Here are some articles that caught our attention this week.

Enjoy!
—Paul, Andrew & Jörn


1

Relationship between cardiac cycle and the timing of actions during action execution and observation
Palser, E.R. (@EleanorPalser), Glass, J., Fotopoulou, A. (@Katlab_UCL), and Kilner, J.M. (@JamesKilner)
bioRxiv, 585414 (2019)
https://www.biorxiv.org/content/10.1101/585414v1

There has been a lot of work recently on the cardiac cycle, the autonomic nervous system and cognitive functions like memory and perception. Here Eleanor Palser and colleagues investigate the role of the cardiac cycle in self-paced voluntary movement and discover two intriguing patterns. First, people tended to finish arm movements in between heartbeats. Second, during action observation, heartbeats of the observers were less likely to occur at the time when the person being observed finished their movement. Also see the tweet thread about the paper.


2

Keep your hands apart: independent representations of ipsilateral and contralateral forelimbs in primary motor cortex
Heming, E.A., Cross, K.P. (@K_P_Cross), Takei, T., Cook, D.J., and Scott, S.H. (@ScottLIMBlab)
bioRxiv, 587378 (2019) https://www.biorxiv.org/content/10.1101/587378v1

Motor cortex signals corresponding to the two arms are shared across hemispheres, mixed among neurons, yet partitioned within the population response
Ames, K.C., and Churchland, M.M.
bioRxiv, 552257 (2019)
https://www.biorxiv.org/content/10.1101/552257v1

We have known for a long time that voluntary arm movements are associated with neural activity in both ipsilateral and contralateral motor cortices. So why doesn’t ispilateral neural activity drive motor output in the contralateral limb? When both hemispheres are activated, how does the sensorimotor system avoid moving the wrong arm? Here are two papers that address these questions and more, using electrophysiology to test how the left and right upper limbs are represented in the left and right hemispheres of primary motor cortex of monkeys.


3

Rapid target foraging with reach or gaze: The hand looks further ahead than the eye
Diamond, J.S., Wolpert, D.M. (@DMWolpert), and Flanagan, J.R.
PLoS Comput. Biol. 13, e1005504 (2017)
https://dx.doi.org/10.1371/journal.pcbi.1005504

Yoon, T., Geary, R.B., Ahmed, A.A. (@AlayaAAhmed), and Shadmehr, R. (@reziliusReza) Control of movement vigor and decision making during foraging
Proc. Natl. Acad. Sci. U.S.A. (2018)
https://dx.doi.org/10.1073/pnas.1812979115

These two studies from different laboratories both use an arm movement “foraging” task to investigate how factors such as movement cost, reward, target size and marginal value affect how human participants “harvest” rewarded objects using their upper limbs in a virtual visual environment.


4

Common statistical tests are linear models (or: how to teach stats)
Jonas Kristoffer Lindeløv (@jonaslindeloev)
https://lindeloev.github.io/tests-as-linear/

This is a really cool blog post from Jonas Kristoffer Lindeløv in which he lays out for us how many common parametric and non-parametric statistical tests can be formulated as variants of a linear model. Jonas includes sample R code throughout, and he finisheds with a section in which he suggests how this approach might be incorporated into teaching materials, including ideas about a course outline. It’s worth a read. Also see the tweet thread.


5

Scaling of sensorimotor delays in terrestrial mammals.
More, H.L., and Donelan, J.M. (@maxdonelan)
Proc. R. Soc. B 285, 20180613 (2018)
https://doi.org/10.1098/rspb.2018.0613

This is a really cool paper from 2018 detailing the challenges faced by the sensorimotor system in dealing with sensory delays in animals ranging in size from shrews to elephants. They characterize the relationship between animal mass and reflex delays (it’s a power law relationship). They also describe how various contributors to reflex relays, (sensing delays, nerve conduction delays, synaptic delays, neuromuscular junction delays, electromechanical delays, and force generation delays) vary in their relative influence with animal size. Also see the tweet thread.


6

Motor Learning
Krakauer, J.W. (@blamlab), Hadjiosif, A.M., Xu, J., Wong, A.L. (@WongAaronL), and Haith, A.M. (@adrianhaith)
Compr. Physiol. 9, 613–663 (2019)
https://dx.doi.org/10.1002/cphy.c170043


7

Current models of speech motor control: A control-theoretic overview of architectures and properties.
Parrell, B. (@parrell), Lammert, A.C., Ciccarelli, G., and Quatieri, T.F.
The Journal of the Acoustical Society of America 145, 1456–1481. (2019)
http://dx.doi.org/10.1121/1.5092807

tweet thread


8

StretchfMRI: a new technique to quantify the contribution of the reticular formation to long-latency responses via fMRI
Zonnino, A., Farrens, A.J., Ress, D., and Sergi, F.
bioRxiv, 582692 (2019)
https://www.biorxiv.org/content/10.1101/582692v1

Also see the tweet thread.


9

Shared Cortex-Cerebellum Dynamics in the Execution and Learning of a Motor Task
Wagner, M.J., Kim, T.H., Kadmon, J., Nguyen, N.D., Ganguli, S., Schnitzer, M.J., and Luo, L.
Cell (2019)
https://www.cell.com/article/S0092867419301680/abstract


10

When Does One Decide How Heavy an Object Feels While Picking It Up?
Plaisier, M.A., Kuling, I.A., Brenner, E., and Smeets, J.B.J. (@JBJSmeets)
Psychol. Sci., 0956797619837981 (2019)
https://dx.doi.org/10.1177/0956797619837981

tweet thread



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Disclaimer

Please keep in mind that the appearance of a paper on our reading list should not necessarily be considered an endorsement of the work unless of course we explicitly endorse it, for example in a blurb. These are just papers that have caught our attention this week. As always, please read papers with a critical eye.