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The influence of sleep on motor skill consolidation has been a research topic of increasing interest. In this study, we distinguished general skill learning from sequence-specific learning in a probabilistic implicit sequence learning task (alternating serial reaction time) in young and old adults before and after a 12-h offline interval which did or did not contain sleep (p.m.-a.m. and a.m.-p.m. groups, respectively). The results showed that general skill learning, as assessed via overall reaction time, improved offline in both the young and older groups, with the young group improving more than the old. However, the improvement was not sleep-dependent, in that there was no difference between the a.m.-p.m. and p.m.-a.m. groups. We did not find sequence-specific offline improvement in either age group for the a.m.-either p.m. or p.m.-a.m. groups, suggesting that consolidation of this kind of implicit motor sequence learning may not be influenced by sleep.

Transcranial direct current stimulation (tDCS) transiently alters cortical excitability and synaptic plasticity. So far, few studies have investigated the behavioral effects of applying tDCS to the cerebellum. Given the cerebellum’s inhibitory effects on cortical motor areas as well as its role in fine motor control and motor coordination, we investigated whether cerebellar tDCS can modulate response selection processes and motor sequence learning. Seventy-two participants received either cerebellar anodal (excitatory), cathodal (inhibitory), or sham (placebo) tDCS while performing a serial reaction time task (SRTT). To compare acute and long-term effects of stimulation on behavioral performance, participants came back for follow-up testing at 24 h after stimulation. Results indicated no group differences in performance prior to tDCS. During stimulation, tDCS did not affect sequence-specific learning, but anodal as compared to cathodal and sham stimulations did modulate response selection processes. Specifically, anodal tDCS increased response latencies independent of whether a trained or transfer sequence was being performed, although this effect became smaller throughout training. At the 24-h follow-up, the group that previously received anodal tDCS again demonstrated increased response latencies, but only when the previously trained sequence and a transfer sequence had to be performed in the same experimental block. This increased behavioral interference tentatively points to a detrimental effect of anodal cerebellar tDCS on sequence consolidation/retention. These results are consistent with the notion that the cerebellum exerts an inhibitory effect on cortical motor areas, which can impair sequential response selection when this inhibition is strengthened by tDCS.

The present experiment was designed to enhance our understanding of how response effects with varying amounts of useful information influence implicit sequence learning. We recorded event-related brain potentials, while participants performed a modified version of the serial reaction time task (SRTT). In this task, participants have to press one of four keys corresponding to four letters on a computer screen. Unknown to participants, in some parts of the experimental blocks, the stimuli appear in a repetitive (structured) deterministic sequence, whereas in other parts, stimuli were determined randomly. Four groups of participants differing in the presentation of tones after each response performed the SRTT. In the no tone group, no tones were presented after a response. The other three groups differed with respect to the melody generated by the key presses: in the unmelodic group, one out of four different tones was chosen randomly and presented immediately after a response. In the consistent melody group, the press of a response key always resulted in the production of the same tone, resulting in a repetitive melody during structured parts of the sequence (consistent redundant effect). In the inconsistent melody group, the “melody” produced in the sequenced parts of the blocks was identical to the consistent melody group, but the same response could produce two different tones depending on the actual position in the stimulus sequence. Thus, during structured sequences, subjects heard the same melody as in the consistent melody group, but every key press could be followed by one out of two different tones. To disentangle effects of sequence awareness from our experimental manipulations, all analyses were restricted to implicit learners. All four groups showed sequence learning, but to a different degree: in general, every kind of tone improved sequence learning relative to the no tone group. However, unmelodic tones were less beneficial for learning than tones forming a melody. Tones mapped consistently to response keys improved learning faster than tones producing the same melody, but not mapped consistently to keys. However, at the end of the learning phase, the two melody groups did not differ in the amount of sequence learning. The error-related negativity (ERN) increased with sequence learning (larger ERN at the end of the experiment for trials following the sequence compared to random trials) and this effect was more pronounced for the groups that showed more learning. These findings indicate that response effects containing useful information foster sequence learning even if the same response can produce different effects. Furthermore, we replicated earlier results showing that the importance of an error with respect to the task at hand modulates the activity of the human performance monitoring system.

Functional activation patterns of an auditory working memory task were examined prior to and after 5 days of training (1 h/day). A control group with no training was scanned twice at the same intervals to assess test–retest effects. Based on behavioral improvement scores, the training group ( n = 14) was divided into “Strong-Learners (SL)” and “Weak-Learners (WL)”. No significant functional or structural brain differences were seen between the SL and WL groups prior to training. Imaging contrasts comparing post- with pre-training sessions showed a significant signal increase in the left Heschl's gyrus (HG) as well as in the left posterior superior temporal and supramarginal gyrus for the SL group, while the WL group showed significant signal increases in the left HG and anterior insular cortex as well as in a lingual–orbitofrontal–parahippocampal network. The test–retest analysis in the control group revealed only minimal signal increases in a right dorsolateral prefrontal region. A random effects analysis comparing the SL group with the WL group using the post- and pre-training contrast images showed increased activation only in the left supramarginal gyrus but not in HG. The importance of HG in pitch discrimination has been established in previous studies. The pitch memory component differentiated our task from a straight pitch discrimination task. It is most likely that the activation of the SMG reflects its importance in the short-term storage of auditory material, and it was this activation that best differentiated between subjects' levels of performance.

It is controversial whether or not old adults are capable of learning new motor skills and consolidate the performance gains into motor memory in the offline period. The underlying neuronal mechanisms are equally unclear. We determined the magnitude of motor learning and motor memory consolidation in healthy old adults and examined if specific metrics of neuronal excitability measured by magnetic brain stimulation mediate the practice and retention effects. Eleven healthy old adults practiced a wrist extension-flexion visuomotor skill for 20 min (MP, 71.3 years), while a second group only watched the templates without movements (attentional control, AC, n  = 11, 70.5 years). There was 40 % motor learning in MP but none in AC (interaction, p  < 0.001) with the skill retained 24 h later in MP and a 16 % improvement in AC. Corticospinal excitability at rest and during task did not change, but when measured during contraction at 20 % of maximal force, it strongly increased in MP and decreased in AC (interaction, p  = 0.002). Intracortical inhibition at rest and during the task decreased and facilitation at rest increased in MP, but these metrics changed in the opposite direction in AC. These neuronal changes were especially profound at retention. Healthy old adults can learn a new motor skill and consolidate the learned skill into motor memory, processes that are most likely mediated by disinhibitory mechanisms. These results are relevant for the increasing number of old adults who need to learn and relearn movements during motor rehabilitation.

Background Following practice of skilled movements, changes continue to take place in the brain that both strengthen and modify memory for motor learning. These changes represent motor memory consolidation a process whereby new memories are transformed from a fragile to a more permanent, robust and stable state. In the present study, the neural correlates of motor memory consolidation were probed using repetitive transcranial magnetic stimulation (rTMS) to the dorsal premotor cortex (PMd). Participants engaged in four days of continuous tracking practice that immediately followed either excitatory 5 HZ, inhibitory 1 HZ or control, sham rTMS. A delayed retention test assessed motor learning of repeated and random sequences of continuous movement; no rTMS was applied at retention. Results We discovered that 5 HZ excitatory rTMS to PMd stimulated motor memory consolidation as evidenced by off-line learning, whereas only memory stabilization was noted following 1 Hz inhibitory or sham stimulation. Conclusion Our data support the hypothesis that PMd is important for continuous motor learning, specifically via off-line consolidation of learned motor behaviors.

Sequence learning underlies numerous motor, cognitive, and social skills. Previous models and empirical investigations of sequence learning in humans and non-human animals have implicated cortico-basal ganglia-cerebellar circuitry as well as other structures. To systematically examine the functional neuroanatomy of sequence learning in humans, we conducted a series of neuroanatomical meta-analyses. We focused on the serial reaction time (SRT) task. This task, which is the most widely used paradigm for probing sequence learning in humans, allows for the rigorous control of visual, motor, and other factors. Controlling for these factors (in sequence-random block contrasts), sequence learning yielded consistent activation only in the basal ganglia, across the striatum (anterior/mid caudate nucleus and putamen) and the globus pallidus. In contrast, when visual, motor, and other factors were not controlled for (in a global analysis with all sequence-baseline contrasts, not just sequence-random contrasts), premotor cortical and cerebellar activation were additionally observed. The study provides solid evidence that, at least as tested with the visuo-motor SRT task, sequence learning in humans relies on the basal ganglia, whereas cerebellar and premotor regions appear to contribute to aspects of the task not related to sequence learning itself. The findings have both basic research and translational implications. •Using ALE, we synthesized the functional neuroanatomical data on sequence learning.•We focused on the widely used serial reaction time (SRT) task paradigm.•Sequence learning (sequence ​> ​random contrast) showed only basal ganglia activation.•This was found in the anterior/mid caudate and putamen, and in the globus pallidus.•Cerebellar/premotor activation was linked to other (visual/motor) SRT task factors.

Previous studies of motor learning have proposed a distinction betweenfast and slow learning, but these mechanisms have rarely been examined simultaneously. We examined the influence of long-term motor expertise (slow learning) while pianists and nonpianists performed alternating epochs of sequenced and random keypresses in response to visual cues (fast learning) during functional neuroimaging. All of the participants demonstrated learning of the sequence as demonstrated by decreasing reaction times (RTs) on sequence trials relative to random trials throughout the session. Pianists also demonstrated faster RTs and superior sequence acquisition in comparison with nonpianists. Within-session decreases in bilateral sensorimotor and parietal activation were observed for both groups. Additionally, there was more extensive activation throughout the session for pianists in comparison with nonpianists across a network of primarily right-lateralized prefrontal, sensorimotor, and parietal regions. These findings provide evidence that different neural systems subserve slow and fast phases of learning.

Here the authors report that repeated presentations of a visual sequence over a course of days causes evoked response potentiation in mouse V1 that is highly specific for stimulus order and timing. After V1 is trained to recognize a sequence, cortical activity regenerates the full sequence even when individual stimulus elements are omitted. Learning to recognize and predict temporal sequences is fundamental to sensory perception and is impaired in several neuropsychiatric disorders, but little is known about where and how this occurs in the brain. We discovered that repeated presentations of a visual sequence over a course of days resulted in evoked response potentiation in mouse V1 that was highly specific for stimulus order and timing. Notably, after V1 was trained to recognize a sequence, cortical activity regenerated the full sequence even when individual stimulus elements were omitted. Our results advance the understanding of how the brain makes 'intelligent guesses' on the basis of limited information to form visual percepts and suggest that it is possible to study the mechanistic basis of this high-level cognitive ability by studying low-level sensory systems.

In tasks that measure serial-order memory, it is common to observe a “fill-in tendency”—when a person skips an item, the next item they report is more likely to be the skipped item (a fill-in response) than the next list item (an infill response). They tend to “fill in” the blank they skipped. The fill-in tendency has informed the modeling of serial-order memory—it presents strong evidence against associative chaining accounts because they predict more infill responses than fill-in responses. Despite the failures of associative chaining theories, evidence grows for the use of chaining-like item-dependent cues in serial-order memory. In this paper, we analyzed fill-in and infill responses from nine serial learning experiments (one new experiment and eight previously published experiments) that used variants of the spin list procedure and found strong evidence of item-dependent retrieval cues in serial-order memory. The current analyses revealed a fill-in tendency in all lists—even in those in which item-dependent cues were suspected to have been used. However, in those lists the likelihood of infill responses was higher, and consequently, the fill-in tendency was weaker. Our results expose a flaw in the conventional understanding of fill-in and infill responses. That is, the presence (or absence) of the fill-in tendency is not a strong test of item-dependent cues. Instead, changes in the magnitude of the fill-in tendency—more specifically, an increase in the likelihood of infill responses—across task conditions seem to better indicate the use of item-dependent cues.