Measuring the effects of attention to individual fingertips in somatosensory cortex using ultra-high field (7T) fMRI

Bayesian population receptive field modeling in human somatosensory cortex

“…With this knowledge and 132 thoughtful experimental designs, however, it is possible to non-invasively gain 133 unprecedented insight into the receptive field properties of the neurons contained 134 within each voxel. 135136Here we extend this line of research by using previously collected, high-resolution 137 fMRI somatotopic mapping data(Puckett et al, 2017) with a novel Bayesian pRF 138 modeling framework(Zeidman et al, 2018) to demonstrate the feasibility of using 139 vibrotactile driven sensory responses in S1 to directly estimate each voxel's pRF. The140 pRF modeling approach marks an improvement over conventional phase-encoded 141 techniques (Puckett et al, 2017; Sanchez-Panchuelo et al, 2010) by providing an 142 estimate of not only the preferred fingertip (pRF center location) but also the size and 143 shape (i.e., the topography) of the pRF.…”

“…It is important to understand that pRF properties are not only relevant to the processing 573 of different forms of bottom-up, sensory driven information, but that they also influence 574 top-down effects such as attention. Findings have shown that attention modulates the 575 responses of neurons with tactile receptive fields centered on an attended stimulus 576 (Hsiao et al, 1993), and we have previously shown using high-resolution fMRI that the 577 attentional field (AF) is able to modulate somatotopically appropriate regions of cortex 578 with a fine level of detail (i.e., with individual fingertip specificity) (Puckett et al, 2017). 579…”

Similar somatotopy for active and passive digit representation in primary somatosensory cortex

“…This includes activation of deep mechanoreceptors, muscle proprioceptors, and skin stretch receptors (Bensmaia & Tillery, 2014;Chouvardas, Miliou, & Hatalis, 2008;Saal, Delhaye, Rayhaun, & Bensmaia, 2017). Active movement also causes efferent signals into SI from the motor system (Wolpert & Flanagan, 2001;Wolpert, Ghahramani, & Jordan, 1995), as well as top down inputs from high-order cognitive processing, e.g., attention, visual input (Kuehn, Mueller, Turner, & Schütz-Bosbach, 2014;Puckett, Bollmann, Barth, & Cunnington, 2017). In our daily life, this multitude of inputs are meaningfully integrated in our actions and interactions with the world.…”

Addressing challenges of high spatial resolution UHF fMRI for group analysis of higher‐order cognitive tasks: An inter‐sensory task directing attention between visual and somatosensory domains

“…To date, the majority of UHF fMRI studies have used reduced field‐of‐view (FOV) 2D‐and 3D echo planar imaging (EPI) acquisitions to study chosen primary sensory areas, such as the visual and sensorimotor cortices (Fracasso, Luijten, Dumoulin, & Petridou, ; Puckett, Bollmann, Barth, & Cunnington, ; Reithler, Peters, & Goebel, ; Schluppeck, Sanchez‐Panchuelo, & Francis, ), thus overcoming a number of challenges of B 0 and B 1 inhomogeneities associated with larger FOV acquisitions (Polimeni, Renvall, Zaretskaya, & Fischl, ; Uludag & Blinder, ). For example, the increase in BOLD CNR of UHF experiments has been used to provide detailed maps of individual subjects’ visual (Goncalves et al, ; Kemper, De Martino, Emmerling, Yacoub, & Goebel, ; Poltoratski, Ling, McCormack, & Tong, ; Rua et al, ) and somatosensory functional responses (Puckett et al, ; Sanchez Panchuelo et al, ; Sanchez Panchuelo, Schluppeck, Harmer, Bowtell, & Francis, ) and how these relate to individual brain anatomy (Besle, Sanchez‐Panchuelo, Bowtell, Francis, & Schluppeck, ; Sanchez‐Panchuelo et al, ; Sanchez‐Panchuelo et al, ). These functional maps have been shown to spatially vary across subjects, highlighting inter‐subject variability, whilst the reproducibility of these maps has been shown to be high within subjects across sessions (Goncalves et al, ; Sanchez‐Panchuelo et al, ).…”