Neural Control of Action, Especially of Rapid Motor Sequences

I got interested in this subject because of William Calvin's "projectile theory of consciousness" or "throwing theory of thought"; his reasoning is something like this. Throwing something at a small moving target (even a large, distant moving target) needs very accurate motor control, particularly timing; doubling the distance of the throw can reduce the acceptable launch window by a factor of eight. In fact it happens too fast to be controlled by feedback from the muscles, and the precision seems to be beyond that of a single neuron, which is apt to be quite noisy. The obvious solution is to average lots of the neurons. The obvious problem is that, normally, noise will go down as the square of the number of neurons you average over, so an eight-fold reduction in noise needs a sixty-four fold increase in the number of neurons, and this is a lot of metabolically expensive brain to dedicate to lobbing rocks. Calvin's ingenious idea is that the needed neurons could be recruited as needed, and released for other tasks when not harassing the wild-life. He supposes that there are many different "sequencing tracks," each one of which carries one particular candidate sequence of muscle commands, and that these are "shaped up" by a Darwinian process, i.e. better-rated ones get copied into more tracks at the expense of the less favored, with occasional mutations, so that eventually all the tracks contain clones or near-clones of a single, highly-rated sequence, which is then executed.

Now once you have the neural machinery for this kind of sequence-generation, it's not such a stretch to imagine that your descendants will turn it to other uses. And a lot of what we do that is characteristically human --- speech, music, stories, poetry, planning, consciousness, composition of Web pages (I never said these were all admirable) ---- involves combining units into strings, with a good deal of trial and error, some of it even conscious. Calvin suggests that, in fact, Darwin Machines which originally evolved for throwing and similar ballistic motion were adapted to all these roles. I think this is a neat idea which ought to be followed up, and in particular I'd like to know if it leads to any specific predictions about the effects of brain lesions (say, damage to the planning tracks distrupting all those functions, but damage to the connections to memory of one or another leaving the rest intact), and how, if at all, it can be squared with what we know about grammar. (I'd also like to know whether it has any connection with the ideas about "strings and sequences" William James puts forth in the last chapter of his Psychology, but that's because I suspect James anticipated everything.) Of course even if Calvin's specific idea about how action is controlled turns out to be wrong, a more general notion that higher cognitive functions use the same kind of machinery as motion control could still be true.

Originally, Calvin proposed that the evaluation was done against some kind of stored memories of what had worked well in the past. More recent work in cognitive neuroscience, especially functional neuroimaging, shows that learning to use tools or perform actions creates "forward models" in the brain, circuits which can evaluate the consequences of possible lines of action. These would serve very nicely as the evaluators in his Darwin machines, at least for motion.

William Calvin
- The Cerebral Symphony: Seashore Reflections on the Structure of Consciousness [on-line]
- "The Brain as a Darwin Machine," Nature 330 (1987): 33--34 [PDF]
William Calvin and Derek Bickerton, Lingua ex Machina [website]
Christian Ethier, Laurent Brizzi, Warren G. Darling and Charles Capaday, "Linear Summation of Cat Motor Cortex Outputs", The Journal of Neuroscience 26 (2006): 5574--5581 [Thanks to Prof. Capaday for a reprint]
Hiroshi Imamizu, Satoru Miyauchi, Tomoe Tamada, Yuka Sasaki, Ryousuke Takino, Benno Pütz, Toshinori Yoshioka and Mitsuo Kawato, "Human Cerebellar Activity Reflecting an Acquired Internal Model of a New Tool," Nature 403 (2000): 192--195
Masao Ito, "Internal Model Visualized," Nature 403 (2000): 153--154 [Commentary on Imamizu et al. above]
William James, Principles of Psychology, ch. 23, ch. 26 and ch. 28
Marc Jeannerod
- The Cognitive Neuroscience of Action
- The Brain Machine: The Development of Neurophysiological Thought [The French title (Le Cerveau-Machine: Physiologie de la Volonté) is better: not only does it describe the subject more precisely (voluntary motion), the English loses the play on La Mettrie.]
Miller, Galanter and Pribram, Plans and the Structure of Behavior
Daniel M. Wolpert, R. Chris Miall and Mitsuo Kawato, "Internal Models in the Cerebellum," Trends in Cognitive Sciences 2 (1998): 338--347

BBS

Behavioral and Brain Sciences

Terra D. Barnes, Yasuo Kubota, Dan Hu, Dezhe Z. Jin and Ann M. Graybiel, "Activity of striatal neurons reflects dynamic encoding and recoding of procedural memories", Nature 437 (2005): 1158--1161
A. Berti, G. Bottini, M. Gandola, L. Pia, N. Smania, A. Stracciari, I. Castiglioni, G. Vallar, E. Paulesu, "Shared Cortical Anatomy for Motor Awareness and Motor Control", Science 309 (2005): 488--491
James R. Bloedel et al. (eds.), The Acquisition of Motor Behavior in Vertebrates
Valentino Braitenberg, Detlef Heck and Fahad Sultan, "The Detection and Generation of Sequences as a Key to Cerebellar Function. Experiments and Theory," BBBS 20(2): 229--277 [preprint]
Silvia A. Bunge and Jonathan D. Wallis (eds.), Neuroscience of Rule-Guided Behavior
William Calvin
- The Cerebral Code
- "Cortical Columns, Modules, and Hebbian Cell Assemblies," in Michael Arbib (ed.), The Handbook of Brain Theory and Neural Networks [on-line]
Yinong Chen, A Motor Control Model Based on Self-organizing Feature Maps (Technical Report 3816, Computer Science Department, University of Maryland-College Park, available on-line via NCSTRL)
Manu Chhabra and Robert A. Jacobs, "Near-Optimal Human Adaptive Control across Different Noise Environments", The Journal of Neuroscience 26 (2006): 10883--10887 [PDF via Prof. Jacobs]
Paul Cisek, "Integrated Neural Processes for Defining Potential Actions and Deciding between Them: A Computational Model", The Journal of Neuroscience 26 (2006): 9761--9770
Dana Cohen and Miguel A. L. Nicolelis, "Reduction of Single-Neuron Firing Uncertainty by Cortical Ensembles during Motor Skill Learning", Journal of Neuroscience 241 (2004): 3574--3582 [Thanks to Greg Gage for the pointer and a copy]
Benjamin A. Clegg, Gregory J. DiGirolamo and Steven W. Keele, "Sequence Learning," Trends in Cognitive Sciences 8 (1998): 275--281
Eddy J. Davelaar, "Sequential Retrieval and Inhibition of Parallel (Re)Activated Representations: A Neurocomputational Comparison of Competitive Queuing and Resampling Models", Adaptive Behavior 15 (2007): 51--71
Peter Ford Dominey, "From Sensorimotor Sequence to Grammatical Construction: Evidence from Simulation and Neurophysiology", Adaptive Behavior 13 (2005): 347--361 [Very cool, if it's right: "The current research describes a functional trajectory from sensorimotor sequence learning to the learning of grammatical constructions in language. A brief review of the functional neurophysiology of the cortex and basal ganglia will be provided as background for a neural network model of this system in sensorimotor sequence learning. Sequential behavior is then defined in terms of serial, temporal and abstract structure. The resulting neuro-computational framework is demonstrated to account for observed sequence learning behavior. More interestingly, this framework naturally extends to grammatical constructions as form-to-meaning mappings. Predictions from the neuro-computational model concerning parallels in language and cognitive sequence processing are tested against behavioral and neurophysiological observations in humans, resulting in a refinement of the allocation of model functions to subdivisions of Broca's area. From a functional perspective this analysis will provide insight into the relation between the coding structure in human languages, and constraints derived from the underlying neurophysiological computational mechanisms." PDF preprint]
Berent Enc, How We Act: Causes, Reasons and Intentions
David R. Euston and Bruce L. McNaughton, "Apparent Encoding of Sequential Context in Rat Medial Prefrontal Cortex Is Accounted for by Behavioral Variability", The Journal of Neuroscience 26 (2006): 13143--13155
Scott H. Frey and Valerie E. Gerry, "Modulation of Neural Activity during Observational Learning of Actions and Their Sequential Orders", The Journal of Neuroscience 26 (2006): 13194--13201
Okihide Hikosaka Miroyuki Nakahara, Miya K. Rand, Katsuyuki Sakai, Xiaofeng Lu, Kae Nakamura, Shigehrio Miyachi and Kenji Doya, "Parallel Neural Networks for Learning Sequential Procedures," Trends in Neurosciences 22 (1999): 464--471
Bernhard Hommel, "Event files: feature binding in and across perception and action", Trends in Cognitive Sciences 8 (2004): 494--500
James C. Houk, Jay T. Buckingham and Andrew G. Barto, "Models of the cerebellum and motor learning", BBS (1996) [preprint]
Marc Jeannerod, "The Representing Brain: Neural Correlates of Motor Intention and Imagery," BBS 17(2): 187-245 [preprint]
Scott H. Johnson-Frey (ed.), Taking Action: Cognitive Neuroscience Perspetives on Intentional Acts [Blurb]
Scott H. Johnson-Frey, "The neural bases of complex tool use in humans", Trends in Cognitive Sciences 8 (2004): 71--78
Michael I. Jordan and Daniel M. Wolpert, "Computational motor control", in M. Gazzaniga (ed.), The Cognitive Neurosciences [PDF preprint]
Angelo Maravita and Atsushi Iriki, "Tools for the body (schema)", Trends in Cognitive Sciences 8 (2004): 79--86
Frank A. Middleton and Peter L. Strick, "Cerebellar Output: Motor and Cognitive Channels," Trends in Cognitive Sciences 2 (1998): 348--354
Michael G. Paulin, "Evolutionary Origins and Principles of Distributed Neural Computation for State Estimation and Movement Control in Vertebrates", Complexity 10 (2005): 56--65
Rejean Plamondon and Adel M. Alimi, Speed vs. Accuracy Tradeoffs in Target Directed Movements
Tony J. Prescott, "Forced Moves or Good Tricks in Design Space? Landmarks in the Evolution of Neural Mechanisms for Action Selection", Adaptive Behavior 15 (2007): 9--31
Friedemann Pulvermuller, The Neuroscience of Language: On Brain Circuits of Words and Serial Order [Blurb]
Rosenbaum and Colley (eds.), Timing of Behavior [Blurb]
Jeremy D. Schmahmann, "Dysmetria of Thought: Clinical Consequences of Cerebellar Dysfunction on Cognition and Affect," Trends in Cognitive Sciences 2 (1998): 362--371
Stephen H. Scott, "Optimal Feedback Control and the Neural Basis of Volitional Motor Control", Nature Reviews Neuroscience 5 (2004): 532--546
Natalie Sebanz and Wolfgang Prinz (eds.), Disorders of Volition [Blurb]
Keisetsu Shima, Masaki Isoda, Hajime Mushiake and Jun Tanji, "Categorization of behavioural sequences in the prefrontal cortex", Nature 445 (2007): 315--318
Stein, Grillner, Selverston and Stuart (eds.), Neurons, Networks, and Motor Behavior
Jun Tanji, "Sequential Organization of Multiple Movements: Involvement of Cortical Motor Areas", Annual Review of Neuroscience 24 (2001): 631--651
William T. Thach, "What Is the Role of the Cerebellum in Motor Learning and Cognition?" Trends in Cognitive Sciences 2 (1998): 331--337
Kurt A. Thoroughman and Reza Shadmehr, "Learning of Action Through Adaptive Combination of Motor Primitives," Nature 407 (2000): 742--747 [Plus comment by Zoubin Ghahramani, "Building Blocks of Movement," same issue]
Kurt A. Thoroughman and Jordan A. Taylor, "Rapid Reshaping of Human Motor Generalization", The Journal of Neuroscience 25 (2005): 8948--8953
Frederick Toates, "The interaction of cognitive and stimulus-response processes in the control of behavior", Neuroscience and Biobehavioral Reviews 22 (1998): 59--83
Mark Witkowski, "An Action-Selection Calculus", Adaptive Behavior 15 (2007): 73--97
D. Wolpert, Z. Ghahramani and M. Jordan, "An Internal Model for Sensorimotor Integration," Science 272 (1995): 1880--1882.
D. Wolpert and M. Kawato, "Multiple Paired Forward and Inverse Models for Motor Control," Neural Network 11 (1998): 1317--1329.
Florentin Wörgötter and Bernd Porr, "Temporal Sequence Learning, Prediction, and Control: A Review of Different Models and Their Relation to Biological Mechanisms", Neural Computation 17 (2005): 245--319

Notebooks

Neural Control of Action, Especially of Rapid Motor Sequences