imagined visual motion using 7T ultra-high field fMRI.

There is a long-standing debate about the neurocognitive implementation of mental imagery. One form of mental imagery is the imagery of visual motion, which is of interest due to its naturalistic and dynamic character. However, so far only the mere occurrence rather than the specific content of motion imagery was shown to be detectable. In the current study, the application of multi-voxel pattern analysis to high-resolution functional data of 12 subjects acquired with ultra-high field 7T functional magnetic resonance imaging allowed us to show that imagery of visual motion can indeed activate the earliest levels of the visual hierarchy, but the extent thereof varies highly between subjects. Our approach enabled classification not only of complex imagery, but also of its actual contents, in that the direction of imagined motion out of four options was successfully identified in two thirds of the subjects and with accuracies of up to 91.3% in individual subjects. A searchlight analysis confirmed the local origin of decodable information in striate and extra-striate cortex. These high-accuracy findings not only shed new light on a central question in vision science on the constituents of mental imagery, but also show for the first time that the specific sub-categorical content of visual motion imagery is reliably decodable from brain imaging data on a single-subject level.

The cortex-based alignment approach to TMS coil positioning.

TMS allows noninvasive manipulation of brain activity in healthy participants and patients. The effectiveness of TMS experiments critically depends on precise TMS coil positioning, which is best for most brain areas when a frameless stereotactic system is used to target activation foci based on individual fMRI data. From a purely scientific perspective, individual fMRI-guided TMS is thus the method of choice to ensure optimal TMS efficiency. Yet, from a more practical perspective, such individual functional data are not always available, and therefore alternative TMS coil positioning approaches are often applied, for example, based on functional group data reported in Talairach coordinates. We here propose a novel method for TMS coil positioning that is based on functional group data, yet only requires individual anatomical data. We used cortex-based alignment (CBA) to transform individual anatomical data to an atlas brain that includes probabilistic group maps of two functional regions (FEF and hMT+/V5). Then, these functional group maps were back-transformed to the individual brain anatomy, preserving functional-anatomical correspondence. As a proof of principle, the resulting CBA-based functional targets in individual brain space were compared with individual FEF and hMT+/V5 hotspots as conventionally localized with individual fMRI data and with targets based on Talairach coordinates as commonly done in TMS research in case only individual anatomical data are available. The CBA-based approach significantly improved localization of functional brain areas compared with traditional Talairach-based targeting. Given the widespread availability of CBA schemes and preexisting functional group data, the proposed procedure is easy to implement and at no additional measurement costs. However, the accuracy of individual fMRI-guided TMS remains unparalleled, and the CBA-based approach should only be the method of choice when individual functional data cannot be obtained or experimental factors argue against it.

Improved correspondence of resting-state networks after macroanatomical alignment.

Resting state brain activity, as measured with functional magnetic resonance imaging (fMRI) in the absence of stimulation, is widely investigated in clinical, pharmacological, developmental and cross-species neuroscience research. However, despite the general and broad interest in understating the nature of resting state networks (RSNs), there has not been a thorough investigation into the relationship between these functional networks and their adherence to underling brain anatomy. We acquired resting state fMRI data from 10 subjects and extracted individual and group RSN maps respectively using independent component analysis (ICA) and self organising group-level ICA (sogICA). Cortex based alignment (CBA), an advanced surface based alignment technique which uses individual curvature information to align individual subjects' brains to a dynamic group average, was used to maximise anatomical correspondence across subjects. Cross subject spatial correlations of the RSN maps (independent components) were carried out with and without CBA. Seven RSNs, which are amongst the most reported and studied networks, were identified. We observed a systematic gain in the spatial correlation in all of them following CBA, although this gain was not uniform across RSNs. The observed increase in similarity of the functional RSNs after anatomical alignment illustrates that these functional networks are indeed related to underlying macroanatomical features. Moreover, our results demonstrate that by correcting for individual anatomical differences, advanced surface based alignment techniques increase the overlap of corresponding resting state networks across subjects, thereby providing a useful means to improve resting state group statistics with no need for substantial smoothing.

Functionally informed cortex based alignment: an integrated approach for whole-cortex macro-anatomical and ROI-based functional alignment.

Due to anatomical variability across subjects many brain mapping experiments have analysis focused on a few particular regions of interest so as to circumvent the problem of sub-optimal statistics resulting from the lack of anatomical correspondence across subjects. Since the topographic distribution of experimental effects across the cortex is also often of interest, two separate analyses are often conducted, one on the regions of interest alone, as well as a separate 'whole brain' analysis with sub-optimal spatial correspondence across brains. In this paper we present a new group alignment procedure which incorporates, from each subject, both macro-anatomical (curvature) information and functional information from standard localizer experiments. After specifying appropriate parameters to weight anatomical and functional alignment forces, we were able to create a group cortical reconstruction which was well aligned in terms of both anatomical and functional areas. We observed an increase in the overlap of functional areas as well as an improvement in group statistics following this integrated alignment procedure. We propose that, using this alignment scheme, two separate analyses may not be necessary as both analyses can be integrated into a single procedure. After an integrated structural and functional alignment one is able to carry out a whole brain analysis with improved statistical sensitivity due to the reduction in spatial variation in the location of functional regions of interest which fCBA accomplishes. Furthermore, regions in the vicinity of localised and aligned regions-of-interest will also benefit from the integrated alignment.

Development from childhood to adulthood increases morphological and functional inter-individual variability in the right superior temporal cortex.

We study the developmental trajectory of morphology and function of the superior temporal cortex (STC) in children (8-9 years), adolescents (14-15 years) and young adults. We analyze cortical surface landmarks and functional MRI (fMRI) responses to voices, other natural categories and tones and examine how hemispheric asymmetry and inter-subject variability change across age. Our results show stable morphological asymmetries across age groups, including a larger left planum temporale and a deeper right superior temporal sulcus. fMRI analyses show that a rightward lateralization for voice-selective responses is present in all groups but decreases with age. Furthermore, STC responses to voices change from being less selective and more spatially diffuse in children to highly selective and focal in adults. Interestingly, the analysis of morphological landmarks reveals that inter-subject variability increases during development in the right--but not in the left--STC. Similarly, inter-subject variability of cortically-realigned functional responses to voices, other categories and tones increases with age in the right STC. Our findings reveal asymmetric developmental changes in brain regions crucial for auditory and voice perception. The age-related increase of inter-subject variability in right STC suggests that anatomy and function of this region are shaped by unique individual developmental experiences.

Measuring structural-functional correspondence: spatial variability of specialised brain regions after macro-anatomical alignment.

The central question of the relationship between structure and function in the human brain is still not well understood. In order to investigate this fundamental relationship we create functional probabilistic maps from a large set of mapping experiments and compare the location of functionally localised regions across subjects using different whole-brain alignment schemes. To avoid the major problems associated with meta-analysis approaches, all subjects are scanned using the same paradigms, the same scanner and the same analysis pipeline. We show that an advanced, curvature driven cortex based alignment (CBA) scheme largely removes macro-anatomical variability across subjects. Remaining variability in the observed spatial location of functional regions, thus, reflects the "true" functional variability, i.e. the quantified variability is a good estimator of the underlying structural-functional correspondence. After localising 13 widely studied functional areas, we found a large variability in the degree to which functional areas respect macro-anatomical boundaries across the cortex. Some areas, such as the frontal eye fields (FEF) are strongly bound to a macro-anatomical location. Fusiform face area (FFA) on the other hand, varies in its location along the length of the fusiform gyrus even though the gyri themselves are well aligned across subjects. Language areas were found to vary greatly across subjects whilst a high degree of overlap was observed in sensory and motor areas. The observed differences in functional variability for different specialised areas suggest that a more complete estimation of the structure-function relationship across the whole cortex requires further empirical studies with an expanded test battery.

Reconstructing imagined letters from early visual cortex reveals tight topographic correspondence between visual mental imagery and perception.

Visual mental imagery is the quasi-perceptual experience of "seeing in the mind's eye". While a tight correspondence between imagery and perception in terms of subjective experience is well established, their correspondence in terms of neural representations remains insufficiently understood. In the present study, we exploit the high spatial resolution of functional magnetic resonance imaging (fMRI) at 7T, the retinotopic organization of early visual cortex, and machine-learning techniques to investigate whether visual imagery of letter shapes preserves the topographic organization of perceived shapes. Sub-millimeter resolution fMRI images were obtained from early visual cortex in six subjects performing visual imagery of four different letter shapes. Predictions of imagery voxel activation patterns based on a population receptive field-encoding model and physical letter stimuli provided first evidence in favor of detailed topographic organization. Subsequent visual field reconstructions of imagery data based on the inversion of the encoding model further showed that visual imagery preserves the geometric profile of letter shapes. These results open new avenues for decoding, as we show that a denoising autoencoder can be used to pretrain a classifier purely based on perceptual data before fine-tuning it on imagery data. Finally, we show that the autoencoder can project imagery-related voxel activations onto their perceptual counterpart allowing for visually recognizable reconstructions even at the single-trial level. The latter may eventually be utilized for the development of content-based BCI letter-speller systems.