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Knowing about Tool Use; a fMRI investigation of active brain centers for procedural learning

Discusses the results of a pilot fMRI investigation of active brain centers for procedural learning

Daniel Flynn

on 1 March 2016

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Transcript of Knowing about Tool Use; a fMRI investigation of active brain centers for procedural learning

Knowing about Tools!
Research Question and Hypothesis
Experimental Design and Task Paradigm
The observation of tools is known to elicit a distributed cortical network that reflects close-knit relations of semantic, action-related, and perceptual knowledge.

The neural correlates underlying the critical knowledge of skilled tool use, however, remain to be elucidated.•

It is hypothesized that the parietal activity underlies tool-use knowledge, with supramarginal gyrus storing information about limb and hand positions, and precuneus storing visuospatial information about hand-tool interactions.•

The observation of tools activates distinct regions in predominantly left hemispheric frontal, parietal, and temporal regions independent of the observer’s intention to act (Perani and others, 1995; Martin and others, 1996; Chao and others, 1999; Chao and Martin, 2000).•

specific tool-use skills are believed to be represented in the left posterior parietal cortex (Johnson-Frey, 2004).•

Activation of this network during the mere observation of tools suggests the existence of an automatic link between the perception of a tool and the activation of routines that describe possible interactions with it.•

…robust activation of the left posterior parietal cortex (especially the intraparietal sulcus and the inferior parietal lobule) has been elicited when volunteers make explicit judgments about the type of movement employed during the use of manipulable tools (Kellenbach and others, 2003).•

This finding suggests that the posterior parietal cortex is selectively activated by the retrieval of knowledge concerning an object’s specific action (how to hold, manipulate, and use the tool), rather than by passive viewing or by retrieving knowledge about the function of the object (what the tool is for).
Research Question and Hypotheses
H1: That familiar tools will show greater activation in left hemispheric inferior parietal regions than will unfamiliar tools.

H2: There will be a difference in the neural effects of observing frequently versus infrequently used familiar tools.
• Block Design

•Paradigm 1:
30 18-second blocks,
each with 6 images for 3sec each
24 each Fam-unfam-nonobjects (12r,12l)
72 diff images randomly distributed

•Paradigm 2:
—12 objects each (experienced-unexperienced),
5xe randomly

10 Minutes each paradigm, 20 minutes per subject
Experimental Design and Task Paradigm
Statistical Analysis
• Fourteen healthy volunteers participated in the study (range: 20-24 years, mean age: 22, 8 women and 6 men). All were right handed
3.0 T on a Siemens Trio MRI scanner with echo planar imaging (EPI) capabilities using an eight-channel PA head coil for radio frequency transmission and signal reception.
After automatic shimming of the magnetic field on each participant, a 3D high-resolution T1 anatomical image of the whole brain in the sagittal plane was acquired for coregistration with the functional images (3D MPRAGE, 176 slices, slice thickness=0.9, inplane resolution=0.9°—0.9 mm, TR=1550 ms, TE=2.39).
230 functional EPI images in the axial plane were acquired during each paradigm. They had the following parameters:
• For each run of each subject’s paradigm a protocol file representing the onset and duration of each block for the different conditions was derived. Factorial design matrices were defined automatically from the created protocols. To account for hemodynamic delay and dispersion, the bold response for each predictor was modeled as an epoch and convolved with a canonical hemodynamic response function (gamma) to form covariates in a General Linear Model (GLM). After the GLM had been fitted and the effects of temporal serial correlation allowed for (using AR(1) modeling; (Bullmore and others, 1996)), group (random effects procedure) or individual t-maps were generated for the simple main effects of observing familiar (FamiliarNControl) and unfamiliar tools (UnfamiliarNControl). Most significantly, the experimental conditions were contrasted for direct comparison of the familiar and unfamiliar tools (FamiliarNUnfamiliar; UnfamiliarNFamiliar). These latter contrasts were performed over a priori determined regions of interest (ROI) to increase statistical power.
Tools (Familiar & Unfamiliar) create activation in the
temporal (left lateral posterior middle temporal gyrus) and parietal cortices (left supramarginal gyrus, left inferior parietal lobule, and left precuneus).
Previousely experienced tools predominantly elicited activation in the left posterior parietal and bilateral inferior posterior temporal regions
• Often used tools showed increased activation in the left middle temporal gyrus compared to rarely used tools.
• Confrontation with unfamiliar or infrequently used tools reveals an increase in inferior temporal and medial and lateral occipital activation, predominantly in the left hemisphere, suggesting that these regions reflect visual feature processing for tool identification.
To conclude,
critical knowledge of the functional use of a tool appears represented in a distributed left hemispheric temporo-parietal network.
For my study...
Understanding of the known 'neural tool network' is critical as a context for my study of proximal physical contact's effect on network activation.
I hope to see...
plus something more accounted for by the immediate 'hands-on' experience!
Dan Flynn
March 2, 2011
Dr. vanErp
TR=2.5 s,
TE=33 ms;
flip angle=90°,
33 slices,
slice thickness=2.5 mm,
slice gap=1.25 mm,
FOV=192 mm and
== a resolution of 3°—3°—2.5 mm.
The first eight images were discarded to allow for the establishment of steady-state magnetization.

Functional data were converted into Brain Voyager QX’s FMR format and subjected to a standard sequence of preprocessing steps comprising:
slice scan time correction using sinc interpolation,
3-D motion correction by spatial alignment to the first volume also using sinc interpolation, and
temporal filtering using linear trend removal and high pass filtering for low-frequency drifts of 3 or fewer cycles per time point.

Estimated rotation and translation parameters were inspected after head motion correction and never exceeded 2 mm.

Spatial smoothing using a Gaussian filter(FWHM=8 mm) was applied for the volume based analysis.
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