High-resolution fMRI investigations of the fingertip somatotopy and variability in BA3b and BA1 of the primary somatosensory cortex

Pfannmöller, Jörg P.; Greiner, Marvin; Balasubramanian, Mukund; Lotze, Martín

doi:10.1016/j.neuroscience.2016.10.036

Cited by 23 publications

(23 citation statements)

References 39 publications

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“…Our results indicate that decoding accuracy was higher within the primary than in the secondary somatosensory cortex mask and that it is possible to induce somatotopic discriminative weight patterns by mental imagery. The median x-coordinates of the subjects with highest offline classification accuracies roughly correspond to values reported in the literature for finger (Nelson and Chen, 2008;Schweizer et al, 2008;Sanchez-Panchuelo et al, 2010;Kolasinski et al, 2016;Pfannmöller et al, 2016) and foot representations (Akselrod et al, 2017; Figure 7). The slightly more medial imagery-related weight coordinates could be due to the fact that, in the current study, imagery involved the whole hand whereas stimulation is usually delivered to the fingers only.…”

Section: Topographic Nature Of Somatosensory Imagerysupporting

confidence: 81%

“…In visual mental imagery, the topographic nature of representations has been shown to be preserved in the primary visual cortex, even allowing for decoding of imagery content (Klein et al, 2004;Slotnick et al, 2005;Thirion et al, 2006). The primary somatosensory cortex (S1) also contains topographic representations (hand: Nelson and Chen, 2008;Schweizer et al, 2008;Sanchez-Panchuelo et al, 2010;Kolasinski et al, 2016;Pfannmöller et al, 2016;leg/foot: Akselrod et al, 2017;body: Penfield and Rasmussen, 1950;Zeharia et al, 2015), but although imagery-induced activation has been shown in S1 and S2, it is unknown whether similar somatotopic activity can be induced using somatosensory mental imagery of the body surface. If somatosensory imagery would induce somatotopically specific activation patterns, this would probably simplify (online) classification, and open up the possibility to use it to activate and train particular subregions of the somatosensory map.…”

Section: Introductionmentioning

confidence: 99%

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Topographic Somatosensory Imagery for Real-Time fMRI Brain-Computer Interfacing

Kaas

Goebel

Valente

et al. 2019

Front. Hum. Neurosci.

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Real-time functional magnetic resonance imaging (fMRI) is a promising non-invasive method for brain-computer interfaces (BCIs). BCIs translate brain activity into signals that allow communication with the outside world. Visual and motor imagery are often used as information-encoding strategies, but can be challenging if not grounded in recent experience in these modalities, e.g., in patients with locked-in-syndrome (LIS). In contrast, somatosensory imagery might constitute a more suitable information-encoding strategy as the somatosensory function is often very robust. Somatosensory imagery has been shown to activate the somatotopic cortex, but it has been unclear so far whether it can be reliably detected on a single-trial level and successfully classified according to specific somatosensory imagery content. Using ultra-high field 7-T fMRI, we show reliable and high-accuracy single-trial decoding of left-foot (LF) vs. right-hand (RH) somatosensory imagery. Correspondingly, higher decoding accuracies were associated with greater spatial separation of hand and foot decoding-weight patterns in the primary somatosensory cortex (S1). Exploiting these novel neuroscientific insights, we developed-and provide a proof of concept for-basic BCI communication by showing that binary (yes/no) answers encoded by somatosensory imagery can be decoded with high accuracy in simulated real-time (in 7 subjects) as well as in real-time (1 subject). This study demonstrates that body part-specific somatosensory imagery differentially activates somatosensory cortex in a topographically specific manner; evidence which was surprisingly still lacking in the literature. It also offers proof of concept for a novel somatosensory imagery-based fMRI-BCI control strategy, with particularly high potential for visually and motor-impaired patients. The strategy could also be transferred to lower MRI field strengths and to mobile functional near-infrared spectroscopy. Finally, given that communication BCIs provide the BCI user with a form of feedback based on their brain signals and can thus be considered as a specific form of neurofeedback, and that repeated use of a BCI has been shown to enhance underlying representations, we expect that the current BCI could also offer an interesting new approach for somatosensory rehabilitation training in the context of stroke and phantom limb pain.

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Section: Topographic Nature Of Somatosensory Imagerysupporting

confidence: 81%

Section: Introductionmentioning

confidence: 99%

Topographic Somatosensory Imagery for Real-Time fMRI Brain-Computer Interfacing

Kaas

Goebel

Valente

et al. 2019

Front. Hum. Neurosci.

View full text Add to dashboard Cite

show abstract

“…With the SBA, the overlap of activated and previously stimulated voxels was higher (83% vs 97%) and the overall occurrence of false-positive activations was lower than with the VBA. It is conclusive to assume that the superior registration of the postcentral structures in the SBA is the reason for the better finger segregation in the cortical activation pattern 29 . Although surface mapping of functional MR data has recently been used in other brain regions, such as the visual and auditive [44][45][46] systems, to our knowledge, there is no systematic comparison between the VBA and SBA available.…”

Section: Discussionmentioning

confidence: 94%

“…On the other hand, the SBA can potentially improve scenarios where smaller spatial scales (than pre-and central cortex) and functional heterogeneity, i.e., somatotopic, retinotopic or tonotopic representation, are involved 28 . The registration of individual MR data on the surface can improve accuracy and therefore the localization of small cortical structures 29,30 .…”

Section: Discussionmentioning

confidence: 99%

Surface-based analysis increases the specificity of cortical activation patterns and connectivity results

Brodoehl

Gaser

Dahnke

et al. 2020

Sci Rep

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Spatial smoothing of functional magnetic resonance imaging (fMRI) data can be performed on volumetric images and on the extracted surface of the brain. Smoothing on the unfolded cortex should theoretically improve the ability to separate signals between brain areas that are near together in the folded cortex but are more distant in the unfolded cortex. However, surface-based method approaches (SBA) are currently not utilized as standard procedure in the preprocessing of neuroimaging data. Recent improvements in the quality of cortical surface modeling and improvements in its usability nevertheless advocate this method. In the current study, we evaluated the benefits of an up-to-date surface-based smoothing in comparison to volume-based smoothing. We focused on the effect of signal contamination between different functional systems using the primary motor and primary somatosensory cortex as an example. We were particularly interested in how this signal contamination influences the results of activity and connectivity analyses for these brain regions. We addressed this question by performing fMRI on 19 subjects during a tactile stimulation paradigm and by using simulated BOLD responses. We demonstrated that volume-based smoothing causes contamination of the primary motor cortex by somatosensory cortical responses, leading to false positive motor activation. These false positive motor activations were not found by using surface-based smoothing for reasonable kernel sizes. Accordingly, volume-based smoothing caused an exaggeration of connectivity estimates between these regions. In conclusion, this study showed that surface-based smoothing decreases signal contamination considerably between neighboring functional brain regions and improves the validity of activity and connectivity results.

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“…5 It has been suggested that similar neuroprotective effects might be created by sensory stimulation to the human hands or lips, 4 which possess similarly large and complex cortical representation. 6 Very few studies have directly measured the effect of sensory stimulation of the hands or lips on CBFV in the basal cerebral arteries, 7 although the effects of sensory stimulation of the hand on local or regional CBF have been studied by various modalities, including PET, 8,9 functional MRI (fMRI), 10–12 and functional near-infrared spectroscopy (fNIRS). 13 Each of these modalities has drawbacks and limitations.…”

Section: Introductionmentioning

confidence: 99%