Combined adaptiveness of specific motor cortical ensembles underlies learning.
Learning motor skills entails adaptation of neural computations that can generate or modify associations between sensations and actions. Indeed, humans can use different strategies when adapting to dynamic loads depending on available sensory feedback. Here, we examined how neural activity in motor cortex was modified when monkeys made arm reaches to a visual target and locally adapted to curl force field with or without visual trajectory feedback. We found that firing rates of a large subpopulation of cells were consistently modulated depending on the distance of their preferred direction from the learned movement direction. The newly acquired activity followed a cosine-like function, with maximal increase in directions that opposed the perturbing force and decrease in opposite directions. As a result, the combined neuronal activity generated an adapted population vector. The results suggest that this could be achieved without changing the tuning properties of the cells. This population directional signal was however altered in the absence of visual feedback; while the cosine pattern of modulation was maintained, the population distributions of modulated cells differed across feedback consistent with the different trajectory shapes. Finally, we predicted generalization patterns of force-field learning based on the cosine-like modulation. These conformed to reported features of generalization in humans, suggesting that the generalization function was related to the observed rate modulations in the motor cortex. Overall, the findings suggest that the new combined activation of neuronal ensembles could underlie the change in the internal model of movement dynamics in a way that depends on available sensory feedback and chosen strategy.
Arce
Fritzie
F
Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, Hadassah Medical School, Hadassah University Hospital, Jerusalem 91120, Israel. fritziea@ekmd.huji.ac.il
Novick
Itai
I
Mandelblat-Cerf
Yael
Y
Israel
Zvi
Z
Ghez
Claude
C
Vaadia
Eilon
E
D000200:Action Potentials; D000223:Adaptation, Psychological / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D001132:Arm / Q000502:physiology; D030141:Feedback, Psychological / Q000502:physiology*; D007858:Learning / Q000502:physiology*; D008252:Macaca fascicularis; D008959:Models, Neurological; D009044:Motor Cortex / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology; D009434:Neural Pathways / Q000502:physiology; D009473:Neuronal Plasticity; D009474:Neurons / Q000502:physiology*; D009483:Neuropsychological Tests; D011597:Psychomotor Performance / Q000502:physiology; D014796:Visual Perception / Q000502:physiology*
Eur J Neurosci. 2007 Aug;26(4):1055-66
17714196
Curr Opin Neurobiol. 1999 Dec;9(6):718-27
10607637
Science. 1992 Mar 20;255(5051):1517-23
1549781
Neuron. 2003 Jan 23;37(2):347-59
12546828
Exp Brain Res. 1996 Jun;109(3):367-76
8817266
J Neurosci. 1988 Aug;8(8):2928-37
3411362
Nat Neurosci. 2004 Sep;7(9):907-15
15332089
Nature. 2000 Oct 12;407(6805):742-7
11048720
J Neurophysiol. 1995 Feb;73(2):836-54
7760138
Neural Netw. 2009 Nov;22(9):1203-13
19502004
J Neurophysiol. 1968 Jan;31(1):14-27
4966614
Nat Rev Neurosci. 2000 Nov;1(2):125-32
11252775
J Neurosci. 1989 Jun;9(6):2080-102
2723767
Neuroscience. 1991;44(3):521-35
1754050
J Neurosci. 2002 Nov 15;22(22):9656-60
12427820
J Neurosci. 1982 Nov;2(11):1527-37
7143039
Proc Natl Acad Sci U S A. 2008 Dec 9;105(49):19486-91
19047633
J Neurosci. 2000 Oct 15;20(20):7807-15
11027245
J Neurophysiol. 2007 Dec;98(6):3600-13
17913996
J Neurosci. 2004 Sep 29;24(39):8551-61
15456829
J Neurosci. 1990 Jul;10(7):2039-58
2376768
J Neurosci. 1994 May;14(5 Pt 2):3208-24
8182467
Nature. 2002 Jun 27;417(6892):938-41
12087402
J Neurosci. 2007 May 9;27(19):5105-14
17494696
Exp Brain Res. 1998 Aug;121(3):285-99
9746135
J Neurophysiol. 2007 Dec;98(6):3321-9
17928561
Nature. 2004 Oct 14;431(7010):768-74
15483597
Curr Opin Neurobiol. 2003 Apr;13(2):225-31
12744978
Nat Neurosci. 2006 Nov;9(11):1404-11
17028585
J Neurophysiol. 1995 Jan;73(1):361-72
7714578
PLoS One. 2009;4(1):e4214
19148302
J Neurosci. 1997 Jan 1;17(1):409-19
8987766
Neural Netw. 2009 Nov;22(9):1224-34
19525091
Proc Natl Acad Sci U S A. 2000 Feb 29;97(5):2259-63
10681435
J Neurophysiol. 1993 Nov;70(5):2097-116
8294972
J Neurophysiol. 2001 Jun;85(6):2576-89
11387402
J Neurophysiol. 1992 Aug;68(2):528-41
1527573
Science. 1991 Jul 19;253(5017):287-91
1857964
Cold Spring Harb Symp Quant Biol. 1990;55:899-910
2132866
Nat Neurosci. 2005 Apr;8(4):498-504
15768037
J Neurosci. 2003 Oct 8;23(27):9032-45
14534237
Science. 1999 Sep 24;285(5436):2136-9
10497133
Eur J Neurosci. 1999 Dec;11(12):4433-45
10594670
Science. 2004 Jan 16;303(5656):380-3
14726593
Neuron. 2001 May;30(2):593-607
11395017
Proc Natl Acad Sci U S A. 1994 Aug 2;91(16):7534-8
8052615
J Neurosci. 1988 Aug;8(8):2913-27
3411361
J Neurophysiol. 2003 Jan;89(1):168-76
12522169
Nat Neurosci. 2000 Nov;3 Suppl:1192-8
11127837
Nat Rev Neurosci. 2004 Jul;5(7):532-46
15208695
Cereb Cortex. 1994 Nov-Dec;4(6):590-600
7703686
Proc Natl Acad Sci U S A. 2006 Feb 21;103(8):2909-14
16473936
Proc Natl Acad Sci U S A. 1996 Apr 30;93(9):3843-6
8632977
J Neurophysiol. 1999 Nov;82(5):2676-92
10561437
Trends Neurosci. 2004 Aug;27(8):496-503
15271498
Exp Brain Res. 2006 Jan;168(1-2):106-19
16177830
Nat Neurosci. 2003 Aug;6(8):882-90
12872127
J Neurosci. 2004 Oct 6;24(40):8662-71
15470131
Curr Opin Neurobiol. 2008 Dec;18(6):573-81
19054663