RESUMO
In the last decade, the exclusive role of the hippocampus in human declarative learning has been challenged. Recently, we have shown that gains in performance observed in motor sequence learning (MSL) during the quiet rest periods interleaved with practice are associated with increased hippocampal activity, suggesting a role of this structure in motor memory reactivation. Yet, skill also develops offline as memory stabilizes after training and overnight. To examine whether the hippocampus contributes to motor sequence memory consolidation, here we used a network neuroscience strategy to track its functional connectivity offline 30 min and 24 h post learning using resting-state functional magnetic resonance imaging. Using a graph-analytical approach we found that MSL transiently increased network modularity, reflected in an increment in local information processing at 30 min that returned to baseline at 24 h. Within the same time window, MSL decreased the connectivity of a hippocampal-sensorimotor network, and increased the connectivity of a striatal-premotor network in an antagonistic manner. Finally, a supervised classification identified a low-dimensional pattern of hippocampal connectivity that discriminated between control and MSL data with high accuracy. The fact that changes in hippocampal connectivity were detected shortly after training supports a relevant role of the hippocampus in early stages of motor memory consolidation.
Assuntos
Conectoma , Hipocampo , Consolidação da Memória , Consolidação da Memória/fisiologia , Hipocampo/fisiologia , Hipocampo/ultraestrutura , Humanos , Masculino , Feminino , Adulto Jovem , Adulto , Imageamento por Ressonância Magnética , Rede Nervosa/fisiologia , Rede Nervosa/ultraestruturaRESUMO
Recent evidence suggests that gains in performance observed while humans learn a novel motor sequence occur during the quiet rest periods interleaved with practice (micro-offline gains, MOGs). This phenomenon is reminiscent of memory replay observed in the hippocampus during spatial learning in rodents. Whether the hippocampus is also involved in the production of MOGs remains currently unknown. Using a multimodal approach in humans, here we show that activity in the hippocampus and the precuneus increases during the quiet rest periods and predicts the level of MOGs before asymptotic performance is achieved. These functional changes were followed by rapid alterations in brain microstructure in the order of minutes, suggesting that the same network that reactivates during the quiet periods of training undergoes structural plasticity. Our work points to the involvement of the hippocampal system in the reactivation of procedural memories.
Assuntos
Hipocampo/fisiologia , Aprendizagem/fisiologia , Destreza Motora/fisiologia , Adolescente , Adulto , Feminino , Humanos , Imageamento por Ressonância Magnética , Masculino , Memória , Adulto JovemRESUMO
BACKGROUND: Fractional anisotropy (FA) and mean diffusivity (MD) are frequently used to evaluate longitudinal changes in white matter (WM) microstructure. Recently, there has been a growing interest in identifying experience-dependent plasticity in gray matter using MD. Improving registration has thus become a major goal to enhance the detection of subtle longitudinal changes in cortical microstructure. PURPOSE: To optimize normalization of diffusion tensor images (DTI) to improve registration in gray matter and reduce variability associated with multisession registrations. STUDY TYPE: Prospective longitudinal study. SUBJECTS: Twenty-one healthy subjects (18-31 years old) underwent nine MRI scanning sessions each. FIELD STRENGTH/SEQUENCE: 3.0T, diffusion-weighted multiband-accelerated sequence, MP2RAGE sequence. ASSESSMENT: Diffusion-weighted images were registered to standard space using different pipelines that varied in the features used for normalization, namely, the nonlinear registration algorithm (FSL vs. ANTs), the registration target (FA-based vs. T1 -based templates), and the use of intermediate individual (FA-based or T1 -based) targets. We compared the across-session test-retest reproducibility error of these normalization approaches for FA and MD in white and gray matter. STATISTICAL TESTS: Reproducibility errors were compared using a repeated-measures analysis of variance with pipeline as the within-subject factor. RESULTS: The registration of FA data to the FMRIB58 FA atlas using ANTs yielded lower reproducibility errors in white matter (P < 0.0001) with respect to FSL. Moreover, using the MNI152 T1 template as the target of registration resulted in lower reproducibility errors for MD (P < 0.0001), whereas the FMRIB58 FA template performed better for FA (P < 0.0001). Finally, the use of an intermediate individual template improved reproducibility when registration of the FA images to the MNI152 T1 was carried out within modality (FA-FA) (P < 0.05), but not via a T1 -based individual template. DATA CONCLUSION: A normalization approach using ANTs to register FA images to the MNI152 T1 template via an individual FA template minimized test-retest reproducibility errors both for gray and white matter. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1 J. Magn. Reson. Imaging 2020;52:766-775.