2014
DOI: 10.1016/j.neuropsychologia.2014.05.008
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Spatial imagery in haptic shape perception

Abstract: We have proposed that haptic activation of the shape-selective lateral occipital complex (LOC) reflects a model of multisensory object representation in which the role of visual imagery is modulated by object familiarity. Supporting this, a previous functional magnetic resonance imaging (fMRI) study from our laboratory used inter-task correlations of blood oxygenation level-dependent (BOLD) signal magnitude and effective connectivity (EC) patterns based on the BOLD signals to show that the neural processes und… Show more

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Cited by 42 publications
(51 citation statements)
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References 68 publications
(113 reference statements)
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“…Additionally, this area responds to vestibular self-motion in both humans38 and monkeys394041. In one view, V5/hMT+ might house visual imagery, yet not be multimodal4243. For example, tactile motion might be transformed into a visual code.…”
Section: Discussionmentioning
confidence: 99%
“…Additionally, this area responds to vestibular self-motion in both humans38 and monkeys394041. In one view, V5/hMT+ might house visual imagery, yet not be multimodal4243. For example, tactile motion might be transformed into a visual code.…”
Section: Discussionmentioning
confidence: 99%
“…Individual preferences for object and spatial imagery are found not only in the visual, but also in the haptic modality (Lacey et al, 2011). Here, we tested spatial imagery, which emphasizes spatial relationships, using a task modified from an earlier study (Lacey et al, 2014). The task used here required participants to imagine cells numbered 1 to 25 in a 5 × 5 matrix (Figure 2) and, in response to auditorily presented four-digit strings, to imagine the shapes that would result from filling those four cells.…”
Section: Methodsmentioning
confidence: 99%
“…Investigation of the effective (or directional) brain connectivity in the network of activated brain regions was performed through multivariate Granger causality analysis (GCA) using a custom MATLAB 4 code as previously described by Grant et al (2014); Kapogiannis et al (2014) and Lacey et al (2014). Granger causality is based on a temporal precedence concept (Granger, 1969) that can be applied to multivariate effective connectivity modeling of ROI (region of interest) time courses to predict directional influences among brain regions (Friston et al, 2003; Deshpande et al, 2009; Strenziok et al, 2010; Preusse et al, 2011; Sathian et al, 2011).…”
Section: Methodsmentioning
confidence: 99%
“…Therefore, directional connectivity between selected ROIs can be estimated using the dMVAR model coefficients at each specific time instant. Since the experimental design consists of conditions of interest as well as inter-trial rest intervals, condition-specific connectivity values can be obtained as sample distributions by aggregating model coefficients corresponding to all time instants for specific conditions (Sathian et al, 2013; Grant et al, 2014, 2015; Lacey et al, 2014; Wheelock et al, 2014; Hutcheson et al, 2015; Feng et al, 2016). Granger connectivity (GC) path weights, i.e., the model coefficients, for conditions of interest (bad advice) for each agent (human, machine) were extracted.…”
Section: Methodsmentioning
confidence: 99%