Deficits in rate of force production during multifinger tasks are associated with cognitive status

Abstract

Objectives The multifinger force deficit (MFFD) is the decline in force generated by an individual finger as the number of fingers contributing to the action is increased. It has been proposed that as a measure of neural sufficiency rather than muscle status, it provides a means of detecting individuals at risk of cognitive decline. Age‐related deficits in central neural drive exert a disproportionate impact on the rate at which force can be generated. We examined whether a MFFD derived from the maximum rate at which force is generated, is more sensitive to individual differences in cognitive status, than one calculated using the maximum level of force. Methods Monotonic associations between each of two variants of the MFFD, and cognition (measured with the Montreal Cognitive Assessment), were estimated cross sectionally using generalized partial rank correlations, in which age, level of education and degree of handedness were included as covariates. The participants (n=26) were community dwelling adults aged 66‐87. Results The MFFD derived using the maximum rate of force development was negatively associated with cognitive status. The association for the MFFD based on the maximum level of force, was not statistically reliable. The associations with cognitive status obtained for both variants of the MFFD were of greater magnitude than those reported previously for standard grip strength dynamometry. Conclusion The sensitivity with which the MFFD detects risk of cognitive decline may be enhanced by using the maximum rate of force developed by each finger, rather than the maximum force generated by each finger.

Deficits in force production during multifinger tasks demarcate cognitive dysfunction

“…Based on the correlation of −0.38 between the rofMFFD and MoCA obtained by Carson and Holton [ 21 ]; α = 0.05; power (1 − β error prob) = 0.80; a minimum sample size of 45 was estimated for the Kendall coefficient using the method of Looney [ 28 ]. Sixty-two volunteers took part in the study (42 females, 20 males, range 65–87, median 72.5 years) (see Supplementary Information).…”

“…Corresponding calculations were undertaken to obtain the rofMFFD. This was the (mean) maximum rof generated in the multifinger condition, as a ratio of the (mean) maximum rof generated when that finger was used in isolation [ 21 ].…”

“…Robust statistical analysis methods were therefore used. Following the approach described in Carson and Holton [ 21 ], generalized partial rank correlations [ 39 ], implemented in R via the taba package, were used to determine the degree of monotonic association between (separately) the MoCA and PCA-derived estimates of cognitive status and, respectively, the MFFD and the rofMFFD. With respect to the measures of cognition, age and ISCED classification were included as covariates.…”

“…We have shown [ 21 ] that the association between the MFFD, and cognitive status—measured with the Montreal Cognitive Assessment (MoCA), is greater than that which has been reported previously for GS [ 22 ]. Furthermore, the sensitivity with which the MFFD reflected cognitive decline was enhanced using as the basis for its calculation, the maximum rate of force (rof) developed by each finger, rather than the maximum force generated by each finger.…”

Grip force as a functional window to somatosensory cognition

“…Stronger grip forces have been associated with better cognitive performance in 527 patients between 45 and 62 years of age diagnosed with major depression (Firth, Smith, and Sarris, 2020). Multi-finger grip force deployment involves sophisticated neural control mechanisms (Kilgour, Todd, and Starr, 2014), and it has been suggested that decline in multi-finger grip strength is a marker of brain health (Carson and Holton, 2022). In healthy subjects (Cai et al , 2018) grip force is accurately scaled to just a little stronger than the minimum necessary to prevent the object from slipping out of the hand as a result of adaptive processes in finger force control during motor learning (Zatsiorsky and Latash, 2008;Cole, Potash, and Peterson, 2008).…”