Pierre Orban

Offline Persistence of Memory-Related Cerebral Activity during Active Wakefulness

Much remains to be discovered about the fate of recent memories in the human brain. Several studies have reported the reactivation of learning-related cerebral activity during post-training sleep, suggesting that sleep plays a role in the offline processing and consolidation of memory. However, little is known about how new information is maintained and processed during post-training wakefulness before sleep, while the brain is actively engaged in other cognitive activities. We show, using functional magnetic resonance imaging, that brain activity elicited during a new learning episode modulates brain responses to an unrelated cognitive task, during the waking period following the end of training. This post-training activity evolves in learning-related cerebral structures, in which functional connections with other brain regions are gradually established or reinforced. It also correlates with behavioral performance. These processes follow a different time course for hippocampus-dependent and hippocampus-independent memories. Our experimental approach allowed the characterization of the offline evolution of the cerebral correlates of recent memories, without the confounding effect of concurrent practice of the learned material. Results indicate that the human brain has already extensively processed recent memories during the first hours of post-training wakefulness, even when simultaneously coping with unrelated cognitive demands.

Brain plasticity related to the consolidation of motor sequence learning and motor adaptation

This study aimed to investigate, through functional MRI (fMRI), the neuronal substrates associated with the consolidation process of two motor skills: motor sequence learning (MSL) and motor adaptation (MA). Four groups of young healthy individuals were assigned to either (i) a night/sleep condition, in which they were scanned while practicing a finger sequence learning task or an eight-target adaptation pointing task in the evening (test) and were scanned again 12 h later in the morning (retest) or (ii) a day/awake condition, in which they were scanned on the MSL or the MA tasks in the morning and were rescanned 12 h later in the evening. As expected and consistent with the behavioral results, the functional data revealed increased test–retest changes of activity in the striatum for the night/sleep group compared with the day/awake group in the MSL task. By contrast, the results of the MA task did not show any difference in test–retest activity between the night/sleep and day/awake groups. When the two MA task groups were combined, however, increased test–retest activity was found in lobule VI of the cerebellar cortex. Together, these findings highlight the presence of both functional and structural dissociations reflecting the off-line consolidation processes of MSL and MA. They suggest that MSL consolidation is sleep dependent and reflected by a differential increase of neural activity within the corticostriatal system, whereas MA consolidation necessitates either a period of daytime or sleep and is associated with increased neuronal activity within the corticocerebellar system.

Partially Segregated Neural Networks for Spatial and Contextual Memory in Virtual Navigation

Finding our way in a previously learned, ecologically valid environment concurrently involves spatial and contextual cognitive operations. The former process accesses a cognitive map representing the spatial interactions between all paths in the environment. The latter accesses stored associations between landmark objects and their milieu. Here, we aimed at dissociating their neural basis in the context of memory‐based virtual navigation. To do so, subjects freely explored a virtual town for 1 h, then were scanned using fMRI while retrieving their way between two locations, under four navigation conditions designed to probe separately or jointly the spatial and contextual memory components. Besides prominent commonalities found in a large hippocampo‐neocortical network classically involved in topographical navigation, results yield evidence for a partial dissociation between the brain areas supporting spatial and contextual components of memory‐based navigation. Performance‐related analyses indicate that hippocampal activity mostly supports the spatial component, whereas parahippocampal activity primarily supports the contextual component. Additionally, the recruitment of contextual memory during navigation was associated with higher frontal, posterior parietal and lateral temporal activity. These results provide evidence for a partial segregation of the neural substrates of two crucial memory components in human navigation, whose combined involvement eventually leads to efficient navigation behavior within a learned environment.

Sleep Modulates the Neural Substrates of Both Spatial and Contextual Memory Consolidation

It is known that sleep reshapes the neural representations that subtend the memories acquired while navigating in a virtual environment. However, navigation is not process-pure, as manifold learning components contribute to performance, notably the spatial and contextual memory constituents. In this context, it remains unclear whether post-training sleep globally promotes consolidation of all of the memory components embedded in virtual navigation, or rather favors the development of specific representations. Here, we investigated the effect of post-training sleep on the neural substrates of the consolidation of spatial and contextual memories acquired while navigating in a complex 3D, naturalistic virtual town. Using fMRI, we mapped regional cerebral activity during various tasks designed to tap either the spatial or the contextual memory component, or both, 72 h after encoding with or without sleep deprivation during the first post-training night. Behavioral performance was not dependent upon post-training sleep deprivation, neither in a natural setting that engages both spatial and contextual memory processes nor when looking more specifically at each of these memory representations. At the neuronal level however, analyses that focused on contextual memory revealed distinct correlations between performance and neuronal activity in frontal areas associated with recollection processes after post-training sleep, and in the parahippocampal gyrus associated with familiarity processes in sleep-deprived participants. Likewise, efficient spatial memory was associated with posterior cortical activity after sleep whereas it correlated with parahippocampal/medial temporal activity after sleep deprivation. Finally, variations in place-finding efficiency in a natural setting encompassing spatial and contextual elements were associated with caudate activity after post-training sleep, suggesting the automation of navigation. These data indicate that post-training sleep modulates the neural substrates of the consolidation of both the spatial and contextual memories acquired during virtual navigation.

Functional neuroanatomy associated with the expression of distinct movement kinematics in motor sequence learning.

A broad range of motor skills, such as speech and writing, evolves with the ability to articulate elementary motor movements into novel sequences that come to be performed smoothly through practice. Neuroimaging studies in humans have demonstrated the involvement of the cerebello-cortical and striato-cortical motor loops in the course of motor sequence learning. Nonetheless, the nature of the improvement and brain mechanisms underlying different parameters of movement kinematics are not yet fully ascertained. We aimed at dissociating the cerebral substrates related to the increase in performance on two kinematic indices: velocity, that is the speed with which each single movement in the sequence is produced, and transitions, that is the duration of the gap between these individual movements. In this event-related fMRI experiment, participants practiced an eight-element sequence of finger presses on a keypad which allowed to record those kinematic movement parameters. Velocity was associated with activations in the ipsilateral spinocerebellum (lobules 4-5, 8 and medial lobule 6) and in the contralateral primary motor cortex. Transitions were associated with increased activity in the neocerebellum (lobules 6 bilaterally and lobule 4-5 ipsilaterally), as well as with activations within the right and left putamen and a broader bilateral network of motor cortical areas. These findings indicate that, rather than being the product of a single mechanism, the general improvement in motor performance associated with early motor sequence learning arises from at least two distinct kinematic processes, whose behavioral expressions are supported by partially overlapping and segregated brain networks.

Motor Sequence Learning and Developmental Dyslexia

Beyond the reading‐related deficits typical of developmental dyslexia (DD), recent evidence suggests that individuals afflicted with this condition also show difficulties in motor sequence learning. To date, however, little is known with respect to the characteristics of the learning impairments, nor to the neural correlates associated with this type of procedural deficit in DD patients. Here, we first summarize the results of the few behavioral and brain imaging studies that have investigated the effects of DD on motor sequence learning. To help guide research in this field, we then discuss relevant psychophysical and neuroimaging work conducted in healthy volunteers in relation to three different conceptual perspectives: when, how, and what. More specifically, we examine the cognitive boundaries that affect performance across the different stages of learning (i.e., “when”), the different cognitive processes (i.e., “how”) under which learning occurs, and the mental representations (i.e., “what”) that are elicited when acquiring this type of skilled behavior. It is hoped that this conceptual framework will be useful to researchers interested in further studying the nature of the motor learning impairment reported in DD.

The Richness of Task-Evoked Hemodynamic Responses Defines a Pseudohierarchy of Functionally Meaningful Brain Networks

Functional magnetic resonance imaging can measure distributed and subtle variations in brain responses associated with task performance. However, it is unclear whether the rich variety of responses observed across the brain is functionally meaningful and consistent across individuals. Here, we used a multivariate clustering approach that grouped brain regions into clusters based on the similarity of their task-evoked temporal responses at the individual level, and then established the spatial consistency of these individual clusters at the group level. We observed a stable pseudohierarchy of task-evoked networks in the context of a delayed sequential motor task, where the fractionation of networks was driven by a gradient of involvement in motor sequence preparation versus execution. In line with theories about higher-level cognitive functioning, this gradient evolved in a rostro-caudal manner in the frontal lobe. In addition, parcellations in the cerebellum and basal ganglia matched with known anatomical territories and fiber pathways with the cerebral cortex. These findings demonstrate that subtle variations in brain responses associated with task performance are systematic enough across subjects to define a pseudohierarchy of task-evoked networks. Such networks capture meaningful functional features of brain organization as shaped by a given cognitive context.

Impact of the resolution of brain parcels on connectome-wide association studies in fMRI.

A recent trend in functional magnetic resonance imaging is to test for association of clinical disorders with every possible connection between selected brain parcels. We investigated the impact of the resolution of functional brain parcels, ranging from large-scale networks to local regions, on a mass univariate general linear model (GLM) of connectomes. For each resolution taken independently, the Benjamini-Hochberg procedure controlled the false-discovery rate (FDR) at nominal level on realistic simulations. However, the FDR for tests pooled across all resolutions could be inflated compared to the FDR within resolution. This inflation was severe in the presence of no or weak effects, but became negligible for strong effects. We thus developed an omnibus test to establish the overall presence of true discoveries across all resolutions. Although not a guarantee to control the FDR across resolutions, the omnibus test may be used for descriptive analysis of the impact of resolution on a GLM analysis, in complement to a primary analysis at a predefined single resolution. On three real datasets with significant omnibus test (schizophrenia, congenital blindness, motor practice), markedly higher rate of discovery were obtained at low resolutions, below 50, in line with simulations showing increase in sensitivity at such resolutions. This increase in discovery rate came at the cost of a lower ability to localize effects, as low resolution parcels merged many different brain regions together. However, with 30 or more parcels, the statistical effect maps were biologically plausible and very consistent across resolutions. These results show that resolution is a key parameter for GLM-connectome analysis with FDR control, and that a functional brain parcellation with 30 to 50 parcels may lead to an accurate summary of full connectome effects with good sensitivity in many situations.

Resting-state network dysfunction in Alzheimer's disease: A systematic review and meta-analysis

We performed a systematic review and meta‐analysis of the Alzheimers disease (AD) literature to examine consistency of functional connectivity alterations in AD dementia and mild cognitive impairment, using resting‐state functional magnetic resonance imaging.

Common Effects of Amnestic Mild Cognitive Impairment on Resting-State Connectivity Across Four Independent Studies.

Resting-state functional connectivity is a promising biomarker for Alzheimers disease. However, previous resting-state functional magnetic resonance imaging studies in Alzheimers disease and amnestic mild cognitive impairment (aMCI) have shown limited reproducibility as they have had small sample sizes and substantial variation in study protocol. We sought to identify functional brain networks and connections that could consistently discriminate normal aging from aMCI despite variations in scanner manufacturer, imaging protocol, and diagnostic procedure. We therefore combined four datasets collected independently, including 112 healthy controls and 143 patients with aMCI. We systematically tested multiple brain connections for associations with aMCI using a weighted average routinely used in meta-analyses. The largest effects involved the superior medial frontal cortex (including the anterior cingulate), dorsomedial prefrontal cortex, striatum, and middle temporal lobe. Compared with controls, patients with aMCI exhibited significantly decreased connectivity between default mode network nodes and between regions of the cortico-striatal-thalamic loop. Despite the heterogeneity of methods among the four datasets, we identified common aMCI-related connectivity changes with small to medium effect sizes and sample size estimates recommending a minimum of 140 to upwards of 600 total subjects to achieve adequate statistical power in the context of a multisite study with 5–10 scanning sites and about 10 subjects per group and per site. If our findings can be replicated and associated with other established biomarkers of Alzheimers disease (e.g., amyloid and tau quantification), then these functional connections may be promising candidate biomarkers for Alzheimers disease.