Biology subjects

Liparoti, M.

Publications and source records attributed to Liparoti, M..

7 recordsLinked to original sources

bioRxiv2020

The structural connectome constrains fast brain dynamics

Brain activity during rest displays complex, rapidly evolving patterns in space and time. Structural connections comprising the human connectome are hypothesized to impose constraints on the dynamics of this activity. Here, we use magnetoencephalography (MEG) to quantify the extent to which fast neural dynamics in the human brain are constrained by structural connections inferred from diffusion MRI tractography. We characterize the spatio-temporal unfolding of whole-brain activity at the millisecond scale from source-reconstructed MEG data, estimating the probability that any two brain regions will significantly deviate from baseline activity in consecutive time epochs. We find that the structural connectome relates to, and likely affects, the rapid spreading of neuronal avalanches, evidenced by a significant association between these transition probabilities and structural connectivity strengths (r=0.37, p<0.0001). This finding opens new avenues to study the relationship between brain structure and neural dynamics.

neuroscience↗

bioRxiv2020

The effects of different frequencies of rhythmic acoustic stimulation on gait kinematics and trunk sway in healthy elderly population

The use of rhythmic acoustic stimulation (RAS) in improving gait and balance in healthy elderly subjects has been widely investigated. However, methodologies and results are often controversial. In this study, we hypothesize that both the kinematic features of gait and stability, depend on the frequency at which RAS is administered. Our aim was to observe, through 3D Gait Analysis, the effect of different types of RAS (at a fixed frequency or based on the average cadence of each subject) on both gait spatio-temporal parameters and stability. The latter was estimated through an innovative measure, the trunk displacement index (TDI) that we have recently implemented. We observed that the low frequencies RAS led to a general slowdown of gait, which did not provide any clear benefit and produced harmful effects on stability when the frequency became too low compared to the individual natural frequency. On the contrary, the high frequencies of RAS showed a slight acceleration of gait, accompanied by better stability (as documented by a lower TDI value), regardless of the type of RAS. Finally, the RAS equal to the individual natural cadence also produced an increase in stability.

neuroscience↗

bioRxiv2020

Functional brain network topology across the menstrual cycle is sex hormone dependent and correlates with the individual well-being

The menstrual cycle is known to influence the behaviour. The neuronal bases of this phenomenon are poorly understood. We hypothesized that hormones, might affect the large-scale organization of the brain functional networks and that, in turn, such changes might have behavioural correlates in terms of the affective state. To test our hypothesis, we took advantage of magnetoencephalography to investigate brain topology in early follicular, ovulatory and luteal phases, in twenty-four naturally-cycling women without signs of anxiety and/or depression. We show that in the alpha band the betweenness centrality (BC) of the right posterior cingulate gyrus (PCG) during the ovulatory phase is increased and the rise is predicted by the levels of estradiol. We also demonstrate that the increase in the BC is related to improved subjective well-being that, in turn, is correlated to the estradiol levels. The increased topological centrality of the PCG during the ovulatory phase could have implications in reproductive psychology.

neuroscience↗

bioRxiv2020

Time scale separation of information processing between sensory and associative regions

A hierarchy of local timescales with a back (sensory)-to-front (prefrontal) gradient reflects brain region specialization. However, cognitive processes emerge from the coordinated activity across regions, and the corresponding timescales should refer to the interactions rather than to regional activity. Using edgewise connectivity on magnetoencephalography signals, we demonstrate a reverse front-to-back gradient when non-local interactions are prominent. Thus, the timescales are dynamic and reconfigure between back-to-front and front-to-back patterns.

neuroscience↗

bioRxiv2020

Clinical connectome fingerprints of cognitive decline

Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain data. We hypothesize that dysregulation of brain activity in disease would reflect in worse subject identification. Hence, we propose a novel framework, Clinical Connectome Fingerprinting, to detect individual connectome features from clinical populations. We show that "clinical fingerprints" can map individual variations between elderly healthy subjects and patients undergoing cognitive decline in functional connectomes extracted from magnetoencephalography data. We find that identifiability is reduced in patients as compared to controls, and show that these connectivity features are predictive of the individual Mini-Mental State Examination (MMSE) score in patients. We hope that the proposed methodology can help in bridging the gap between connectivity features and biomarkers of brain dysfunction in large-scale brain networks.

neuroscience↗

bioRxiv2020

Loss of integration of brain netwroks after one night of sleep deprivation underlies worsening of attentive functions

The topology of brain networks changes according to environmental demands and can be described within the framework of graph theory. We hypothesized that 24-hours long sleep deprivation (SD) causes functional rearrangements of the brain topology so as to impair optimal communication, and that such rearrangements relate to the performance in specific cognitive tasks, namely the ones specifically requiring attention. Thirty-two young men underwent resting-state MEG recording and assessments of attention and switching abilities before and after SD. We found loss of integration of brain network and a worsening of attention but not of switching abilities. These results show that brain network changes due to SD affect switching abilities, worsened attention and induce large-scale rearrangements in the functional networks.

neuroscience↗

bioRxiv2020

A synthetic kinematic index of trunk displacement conveying the overall motor condition in Parkinson's disease

BACKGROUNDParkinsons disease (PD) is characterized by motor impairment, affecting quality of life and increasing fall risk, due to ineffective postural control. To this day, the diagnosis remains based on clinical approach. Similarly, motor evaluation is based on heterogeneous, operator-dependent observational criteria. A synthetic, replicable index to quantify motor impairment is still lacking. In this paper, we build upon the idea that the trunk is crucial in balance control. Hence, we have designed a new measure of postural stability which assesses the trunk displacement in relation to the center of mass, that we named trunk displacement index (TDI). METHODSTwenty-three PD patients and twenty-three healthy controls underwent clinical (UPDRS-III) and motor examination (3D gait analysis). The TDI was extracted from kinematic measurements using a stereophotogrammetric system. A correlation analysis was performed to assess the relationship of TDI with typical gait parameters, to verify its biomechanical value, and UPDRS-III, to observe its clinical relevance. Finally, its sensitivity was measured, comparing pre- and post-L-DOPA subclinical intake. RESULTSThe TDI showed significant correlations with many gait parameters, including both velocity and stability characteristics of gait, and with the UPDRS-III. Finally, the TDI resulted capable in discriminating between off and on state in PD, whereas typical gait parameters failed two show any difference between those two conditions. CONCLUSIONSOur results suggest that the TDI may be considered a highly sensitive biomechanical index, reflecting the overall motor condition in PD, and provided of clinical relevance due to the correlation with the clinical evaluation.

neuroscience↗