Abstract
In the early visual and auditory system neurons are sensitive to a variety of parameters including orientation, contrast, and spatial and temporal frequencies, amplitude, timing, and spectral variables. There are theoretical reasons to believe that neural tuning for these particular parameters is fundamental to the information processing in each area. In contrast, we argue on both principled and empirical grounds that the idea of parametric encoding that has been so fruitfully applied to processing in early sensory systems does not have the potential to achieve more than heuristic or operational status in explanations of the motor system. In the motor system, inherent correlations among parameters of motion that occur in natural movements will necessarily make a neuron that is tuned to one variable also appear to be sensitive to other variables at different time lags. Similarly, depending on the nature of the task, neurons that appear to be tuned to parameters in one coordinate frame will often appear to be tuned to correlated variables in other coordinate frames. Finally, we point out that the tuning for any parameter can vary significantly with time lag. For all these reasons, we suggest that it may not be particularly meaningful to ask whether one or another movement parameter is represented in motor cortex. Instead, we propose that the tuning of any movement-sensitive cortical neuron is best envisioned as carving out a specific hyper-volume in a high-dimensional movement space. When one considers the way this tuning space changes over time, the time-varying preferred parameter values of the neuron describe a small segment of movement that we call a “movement fragment”.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alexander GE and Crutcher MD. Neural representations of the target (goal) of visually guided arm movements in three motor areas of the monkey. J. Neurophysiol. 64: 164–178, 1990.
Ashe J and Georgopoulos AP. Movement parameters and neural activity in motor cortex and area 5. Cerebral Cortex 6: 590–600, 1994.
Cabel DW, Cisek P and Scott SH. Neural activity in primary motor cortex related to mechanical loads applied to the shoulder and elbow during a postural task. J Neurophysiol 86: 2102–2108, 2001.
Cheney PD and Fetz EE. Functional classes of primate corticomotoneuronal cells and their relation to active force. J Neurophysiol 44: 773–791, 1980.
Evarts EV. Relation of pyramidal tract activity to force exerted during voluntary movement. Journal of Neurophysiology 31: 14–27, 1968.
Fetz EE. Are movement parameters recognizably coded in the activity of single neurons? Behavioral and Brain Sciences 15: 679–690, 1992.
Fu Q-G, Flament D, Coltz JD and Ebner TJ. Temporal encoding of movement kinematics in the discharge of primate primary motor and premotor neurons. J. Neurophysiol. 73: 836–854, 1995.
Fu Q-G, Suarez JI and Ebner TJ. Neuronal specification of direction and distance during reaching movements in the superior precentral premotor area and primary motor cortex of monkeys. J. Neurophysiol. 70: 2097–2116, 1993.
Georgopoulos AP, Caminiti R and Kalaska JF. Static spatial effects in motor cortex and area 5: Quantitative relations in a two-dimensional space. Experimental Brain Research 54: 446–454, 1984.
Georgopoulos AP, Kalaska JF, Caminiti R and Massey JT. On the relations between the direction of two-dimensional arm movements and cell discharge in primate motor cortex. 2: 1527–1537, 1982.
Graziano M. The Organization of Behavioral Repertoire in Motor Cortex. Annu Rev Neurosci, 2006.
Graziano MS, Cooke DF, Taylor CS and Moore T. Distribution of hand location in monkeys during spontaneous behavior. Exp Brain Res 155: 30–36, 2004.
Hepp-Reymond M-C, Wyss UR and Anner R. Neuronal coding of static force in the primate motor cortex. 74: 287–291, 1978.
Jackson A, Gee VJ, Baker SN and Lemon RN. Synchrony between neurons with similar muscle fields in monkey motor cortex. Neuron 38: 115–125, 2003.
Kakei S, Hoffman DS and Strick PL. Muscle and Movement Representations in the Primary Motor Cortex. Science 285: 2136–2139, 1999.
Kalaska JF, Cohen DAD, Hyde ML and Prud′homme M. A comparison of movement direction-related versus load direction-related activity in primate motor cortex, using a two-dimensional reaching task. 9: 2080–2102, 1989.
Kurata K. Premotor cortex of monkeys: Set- and movement-related activity reflecting amplitude and direction of wrist movements. Journal of Neurophysiology 77: 1195–1212, 1993.
Liu J and Newsome WT. Correlation between speed perception and neural activity in the middle temporal visual area. J Neurosci 25: 711–722, 2005.
Moran DW and Schwartz AB. Motor cortical representation of speed and direction during reaching. J Neurophysiol 82: 2676–2692, 1999.
Paninski L, Fellows MR, Hatsopoulos NG and Donoghue JP. Spatiotemporal tuning of motor cortical neurons for hand position and velocity. Journal of Neurophysiology 91: 515–532, 2004.
Salzman CD, Murasugi CM, Britten KH and Newsome WT. Microstimulation in visual area MT: effects on direction discrimination performance. J Neurosci 12: 2331–2355, 1992.
Scott SH, Gribble PL, Graham KM and Cabel DW. Dissociation between hand motion and population vectors from neural activity in motor cortex. Nature 413: 161–165, 2001.
Serruya MD, Hatsopoulos NG, Paninski L, Fellows MR and Donoghue JP. Instant neural control of a movement signal. Nature 416: 141–142, 2002.
Smith AM, Hepp-Reymond MC and Wyss UR. Relation of activity in precentral cortical neurons to force and rate of force change during isometric contractions of finger muscles. Exp Brain Res 23: 315–332, 1975.
Stark E, Drori R and Abeles M. Partial cross-correlation analysis resolves ambiguity in the encoding of multiple movement features. J Neurophysiol 95: 1966–1975, 2006.
Taira M, Boline J, Smyrnis N, Georgopoulos AP and Ashe J. On the relations between single cell activity in the motor cortex and the direction and magnitude of three-dimensional static isometric force. Exp Brain Res 109: 367–376, 1996.
Taylor DM, Tillery SI and Schwartz AB. Direct cortical control of 3D neuroprosthetic devices. Science 296: 1829–1832, 2002.
Wessberg J, Stambaugh CR, Kralik JD, Beck PD, Laubach M, Chapin JK, Kim J, Biggs SJ, Srinivasan MA and Nicolelis MA. Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408: 361–365, 2000.
Wolpaw JR and McFarland DJ. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc Natl Acad Sci U S A 101: 17849–17854, 2004.
Wu W and Hatsopoulos NG. Evidence against a single coordinate system representation in the motor cortex. Journal of Neurophysiology, 2007.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Reimer, J., Hatsopoulos, N.G. (2009). The Problem of Parametric Neural Coding in the Motor System. In: Sternad, D. (eds) Progress in Motor Control. Advances in Experimental Medicine and Biology, vol 629. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77064-2_12
Download citation
DOI: https://doi.org/10.1007/978-0-387-77064-2_12
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-77063-5
Online ISBN: 978-0-387-77064-2
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)