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Jacobacci, F.

Publications and source records attributed to Jacobacci, F..

3 recordsLinked to original sources

The human hippocampus is involved in implicit motor learning

Recent evidence suggests that the human hippocampus, traditionally associated with declarative memory, plays a role in motor sequence learning (MSL). However, the classic MSL paradigm depends initially on declarative learning. Therefore, it is critical to discern whether the participation of the hippocampus relates to its canonical role or to processing a general aspect of learning that transcends the declarative/non-declarative distinction. To address this issue, here we turn to visuomotor adaptation -a type of motor learning involving skill recalibration-which unlike MSL can be easily manipulated to eliminate the explicit component. Here, we examined the broader involvement of the hippocampus in procedural motor learning by using diffusion MRI to indirectly assess structural plasticity associated with memory consolidation in visuomotor adaptation (VMA) and an implicit-only version (IVMA). We found that both VMA and IVMA engaged the left posterior hippocampus in a learning-specific manner. Remarkably, while VMA induced only transient hippocampal alterations, IVMA elicited structural changes that persisted overnight, underscoring the reliance on implicit learning for enduring neuroplasticity. As expected, training on both visuomotor tasks impacted the microstructure of the cerebellum, the motor and the posterior parietal cortex. Notably, the temporal dynamics of changes in these regions closely paralleled those of the left hippocampus, suggesting that motor and limbic regions operate in a coordinated manner as part of the same neural network. Collectively, our findings support an active role of the hippocampus in procedural motor memory and argue for a unified function in memory encoding regardless of the declarative or non-declarative nature of the task.

neuroscience↗

The origins of anterograde interference in visuomotor adaptation

Anterograde interference refers to the negative impact of prior learning on the propensity for future learning. Previous work has shown that subsequent adaptation to two perturbations of opposing sign, A and B, impairs performance in B. Here, we aimed to unveil the mechanism at the basis of anterograde interference by tracking its impact as a function of time through a 24h period. We found that the memory of A biased performance in B for all time intervals. Conversely, learning from error was hindered up to 1h following acquisition of A, with release from interference occurring at 6h. These findings suggest that poor performance induced by prior learning is driven by two distinct mechanisms: a long-lasting bias that acts as a prior and hinders the initial level of performance, and a short-lasting learning impairment that originates from a reduction in error-sensitivity. Our work provides insight into the timeline of memory stabilization in visuomotor adaptation.

neuroscience↗

Improving spatial normalization of brain diffusion MRI to measure longitudinal changes of tissue microstructure in human cortex and white matter.

BackgroundFractional anisotropy (FA) and mean diffusivity (MD) are frequently used to evaluate longitudinal changes in white matter 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. PurposeTo optimize normalization to improve registration in gray matter and reduce variability associated with multi-session registrations. Study TypeProspective longitudinal study SubjectsTwenty-one healthy subjects (18-31 years old) underwent 9 magnetic resonance imaging (MRI) scanning sessions each. Field Strength/Sequence3.0T, diffusion-weighted multiband-accelerated sequence, MP2RAGE sequence. AssessmentDiffusion-weighted images were registered to standard space using different pipelines that varied in the features used for normalization, namely the non-linear 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 from these normalization approaches for FA and MD in white and gray matters. Statistical TestsReproducibility errors were compared using a repeated-measures analysis of variance with pipeline as within-subject factor. ResultsThe 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 ConclusionA 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.

neuroscience↗