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The neural correlates of memory formation in humans have long been investigated by exposing subjects to diverse material and comparing responses to items later remembered to those forgotten. Tasks requiring memorization of sensory sequences afford unique possibilities for linking neural memorization processes to behavior, because, rather than comparing across different items of varying content, each individual item can be examined across the successive learning states of being initially unknown, newly learned, and eventually, fully known. Sequence learning paradigms have not yet been exploited in this way, however. Here, we analyze the event-related potentials of subjects attempting to memorize sequences of visual locations over several blocks of repeated observation, with respect to pre- and post-block recall tests. Over centro-parietal regions, we observed a rapid P300 component superimposed on a broader positivity, which exhibited distinct modulations across learning states that were replicated in two separate experiments. Consistent with its well-known encoding of surprise, the P300 deflection monotonically decreased over blocks as locations became better learned and hence more expected. In contrast, the broader positivity was especially elevated at the point when a given item was newly learned, i.e., started being successfully recalled. These results implicate the Broad Positivity in endogenously-driven, intentional memory formation, whereas the P300, in processing the current stimulus to the degree that it was previously uncertain, indexes the cumulative knowledge thereby gained. The decreasing surprise/P300 effect significantly predicted learning success both across blocks and across subjects. This presents a new, neural-based means to evaluate learning capabilities independent of verbal reports, which could have considerable value in distinguishing genuine learning disabilities from difficulties to communicate the outcomes of learning, or perceptual impairments, in a range of clinical brain disorders.

Recently we found that modulation depth of beta power during movement increases with practice over sensory-motor areas in normal subjects but not in patients with Parkinson’s disease (PD). As such changes might reflect use-dependent modifications, we concluded that reduction of beta enhancement in PD represents saturation of cortical plasticity. A few questions remained open: What is the relation between these EEG changes and retention of motor skills? Would a second task exposure restore beta modulation enhancement in PD? Do practice-induced increases of beta modulation occur within each block? We thus recorded EEG in patients with PD and age-matched controls in two consecutive days during a forty-minute reaching task divided in fifteen blocks of 56 movements each. The results confirmed that, with practice, beta modulation depth over the contralateral sensory-motor area significantly increased across blocks in controls but not in PD, while performance improved in both groups without significant correlations between behavioral and EEG data. The same changes were seen the following day in both groups. Also, beta modulation increased within each block with similar values in both groups and such increases were partially transferred to the successive block in controls, but not in PD. Retention of performance improvement was present in the controls but not in the patients and correlated with the increase in day 1 modulation depth. Therefore, the lack of practice-related increase beta modulation in PD is likely due to deficient potentiation mechanisms that permit between-block saving of beta power enhancement and trigger mechanisms of memory formation.

Adapting movements to a visual rotation involves the activation of right posterior parietal areas. Further performance improvement requires an increase of slow wave activity in subsequent sleep in the same areas. Here we ascertained whether a post-learning trace is present in wake EEG and whether such a trace is influenced by sleep slow waves.In two separate sessions, we recorded high-density EEG in 17 healthy subjects before and after a visuomotor rotation task, which was performed both before and after sleep. High-density EEG was recorded also during sleep. One session aimed to suppress sleep slow waves, while the other session served as a control.After learning, we found a trace in the eyes-open wake EEG as a local, parietal decrease in alpha power. After the control night, this trace returned to baseline levels, but it failed to do so after slow wave deprivation. The overnight change of the trace correlated with the dissipation of low frequency (8 Hz) NREM sleep activity only in the control session.Visuomotor learning leaves a trace in the wake EEG alpha power that appears to be renormalized by sleep slow waves.These findings link visuomotor learning to regional changes in wake EEG and sleep homeostasis.

To determine whether the process involved in movement preparation of patients in the early stages of Parkinson's disease (PD) shares attentional resources with visual learning, we tested 23 patients with PD and 13 normal controls with two different tasks. The first was a motor task where subjects were required to move as soon as possible to randomly presented targets by minimizing reaction time. The second was a visual learning task where targets were presented in a preset order and subjects were asked to learn the sequence order by attending to the display without moving. PD patients showed higher reaction and movement times, while visual learning was reduced compared to controls. For PD patients, reaction times, but not movement times, displayed an inverse significant correlation with the scores of visual learning. We conclude that visual declarative learning and movement preparation might share similar attentional and working memory resources.

Recent EEG studies have shown that implicit learning involving specific cortical circuits results in an enduring local trace manifested as local changes in spectral power. Here we used a well characterized visual sequence learning task and high density-(hd-)EEG recording to determine whether also declarative learning leaves a post-task, local change in the resting state oscillatory activity in the areas involved in the learning process. Thus, we recorded hd-EEG in normal subjects before, during and after the acquisition of the order of a fixed spatial target sequence (VSEQ) and during the presentation of targets in random order (VRAN). We first determined the temporal evolution of spectral changes during VSEQ and compared it to VRAN. We found significant differences in the alpha and theta bands in three main scalp regions, a right occipito-parietal (ROP), an anterior-frontal (AFr), and a right frontal (RFr) area. The changes in frontal theta power during VSEQ were positively correlated with the learning rate. Further, post-learning EEG recordings during resting state revealed a significant increase in alpha power in ROP relative to a pre-learning baseline. We conclude that declarative learning is associated with alpha and theta changes in frontal and posterior regions that occur during the task, and with an increase of alpha power in the occipito-parietal region after the task. These post-task changes may represent a trace of learning and a hallmark of use-dependent plasticity.

Learning deficits may be part of the early symptoms of Huntington's disease (HD). Here we characterized implicit and explicit aspects of sequence learning in eleven pre-symptomatic HD gene carriers (pHD) and eleven normal controls. Subjects moved a cursor on a digitizing tablet and performed the following tasks: SEQ: learning to anticipate the appearance of a target sequence in two blocks; VSEQ: learning a sequence by attending to the display without moving for one block, and by moving to the sequence in a successive block (VSEQtest). Explicit learning was measured with declarative scores and number of anticipatory movements. Implicit learning was measured as a strategy change reflected in movement time. By the end of SEQ, pHD had a significantly lower number of correct anticipatory movements and lower declarative scores than controls, while in VSEQ and VSEQtest these indices improved. During all three tasks, movement time changed in controls, but not in pHD. These results suggest that both explicit and implicit aspects of sequence learning may be impaired before the onset of motor symptoms. However, when attentional demands decrease, explicit, but not implicit, learning may improve.