Motor sequence learning-induced corticospinal plasticity is biased towards sensorimotor mu rhythm peak phases.

Motor cortical (M1) transcranial magnetic stimulation (TMS) increases corticospinal output and improves motor learning when delivered during sensorimotor mu rhythm trough but not peak phases, suggesting that mechanisms supporting motor learning may be most active during mu trough phases. If so, learning-related corticospinal plasticity should be most evident during mu trough phases. Healthy adults were assigned to either a sequence or control group. Participants in the sequence group practiced the implicit serial reaction time task (SRTT), which contained an embedded, repeating 12-item sequence. Participants in the control group practiced a version of the SRTT that contained no sequence. We measured mu phase-independent and phase-dependent MEP amplitudes using EEG-informed single-pulse TMS before, immediately, and 30 minutes after the SRTT in both groups. All participants performed a retention test one hour after SRTT acquisition. In both groups, mu phase-independent MEP amplitudes increased following SRTT acquisition, but the pattern of mu phase-dependent MEP amplitude increases after SRTT acquisition differed between groups. MEP amplitude changes from baseline to 30 minutes after SRTT acquisition more strongly differed across phases in the control relative to the sequence group, with the control group showing smaller increases in peak- than trough-specific MEPs. Contrary to our original hypothesis, results revealed that sequence learning recruits peak- rather than trough-specific neurophysiological mechanisms. Overall, these findings suggest that mu peak phases may provide protected time windows for motor memory consolidation and demonstrate the presence of a mu phase-dependent motor learning mechanism in the human brain. Significance statement: Recent work suggests that the neurophysiological mechanisms supporting motor learning may be most active during sensorimotor mu rhythm trough phases. Here, we evaluated this possibility by measuring mu phase-dependent corticospinal plasticity induced by motor sequence learning. Results provide first evidence that motor sequence learning produced corticospinal plasticity that was more pronounced during mu peak than trough phases, demonstrating the presence of a phase-dependent learning mechanism within the human motor system.

The balance of hippocampal and caudate network functional connectivity is associated with episodic memory performance and its decline across adulthood.

The hippocampal and caudate networks interact to support episodic memory, but the relationship between hippocampal and caudate connectivity strength and episodic memory is unclear. In general, cognition is optimally supported when connectivity within a functional network dominates connectivity from other networks. For example, episodic memory may be optimally supported when the hippocampal and caudate networks express this pattern of connectivity, consistent with research showing that the two networks are organized competitively. Alternatively, episodic memory may be optimally supported when connectivity in both networks is more balanced, consistent with fMRI reports showing cooperation between networks. Using cross-sectional behavioral and resting state fMRI data from a diverse sample (N = 347; Ages 18-85), I tested the hypothesis that reduced hippocampal and caudate network dominance would be associated with reduced episodic memory across individuals and age. Consistent with this hypothesis, lower caudate network dominance in bilateral thalamic regions was associated with worse episodic memory regardless of age. Age-related differences in caudate network dominance in the pallidum and putamen were also associated with worse episodic memory performance, but through their shared variance with age. I found no evidence that network dominance was related to processing speed or executive function, or that hippocampal network dominance was relate to episodic memory performance. These results show that ongoing biological dynamics between the hippocampal and caudate networks throughout adulthood are related to episodic memory performance and support a growing literature specifying the role of the caudate network in episodic memory.

A direct test of competitive versus cooperative episodic-procedural network dynamics in human memory.

Classical lesion studies led to a consensus that episodic and procedural memory arises from segregated networks identified with the hippocampus and the caudate nucleus, respectively. Neuroimaging studies, however, show that competitive and cooperative interactions occur between networks during memory tasks. Furthermore, causal experiments to manipulate connectivity between these networks have not been performed in humans. Although nodes common to both networks, such as the precuneus and ventrolateral thalamus, may mediate their interaction, there is no experimental evidence for this. We tested how network-targeted noninvasive brain stimulation affects episodic-procedural network interactions and how these network manipulations affect episodic and procedural memory in healthy young adults. Compared to control (vertex) stimulation, hippocampal network-targeted stimulation increased within-network functional connectivity and hippocampal connectivity with the caudate. It also increased episodic, relative to procedural, memory, and this persisted one week later. The differential effect on episodic versus procedural memory was associated with increased functional connectivity between the caudate, precuneus, and ventrolateral thalamus. These findings provide direct evidence of episodic-procedural network competition, mediated by regions common to both networks. Enhanced hippocampal network connectivity may boost episodic, but decrease procedural, memory by co-opting resources shared between networks.

Reproducing the effect of hippocampal network-targeted transcranial magnetic stimulation on episodic memory.

Repetitive transcranial magnetic stimulation (rTMS) targeted to the hippocampal network via the inferior parietal cortex (HN-Stim) can strengthen hippocampal-cortical connectivity and improve episodic memory, offering a potential clinical intervention. However, acceptance of this technique has been tempered by the infrequent reproduction of findings in rTMS research on cognitive processes. We tested the reproducibility of the HN-Stim effect on episodic memory in our laboratory using different procedures from those previously published. We tested episodic memory in 29 participants before, one day, and one week after, three consecutive days of 20 Hz HN-Stim. Participants received stimulation targeted to either the area of inferior parietal cortex maximally connected to the left anterior hippocampus (HN-Stim; N = 14) or the vertex (control; N = 15), where we expected no effect. HN-Stim increased episodic memory performance one day, but not one week, after the last stimulation session. While failing to reproduce the lasting beneficial effect on memory found by others after five days of treatment, we found robust effects on behavior 24 h after treatment. HN-Stim is a safe and reliable means of enhancing episodic memory and may have potential for boosting learning and treating memory deficits.

Simultaneous training on overlapping grapheme phoneme correspondences augments learning and retention.

An important component of learning to read is the acquisition of letter-to-sound mappings. The sheer quantity of mappings and many exceptions in opaque languages such as English suggests that children may use a form of statistical learning to acquire them. However, whereas statistical models of reading are item-based, reading instruction typically focuses on rule-based approaches involving small sets of regularities. This discrepancy poses the question of how different groupings of regularities, an unexamined factor of most reading curricula, may affect learning. Exploring the interplay between item statistics and rules, this study investigated how consonant variability, an item-level factor, and the degree of overlap among the to-be-trained vowel strings, a group-level factor, influence learning. English-speaking first graders (N = 361) were randomly assigned to be trained on vowel sets with high overlap (e.g., EA, AI) or low overlap (e.g., EE, AI); this was crossed with a manipulation of consonant frame variability. Whereas high vowel overlap led to poorer initial performance, it resulted in more learning when tested immediately and after a 2-week-delay. There was little beneficial effect of consonant variability. These findings indicate that online letter/sound processing affects how new knowledge is integrated into existing information. Moreover, they suggest that vowel overlap should be considered when designing reading curricula.