Neuroimaging studies have improved our understanding of which brain structures are involved in motor learning. Despite this, questions remain regarding the areas that contribute consistently across ...paradigms with different task demands. For instance, sensorimotor tasks focus on learning novel movement kinematics and dynamics, while serial response time task (SRTT) variants focus on sequence learning. These differing task demands are likely to elicit quantifiably different patterns of neural activity on top of a potentially consistent core network. The current study identified consistent activations across 70 motor learning experiments using activation likelihood estimation (ALE) meta-analysis. A global analysis of all tasks revealed a bilateral cortical–subcortical network consistently underlying motor learning across tasks. Converging activations were revealed in the dorsal premotor cortex, supplementary motor cortex, primary motor cortex, primary somatosensory cortex, superior parietal lobule, thalamus, putamen and cerebellum. These activations were broadly consistent across task specific analyses that separated sensorimotor tasks and SRTT variants. Contrast analysis indicated that activity in the basal ganglia and cerebellum was significantly stronger for sensorimotor tasks, while activity in cortical structures and the thalamus was significantly stronger for SRTT variants. Additional conjunction analyses then indicated that the left dorsal premotor cortex was activated across all analyses considered, even when controlling for potential motor confounds. The highly consistent activation of the left dorsal premotor cortex suggests it is a critical node in the motor learning network.
► Activation likelihood estimation was used to analyze 70 motor learning experiments. ► Analysis revealed a cortico-subcortical network for motor learning. ► Consistent activations were found across subgroups with differing task demands. ► Left dorsal premotor cortex was identified as a key structure in motor learning.
Cognition presumably emerges from neural activity in the network of association connections between cortical regions that is modulated by inputs from sensory and state systems and directs voluntary ...behavior by outputs to the motor system. To reveal global architectural features of the cortical association connectome, network analysis was performed on >16,000 reports of histologically defined axonal connections between cortical regions in rat. The network analysis reveals an organization into four asymmetrically interconnected modules involving the entire cortex in a topographic and topologic core–shell arrangement. There is also a topographically continuous U-shaped band of cortical areas that are highly connected with each other as well as with the rest of the cortex extending through all four modules, with the temporal pole of this band (entorhinal area) having the most cortical association connections of all. These results provide a starting point for compiling a mammalian nervous system connectome that could ultimately reveal novel correlations between genome-wide association studies and connectome-wide association studies, leading to new insights into the cellular architecture supporting cognition.
Significance Connections between cerebral cortex regions are known as association connections, and neural activity in the network formed by these connections is thought to generate cognition. Network analysis of microscopic association connection data produced over the last 40 years in a small, easily studied mammal suggests a new way to describe the organization of the cortical association network. Basically, it consists of four modules with an anatomical shell–core arrangement and asymmetric connections within and between modules, implying at least partly “hardwired,” genetically determined biases of information flow through the cortical association network. The results advance the goal of achieving a global nervous system wiring diagram of connections and provide another step toward understanding the cellular architecture and mechanisms underpinning cognition.
Novel motor skills are learned through repetitive practice and, once acquired, persist long after training stops. Earlier studies have shown that such learning induces an increase in the efficacy of ...synapses in the primary motor cortex, the persistence of which is associated with retention of the task. However, how motor learning affects neuronal circuitry at the level of individual synapses and how long-lasting memory is structurally encoded in the intact brain remain unknown. Here we show that synaptic connections in the living mouse brain rapidly respond to motor-skill learning and permanently rewire. Training in a forelimb reaching task leads to rapid (within an hour) formation of postsynaptic dendritic spines on the output pyramidal neurons in the contralateral motor cortex. Although selective elimination of spines that existed before training gradually returns the overall spine density back to the original level, the new spines induced during learning are preferentially stabilized during subsequent training and endure long after training stops. Furthermore, we show that different motor skills are encoded by different sets of synapses. Practice of novel, but not previously learned, tasks further promotes dendritic spine formation in adulthood. Our findings reveal that rapid, but long-lasting, synaptic reorganization is closely associated with motor learning. The data also suggest that stabilized neuronal connections are the foundation of durable motor memory.
Resting state-functional magnetic resonance imaging (RS-FMRI) is a neuroimaging technique that allows repeated assessments of functional connectivity in resting state. While task-related FMRI is ...limited to indirectly measured drug effects in areas affected by the task, resting state can show direct CNS effects across all brain networks. Hence, RS-FMRI could be an objective measure for compounds affecting the CNS. Several studies on the effects of cannabinoid receptor type 1 (CB1)-receptor agonist δ9-tetrahydrocannabinol (THC) on task-dependent FMRI have been performed. However, no studies on the effects of cannabinoids on resting state networks using RS-FMRI have been published. Therefore, we investigated the effects of THC on functional brain connectivity using RS-FMRI. Twelve healthy volunteers (9 male, 3 female) inhaled 2, 6 and 6mg THC or placebo with 90-minute intervals in a randomized, double blind, cross-over trial. Eight RS-FMRI scans of 8min were obtained per occasion. Subjects rated subjective psychedelic effects on a visual analog scale after each scan, as pharmacodynamic effect measures. Drug-induced effects on functional connectivity were examined using dual regression with FSL software (FMRIB Analysis Group, Oxford). Eight maps of voxel-wise connectivity throughout the entire brain were provided per RS-FMRI series with eight predefined resting-state networks of interest. These maps were used in a mixed effects model group analysis to determine brain regions with a statistically significant drug-by-time interaction. Statistical images were cluster-corrected, and results were Bonferroni-corrected across multiple contrasts. THC administration increased functional connectivity in the sensorimotor network, and was associated with dissociable lateralized connectivity changes in the right and left dorsal visual stream networks. The brain regions showing connectivity changes included the cerebellum and dorsal frontal cortical regions. Clear increases were found for feeling high, external perception, heart rate and cortisol, whereas prolactin decreased. This study shows that THC induces both increases and (to a lesser extent) decreases in functional brain connectivity, mainly in brain regions with high densities of CB1-receptors. Some of the involved regions could be functionally related to robust THC-induced CNS-effects that have been found in previous studies (Zuurman et al., 2008), such as postural stability, feeling high and altered time perception.
The substantial phenotypic heterogeneity in autism limits our understanding of its genetic etiology. To address this gap, here we investigated genetic differences between autistic individuals (n
= ...12,893) based on core and associated features of autism, co-occurring developmental disabilities and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants were associated with the core factors, but de novo variants were not. We found that higher autism polygenic scores (PGS) were associated with lower likelihood of co-occurring developmental disabilities in autistic individuals. Furthermore, in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observed higher SNP heritability for autistic males and for autistic individuals without ID. Deeper phenotypic characterization will be critical in determining how the complex underlying genetics shape cognition, behavior and co-occurring conditions in autism.
The human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly ...desirable to measure and understand the cerebellum role in normal and pathological brain development. In this work, we propose a patch-based multi-atlas segmentation tool called CERES (CEREbellum Segmentation) that is able to automatically parcellate the cerebellum lobules. The proposed method works with standard resolution magnetic resonance T1-weighted images and uses the Optimized PatchMatch algorithm to speed up the patch matching process. The proposed method was compared with related recent state-of-the-art methods showing competitive results in both accuracy (average DICE of 0.7729) and execution time (around 5 minutes).
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•We present a novel method for cerebellum lobule segmentation on MRI.•The method consists of a fast multi-atlas non-local patch-based label fusion.•Our proposed method was shown to improve the state-of-the-art methods with a reduced temporal cost (5 minutes).•The pipeline presented in this work will be made available to scientific community through our web -based platform volBrain.
Independent locomotion is associated with a range of positive developmental outcomes, but unlike cognitive, linguistic, and social skills, acquiring motor skills requires infants to generate their ...own input for learning. We tested factors that shape infants' spontaneous locomotion by observing forty 12- to 22-month-olds (19 girls, 21 boys) during free play. Infants were recruited from the New York City area, and caregivers reported that 25 infants were White, six were Asian, four were Black, and five had multiple races; four were Hispanic or Latino. All infants played in four conditions: two environmental conditions (gross-motor toys, fine-motor toys) crossed with two social conditions (alone, together with a caregiver). Infants moved more in the gross-motor toy conditions than in the fine-motor toy conditions. However, the effect of playing with a caregiver differed by toy condition. In the gross-motor toy conditions, playing with a caregiver did not affect how much infants moved, but in the fine-motor toy conditions, playing with a caregiver further depressed infant locomotion. Infants with more walking experience moved more with gross-motor toys but not with fine-motor toys. Differences in the amount of locomotion between conditions were related to how infants used toys and the interactions between infants and caregivers.
Public Significance Statement
Toys like strollers, brooms, grocery carts, and balls, along with a "hands-off" caregiver play style, encourage toddlers to engage in locomotor play. In contrast, toys like pop-ups, xylophones, shape-sorters, and bricks, along with a "hands-on" caregiver play style, encourage more manual, stationary play.
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