Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
Add more filters










Database
Language
Publication year range
1.
Nat Hum Behav ; 4(12): 1303-1312, 2020 12.
Article in English | MEDLINE | ID: mdl-33199859

ABSTRACT

Assessing the effectiveness of non-pharmaceutical interventions (NPIs) to mitigate the spread of SARS-CoV-2 is critical to inform future preparedness response plans. Here we quantify the impact of 6,068 hierarchically coded NPIs implemented in 79 territories on the effective reproduction number, Rt, of COVID-19. We propose a modelling approach that combines four computational techniques merging statistical, inference and artificial intelligence tools. We validate our findings with two external datasets recording 42,151 additional NPIs from 226 countries. Our results indicate that a suitable combination of NPIs is necessary to curb the spread of the virus. Less disruptive and costly NPIs can be as effective as more intrusive, drastic, ones (for example, a national lockdown). Using country-specific 'what-if' scenarios, we assess how the effectiveness of NPIs depends on the local context such as timing of their adoption, opening the way for forecasting the effectiveness of future interventions.


Subject(s)
Basic Reproduction Number/statistics & numerical data , COVID-19/prevention & control , Global Health/statistics & numerical data , Government , Artificial Intelligence , Datasets as Topic , Humans , Models, Theoretical
2.
Cogn Process ; 12(1): 23-31, 2011 Feb.
Article in English | MEDLINE | ID: mdl-21046191

ABSTRACT

The value of λ is one of the main issues debated in international usability studies. The debate is centred on the deficiencies of the mathematical return on investment model (ROI model) of Nielsen and Landauer (1993). The ROI model is discussed in order to identify the base of another model that, respecting Nielsen and Landauer's one, tries to consider a large number of variables for the estimation of the number of evaluators needed for an interface. Using the bootstrap model (Efron 1979), we can take into account: (a) the interface properties, as the properties at zero condition of evaluation and (b) the probability that the population discovery behaviour is represented by all the possible discovery behaviours of a sample. Our alternative model, named Bootstrap Discovery Behaviour (BDB), provides an alternative estimation of the number of experts and users needed for a usability evaluation. Two experimental groups of users and experts are involved in the evaluation of a website (http://www.serviziocivile.it). Applying the BDB model to the problems identified by the two groups, we found that 13 experts and 20 users are needed to identify 80% of usability problems, instead of 6 experts and 7 users required according to the estimation of the discovery likelihood provided by the ROI model. The consequence of the difference between the results of those models is that in following the BDB the costs of usability evaluation increase, although this is justified considering that the results obtained have the best probability of representing the entire population of experts and users.


Subject(s)
Statistics as Topic , Models, Theoretical
3.
Brain Res Bull ; 82(1-2): 46-56, 2010 Apr 29.
Article in English | MEDLINE | ID: mdl-20223285

ABSTRACT

Meditation refers to a family of complex emotional and attentional regulatory practices, which can be classified into two main styles - focused attention (FA) and open monitoring (OM) - involving different attentional, cognitive monitoring and awareness processes. In a functional magnetic resonance study we originally characterized and contrasted FA and OM meditation forms within the same experiment, by an integrated FA-OM design. Theravada Buddhist monks, expert in both FA and OM meditation forms, and lay novices with 10 days of meditation practice, participated in the experiment. Our evidence suggests that expert meditators control cognitive engagement in conscious processing of sensory-related, thought and emotion contents, by massive self-regulation of fronto-parietal and insular areas in the left hemisphere, in a meditation state-dependent fashion. We also found that anterior cingulate and dorsolateral prefrontal cortices play antagonist roles in the executive control of the attention setting in meditation tasks. Our findings resolve the controversy between the hypothesis that meditative states are associated to transient hypofrontality or deactivation of executive brain areas, and evidence about the activation of executive brain areas in meditation. Finally, our study suggests that a functional reorganization of brain activity patterns for focused attention and cognitive monitoring takes place with mental practice, and that meditation-related neuroplasticity is crucially associated to a functional reorganization of activity patterns in prefrontal cortex and in the insula.


Subject(s)
Attention/physiology , Brain , Cognition/physiology , Meditation , Adult , Brain/anatomy & histology , Brain/physiology , Buddhism/psychology , Humans , Magnetic Resonance Imaging/methods , Male , Meditation/psychology , Middle Aged , Psychomotor Performance/physiology
4.
Hum Brain Mapp ; 31(4): 567-80, 2010 Apr.
Article in English | MEDLINE | ID: mdl-19780042

ABSTRACT

The act of listening to speech activates a large network of brain areas. In the present work, a novel data-driven technique (the combination of independent component analysis and Granger causality) was used to extract brain network dynamics from an fMRI study of passive listening to Words, Pseudo-Words, and Reverse-played words. Using this method we show the functional connectivity modulations among classical language regions (Broca's and Wernicke's areas) and inferior parietal, somatosensory, and motor areas and right cerebellum. Word listening elicited a compact pattern of connectivity within a parieto-somato-motor network and between the superior temporal and inferior frontal gyri. Pseudo-Word stimuli induced activities similar to the Word condition, which were characterized by a highly recurrent connectivity pattern, mostly driven by the temporal lobe activity. Also the Reversed-Word condition revealed an important influence of temporal cortices, but no integrated activity of the parieto-somato-motor network. In parallel, the right cerebellum lost its functional connection with motor areas, present in both Word and Pseudo-Word listening. The inability of the participant to produce the Reversed-Word stimuli also evidenced two separate networks: the first was driven by frontal areas and the right cerebellum toward somatosensory cortices; the second was triggered by temporal and parietal sites towards motor areas. Summing up, our results suggest that semantic content modulates the general compactness of network dynamics as well as the balance between frontal and temporal language areas in driving those dynamics. The degree of reproducibility of auditory speech material modulates the connectivity pattern within and toward somatosensory and motor areas.


Subject(s)
Brain/physiology , Comprehension/physiology , Speech Perception/physiology , Acoustic Stimulation , Adult , Algorithms , Brain Mapping , Humans , Magnetic Resonance Imaging , Male , Models, Neurological , Neural Pathways/physiology , Pattern Recognition, Physiological/physiology , Signal Processing, Computer-Assisted , Speech
5.
Cogn Process ; 7(1): 42-52, 2006 Mar.
Article in English | MEDLINE | ID: mdl-16628465

ABSTRACT

One of the most important achievements in understanding the brain is that the emergence of complex behavior is guided by the activity of brain networks. To fully apply this theoretical approach fully, a method is needed to extract both the location and time course of the activities from the currently employed techniques. The spatial resolution of fMRI received great attention, and various non-conventional methods of analysis have previously been proposed for the above-named purpose. Here, we briefly outline a new approach to data analysis, in order to extract both spatial and temporal activities from fMRI recordings, as well as the pattern of causality between areas. This paper presents a completely data-driven analysis method that applies both independent components analysis (ICA) and the Granger causality test (GCT), performed in two separate steps. First, ICA is used to extract the independent functional activities. Subsequently the GCT is applied to the independent component (IC) most correlated with the stimuli, to indicate its causal relation with other ICs. We therefore propose this method as a promising data-driven tool for the detection of cognitive causal relationships in neuroimaging data.


Subject(s)
Cognition/physiology , Image Processing, Computer-Assisted , Magnetic Resonance Imaging/statistics & numerical data , Algorithms , Chi-Square Distribution , Data Interpretation, Statistical , Models, Neurological , Models, Statistical , Principal Component Analysis , Reproducibility of Results
SELECTION OF CITATIONS
SEARCH DETAIL
...