Biology subjects

Daniele Marinazzo

Publications and source records attributed to Daniele Marinazzo.

4 recordsLinked to original sources

bioRxiv2016

Enhanced pre-frontal functional-structural networks to support behavioural deficits after traumatic brain injury

Traumatic brain injury (TBI) affects its structural connectivity, triggering the re-organization of structural-functional circuits in a manner that remains poorly understood. We studied the re-organization of brain networks after TBI, taking advantage of a computational method based on magnetic resonance imaging (MRI) including diffusion-weighted imaging in combination with functional resting state data obtained from the blood-oxygenation-level-dependent T2* signal. We enrolled young participants who had suffered moderate to severe TBI (N=14, age 13.14 {+/-} 3.25 years), comparing them to young typically developing control participants (N=27, age 15.04 {+/-} 2.26 years). We found increased functional and structural connectivity within a cortico-subcortical network in TBI patients brains that involved prefrontal cortex, anterior cingulate gyrus, orbital gyrus and caudate nucleus. In comparison to control participants, TBI patients increased functional connectivity from prefrontal regions towards two different networks: 1) a subcortical network including part of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulum and precuneus; and 2) a task-positive network, involving regions of the dorsal attention system together with the dorsolateral and ventrolateral prefrontal regions. We also found the increased prefrontal activation in TBI patients was correlated with some behavioural indices, such as the amount of body sway, whereby patients with worse balance activated frontal regions more strongly. The enhanced prefrontal activation found in TBI patients may provide the structural scaffold for stronger cognitive control of certain behavioural functions, consistent with the observation that various motor tasks are performed less automatically following TBI and that more cognitive control is associated with such actions.

Neuroscience↗

bioRxiv2015

Hemodynamic response function in resting brain: disambiguating neural events and autonomic effects

It has been shown that resting state brain dynamics can be characterized by looking at sparse blood-oxygen-level dependent (BOLD) events, which can be retrieved by point process analysis. Cardiac activity can also induce changes in the BOLD signal, thus affect both the number of these events and the mapping between neural events and BOLD signal, namely the hemodynamic response. To isolate neural activity and autonomic effects, we compare the resting state hemodynamic response retrieved by means of a point process analysis with and without deconvolving the cardiac fluctuations. Brainstem and the surrounding cortical area (such as precuneus, insula etc.) are found to be significantly affected by cardiac pulses. Methodological and physiological implications are then discussed.

Neuroscience↗

bioRxiv2015

Structural constraints to information flow within cortical circuits: a TMS/EEG-dMRI study

Transcranial magnetic stimulation (TMS) has been used for more than 20 years to investigate brain function by perturbing and observing the consequent behavioral, pathophysiological and electrophysiological modulations. These latter, mainly measured by high-density electroencephalography (hd-EEG), revealed signatures of the functional organization in a brain network. In order to unveil the nature and the underlying mechanism of these signatures, we here mapped TMS-induced hd-EEG changes onto changes in information flow and brain structural architecture, using multimodal modeling of source reconstructed TMS/hd-EEG recordings and diffusion magnetic resonance imaging (dMRI) tractography in a cohort of awake healthy volunteers. We observed that the relationship between information flow and structural connections depend on the stimulation site and on the frequency of the TMS-induced brain rhythms. These findings highlight the importance of taking into account the dynamics of different local oscillations when investigating the mechanisms for integration and segregation of information in the human brain. Our whole-brain analysis sheds light on the function-structure organization of the brain network after TMS, and on the huge variety of information contained in it. TMS/EEG dMRI directed functional connectivity structural connectivity structure-function brain information flow

Neuroscience↗

bioRxiv2015

Estimating directed connectivity from cortical recordings and reconstructed sources

In cognitive neuroscience, electrical brain activity is most commonly recorded at the scalp. In order to infer the contributions and connectivity of underlying neuronal sources within the brain, it is necessary to reconstruct sensor data at the source level. Several approaches to this reconstruction have been developed, thereby solving the so-called implicit inverse problem (Michel et al. 2004). However, a unifying premise against which to validate these source reconstructions is seldom available. The dataset provided in this work, in which brain activity is simultaneously recorded on the scalp (non-invasively) by electroencephalography (EEG) and on the cortex (invasively) by electrocorticography (ECoG), can be of a great help in this direction. These multimodal recordings were obtained from a macaque monkey under wakefulness and sedation. Our primary goal was to establish the connectivity architecture between two sources of interest (frontal and parietal), and to assess how their coupling changes over the conditions. We chose these sources because previous studies have shown that the connections between them are modified by anaesthesia (Boly et al. 2012). Our secondary goal was to evaluate the consistency of the connectivity results when analyzing sources recorded from invasive data (128 implanted ECoG sources) and source activity reconstructed from scalp recordings (19 EEG sensors) at the same locations as the ECoG sources. We conclude that the directed connectivity in the frequency domain between cortical sources reconstructed from scalp EEG is qualitatively similar to the connectivity inferred directly from cortical recordings, using both data-driven (directed transfer function; DTF) and biologically grounded (dynamic causal modelling; DCM) methods. Furthermore, the connectivity changes identified were consistent with previous findings (Boly et al. 2012). Our findings suggest that inferences about directed connectivity based upon non-invasive electrophysiological data have construct validity in relation to invasive recordings.

Neuroscience↗