40,319 research outputs found
Functional connectivity changes and their relationship with clinical disability and white matter integrity in patients with relapsing-remitting multiple sclerosis
Background and objective: To define the pathological substrate underlying disability in multiple sclerosis by evaluating the relationship of resting-state functional connectivity with microstructural brain damage, as assessed by diffusion tensor maging, and clinical impairments. Methods: Thirty relapsing–remitting patients and 24 controls underwent 3T-MRI; motor abilities were evaluated by using measures of walking speed, hand dexterity and balance capability, while information processing speed was evaluated by a paced auditory serial addiction task. Independent component analysis and tract-based spatial statistics were applied to RS-fMRI and diffusion tensor imaging data using FSL software. Group differences, after dual regression, and clinical correlations were modelled with GeneralLinear-Model and corrected for multiple comparisons. Results: Patients showed decreased functional connectivity in 5 of 11 resting-state-networks (cerebellar, executive-control, medial-visual, basal ganglia and sensorimotor), changes in inter-network correlations and widespread white matter microstructural damage. In multiple sclerosis, corpus callosum microstructural damage positively correlated with functional connectivity in cerebellar and auditory networks. Moreover, functional connectivity within the medial-visual network inversely correlated with information processing speed. White matter widespread microstructural damage inversely correlated with both the paced auditory serial addiction task and hand dexterity. Conclusions: Despite the within-network functional connectivity decrease and the widespread microstructural damage, the inter-network functional connectivity changes suggest a global brain functional rearrangement in multiple sclerosis. The correlation between functional connectivity alterations and callosal damage uncovers a link between functional and structural connectivity. Finally, functional connectivity abnormalities affect information processing speed rather than motor abilities
Resting state functional thalamic connectivity abnormalities in patients with post-stroke sleep apnoea: a pilot case-control study
OBJECTIVE: Sleep apnoea is common
after stroke, and has adverse effects on the
clinical outcome of affected cases. Its pathophysiological
mechanisms are only partially known. Increases
in brain connectivity after stroke might influence
networks involved in arousal modulation
and breathing control. The aim of this study was to
investigate the resting state functional MRI thalamic
hyper connectivity of stroke patients affected
by sleep apnoea (SA) with respect to cases not
affected, and to healthy controls (HC).
PATIENTS AND METHODS: A series of stabilized
strokes were submitted to 3T resting state
functional MRI imaging and full polysomnography.
The ventral-posterior-lateral thalamic nucleus was
used as seed.
RESULTS: At the between groups comparison
analysis, in SA cases versus HC, the regions significantly
hyper-connected with the seed were
those encoding noxious threats (frontal eye
field, somatosensory association, secondary visual
cortices). Comparisons between SA cases
versus those without SA, revealed in the former
group significantly increased connectivity with
regions modulating the response to stimuli independently
to their potentiality of threat (prefrontal,
primary and somatosensory association, superolateral
and medial-inferior temporal, associative
and secondary occipital ones). Further
significantly functionally hyper connections were
documented with regions involved also in the modulation
of breathing during sleep (pons, midbrain,
cerebellum, posterior cingulate cortices), and in
the modulation of breathing response to chemical
variations (anterior, posterior and para-hippocampal
cingulate cortices).
CONCLUSIONS: Our preliminary data support
the presence of functional hyper connectivity in
thalamic circuits modulating sensorial stimuli, in
patients with post-stroke sleep apnoea, possibly
influencing both their arousal ability and breathing
modulation during sleep
Towards a neural hierarchy of time scales for motor control
Animals show remarkable rich motion skills which are still far from realizable with robots. Inspired by the neural circuits which generate rhythmic motion patterns in the spinal cord of all vertebrates, one main research direction points towards the use of central pattern generators in robots. On of the key advantages of this, is that the dimensionality of the control problem is reduced. In this work we investigate this further by introducing a multi-timescale control hierarchy with at its core a hierarchy of recurrent neural networks. By means of some robot experiments, we demonstrate that this hierarchy can embed any rhythmic motor signal by imitation learning. Furthermore, the proposed hierarchy allows the tracking of several high level motion properties (e.g.: amplitude and offset), which are usually observed at a slower rate than the generated motion. Although these experiments are preliminary, the results are promising and have the potential to open the door for rich motor skills and advanced control
Complexity without chaos: Plasticity within random recurrent networks generates robust timing and motor control
It is widely accepted that the complex dynamics characteristic of recurrent
neural circuits contributes in a fundamental manner to brain function. Progress
has been slow in understanding and exploiting the computational power of
recurrent dynamics for two main reasons: nonlinear recurrent networks often
exhibit chaotic behavior and most known learning rules do not work in robust
fashion in recurrent networks. Here we address both these problems by
demonstrating how random recurrent networks (RRN) that initially exhibit
chaotic dynamics can be tuned through a supervised learning rule to generate
locally stable neural patterns of activity that are both complex and robust to
noise. The outcome is a novel neural network regime that exhibits both
transiently stable and chaotic trajectories. We further show that the recurrent
learning rule dramatically increases the ability of RRNs to generate complex
spatiotemporal motor patterns, and accounts for recent experimental data
showing a decrease in neural variability in response to stimulus onset
Dentate nucleus connectivity in adult patients with multiple sclerosis: functional changes at rest and correlation with clinical features
Background and objective: The dentate nucleus, which is the largest of the cerebellar nuclei, plays a critical role in movement and cognition. The aim of our study was to assess any changes in dentate functional connectivity (FC) in adult relapsing remitting multiple sclerosis (RR-MS) patients and to investigate possible clinical correlates.
Materials and methods: In all, 54 patients and 24 healthy subjects (HS) underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI), three-dimensional-T1-weighted and resting state (RS) functional images; they also underwent a cognitive evaluation, that is, attention and information processing speed, by means of the Paced Auditory Serial Addition Test (PASAT). Patients were also scored according to Expanded Disability Status Scale (EDSS). RS-MRI data were analysed using FMRIB Software Library (FSL) tools, with the seed-based method to identify dentate FC.
Results: When compared with HS, patients exhibited brain atrophy and widespread DTI abnormalities, as well as greater FC between the dentate nucleus and cortical areas, particularly in the frontal and parietal lobes. Within these areas, FC in patients correlated inversely with clinical impairment. Finally, FC correlated inversely with lesion load and microstructural brain damage.
Conclusion: Our findings indicate that dentate FC at rest is altered in MS patients. Whether these functional changes are induced by the disease and play a compensatory role remains to be established
Abnormal resting-state functional connectivity in progressive supranuclear palsy and corticobasal syndrome
Background: Pathological and MRI-based evidence suggests that multiple brain structures
are likely to be involved in functional disconnection between brain areas. Few studies
have investigated resting-state functional connectivity (rsFC) in progressive supranuclear
palsy (PSP) and corticobasal syndrome (CBS). In this study, we investigated within- and
between-network rsFC abnormalities in these two conditions.
Methods: Twenty patients with PSP, 11 patients with CBS, and 16 healthy subjects (HS)
underwent a resting-state fMRI study. Resting-state networks (RSNs) were extracted to
evaluate within- and between-network rsFC using the Melodic and FSLNets software
packages.
results: Increased within-network rsFC was observed in both PSP and CBS patients,
with a larger number of RSNs being involved in CBS. Within-network cerebellar rsFC
positively correlated with mini-mental state examination scores in patients with PSP.
Compared to healthy volunteers, PSP and CBS patients exhibit reduced functional
connectivity between the lateral visual and auditory RSNs, with PSP patients additionally
showing lower functional connectivity between the cerebellar and insular RSNs.
Moreover, rsFC between the salience and executive-control RSNs was increased in
patients with CBS compared to HS.
conclusion: This study provides evidence of functional brain reorganization in both PSP
and CBS. Increased within-network rsFC could represent a higher degree of synchronization
in damaged brain areas, while between-network rsFC abnormalities may mainly
reflect degeneration of long-range white matter fibers
Disrupted functional brain network organization in patients with obstructive sleep apnea.
IntroductionObstructive sleep apnea (OSA) subjects show impaired autonomic, affective, executive, sensorimotor, and cognitive functions. Brain injury in OSA subjects appears in multiple sites regulating these functions, but the integrity of functional networks within the regulatory sites remains unclear. Our aim was to examine the functional interactions and the complex network organization of these interactions across the whole brain in OSA, using regional functional connectivity (FC) and brain network topological properties.MethodsWe collected resting-state functional magnetic resonance imaging (MRI) data, using a 3.0-Tesla MRI scanner, from 69 newly diagnosed, treatment-naïve, moderate-to-severe OSA (age, 48.3 ± 9.2 years; body mass index, 31 ± 6.2 kg/m(2); apnea-hypopnea index (AHI), 35.6 ± 23.3 events/h) and 82 control subjects (47.6 ± 9.1 years; body mass index, 25.1 ± 3.5 kg/m(2)). Data were analyzed to examine FC in OSA over controls as interregional correlations and brain network topological properties.ResultsObstructive sleep apnea subjects showed significantly altered FC in the cerebellar, frontal, parietal, temporal, occipital, limbic, and basal ganglia regions (FDR, P < 0.05). Entire functional brain networks in OSA subjects showed significantly less efficient integration, and their regional topological properties of functional integration and specialization characteristics also showed declined trends in areas showing altered FC, an outcome which would interfere with brain network organization (P < 0.05; 10,000 permutations). Brain sites with abnormal topological properties in OSA showed significant relationships with AHI scores.ConclusionsOur findings suggest that the dysfunction extends to resting conditions, and the altered FC and impaired network organization may underlie the impaired responses in autonomic, cognitive, and sensorimotor functions. The outcomes likely result from the prominent structural changes in both axons and nuclear structures, which occur in the condition
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