A critical re-evaluation of fMRI signatures of motor sequence learning

Berlot, Eva; Popp, Nicola J.; Diedrichsen, Jörn

doi:10.1101/2020.01.08.899229

Cited by 13 publications

(33 citation statements)

References 79 publications

(123 reference statements)

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“…Previous work demonstrates that delay-period activity in the supplementary motor area (SMA) reflects the identity of upcoming two-element 61 and three-element 62 sequences. A similar segregation has also been found in human subjects performing a key-press task; while there is no evidence for sequence-specific selectivity in the M1 BOLD signal, such selectivity is present in upstream areas 16–18 . Using a cycling task, which shares some features with sequence tasks, Russo et al 63 found that M1 activity reflects only the present motor output while SMA activity distinguishes situations that will have different future outputs.…”

Section: Discussionsupporting

confidence: 72%

“…Or is chunking a motor skill, in which motor areas generate, holistically, actions that were originally generated separately? Studies of motor cortex report ‘sequence selectivity’: responses that reflect whether an action is performed alone or within a sequence 10–15 (although see 16–18 ). Sequence selectivity concurs with the hypothesis that chunking is a motor phenomenon, with chunks executed differently from their component elements.…”

Section: Introductionmentioning

confidence: 99%

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Generation of Rapid Sequences by Motor Cortex

Zimnik

Churchland

2020

Preprint

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1 Rapid execution of motor sequences is believed to depend upon the fusing of movement elements into 2 cohesive units that are executed holistically. We sought to determine the contribution of motor cortex 3 activity to this ability. Two monkeys performed highly practiced two-reach sequences, interleaved with 4 matched reaches performed alone or separated by a delay. We partitioned neural population activity 5 into components pertaining to preparation, initiation, and execution. The hypothesis that movement 6 elements fuse makes specific predictions regarding all three forms of activity. We observed none of 7 these predicted effects. Instead, two-reach sequences involved the same set of neural events as 8 individual reaches, but with a remarkable temporal compression: preparation for the second reach 9 occurred as the first was in flight. Thus, at the level of motor cortex, skillfully executing a rapid sequence 10 depends not on fusing elements, but on the ability to perform two computations at the same time. 65first reach and did so without disrupting the first reach. Thus, at the level of motor and premotor cortex, 66 skilled performance depends not on fusing elements, but upon the ability to prepare one element while 67 executing another. 68 Results 69Task and Behavior 70We trained two rhesus macaques (monkeys B and H) to perform a modified delayed-reach task ( Fig. 71 1a,b). All trials began with a randomized (0-1000 ms) instructed delay period. Each trial required the 72 monkey to make either a single reach, two reaches separated by an instructed pause (delayed double-73 reach), or two reaches with no pause between them (compound reach). Target color indicated which 74 should be acquired first. A salient visual cue (the diameter of the colored portion of the first target) 75 indicated whether a pause was required. For monkey H, the pause between delayed double-reaches was 76 always 600 ms. For monkey B it was variable (100, 300, or 600 ms; the last is used for most analyses) and 77 indicated by the visual cue. Thus, all key information -target locations and any instructed pause -was 78 given during the instructed delay. Reach paths are illustrated ( Fig. 1a) for all single reaches, for three 79 compound reaches that began down-and-right, and for three compound reaches that began down-and-80 left (Extended Data Fig. 1 shows paths for all compound reaches). 81Compound reaches were performed briskly; the hand stayed on the first target only briefly before 82 moving to the second target. Median dwell times on the first target were 119 ms (monkey B) and 137 83 ms (monkey H). The median duration for the full two-reach sequence was 561 ms (monkey B) and 645 84 ms (monkey H). This rapid pace resulted from extensive training over months, with each sequence 85 performed tens of thousands of times. This pace is even faster than that reported in other motor 86 sequence tasks performed by non-human primates, where dwell times are typically >200 ms 10,11,29 . 87To enable comparisons at the neural level, every compound r...

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Section: Discussionsupporting

confidence: 72%

Section: Introductionmentioning

confidence: 99%

Generation of Rapid Sequences by Motor Cortex

Zimnik

Churchland

2020

Preprint

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“…Given the nature of the exponential fit, it is hard to separate the relative contributions of planning efficiency (i.e., benefitting more from a specific window size) and larger horizons to such improvements. Unlike previous studies that examined sequence-specific effects in sequence production (Ariani and Diedrichsen, 2019; Berlot et al, 2020; Verwey, 2001; Verwey and Wright, 2004; Wiestler and Diedrichsen, 2013), here we focused on random sequences. Note that, because of this, the observed practice effects cannot be explained by the formation of specific chunking structures previously proposed as a way to deal with the complexity of planning long movement sequences (Popp et al, 2020; Ramkumar et al, 2016).…”

Section: Discussionmentioning

confidence: 99%

The planning horizon for movement sequences

Ariani

Kordjazi

Pruszynski

et al. 2020

Preprint

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When performing a long chain of actions in rapid sequence, future movements need to be planned concurrently with ongoing action. However, how far ahead we plan, and whether this ability improves with practice, is currently unknown. Here we designed an experiment in which healthy volunteers were asked to produce 14-item sequences of finger movements quickly and accurately on a keyboard in response to numerical stimuli. On every trial, participants were only shown a fixed number of stimuli ahead of the current keypress. The size of this viewing window varied between 1 (next digit revealed with the pressing of the current key) and 14 (full view of the sequence). Participants practiced the task for five days and their performance was continuously assessed on random sequences. Our results indicate that participants used the available visual information to plan multiple actions into the future, but that the planning horizon was limited: receiving more information than 3 movements ahead did not result in faster sequence production. Over the course of practice, we found larger performance improvements for larger viewing windows. Additionally, we show that improved planning was accompanied by an expansion of the planning horizon with practice. Together, these findings show that one important aspect of sequential motor skills is the ability of the motor system to exploit visual information for planning multiple responses into the future.

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“…They were instructed to perform the sequences as fast as possible while keeping the overall accuracy >85%. The details of the training protocol, as well as a few other design features (which were not assessed for this paper) have been described elsewhere (Berlot et al, 2020).…”

Section: Methodsmentioning

confidence: 99%

“…One prominent issue in this debate is whether skilled sequence execution relies on representations in premotor and supplementary motor areas, or whether the sequences are represented in the primary motor cortex (M1) (see Dayan and Cohen, 2011; Berlot et al, 2018 for reviews). We recently conducted a systematic longitudinal 5-week training study (Berlot et al, 2020) employing functional magnetic resonance imaging (fMRI) to assess brain changes with motor sequence learning. We observed no overall change in overall activity with learning in M1, and no changes in the sequence-specific activity patterns.…”

Section: Introductionmentioning

confidence: 99%

Combining repetition suppression and pattern analysis provides new insights into the role of M1 and parietal areas in skilled sequential actions

Berlot

Popp

Grafton

et al. 2020

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How does the brain change during learning? Functional magnetic resonance imaging studies have used both pattern analysis and repetition suppression (RS) to detect changes in neuronal representations. In the context of motor sequence learning, the two techniques have provided discrepant findings. Specifically, pattern analysis showed that only premotor and parietal regions, but not primary motor cortex (M1), develop a representation of trained sequences. In contrast, RS suggested trained sequence representations in all these regions. Here we applied both analysis techniques to data from a 5-week finger sequence training study, in which participants executed each sequence twice before switching to a different sequence. While we replicated both previously reported findings in the same paradigm, a more fine-grained analysis revealed that the RS effect in M1 and parietal areas reflect fundamentally different processes. On the first execution, M1 represents especially the first finger of each sequence, which might reflect preparatory processes, and this effect dramatically reduces during the second execution. In contrast, parietal areas represent the identity of a sequence, and this representation stays relatively stable on the second execution, only reducing proportionally to the reduction in overall activity. These results suggest that the RS effect in M1 does not reflect trained sequence representation, but rather the altered communication with higher-order areas. More generally, our study demonstrates that RS can reflect different representational changes in the underlying neuronal population code across regions, emphasizing the importance of combining pattern analysis and RS techniques.

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A critical re-evaluation of fMRI signatures of motor sequence learning

Cited by 13 publications

References 79 publications

Generation of Rapid Sequences by Motor Cortex

Generation of Rapid Sequences by Motor Cortex

The planning horizon for movement sequences

Combining repetition suppression and pattern analysis provides new insights into the role of M1 and parietal areas in skilled sequential actions

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