Presupplementary motor area activation during sequence learning reflects visuo-motor association (original) (raw)
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Journal of neurophysiology, 1996
1. Using functional magnetic resonance imaging, we investigated the neural correlates of sequential procedural learning. During the test scans the subjects learned a new sequence (position or color) of button presses; during the control scans they pressed the buttons in any order. The comparison of the test and control scans was expected to reveal the neural activities related to learning, not sensory-motor processes. 2. We found that a localized area in what we regard to be the human homologue of the presupplementary motor area (pre-SMA) was particularly active for learning of new sequential procedures (either position or color sequences), not movements per se. 3. In contrast, the SMA proper (posterior to pre-SMA) was active for the performance of sequential movements, not learning. This was shown in another paradigm in which the subjects pressed the buttons in any order in the test scans and just watched the sequence in the control scans. 4. The learning-related pre-SMA region, wh...
Transition of brain activation from frontal to parietal areas in visuomotor sequence learning
The Journal of neuroscience : the official journal of the Society for Neuroscience, 1998
We studied the neural correlates of visuomotor sequence learning using functional magnetic resonance imaging (fMRI). In the test condition, subjects learned, by trial and error, the correct order of pressing two buttons consecutively for 10 pairs of buttons (2 x 10 task); in the control condition, they pressed buttons in any order. Comparison between the test condition and the control condition revealed four brain areas specifically related to learning: the dorsolateral prefrontal cortex (DLPFC), the presupplementary motor area (pre-SMA), the precuneus, and the intraparietal sulcus (IPS). We found that the time course of activation during learning was different between these areas. To normalize the individual differences in the speed of learning, we classified the performance of each subject into three learning stages: early, intermediate, and advanced stages. Both the relative increase of signal intensity and the number of activated pixels within the four areas showed significant c...
A visuo-motor sequence can be learned as a series of visuo-spatial cues or as a sequence of effector movements. Earlier imaging studies have revealed that a network of brain areas is activated in the course of motor sequence learning. However, these studies do not address the question of the type of representation being established at various stages of visuo-motor sequence learning. In an earlier behavioral study, we demonstrated that acquisition of visuo-spatial sequence representation enables rapid learning in the early stage and progressive establishment of somato-motor representation helps speedier execution by the late stage.We conducted functional magnetic resonance imaging (fMRI) experiments wherein subjects learned and practiced the same sequence alternately in normal and rotated settings. In one rotated setting (visual), subjects learned a new motor sequence in response to an identical sequence of visual cues as in normal. In another rotated setting (motor), the display sequence was altered as compared to normal, but the same sequence of effector movements was used to perform the sequence. Comparison of different rotated settings revealed analogous transitions both in the cortical and subcortical sites during visuo-motor sequence learning—a transition of activity from parietal to parietal–premotor and then to premotor cortex and a concomitant shift was observed from anterior putamen to a combined activity in both anterior and posterior putamen and finally to posterior putamen. These results suggest a putative role for engagement of different cortical and subcortical networks at various stages of learning in supporting distinct sequence representations. Keywords: Sequence representation; Anterior striatum; Posterior striatum; DLPFC; Pre-SMA; SMA
Prefrontal lesions impair the implicit and explicit learning of sequences on visuomotor tasks
Experimental Brain Research, 2002
Objective: (1) To verify whether the prefrontal cortex (PFC) is specifically involved in visuomotor sequence learning as opposed to other forms of motor learning and (2) to establish the role of executive functions in visuomotor sequence learning. Background: Visuomotor skill learning depends on the integrity of the premotor and parietal cortex; the prefrontal cortex, however, is essential when the learning of a sequence is required. Methods: We studied 25 patients with PFC lesions and 86 controls matched for age and educational level. Participants performed: (1) a Pursuit Tracking Task (PTT), composed of a random tracking task (perceptual learning) and a pattern tracking task (explicit motor sequence learning with learning indicated by the decrease in mean root square error across trial blocks), (2) a 12-item sequence version of a serial reaction time task (SRTT) with specific implicit motor sequence learning indicated by the rebound increase in response time when comparing the last sequence block with the next random block, and (3) a neuropsychological battery that assessed executive functions. Results: PFC patients were impaired in sequence learning on the pattern tracking task of the PTT and on the SRTT as compared to controls, but performed normally on the PTT random tracking task. Learning on the PTT did not correlate with learning on the SRTT. PTT performance correlated with planning functions while SRTT performance correlated with working memory capacity. Conclusions: The PFC is specifically involved in explicit and implicit motor sequence learning. Different PFC regions may be selectively involved in such learning depending on the cognitive demands of the sequential task.
Neural Substrates of Response-based Sequence Learning using fMRI
Journal of Cognitive Neuroscience, 2004
& Representation of sequential structure can occur with respect to the order of perceptual events or the order in which actions are linked. Neural correlates of sequence retrieval associated with the order of motor responses were identified in a variant of the serial reaction time task in which training occurred with a spatially incompatible mapping between stimuli and finger responses. After transfer to a spatially compatible version of the task, performance enhancements indicative of learning were only present in subjects required to make finger movements in the same order used during training. In contrast, a second group of subjects performed the compatible task using an identical sequence of stimuli (and different order of finger movements) as in training. They demonstrated no performance benefit, indicating that learning was response based. Analysis was restricted to subjects demonstrating low recall of the sequence structure to rule out effects of explicit awareness. The interaction of group (motor vs. perceptual transfer) with sequence retrieval (sequencing vs. rest) revealed significantly greater activation in the bilateral supplementary motor area, cingulate motor area, ventral premotor cortex, left caudate and inferior parietal lobule for subjects in the motor group (illustrating successful sequence retrieval at the response level). Retrieval of sequential responses occurs within mesial motor areas and related motor planning areas. &
Dynamic cortical involvement in implicit and explicit motor sequence learning. A PET study
Brain, 1998
We examined the dynamic involvement of different brain regions in implicit and explicit motor sequence learning using PET. In a serial reaction time task, subjects pressed each of four buttons with a different finger of the right hand in response to a visually presented number. Test sessions consisted of 10 cycles of the same 10-item sequence. The effects of explicit and implicit learning were assessed separately using a different behavioural parameter for each type of learning: correct recall of the test sequence for explicit learning and improvement of reaction time before the successful recall of any component of the test sequence for implicit learning. Regional cerebral blood flow was measured repeatedly during the task, and a parametric analysis was performed to identify brain regions in which activity was significantly correlated with subjects' performances: i.e. with correct recall of the test sequence or with reaction time. Explicit learning, shown as a positive correlation with the correct recall of the sequence, was associated with increased activity in Abbreviations: PRE ϭ training block; rCBF ϭ regional CBF; RND ϭ random condition block; SEQ ϭ sequence condition block; SMA ϭ supplementary motor area; SM1 ϭ primary sensorimotor cortex; SRTT ϭ serial reaction time task; VIS ϭ visual control condition block © Oxford University Press 1998 the posterior parietal cortex, precuneus and premotor cortex bilaterally, also in the supplementary motor area (SMA) predominantly in the left anterior part, left thalamus, and right dorsolateral prefrontal cortex. In contrast, the reaction time showed a different pattern of correlation during different learning phases. During the implicit learning phase, when the subjects were not aware of the sequence, improvement of the reaction time was associated with increased activity in the contralateral primary sensorimotor cortex (SM1). During the explicit learning phase, the reaction time was significantly correlated with activity in a part of the frontoparietal network. During the post-learning phase, when the subjects achieved all components of the sequence explicitly, the reaction time was correlated with the activity in the ipsilateral SM1 and posterior part of the SMA. These results show that different sets of cortical regions are dynamically involved in implicit and explicit motor sequence learning.
An fMRI Study of the Role of the Medial Temporal Lobe in Implicit and Explicit Sequence Learning
Neuron, 2003
and Brain longer-term, explicit episodic retrieval of longer se-Department of Psychology quences, memory accounts implicate the MTL (Squire Boston University and Zola-Morgan, 1991). For implicit sequence learning, Boston, Massachusetts 02215 both frameworks implicate the striatum. While motor 2 MGH-NMR Center models also include the supplementary motor area Department of Radiology (SMA), parietal lobe, and cerebellum (Willingham, 1998; Harvard Medical School Middleton and Strick, 2000), some memory accounts Charlestown, Massachusetts 02129 implicate MTL structures in certain types of implicit learning (Curran, 1997; Cohen and Eichenbaum, 1993). We used fMRI to investigate the role of the human Summary MTL in implicit and explicit sequence learning. fMRI data were acquired while subjects performed a serial reaction fMRI was used to investigate the neural substrates time task (SRTT; Figure 1A), developed originally by Nissupporting implicit and explicit sequence learning, fosen and Bullemer (1987). In the SRTT, learning results in cusing especially upon the role of the medial temporal faster response times (RTs) for repeated than for random lobe. Participants performed a serial reaction time sequences of cued locations. task (SRTT). For implicit learning, they were naive For implicit SRTT learning, convergent evidence impliabout a repeating pattern, whereas for explicit learncates subcortical and cortical components of frontostriing, participants memorized another repeating seatal pathways. Patients with striatal dysfunction are imquence. fMRI analyses comparing repeating versus paired on implicit SRTTs (Knopman and Nissen, 1991; random sequence blocks demonstrated activation of Vakil et al., 2000; Jackson et al., 1995; Doyon et al., 1997, frontal, parietal, cingulate, and striatal regions impli-1998). Neuroimaging studies using an implicit SRTT with cated in previous SRTT studies. Importantly, mediohealthy adults have shown activation in the caudate, temporal lobe regions were active in both explicit and putamen (Rauch et al., 1995, 1997a; Hazeltine et al., implicit SRTT learning. Moreover, the results provide 1997; Grafton et al., 1995; Willingham et al., 2002; Peigevidence of a role for the hippocampus and related neux et al., 2000) and ventral striatum (Berns et al., 1997; cortices in the formation of higher order associations Doyon et al., 1996). The caudate has been proposed to under both implicit and explicit learning conditions, be important for stimulus-response association (Polregardless of conscious awareness of sequence drack et al., 2001) and cognitive abilities, such as workknowledge. ing memory (Owen et al., 1998). Activation has also been found in cortical components of frontostriatal circuits, Introduction including the DLPFC, parietal lobe, premotor cortex, anterior cingulate, and SMA (Rauch et al., 1995, 1997b; Sequence learning is used for behaviors like typing, mu-Berns et al., 1997; Grafton et al., 1995, 1998; Hazeltine sical performance, and route navigation. Researchers et al., 1997; Willingham et al., 2002; Peigneux et al., have described the acquisition of perceptuomotor se-2000). quencing skills using either motor control (e.g., Hazeltine For explicit SRTT learning, while striatal activation has et al., 1997) or learning and memory frameworks (e.g., rarely been noted, neuroimaging studies consistently Reber and Squire, 1998). Both explanations agree that find activation in cortical components of frontostriatal distinct brain processes support explicit learning, which circuits, including the DLPFC, ventrolateral prefrontal, occurs with awareness, and implicit learning, which ocpremotor, anterior cingulate, and dorsal and inferior pacurs without awareness. However, the two accounts rietal cortices (Hazeltine et al., 1997; Jenkins et al., 1994; diverge over which brain systems are important. Most Grafton et al., 1995; Rauch et al., 1995; Willingham et critically, only memory frameworks posit a role for the al., 2002). Motor accounts posit the DLPFC controls mediotemporal lobe (MTL) in sequence learning. strategic processes throughout the explicit SRTT, and For explicit sequence learning, both motor control and it can be recruited during an implicit SRTT, if participants memory accounts implicate the dorsolateral prefrontal become aware of a sequence (Willingham, 1998). This cortex (DLPFC). This region, by motor accounts, supidea resembles an explicit-implicit variety of memory ports conscious executive motor control to select goals account but with the DLPFC, not MTL, being necessary or to select and maintain a spatial sequence in working for conscious sequence acquisition. memory (Willingham, 1998; Grafton et al., 1995; Ha-Memory, but not motor, accounts consider the MTL zeltine et al., 1997) or, by memory accounts, supports system to be necessary for learning sequences, espethe manipulation and monitoring functions of working cially those beyond the capacity of DLPFC processes memory (Smith and Jonides, 1999). Memory models, of working memory. Each account, however, posits a however, also posit that the role of the DLPFC is limited somewhat different role for MTL. For explicit learning, explicit-implicit (or declarative-nondeclarative) memory accounts state that the MTL is necessary for long-term
The Time Course of Changes during Motor Sequence Learning: A Whole-Brain fMRI Study
NeuroImage, 1998
There is a discrepancy between the results of imaging studies in which subjects learn motor sequences. Some experiments have shown decreases in the activation of some areas as learning increased, whereas others have reported learning-related increases as learning progressed. We have exploited fMRI to measure changes in blood oxygen level-dependent (BOLD) signal throughout the course of learning. T2*-weighted echo-planar images were acquired over the whole brain for 40 min while the subjects learned a sequence eight moves long by trial and error. The movements were visually paced every 3.2 s and visual feedback was provided to the subjects. A baseline period followed each activation period. The effect due to the experimental conditions was modeled using a squarewave function, time locked to their occurrence. Changes over time in the difference between activation and baseline signal were modeled using a set of polynomial basis functions. This allowed us to take into account linear as well as nonlinear changes over time. Low-frequency changes over time common to both activation and baseline conditions (and thus not learning related) were modeled and removed. Linear and nonlinear changes of BOLD signal over time were found in prefrontal, premotor, and parietal cortex and in neostriatal and cerebellar areas. Single-unit recordings in nonhuman primates during the learning of motor tasks have clearly shown increased activity early in learning, followed by a decrease as learning progressed. Both phenomena can be observed at the population level in the present study. 1998 Academic Press
2002
that in humans and animals supports behaviors based on reward and reinforcement (Apicella et al., 1991; Delgado et al., 2000; Schultz et al., 1992) and that mediates the acquisition of motor action plans (Doyon et al.; Shidara et al., 1998). In addition, both VS and 75005 Paris AMPC are important projection sites of dopaminergic France neurons that are known to implement motivational and 2 Cognitive Neuroscience Section reinforcement mechanisms (Lewis et al., 1988; Robbins NINDS and Everitt, 1996; Schultz, 1997). Bethesda, Maryland 20892