Controlling instabilities in manipulation requires specific cortical-striatal-cerebellar networks.

Abstract

Dexterous manipulation requires both strength, the ability to produce fingertip forces of a specific magnitude, and dexterity, the ability to dynamically regulate the magnitude and direction of fingertip force vectors and finger motions. Although cortical activity in fronto-parietal networks has been established for stable grip and pinch forces, the cortical regulation in the dexterous control of unstable objects remains unknown. We used functional magnetic resonance imaging (fMRI) to interrogate cortical networks engaged in the control of four objects with increasing instabilities but requiring constant strength. In addition to expected activity in fronto-parietal networks we find that dexterous manipulation of increasingly unstable objects is associated with a linear increase in the amplitude of the BOLD signal in the basal ganglia (P = 0.007 and P = 0.023 for 2 compression tasks). A computational regression (connectivity) model identified independent subsets of cortical networks whose connection strengths were mutable and associated with object instability (P < 0.001). Our results suggest that in the presence of object instability, the basal ganglia may modulate the activity of premotor areas and subsequent motor output. This work, therefore, provides new evidence for the selectable cortical representation and execution of dynamic multifinger manipulation for grasp stability.

Full text

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Articles in Press. J Neurophysiol (January 12, 2011). doi:10.1152/jn.00757.2010

Controlling instabilities in manipulation requires specific cortical-striatal-cerebellar
networks


Kristine Mosier1, Chad Lau2, Yang Wang1, Madhusudhan Venkadesan3,4, Francisco J.
Valero-Cuevas3,5
1 Department of Radiology, Indiana University School of Medicine, Indianapolis, Indiana
2 Wheldon School of Biomedical Engineering, Purdue University, West Lafayette,
Indiana
3 Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca,
NY
4School of Engineering & Applied Sciences and Department of Human Evolutionary
Biology, Harvard University, Cambridge, MA
5Department of Biomedical Engineering and Division of Biokinesiology & Physical
Therapy, The University of Southern California, Los Angeles, CA

Correspondence should be addressed to:
Kristine Mosier D.M.D., Ph.D.
Department of Radiology
Indiana University School of Medicine
950 W. Walnut St.
R2 E124
Indianapolis, IN
46202 USA
Email: kmosier@iupui.edu

Abstract
Dexterous manipulation requires both “strength”, the ability to produce fingertip
forces of a specific magnitude; and “dexterity”, the ability to dynamically regulate the
magnitude and direction of fingertip force vectors and finger motions. While cortical
activity in fronto-parietal networks has been established for stable grip and pinch forces,
the cortical regulation in the dexterous control of unstable objects remains unknown. We
employed functional magnetic resonance imaging (fMRI) to interrogate cortical networks
engaged in the control of four objects with increasing instabilities but requiring constant
strength. In addition to expected activity in fronto-parietal networks we find that

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Cortical-striatal-cerebellar networks for manipulation. Mosier, Lau, Wang, Venkadesan and Valero-Cuevas

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dexterous manipulation of increasingly unstable objects is associated with a linear
increase in the amplitude of the BOLD signal in the basal ganglia (p = 0.007 and p =
0.023 for two compression tasks). A computational regression (connectivity) model
identified independent subsets of cortical networks whose connection strengths were
mutable and associated with object instability (p< 0.001). Our results suggest that in the
presence of object instability, the basal ganglia may modulate the activity of premotor
areas and subsequent motor output. This work, therefore, provides new evidence for the
selectable cortical representation and execution of dynamic multifinger manipulation for
grasp stability.
Introduction
Dynamic dexterous manipulation of objects is essential to everyday life yet its
cortical underpinnings remain poorly characterized. One reason is that the classical
categorization of grip into “power” and “precision” grips (Napier, 1956; Cutkosky, 1989)
and neurophysiological studies thereof apply to holding solid objects in a fixed
orientation using isometric finger forces, but not to dynamical manipulation of unstable
objects. The power grip is used when the pads of all of the fingers hold an object against
the palm, typically with high magnitude forces to hold large or heavy objects.
Conversely, the precision grip involves holding small or delicate objects between the tips
of the thumb and one or more fingers using forces of lower magnitude. The regulation of
precision grip force magnitude to prevent slippage has been extensively studied in the
context of maintaining a constant posture of the fingers against constant or impulsive
perturbation loads, or a change in orientation with respect to the gravitation field
(Gordon, 1991; Johansson and Cole, 1992; Hepp-Raymond et al. 1996). In response to

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these perturbations, grip forces normal to the contact surface are known to appropriately
increase and counteract slippage produced by these tangential forces (Cole and Abbs,
1988; Johansson and Cole, 1992; Johansson, 1996, 1998; Ehrsson et al. 2003; Kuhtz-
Buschbeck et al. 2001). A number of previous investigations have examined the neural
correlates underlying the control of finger force magnitudes in precision grip in both
human subjects and nonhuman primates. Primate investigations and functional imaging
(PET, fMRI) studies in humans consistently reveal a network of frontal and parietal
regions (including the dorsal and ventral premotor cortex, cingulate cortex, sensorimotor
cortex and parietal cortex) active during grasping and in precision grip tasks (Rizzolatti et
al. 1987, 1996; Jeannerod et al. 1995; Sakata et al. 1995; Binkofski et al. 1999; Murata et
al. 2000; Kuhtz-Buschbeck et al. 2001; Ehrsson et al. 2000, 2001, 2003;Tunik et al.
2005). Moreover, fMRI studies of precise force scaling in a static precision grip task
demonstrate task-specific activity in sensorimotor cortex (M1/S1), supplementary and
cingulate motor areas (SMA/CMA), ventral premotor cortex (PMv) and inferior parietal
cortex (Kuhtz-Buschbeck et al. 2001). However, these studies demonstrating parietal
cortex involvement in object manipulation examined manipulation of either stable objects
or used a stable grip paradigm. Dexterous manipulation in general, however, requires the
ability to not only generate and scale the magnitude of fingertip forces, but it also
requires the sensorimotor ability to dynamically regulate the posture of the finger and the
direction of the force vectors.
To address this gap in our knowledge of brain function for the control of stability
of dexterous manipulation, we interrogate the nervous system with tasks of varying
stability requirements. This allows us to test the hypothesis of whether dynamic

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manipulation of increasingly unstable objects is associated with the scaling of activity in
sensorimotor and parietal cortex, or alternatively, is associated with increased activity in
other subcortical or cerebellar networks. We have previously formalized the ability to
produce a fingertip force vector of a specific magnitude as “strength”, and conversely,
“dexterity”, as the ability to dynamically regulate the posture of the finger and the
direction of the fingertip force vector (Valero-Cuevas, 2003b; Valero-Cuevas et al.
2003a, 2005). In this study we focus on understanding the cortical, subcortical and
cerebellar activity associated with tasks where human participants squeezed springs
requiring the same amount of fingertip force magnitude, but differing dexterity
requirements (i.e., different levels of instability). Our results show that control of stability
in dynamic manipulation is achieved through independent and tunable networks arising
from differential activity in cortical-striatal-cerebellar circuits.


Materials and Methods
A total of 16 healthy adult right-handed human subjects (10M, 6F; age range =
22-54; mean age = 32) participated in this investigation. Due to congenital hand defects
in one subject unknown prior to enrollment, data from only fifteen of the subjects were
included in the data analysis. All subjects gave written informed consent prior to the
experiment using consent approved by the Indiana University Institutional Review Board.

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Experimental paradigm
In order to identify neural correlates of dexterity for a chosen strength level (as
defined in the introduction) we employed a modified version (suitable for fMRI) of a
behavioral task that quantifies the strength and dexterity requirements for precision pinch
tasks (Valero-Cuevas et al. 2003a). Briefly, the Strength-Dexterity Test (S-D Test) is
based on the compression of commercially available stainless steel springs (Century
Spring Corp., Los Angeles, CA) using 3-point precision pinch grip between the index
finger, middle finger and opposing thumb. The strength requirement is the pinch force
required to compress the spring to solid length, defined by the linear stiffness constant
and free length of each spring. The dexterity requirement is the ability to prevent the
spring from buckling when compressed, and is mathematically defined by the material
properties and slenderness of the spring. A subset of four compression springs from the
S-D Test kit were chosen to have similar strength requirements (29N-34N) but different
dexterity requirements ranging from the largest more stable Spring 1,to the most slender
and least stable Spring 4 (dexterity indices of 0.40 – 1.67 as defined in Valero-Cuevas et
al. 2003a).The MR-compatible springs were made of high-quality Austenitic stainless
steel, which is neither ferromagnetic nor paramagnetic† and is commonly used in MR
compatible devices and implants. Table 1 lists the specifications for each of the springs.


† Manufacture of the springs involves cold working (bending) of the raw austenitic product which may
induce phase transfer to a ferromagnetic state. The springs exhibit no translational attraction at 1.5T,
however, at 3T the springs were found to exhibit very weak translational attraction of <<450 (ASTM
threshold for MRI devices) within the peak of the magnetic spatial gradient. Therefore the springs were
secured to the subject’s wrist with a 20cm length of string and subjects held the spring parallel to β0
outside of the peak spatial gradient. These precautions ensured that safety conditions were met and there
was no torque imposed on the spring.