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Cocchi, L.

Publications and source records attributed to Cocchi, L..

25 records · Page 2Linked to original sources
bioRxiv2019

ADHD symptoms map onto noise-driven structure-function decoupling between hub and peripheral brain regions

Adults with childhood-onset attention-deficit hyperactivity disorder (ADHD) show altered whole-brain connectivity. However, the relationship between structural and functional brain abnormalities, the implications for the development of life-long debilitating symptoms, and the underlying mechanisms remain uncharted. We recruited a unique sample of 80 medication-naive adults with a clinical diagnosis of childhood-onset ADHD without psychiatric comorbidities, and 123 age-, sex-, and intelligence-matched healthy controls. Structural and functional connectivity matrices were derived from diffusion spectrum imaging and multi-echo resting-state functional MRI data. Hub, feeder, and local connections were defined using diffusion data. Individual-level measures of structural connectivity and structure-function coupling were used to contrast groups and link behavior to brain abnormalities. Computational modeling was used to test possible neural mechanisms underpinning observed group differences in the structure-function coupling. Structural connectivity did not significantly differ between groups but, relative to controls, ADHD showed a reduction in structure-function coupling in feeder connections linking hubs with peripheral regions. This abnormality involved connections linking fronto-parietal control systems with sensory networks. Crucially, lower structure-function coupling was associated with higher ADHD symptoms. Results from our computational model further suggest that the observed structure-function decoupling in ADHD is driven by heterogeneity in neural noise variability across brain regions. By highlighting a neural cause of a clinically meaningful breakdown in the structure-function relationship, our work provides novel information on the nature of chronic ADHD. The current results encourage future work assessing the genetic and neurobiological underpinnings of neural noise in ADHD, particularly in brain regions encompassed by fronto-parietal systems.

neuroscience↗
bioRxiv2019

Relating brain connectivity with persistent symptoms in pediatric concussion

Persistent post-concussion symptoms (PCS) in children following a mild traumatic brain injury (mTBI) is a growing public health concern. There is a pressing need to understand the neural underpinning of PCS. Here, we examined whole-brain functional connectivity from resting-state fMRI with behavioral assessments in a cohort of 110 children with mTBI. Children with mTBI and controls had similar levels of connectivity. PCS symptoms and behaviors including poor cognition and sleep were associated with connectivity within functional brain networks. The identification of a single "positive-negative" dimension linking connectivity with behaviors enables better prognosis and stratification towards personalized therapeutic interventions.

neuroscience↗
bioRxiv2018

Increased cognitive complexity reveals abnormal brain network activity in individuals with corpus callosum dysgenesis

Cognitive reasoning is thought to require functional interactions between whole-brain networks. Such networks rely on both cerebral hemispheres, with the corpus callosum providing cross-hemispheric communication. Here we used high-field functional magnetic resonance imaging (7T fMRI), a well validated cognitive task, and brain network analyses to investigate the functional networks underlying cognitive reasoning in individuals with corpus callosum dysgenesis (CCD), an anatomical abnormality that affects the corpus callosum. Participants with CCD were asked to solve cognitive reasoning problems while their brain activity was measured using fMRI. The complexity of these problems was parametrically varied by changing the complexity of relations that needed to be established between shapes within each problem matrix. Behaviorally, participants showed a typical reduction in task performance as problem complexity increased. Task-evoked neural activity was observed in brain regions known to constitute two key cognitive control systems: the fronto-parietal and cingulo-opercular networks. Under low complexity demands, network topology and the patterns of local neural activity in the CCD group closely resembled those observed in neurotypical controls. By contrast, when asked to solve more complex problems, participants with CCD showed a reduction in neural activity and connectivity within the fronto-parietal network. These complexity-induced, as opposed to resting-state, differences in functional network activity help resolve the apparent paradox between preserved network architecture found at rest in CCD individuals, and the heterogeneous deficits they display in response to cognitive task demands [preprint: https://doi.org/10.1101/312629].

neuroscience↗
bioRxiv2017

Brain-behavior patterns define a dimensional biotype in medication-naïve adults with attention-deficit hyperactivity disorder

BackgroundChildhood-onset attention-deficit hyperactivity disorder (ADHD) in adults is clinically heterogeneous and commonly presents with different patterns of cognitive deficits. It is unclear if this clinical heterogeneity expresses a dimensional or categorical difference in ADHD.\n\nMethodsWe first studied differences in functional connectivity in multi-echo resting-state functional magnetic resonance imaging (rs-fMRI) acquired from 80 medication-naive adults with ADHD and 123 matched healthy controls. We then used canonical correlation analysis (CCA) to identify latent relationships between symptoms and patterns of altered functional connectivity (dimensional biotype) in patients. Clustering methods were implemented to test if the individual associations between resting-state brain connectivity and symptoms reflected a non-overlapping categorical biotype.\n\nResultsAdults with ADHD showed stronger functional connectivity compared to healthy controls, predominantly between the default-mode, cingulo-opercular and subcortical networks. CCA identified a single mode of brain-symptom co-variation, corresponding to an ADHD dimensional biotype. This dimensional biotype is characterized by a unique combination of altered connectivity correlating with symptoms of hyperactivity-impulsivity, inattention, and intelligence. Clustering analyses did not support the existence of distinct categorical biotypes of adult ADHD.\n\nConclusionsOverall, our data advance a novel finding that the reduced functional segregation between default-mode and cognitive control networks supports a clinically important dimensional biotype of childhood-onset adult ADHD. Despite the heterogeneity of its presentation, our work suggests that childhood-onset adult ADHD is a single disorder characterized by dimensional brain-symptom mediators.

neuroscience↗
bioRxiv2017

Reconfiguration of brain network architectures between resting state and complexity-dependent cognitive reasoning

Our capacity for higher cognitive reasoning has a measureable limit. This limit is thought to arise from the brains capacity to flexibly reconfigure interactions between spatially distributed networks. Recent work, however, has suggested that reconfigurations of task-related networks are modest when compared with intrinsic resting state network architecture. Here we combined resting state and task-driven functional magnetic resonance imaging to examine how flexible, task-specific reconfigurations associated with increasing reasoning demands are integrated within a stable intrinsic brain topology. Human participants (21 males and 28 females) underwent an initial resting state scan, followed by a cognitive reasoning task involving different levels of complexity, followed by a second resting state scan. The reasoning task required participants to deduce the identity of a missing element in a 4 x 4 matrix, and item difficulty was scaled parametrically as determined by relational complexity theory. Analyses revealed that external task engagement was characterized by a significant change in functional brain modules. Specifically, resting state and null-task demand conditions were associated with more segregated brain network topology, whereas increases in reasoning complexity resulted in merging of resting state modules. Further increments in task complexity did not change the established modular architecture, but impacted selective patterns of connectivity between fronto-parietal, subcortical, cingulo-opercular and default-mode networks. Larger increases in network efficiency within the newly established task modules were associated with higher reasoning accuracy. Our results shed light on the network architectures that underlie external task engagement, and highlight selective changes in brain connectivity supporting increases in task complexity.\n\nSignificance StatementHumans have clear limits in their ability to solve complex reasoning problems. It is thought that such limitations arise from flexible, moment-to-moment reconfigurations of functional brain networks. It is less clear how such task-driven adaptive changes in connectivity relate to stable, intrinsic networks of the brain and behavioral performance. We found that increased reasoning demands rely on selective patterns of connectivity within cortical networks that emerged in addition to a more general, task-induced modular architecture. This task-driven architecture reverted to a more segregated resting state architecture both immediately before and after the task. These findings reveal how flexibility in human brain networks is integral to achieving successful reasoning performance across different levels of cognitive demand.

neuroscience↗
bioRxiv2017

Neural decoding of visual stimuli varies with fluctuations in global network efficiency

Functional magnetic resonance imaging (fMRI) studies have shown that neural activity fluctuates spontaneously between different states of global synchronization over a timescale of several seconds. Such fluctuations generate transient states of high and low correlation across distributed cortical areas. It has been hypothesized that such fluctuations in global efficiency might alter patterns of activity in local neuronal populations elicited by changes in incoming sensory stimuli. To test this prediction, we used a linear decoder to discriminate patterns of neural activity elicited by face and motion stimuli presented periodically while participants underwent time-resolved fMRI. As predicted, decoding was reliably higher during states of high global efficiency than during states of low efficiency, and this difference was evident across both visual and non-visual cortical regions. The results indicate that slow fluctuations in global network efficiency are associated with variations in the pattern of activity across widespread cortical regions responsible for representing distinct categories of visual stimulus. More broadly, the findings highlight the importance of understanding the impact of global fluctuations in functional connectivity on specialised, stimulus driven neural processes.

neuroscience↗
bioRxiv2016

Structural and functional brain changes following four weeks of unimanual motor training: evidence from behaviour, neural stimulation, cortical thickness and functional MRI

Although different aspects of neuroplasticity can be quantified with behavioural probes, brain stimulation, and brain imaging assessments, no study to date has combined all these approaches into one comprehensive assessment of brain plasticity. Here, 24 healthy right-handed participants practised a sequence of finger-thumb opposition movements for 10 minutes each day with their left hand. After four weeks, performance for the practised sequence improved significantly (p < 0.05 FWE) relative to a matched control sequence, with both the left (mean increase: 53.0% practised, 6.5% control) and right (21.0%; 15.8%) hands. Training also induced significant (cluster p-FWE < 0.001) reductions in functional MRI activation for execution of the learned sequence, relative to the control sequence. These changes were observed as clusters in the premotor and supplementary motor cortices (right hemisphere, 301 voxel cluster; left hemisphere 700 voxel cluster), as well as sensorimotor cortices and superior parietal lobules (right hemisphere 864 voxel cluster; left hemisphere, 1947 voxel cluster). Transcranial magnetic stimulation over the right ( trained) primary motor cortex yielded a 58.6% mean increase in a measure of motor evoked potential amplitude, as recorded at the left abductor pollicis brevis muscle. Cortical thickness analyses based on structural MRI suggested changes in the right precentral gyrus, right post central gyrus, right dorsolateral prefrontal cortex and potentially the right supplementary motor area. Such findings are consistent with LTP-like neuroplastic changes in areas that were already responsible for finger sequence execution, rather than improved recruitment of previously non-utilised tissue.

neuroscience↗