Gabriella Antonucci

Prof. Gabriella Antonucci

Dept of Psychology University of Rome Sapienza
orcid

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 2002 in Archives of Physical Medicine and Rehabilitation
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GAGabriella Antonucci
Gabriella Antonucci
TATeresa Aprile
Teresa Aprile
SPStefano Paolucci
Stefano Paolucci

3 January 2021 in Brain Sciences
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TZTommasa Zagaria
Tommasa Zagaria
GAGabriella Antonucci
Gabriella Antonucci
SBSerafino Buono
Serafino Buono
MRMarilena Recupero
Marilena Recupero
Pierluigi ZoccolottiPierluigi Zoccolotti
Pierluigi Zoccolotti
(1) Background: We made a comprehensive evaluation of executive functions (EFs) and attention processes in a group of adolescents and young adults with mild intellectual disability (ID). (2) Methods: 27 adolescents and young adults (14 females and 13 males) with ID, aged between 15.1 and 23 years (M = 17.4; SD = 2.04), were compared to a control group free of cognitive problems and individually matched for gender and age. (3) Results: As for EFs, individuals with ID were severely impaired on all subtests of the Behavioral Assessment of Dysexecutive Syndrome (BADS) battery. However, we also found appreciable individual differences, with eight individuals (approximately 30%) scoring within normal limits. On the attention tests, individuals with ID were not generally slower but presented specific deficits only on some attention tests (i.e., Choice Reaction Times, Color Naming and Color–Word Interference, and Shifting of Attention for Verbal and for Visual Targets).The role of a global factor (i.e., cognitive speed) was modest in contributing to the group differences; i.e., when present, group differences were selectively associated with specific task manipulations, not global differences in cognitive speed. (4) Conclusions: The study confirmed large group differences in EFs; deficits in attentional processing were more specific and occurred primarily in tasks taxing the selective dimension of attention, with performance on intensive tasks almost entirely spared.

29 August 2021 in Brain Sciences
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Marco IosaMarco Iosa
Marco Iosa
Giovanni MoroneGiovanni Morone
Giovanni Morone
GAGabriella Antonucci
Gabriella Antonucci
SPStefano Paolucci
Stefano Paolucci
There is a large body of literature reporting the prognostic factors for a positive outcome of neurorehabilitation performed in the subacute phase of stroke. Despite the recent development of algorithms based on neural networks or cluster analysis for the identification of these prognostic factors, the literature lacks a rigorous comparison among classical regression, neural network, and cluster analysis. Moreover, the three methods have rarely been tested on a sample independent from that in which prognostic factors have been identified. This study aims at providing this comparison on a wide sample of data (1522 patients) and testing the results on an independent sample (1000 patients) using 30 variables. The accuracy was similar among regression, neural network, and cluster analyses on the analyzed sample (76.6%, 74%, and 76.1%, respectively), but on the test sample, the accuracy of neural network decreased (70.1%). The three models agreed in identifying older age, severe impairment, unilateral spatial neglect, and total anterior circulation infarcts as important prognostic factors. The binary regression analysis also provided solid results in the test sample, especially in terms of specificity (81.8%). Cluster analysis also showed a high sensitivity in the test sample (82.6%) and allowed a meaningful easy-to-use classification tree to be obtained.

29 March 2023 in Journal of Clinical Medicine
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RGRoberto de giorgi
Roberto de giorgi
AFAntonio Fortini
Antonio Fortini
FAFederica Aghilarre
Federica Aghilarre
FGFederico Gentili
Federico Gentili
Giovanni MoroneGiovanni Morone
Giovanni Morone
Marco IosaMarco Iosa
Marco Iosa
In neurorehabilitation, some studies reported the effective use of art therapy for reducing psychological disorders and for enhancing physical functions and cognitive abilities. Neuroaesthetical studies showed that seeing an art masterpiece can spontaneously elicit a widespread brain arousal, also involving motor networks. To combine contemplative and performative benefits of art therapy protocols, we have developed an immersive virtual reality system, giving subjects the illusion that they are able to paint a copy of famous artistic paintings. We previously observed that during this virtual task, subjects perceived less fatigue and performed more accurate movements than when they were asked to color the virtual canvas. We named this upshot the Michelangelo effect. The aim of this study was to test the rehabilitative efficacy of our system. Ten patients with stroke in the subacute phase were enrolled and trained for one month with virtual art therapy (VAT) and physiotherapy. Their data were compared with those of ten patients matched for pathology, age and clinical parameters, trained only with conventional therapy for the same amount of time. The VAT group showed a significantly higher improvements in the Barthel Index score, a measure of independency in activities of daily living (66 ± 33% vs. 31 ± 28%, p = 0.021), and in pinching strength (66 ± 39% vs. 18 ± 33%, p = 0.008), with respect to the group treated with conventional rehabilitation.

26 June 2019 in PLOS ONE
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Augusto FuscoAugusto Fusco
Augusto Fusco
LILuigi Iasevoli
Luigi Iasevoli
MIMarco Iosa
Marco Iosa
Maria Chiara GallottaMaria Chiara Gallotta
Maria Chiara Gallotta
LPLuca Padua
Luca Padua
Laura GuidettiLaura Guidetti
Laura Guidetti
A new form of Motor Imagery (MI), called dynamic Motor Imagery (dMI) has recently been proposed. The dMI adds to conventional static Motor Imagery (sMI) the presence of simultaneous actual movements partially replicating those mentally represented. In a previous research conducted on young participants, dMI showed to be temporally closer than sMI in replicating the real performance for some specific locomotor conditions. In this study, we evaluated if there is any influence of the ageing on dMI. Thirty healthy participants were enrolled: 15 young adults (27.1±3.8 y.o.) and 15 older adults (65.9±9.6y.o.). The performance time and the number of steps needed to either walk to a target (placed at 10m from participants) or to imagine walking to it, were assessed. Parameters were measured for sMI, dMI and real locomotion (RL) in three different locomotor conditions: forward walking (FW), backward walking (BW), and lateral walking (LW). Temporal performances of sMI and dMI did not differ between RL in the FW, even if significantly different to each other (p = 0.0002). No significant differences were found for dMI with respect to RL for LW (p = 0.140) and BW (p = 0.438), while sMI was significantly lower than RL in LW (p<0.001). The p-value of main effect of age on participants’ temporal performances was p = 0.055. The interaction between age and other factors such as the type of locomotion (p = 0.358) or the motor condition (p = 0.614) or third level interaction (p = 0.349) were not statistically significant. Despite a slight slowdown in the performance of elderly compared to young participants, the temporal and spatial accuracy was better in dMI than sMI in both groups. Motor imagery processes may be strengthened by the feedback generated through dMI, and this effect appears to be unaffected by age.

1 April 2019 in Neuroscience Letters
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Marco IosaMarco Iosa
Marco Iosa
Daniela De BartoloDaniela De Bartolo
Daniela De Bartolo
Giovanni MoroneGiovanni Morone
Giovanni Morone
TBTommaso Boffi
Tommaso Boffi
EMElisa Mammucari
Elisa Mammucari
SPStefano Paolucci
Stefano Paolucci