Hippocampal and striatal responses during motor learning are modulated by prefrontal cortex stimulation

Water-Soluble Lynx1 Upregulates Dendritic Spine Density and Stimulates Astrocytic Network and Signaling

Secreted and membrane-tethered mammalian neuromodulators from the Ly6/uPAR family are involved in regulation of many physiological processes. Some of them are expressed in the CNS in the neurons of different brain regions and target neuronal membrane receptors. Thus, Lynx1 potentiates nicotinic acetylcholine receptors (nAChRs) in the brain, while others like Lypd6 and Lypd6b suppress it. However, the mechanisms underlying the regulation of cognitive processes by these neuromodulators remain unclear. Here, we showed that water-soluble analogue of Lynx1 (ws-Lynx-1) targets α7-nAChRs both in the hippocampal neurons and astrocytes. Incubation of astrocytes with ws-Lynx1 increased expression of connexins 30 and 43; α4, α5, and β4 integrins; and E- and P-cadherins. Ws-Lynx1 reduced secretion of pro-inflammatory adhesion factors ICAM-1, PSGL-1, and VCAM-1 and downregulated secretion of CD44 and NCAM, which inhibit synaptic plasticity. Moreover, increased astrocytic secretion of the dendritic growth activator ALCAM and neurogenesis regulator E-selectin was observed. Incubation of neurons with ws-Lynx1 potentiated α7-nAChRs and upregulated dendritic spine density. Thus, the pro-cognitive activity of ws-Lynx1 observed previously can be explained by stimulation of astrocytic network and signaling together with up-regulation of spinogenesis, potentiation of the α7-nAChRs, and neuronal and synaptic plasticity. For comparison, influence of water-soluble analogues of a set of Ly6/uPAR proteins (SLURP-1, SLURP-2, Lypd6, Lypd6b, and PSCA) on dendritic spine density and diameter was studied. Data obtained give new insights on the role of Ly6/uPAR proteins in the brain and open new prospects for the development of drugs to improve cognitive function.

Effective Motor Skill Learning Induces Inverted-U Load-Dependent Activation in Contralateral Pre-Motor and Supplementary Motor Area

Motor learning involves complex interactions between the cognitive and sensorimotor systems, which are susceptible to different levels of task load. While the mechanism underlying load-dependent regulations in cognitive functions has been extensively investigated, their influence on downstream execution in motor skill learning remains less understood. The current study extends the understanding of whether and how learning alters the load-dependent activation pattern by a longitudinal functional near-infrared spectroscopy (fNIRS) study in which 30 healthy participants (15 females) engaged in extensive practice on a two-dimensional continuous hand tracking task with varying task difficulty. We proposed the index of difficulty (ID) as a quantitative measure of task difficulty, which was monotonically associated with a psychometric measure of subjective workload. As learning progressed, participants exhibited enhanced behavioral and metacognitive performance. Behavioral improvements were accompanied by plastic changes in the inferior prefrontal cortex, reflecting a shift in control strategy during motor learning. Most importantly, we found robust evidence of the learning-induced alteration in load-dependent cortical activation patterns, indicating that effective motor skill learning may lead to the emergence of an inverted-U relationship between cortical activation and load level in the contralateral pre-motor and supplementary motor areas. Our findings provide new insights into the learning-induced plasticity in brain and behavior, highlighting the load-dependent contributions in motor skill learning.

Unraveling the neurophysiological correlates of phase-specific enhancement of motor memory consolidation via slow-wave closed-loop targeted memory reactivation

Memory consolidation can be enhanced during sleep using targeted memory reactivation (TMR) and closed-loop (CL) acoustic stimulation on the up-phase of slow oscillations (SOs). Here, we test whether applying TMR at specific phases of the SOs (up vs. down vs. no reactivation) can influence the behavioral and neural correlates of motor memory consolidation in healthy young adults. Results show that up- (as compared to down-) state cueing results in greater performance improvement. Sleep electrophysiological data indicate that up- (as compared to down-) stimulated SOs exhibits higher amplitude and greater peak-nested sigma power. Task-related functional magnetic resonance images reveal that up-state cueing strengthens activity in - and segregation of - striato-motor and hippocampal networks; and that these modulations are related to the beneficial effect of TMR on sleep features and performance. Overall, these findings highlight the potential of CL-TMR to induce phase-specific modulations of motor performance, sleep oscillations and brain responses during motor memory consolidation.

The role of inhibitory and excitatory neurometabolites in age-related differences in action selection

Aging is accompanied by changes in the level of neurometabolites. However, their role in vital behavioral functions is still unclear. We aimed to explore the impact of aging on the neurochemical mechanisms underlying action selection. Young (YA) (n = 25) and older adults (OA) (n = 26) performed a simple (SRT) and a choice (CRT) reaction time tasks. Magnetic resonance spectroscopy was utilized to track task-induced modulations in GABA and glutamate in the sensorimotor cortex (SM1) and dorsolateral prefrontal cortex (dlPFC). Results showed that (i) SM1 Glx levels were higher during the SRT in the full sample, (ii) Glx modulation in the dlPFC predicted better behavioral performance in the SRT only in YA, and iii) a task-induced increase in GABA and Glx in the dlPFC was related to action selection learning in the full sample. Our findings highlight an important role of neurometabolic modulation during action selection and learning.

Enhancing retrieval capacity of the predictive brain through dorsolateral prefrontal cortex intervention

Extracting spatial or temporal patterns across experiences is essential for skill acquisition and predictive processes. The prefrontal cortex plays a central role in regulating competitive cognitive systems, with a particular influence on executive functions, often opposing statistical learning. This regulatory function may account for observed improvements in the acquisition and consolidation of statistical regularities following inhibition of the dorsolateral prefrontal cortex via repetitive transcranial magnetic stimulation. However, whether access to previously acquired statistical knowledge can similarly benefit from dorsolateral prefrontal cortex inhibition remains unclear. This preregistered study investigated the dorsolateral prefrontal cortex's role in retrieving pre-existing statistical knowledge of temporal regularities. Healthy human participants engaged in an implicit probabilistic sequence learning task followed by a 24-h consolidation period. Before retesting, they received either 1 Hz repetitive transcranial magnetic stimulation or sham stimulation over the left, right, or bilateral dorsolateral prefrontal cortex for 10 min. We observed that retrieval of statistical regularities was enhanced in the Bilateral dorsolateral prefrontal cortex group compared to the Sham group. Our findings suggest that dorsolateral prefrontal cortex inhibition may facilitate access to statistical knowledge, particularly when interhemispheric compensatory mechanisms are limited. These insights advance our understanding of the dynamic neural background of statistical learning and may inform strategies for cognitive enhancement.

Intact ultrafast memory consolidation in adults with autism and neurotypicals with autism traits

The processes of learning and memory consolidation are closely interlinked. Therefore, to uncover statistical learning in autism spectrum disorder (ASD), an in-depth examination of memory consolidation is essential. Studies of the last five years have revealed that learning can take place not only during practice but also during micro rest (<1 min) between practice blocks, termed micro offline gains. The concept of micro offline gains refers to performance improvements during short rest periods interspersed with practice, rather than during practice itself. This phenomenon is crucial for the acquisition and consolidation of motor skills and has been observed across various learning contexts. Numerous studies on learning in autism have identified intact learning but there has been no investigation into this fundamental aspect of memory consolidation in autistic individuals to date. We conducted two studies with two different samples: 1) neurotypical adults with distinct levels of autistic traits (N = 166) and 2) ASD-diagnosed adults (NASD = 22, NNTP = 20). Participants performed a well-established probabilistic learning task, allowing us to measure two learning processes separately in the same experimental design: statistical learning (i.e., learning probability-based regularities) and visuomotor performance (i.e., speed-up regardless of probabilities). Here we show considerable individual differences in offline (between blocks) changes during statistical learning and between-blocks improvement during visuomotor performance. However, cumulative evidence from individual studies suggests that the degree of autistic traits and ASD status are not associated with micro offline gains, indicating that, like statistical learning, rapid memory consolidation is intact.

Cingulate and striatal hubs are linked to early skill learning

Early skill learning develops in the context of activity changes in distributed cortico-subcortical regions. Here, we investigated network hubs-centers of information integration and transmission-within the brain network supporting early skill learning. We recorded magnetoencephalographic (MEG) brain activity in healthy human subjects who learned a moderately difficult sequence skill with their non-dominant left hand. We then computed network hub strength by summing top 10% functional connectivity over 86 parcellated brain regions (AAL3 atlas) and five brain oscillatory frequency bands (alpha, low-, high-beta, low- and high-gamma). Virtually all skill gains developed during rest intervals of early learning (micro-offline gains). MEG hub strength in the alpha band (8-13Hz) in bilateral anterior cingulate (ACC) and caudate and in the low-beta band (13-16Hz) in bilateral caudate and right putamen correlated with micro-offline gains. These regions linked strongly with the hippocampus, parahippocampal cortex, and lingual and fusiform gyri. Thus, alpha and low-beta brain oscillatory activity in cingulate and striatal regions appear to contribute as hubs of information integration and transmission during early skill learning.

Identification of a Hippocampus-to-Zona Incerta Projection involved in Motor Learning

Motor learning (ML), which plays a fundamental role in growth and physical rehabilitation, involves different stages of learning and memory processes through different brain regions. However, the neural mechanisms that underlie ML are not sufficiently understood. Here, a previously unreported neuronal projection from the dorsal hippocampus (dHPC) to the zona incerta (ZI) involved in the regulation of ML behaviors is identified. Using recombinant adeno-associated virus, the projections to the ZI are surprisingly identified as originating from the dorsal dentate gyrus (DG) and CA1 subregions of the dHPC. Furthermore, projection-specific chemogenetic and optogenetic manipulation reveals that the projections from the dorsal CA1 to the ZI play key roles in the acquisition and consolidation of ML behaviors, whereas the projections from the dorsal DG to the ZI mediate the retrieval/retention of ML behaviors. The results reveal new projections from the dorsal DG and dorsal CA1 to the ZI involved in the regulation of ML and provide insight into the stages over which this regulation occurs.

Altered functional connectivity in the hippocampal and striatal systems after motor sequence learning consolidation in medial temporal lobe epilepsy individuals

Both the hippocampal and striatal systems participate in motor sequence learning (MSL) in healthy subjects, and the prominent role of the hippocampal system in sleep-related consolidation has been demonstrated. However, some pathological states may change the functional dominance between these two systems in MSL consolidation. To better understand the functional performance within these two systems under the pathological condition of hippocampal impairment, we compared the functional differences after consolidation between patients with left medial temporal lobe epilepsy (LmTLE) and healthy control subjects (HCs). We assessed participants' performance on the finger-tapping task (FTT) during acquisition (on day 1) and after consolidation during sleep (on day 2). All participants underwent an MRI scan (T1 and resting state) before each FTT. We found that the LmTLE group showed performance deficits in offline consolidation compared to the HC group. The LmTLE group exhibited structural changes, such as decreased gray matter volume (GMV) in the left hippocampus and increased GMV in the right putamen (striatum). Our results also revealed that whereas the main effect of consolidation was observed in the hippocampus-related functional connection in the HC group, it was only evident in the striatum-related functional loop in the LmTLE group. Our findings indicated that LmTLE patients may rely more on the striatal system for offline consolidation because of structural impairments in the hippocampus. Additionally, this compensatory mechanism may not fully substitute for the role of the impaired hippocampus itself.NEW & NOTEWORTHY Motor sequence learning (MSL) relies on both the hippocampal and striatal systems, but whether functional performance is altered after MSL consolidation when the hippocampus is impaired remains unknown. Our results indicated that whereas the main effect of consolidation was observed in the hippocampus-related functional connection in the healthy control (HC) group, it was only evident in the striatum-related functional loop in the left medial temporal lobe epilepsy (LmTLE) group.

Additive effect of transcranial direct current stimulation (tDCS) in combination with multicomponent training on elderly physical function capacity: a randomized, triple blind, controlled trial

PURPOSE

To evaluate the additive effect of Transcranial Direct Current Stimulation (tDCS) associated with multi-component training (MT) on the functional capacity (FC) of older adults and to assess whether these effects remain after the end of training. The secondary objectives were to evaluate the locomotion capacity, balance, functional independence, and quality of life and correlate them with functional capacity.

METHODOLOGY

Twenty-eight older adults were randomized into two groups: experimental (MT associated with active tDCS - a-tDCS) and control (MT associated with sham tDCS - s-tDCS). The FC was measured by the Glittre-ADL test, locomotion capacity by the 6-minute walk test, balance by the BESTest, functional independence by the FIM, and quality of life by the WHQOL. The assessments were performed pre-, post-intervention, and 30-day follow-up.

RESULTS

There was a significant decrease in the time to the Glittre-ADL test when comparing the a-tDCS and s-tDCS groups after the interventions (139.77 ± 21.62, 205.10 ± 43.02, p < .001) and at the 30-day follow-up (142.74 ± 17.12, 219.55 ± 54.05, p < .001), respectively. There was a moderate correlation between FC and locomotion capacity and balance.

CONCLUSIONS

The addition of tDCS potentiated the results of MT to impact FC, maintaining the positive results longer. Locomotion and balance influenced the improvement of functional capacity.

Modulating Visuomotor Sequence Learning by Repetitive Transcranial Magnetic Stimulation: What Do We Know So Far?

Predictive processes and numerous cognitive, motor, and social skills depend heavily on sequence learning. The visuomotor Serial Reaction Time Task (SRTT) can measure this fundamental cognitive process. To comprehend the neural underpinnings of the SRTT, non-invasive brain stimulation stands out as one of the most effective methodologies. Nevertheless, a systematic list of considerations for the design of such interventional studies is currently lacking. To address this gap, this review aimed to investigate whether repetitive transcranial magnetic stimulation (rTMS) is a viable method of modulating visuomotor sequence learning and to identify the factors that mediate its efficacy. We systematically analyzed the eligible records (n = 17) that attempted to modulate the performance of the SRTT with rTMS. The purpose of the analysis was to determine how the following factors affected SRTT performance: (1) stimulated brain regions, (2) rTMS protocols, (3) stimulated hemisphere, (4) timing of the stimulation, (5) SRTT sequence properties, and (6) other methodological features. The primary motor cortex (M1) and the dorsolateral prefrontal cortex (DLPFC) were found to be the most promising stimulation targets. Low-frequency protocols over M1 usually weaken performance, but the results are less consistent for the DLPFC. This review provides a comprehensive discussion about the behavioral effects of six factors that are crucial in designing future studies to modulate sequence learning with rTMS. Future studies may preferentially and synergistically combine functional neuroimaging with rTMS to adequately link the rTMS-induced network effects with behavioral findings, which are crucial to develop a unified cognitive model of visuomotor sequence learning.

Prefrontal stimulation as a tool to disrupt hippocampal and striatal reactivations underlying fast motor memory consolidation

BACKGROUND

Recent evidence suggests that hippocampal replay in humans support rapid motor memory consolidation during epochs of wakefulness interleaved with task practice.

OBJECTIVES/HYPOTHESES

The goal of this study was to test whether such reactivation patterns can be modulated with experimental interventions and in turn influence fast consolidation. We hypothesized that non-invasive brain stimulation targeting hippocampal and striatal networks via the prefrontal cortex would influence brain reactivation and the rapid form of motor memory consolidation.

METHODS

Theta-burst stimulation was applied to a prefrontal cluster functionally connected to both the hippocampus and striatum of young healthy participants before they learned a motor sequence task in a functional magnetic resonance imaging (fMRI) scanner. Neuroimaging data acquired during task practice and the interleaved rest epochs were analyzed to comprehensively characterize the effect of stimulation on the neural processes supporting fast motor memory consolidation.

RESULTS

Our results collectively show that active, as compared to control, theta-burst stimulation of the prefrontal cortex hindered fast motor memory consolidation. Converging evidence from both univariate and multivariate analyses of fMRI data indicate that active stimulation disrupted hippocampal and caudate responses during inter-practice rest, presumably altering the reactivation of learning-related patterns during the micro-offline consolidation episodes. Last, stimulation altered the link between the brain and the behavioral markers of the fast consolidation process.

CONCLUSION

These results suggest that stimulation targeting deep brain regions via the prefrontal cortex can be used to modulate hippocampal and striatal reactivations in the human brain and influence motor memory consolidation.

Distinct frequencies balance segregation with interaction between different memory types within a prefrontal circuit

Once formed, the fate of memory is uncertain. Subsequent offline interactions between even different memory types (actions versus words) modify retention.^1,2,3,4,5,6 These interactions may occur due to different oscillations functionally linking together different memory types within a circuit.^{7,8,9,10,11,12,13} With memory processing driving the circuit, it may become less susceptible to external influences.¹⁴ We tested this prediction by perturbing the human brain with single pulses of transcranial magnetic stimulation (TMS) and simultaneously measuring the brain activity changes with electroencephalography (EEG^15,16,17). Stimulation was applied over brain areas that contribute to memory processing (dorsolateral prefrontal cortex, DLPFC; primary motor cortex, M1) at baseline and offline, after memory formation, when memory interactions are known to occur.^1,4,6,10,18 The EEG response decreased offline (compared with baseline) within the alpha/beta frequency bands when stimulation was applied to the DLPFC, but not to M1. This decrease exclusively followed memory tasks that interact, revealing that it was due specifically to the interaction, not task performance. It remained even when the order of the memory tasks was changed and so was present, regardless of how the memory interaction was produced. Finally, the decrease within alpha power (but not beta) was correlated with impairment in motor memory, whereas the decrease in beta power (but not alpha) was correlated with impairment in word-list memory. Thus, different memory types are linked to different frequency bands within a DLPFC circuit, and the power of these bands shapes the balance between interaction and segregation between these memories.

A systematic review of the neurobiological effects of theta-burst stimulation (TBS) as measured using functional magnetic resonance imaging (fMRI)

Theta burst stimulation (TBS) is associated with the modulation of a range of clinical, cognitive, and behavioural outcomes, but specific neurobiological effects remain somewhat unclear. This systematic literature review investigated resting-state and task-based functional magnetic resonance imaging (fMRI) outcomes post-TBS in healthy human adults. Fifty studies that applied either continuous-or intermittent-(c/i) TBS, and adopted a pretest-posttest or sham-controlled design, were included. For resting-state outcomes following stimulation applied to motor, temporal, parietal, occipital, or cerebellar regions, functional connectivity generally decreased in response to cTBS and increased in response to iTBS, though there were some exceptions to this pattern of response. These findings are mostly consistent with the assumed long-term depression (LTD)/long-term potentiation (LTP)-like plasticity effects of cTBS and iTBS, respectively. Task-related outcomes following TBS were more variable. TBS applied to the prefrontal cortex, irrespective of task or state, also produced more variable responses, with no consistent patterns emerging. Individual participant and methodological factors are likely to contribute to the variability in responses to TBS. Future studies assessing the effects of TBS via fMRI must account for factors known to affect the TBS outcomes, both at the level of individual participants and of research methodology.

Connectomics underlying motor functional outcomes in the acute period following stroke

Objective

Stroke remains the number one cause of morbidity in many developing countries, and while effective neurorehabilitation strategies exist, it remains difficult to predict the individual trajectories of patients in the acute period, making personalized therapies difficult. Sophisticated and data-driven methods are necessary to identify markers of functional outcomes.

Methods

Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI (rsfMRI), and diffusion weighted scans were obtained from 79 patients following stroke. Sixteen models were constructed to predict performance across six tests of motor impairment, spasticity, and activities of daily living, using either whole-brain structural or functional connectivity. Feature importance analysis was also performed to identify brain regions and networks associated with performance in each test.

Results

The area under the receiver operating characteristic curve ranged from 0.650 to 0.868. Models utilizing functional connectivity tended to have better performance than those utilizing structural connectivity. The Dorsal and Ventral Attention Networks were among the top three features in several structural and functional models, while the Language and Accessory Language Networks were most commonly implicated in structural models.

Conclusions

Our study highlights the potential of machine learning methods combined with connectivity analysis in predicting outcomes in neurorehabilitation and disentangling the neural correlates of functional impairments, though further longitudinal studies are necessary.

Prefrontal stimulation prior to motor sequence learning alters multivoxel patterns in the striatum and the hippocampus

Motor sequence learning (MSL) is supported by dynamical interactions between hippocampal and striatal networks that are thought to be orchestrated by the prefrontal cortex. In the present study, we tested whether individually-tailored theta-burst stimulation of the dorsolateral prefrontal cortex (DLPFC) prior to MSL can modulate multivoxel response patterns in the stimulated cortical area, the hippocampus and the striatum. Response patterns were assessed with multivoxel correlation structure analyses of functional magnetic resonance imaging data acquired during task practice and during resting-state scans before and after learning/stimulation. Results revealed that, across stimulation conditions, MSL induced greater modulation of task-related DLPFC multivoxel patterns than random practice. A similar learning-related modulatory effect was observed on sensorimotor putamen patterns under inhibitory stimulation. Furthermore, MSL as well as inhibitory stimulation affected (posterior) hippocampal multivoxel patterns at post-intervention rest. Exploratory analyses showed that MSL-related brain patterns in the posterior hippocampus persisted into post-learning rest preferentially after inhibitory stimulation. These results collectively show that prefrontal stimulation can alter multivoxel brain patterns in deep brain regions that are critical for the MSL process. They also suggest that stimulation influenced early offline consolidation processes as evidenced by a stimulation-induced modulation of the reinstatement of task pattern into post-learning wakeful rest.

A role for GABA in the modulation of striatal and hippocampal systems under stress

Previous research has demonstrated that stress modulates the competitive interaction between the hippocampus and striatum, two structures known to be critically involved in motor sequence learning. These earlier investigations, however, have largely focused on blood oxygen-level dependent (BOLD) responses. No study to date has examined the link between stress, motor learning and levels of striatal and hippocampal gamma-aminobutyric acid (GABA). This knowledge gap is surprising given the known role of GABA in neuroplasticity subserving learning and memory. The current study thus examined: a) the effects of motor learning and stress on striatal and hippocampal GABA levels; and b) how learning- and stress-induced changes in GABA relate to the neural correlates of learning. To do so, fifty-three healthy young adults were exposed to a stressful or non-stressful control intervention before motor sequence learning. Striatal and hippocampal GABA levels were assessed at baseline and post-intervention/learning using magnetic resonance spectroscopy. Regression analyses indicated that stress modulated the link between striatal GABA levels and functional plasticity in both the hippocampus and striatum during learning as measured with fMRI. This study provides evidence for a role of GABA in the stress-induced modulation of striatal and hippocampal systems.