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The focus of this paper is on the functional role of brain regions focusing on their modular architecture and individual variability. Our main assumption is that the more variable anti-correlation patterns reflect random connections, while the more conserved ones play a functional role. Within this framework, we expanded on previous results using a different database and a different methodological approach. Aiming to identify the role of specific functional connections within a global network organization which includes subnetworks, we found that the fronto-parietal module acts as the main source of anti-correlations. In addition, the pre-frontal regions (namely: frontal middle, frontal middle orbital, frontal inferior triangular) and the parietal inferior region are highly conserved and, at the same time, act as highly connected nodes, thus confirming their importance in functional modulation.

The aim of this report is to unveil specific prognostic factors for retroperitoneal sarcoma (RPS) patients by univariate and multivariate statistical techniques. A phase I-II study on localized RPS treated with high-dose ifosfamide and radiotherapy followed by surgery (ISG-STS 0303 protocol) demonstrated that chemo/radiotherapy was safe and increased the 3-year relapse-free survival (RFS) with respect to historical controls. Of 70 patients, twenty-six developed local, 10 distant, and 5 combined relapse. Median disease-free interval (DFI) was 29.47 months. According to a discriminant function analysis, DFI, histology, relapse pattern, and the first treatment approach at relapse had a statistically significant prognostic impact. Based on scientific literature and clinical expertise, clinicopathological data were analyzed using both a supervised and an unsupervised classification method to predict the prognosis, with similar sample sizes (66 and 65, resp., in casewise approach and 70 in mean-substitution one). This is the first attempt to predict patients’ prognosis by means of multivariate statistics, and in this light, it looks noticable that (i) some clinical data have a well-defined prognostic value, (ii) the unsupervised model produced comparable results with respect to the supervised one, and (iii) the appropriate combination of both models appears fruitful and easily extensible to different clinical contexts.

Anticorrelations among brain areas observed in fMRI acquisitions under resting state are not endowed with a well-defined set of characters. Some evidence points to a possible physiological role for them, and simulation models showed that it is appropriate to explore such an issue. A large-scale brain representation was considered, implementing an agent-based brain-inspired model (ABBM) incorporating the SER (susceptible-excited-refractory) cyclic mechanism of state change. The experimental data used for validation included 30 selected functional images of healthy controls from the 1000 Functional Connectomes Classic collection. To study how different fractions of positive and negative connectivities could modulate the model efficiency, the correlation coefficient was systematically used to check the goodness-of-fit of empirical data by simulations under different combinations of parameters. The results show that a small fraction of positive connectivity is necessary to match at best the empirical data. Similarly, a goodness-of-fit improvement was observed upon addition of negative links to an initial pattern of only-positive connections, indicating a significant information intrinsic to negative links. As a general conclusion, anticorrelations showed that it is crucial to improve the performance of our simulation and, since these cannot be assimilated to noise, should be always considered in order to refine any brain functional model.

Goal: This minireview aims to highlight recent important aspects to consider and evaluate when passive brain–computer interface (pBCI) systems would be developed and used in operational environments, and remarks future directions of their applications. Methods: Electroencephalography (EEG) based pBCI has become an important tool for real-time analysis of brain activity since it could potentially provide covertly—without distracting the user from the main task—and objectively—not affected by the subjective judgment of an observer or the user itself—information about the operator cognitive state. Results: Different examples of pBCI applications in operational environments and new adaptive interface solutions have been presented and described. In addition, a general overview regarding the correct use of machine learning techniques (e.g., which algorithm to use, common pitfalls to avoid, etc.) in the pBCI field has been provided. Conclusion: Despite recent innovations on algorithms and neurotechnology, pBCI systems are not completely ready to enter the market yet, mainly due to limitations of the EEG electrodes technology, and algorithms reliability and capability in real settings. Significance: High complexity and safety critical systems (e.g., airplanes, ATM interfaces) should adapt their behaviors and functionality accordingly to the user’ actual mental state. Thus, technologies (i.e., pBCIs) able to measure in real time the user's mental states would result very useful in such “high risk” environments to enhance human machine interaction, and so increase the overall safety.

Several models defining different types of cognitive human behaviour are available. For this work, we have selected the Skill, Rule and Knowledge (SRK) model proposed by Rasmussen in 1983. This model is currently broadly used in safety critical domains, such as the aviation. Nowadays, there are no tools able to assess at which level of cognitive control the operator is dealing with the considered task, that is if he/she is performing the task as an automated routine (skill level), as procedures-based activity (rule level), or as a problem-solving process (knowledge level). Several studies tried to model the SRK behaviours from a Human Factor perspective. Despite such studies, there are no evidences in which such behaviours have been evaluated from a neurophysiological point of view, for example, by considering brain activity variations across the different SRK levels. Therefore, the proposed study aimed to investigate the use of neurophysiological signals to assess the cognitive control behaviours accordingly to the SRK taxonomy. The results of the study, performed on 37 professional Air Traffic Controllers, demonstrated that specific brain features could characterize and discriminate the different SRK levels, therefore enabling an objective assessment of the degree of cognitive control behaviours in realistic settings.

The anticorrelations in fMRI measurements are still not well characterized, but some new evidences point to a possible physiological role. We explored the topology of functional brain networks characterized by negative edgess and their possible alterations in schizophrenia, using functional images of 8 healthy subjects and 8 schizophrenic patients in a resting state condition. In order to minimize the insertion of artifactual negative correlations, the preprocessing of images was carried out by the CompCorr procedure, and the results compared with the Global Signal Regression (GSR) procedure. The degree distribution, the centrality, the efficiency and the rich-club behavior were used to characterize the functional brain network with negative links of healthy controls in comparison with schizophrenic patients. The results show that functional brain networks with both positive and negative values have a truncated power-law degree distribution. Moreover, although functional brain networks characterized by negative values have not small-world topology, they show a specific disassortative configuration: the more connected nodes tend to have fewer connections between them. This feature is lost using the GSR procedure. Finally, the comparison with schizophrenic patients showed a decreased (local and global) efficiency associated to a decreased connectivity among central nodes. As a conclusion, functional brain networks characterized by negative values, despite lacking a well defined topology, show specific features, different from random, and indicate an implication in the alterations associated to schizophrenia.

During leisure time, people can decide if they want to expose themselves to solar ultraviolet (UV) radiation and to what extent. While working, people do not have this choice. Outdoor workers are exposed to solar UV radiation (UVR) on a daily basis. This may pose a certain health risk, which can be estimated when the personal solar UVR exposure (PE) is known. During past decades, a variety of studies were conducted to measure PE of outdoor workers and our knowledge of the PE of outdoor workers has increased remarkably. As shown by this review, studies clearly indicate that PE of most outdoor workers exceeds the internationally proposed threshold limit value, which is comparable to 1.0 to 1.3 standard erythema dose (SED), respectively, to 1.1 to 1.5 UV Index received over one hour. Besides working in a high UVR environ, monotonic workflow (limited movement, nearly static posture) is a risk factor. In such cases, PE can be higher than ambient UVR. In this review, we provide also a list of milestones, depicting the progress and the most important findings in this field during the past 45 years. However, in many respects our knowledge is still rudimentary, for several reasons. Different measuring positions have been used so that measured PE is not comparable. Few studies were designed to enable the extension of measured PE to other locations or dates. Although the importance of a proper calibration of the measuring devices in respect to the changing solar spectrum was pointed out from the beginning, this is often not performed, which leads to high uncertainties in the presented PE levels. At the end of our review, we provide some key points, which can be used to evaluate the quality of a study respectively to support the design of future studies.

Tobacco constitutes a global emergency with totally preventable millions of deaths per year and smoking-related illnesses. Public service announcements (PSAs) are the main tool against smoking and by now their efficacy is still assessed through questionnaires and metrics, only months after their circulation. The present study focused on the young population, because at higher risk of developing tobacco addiction, investigating the reaction to the vision of Effective, Ineffective and Awarded antismoking PSAs through: electroencephalography (EEG), autonomic activity variation (Galvanic skin response-GSR- and Heart Rate-HR-) and Eye-Tracking (ET). The employed indices were: the EEG frontal alpha band asymmetry and the frontal theta; the Emotional Index (EI), deriving from the GSR and HR signals matching; the ET Visual Attention (VA) index, based on the ratio between the total time spent fixating an area of interest (AOI) and its area. Smokers expressed higher frontal alpha asymmetry values in comparison to non-smokers. Concerning frontal theta, Awarded PSAs reported the highest values in comparison to both Effective and Ineffective PSAs. EI results highlighted that lowest values were expressed by Heavy Smokers (HS), and Effective PSAs obtained the highest EI values. Finally, concerning the Effective PSAs, regression analysis highlighted a correlation between the number of cigarettes smoked by participants (independent variable) and frontal alpha asymmetry, frontal theta and EI values. ET results suggested that for the Ineffective PSAs the main focus were texts, while for the Effective and Awarded PSAs were the visual elements. Results support the use of methods aimed at assessing the physiological reaction for the evaluation of PSAs images, in particular when considering the smoking habits of target populations.

This contribution reports on the simulation of some dynamical events observed in the collective behavior of different kinds of populations, ranging from shape-changing cells in a Petri dish to functionally correlated brain areas in vivo. The unifying methodological approach, based upon a Multi-Agent Simulation (MAS) paradigm as incorporated in the NetLogo™ interpreter, is a direct consequence of the cornerstone that simple, individual actions within a population of interacting agents often give rise to complex, collective behavior.The discussion will mainly focus on the emergence and spreading of synchronous activities within the population, as well as on the modulation of the collective behavior exerted by environmental force-fields. A relevant section of this contribution is dedicated to the extension of the MAS paradigm to Brain Network models. In such a general framework some recent applications taken from the direct experience of the author, and exploring the activation patterns characteristic of specific brain functional states, are described, and their impact on the Systems-Biology universe underlined.

This contribution reports on the simulation of some dynamical events observed in the collective behavior of different kinds of populations, ranging from shape-changing cells in a Petri dish to functionally correlated brain areas in vivo. The unifying methodological approach, based upon a Multi-Agent Simulation (MAS) paradigm as incorporated in the NetLogo™ interpreter, is a direct consequence of the cornerstone that simple, individual actions within a population of interacting agents often give rise to complex, collective behavior.The discussion will mainly focus on the emergence and spreading of synchronous activities within the population, as well as on the modulation of the collective behavior exerted by environmental force-fields. A relevant section of this contribution is dedicated to the extension of the MAS paradigm to Brain Network models. In such a general framework some recent applications taken from the direct experience of the author, and exploring the activation patterns characteristic of specific brain functional states, are described, and their impact on the Systems-Biology universe underlined.

The taste is a vital sense in humans, because of its active role in regulating nutrition or avoiding harmful substances. Several studies showed the important role of the brain Pre-Frontal Cortex in decoding information coming from the gustatory system. It is also widely known, in neuroscientific literature, that the asymmetry of Pre-Frontal Cortex Activity is closely linked to the feeling of pleasantness experienced by the subject during sensorial stimulation. In this regard, from the electroencephalographic (EEG) signal it is possible to estimate the Approach/Withdrawal (AW) index, which has been largely investigated and validated in scientific literature, regarding visual, acoustic and olfactory stimuli.

Every day we face visual stimuli able to catch our attention, but this aspect becomes crucial if the visual material has the purpose to spread a message aimed at engaging the observer. In this framework, a worthy aspect is how to measure the "visual engagement" produced by visual stimuli exposure. To this purpose, in the present study, employing the eye tracking technique, an index of visual attention (VA) has been proposed, and applied to pictures belonging to antismoking public service announcements, so to investigate the saliency of health-promoting messages in a young sample. The VA index is a non-dimensional index, defined as the ratio between the percentage of the total time spent fixating an area of interest (AOI) weighted on the total time the picture is showed on the screen, and the percentage of the area occupied by the AOI weighted on the total dimension of the picture. It could be predicted that AOI reporting higher VA values will be the ones having more saliency. Three antismoking Public Service Announcements (PSAs) images have been selected for the study and for each of them were identified: i) "picture" (such as a young man with a sarcastic expression depicted while smoking a cigarette, or the image of a lady who underwent a tracheotomy) and ii) "writing" (text of the antismoking message) AOIs. Main results of the analysis revealed that writing AOIs obtained statistically significant higher VA values than visual AOIs (p=0.03), but these held true only for an ineffective PSA, probably because the text was not perceived as pertinent with the surrounding image. On the other hand, an effective PSA obtained higher VA values in response to visual than writing AOIs observation (p=0.02). The VA index appears therefore to represent a useful tool to measure the saliency of visual stimuli elements.

Minimally invasive surgery can be performed with robotic assistance, as evolution of laparoscopic surgery. Robots for assisted surgery are far from being user friendly and require extensive training. To this end, ad-hoc devices and experimental set-ups are needed. The da Vinci system is one of the most diffused surgical robotics technology. The aim of the study was two-fold: i) to propose a neurophysiological measure by which objectively assess the learning progress of the users by means of a simulator of the da Vinci system, and ii) to demonstrate the advantages of cognitive assessment with respect to the standard methodologies for the evaluation of training efficiency.

Advanced methodologies used for the biomedical signal interpretation allow using cerebral signals to assess important cognitive functions in humans. In the present study, as parameter of cerebral effort, has been employed the isolated effective coherence, in order to estimate the effective connectivity and network organization. The hypothesis was that the lower the number of inter-connections engaged, the lower the cerebral effort induced by the experimental condition. In the present research this index has been applied to test the reaction to the use of different cochlear implant processors (Freedom, CP810 and CP910 - Cochlear Ltd), with the aim to identify the most performing device during a word in noise recognition task. Results support the capability of identifying the device eliciting less brain area connections. In particular, the CP910 was the processor inducing the lower number of inter-connections among the tested ones. This investigation appeared to be worthy, since representing a tool to identify devices that would make available user's cognitive resources for additional tasks, a matter susceptible of generalization to various fields of application. The employment of the cerebral signals therefore open the way to the evaluation of the impact of different sensors and prosthetic devices, also using connectivity measures.

It is widely known, in neuroscientific literature, that the brain prefrontal cortex activity asymmetry is closely linked with the pleasantness emotion experienced by the subject during a sensorial stimulation. Thus, from the electroencephalographic (EEG) signal it is possible to estimate the approach/withdrawal index, and this index has been largely investigated and validated in scientific literature, regarding visual and acoustic stimuli. In this work, we present an innovative study aimed to prove, in a systematic way, that such brain AW index is actually correlated with the “pleasant” or “no-pleasant” perception also of olfactory stimuli, conveniently produced by standardised methods in the sensory specific scientific literature. In particular, we recorded the electroencephalographic (EEG) signal from a group, gender balanced, of 24 healthy and no-smokers subjects during the perception of ten different smells, presented by means of the “Screening test-odour identification” set (Sniffin’ sticks, Burghart). The cerebral AW indexes of all the subjects, for each odorous stimulus, were compared with the appreciation numeric score assessed by the subject during the experiment, by performing a statistical correlation test. Findings show that it is possible to evaluate the pleasantness or no-pleasantness of odorous substances by means of the analysis of EEG signals collected during the presentation of such substances, making way for new applications of such measure kind in experimental environments more and more ecological, as the typical ones of the marketing research areas.

In the last decades, it has been a fast-growing concept in the neuroscience field. The passive brain-computer interface (p-BCI) systems allow to improve the human-machine interaction (HMI) in operational environments, by using the covert brain activity (eg, mental workload) of the operator. However, p-BCI technology could suffer from some practical issues when used outside the laboratories. In particular, one of the most important limitations is the necessity to recalibrate the p-BCI system each time before its use, to avoid a significant reduction of its reliability in the detection of the considered mental states. The objective of the proposed study was to provide an example of p-BCIs used to evaluate the users' mental workload in a real operational environment. For this purpose, through the facilities provided by the Ecole Nationale de l'Aviation Civile of Toulouse (France), the cerebral activity of 12 professional air traffic control officers (ATCOs) has been recorded while performing high realistic air traffic management scenarios. By the analysis of the ATCOs' brain activity (electroencephalographic signal-EEG) and the subjective workload perception (instantaneous self-assessment) provided by both the examined ATCOs and external air traffic control experts, it has been possible to estimate and evaluate the variation of the mental workload under which the controllers were operating. The results showed (i) a high significant correlation between the neurophysiological and the subjective workload assessment, and (ii) a high reliability over time (up to a month) of the proposed algorithm that was also able to maintain high discrimination accuracies by using a low number of EEG electrodes (~3 EEG channels). In conclusion, the proposed methodology demonstrated the suitability of p-BCI systems in operational environments and the advantages of the neurophysiological measures with respect to the subjective ones.

Polysulphone (PS) dosimetry has been a widely used technique for more than 30 years to quantify the erythemally effective UV dose received by anatomic sites (personal exposure). The calibration of PS dosimeters is an important issue as their spectral response is different from the erythemal action spectrum. It is performed exposing a set of PS dosimeters on a horizontal plane and measuring the UV doses received by dosimeters using calibrated spectroradiometers or radiometers. In this study, data collected during PS field campaigns (from 2004 to 2006), using horizontal and differently inclined dosimeters, were analyzed to provide some considerations on the transfer of the horizontal calibration to differently inclined dosimeters, as anatomic sites usually are. The role of sky conditions, of the angle of incidence between the sun and the normal to the slope, and of the type of surrounding surface on the calibration were investigated. It was concluded that PS horizontal calibrations apply to differently inclined dosimeters for incidence angles up to approximately 70° and for surfaces excluding ones with high albedo. Caution should be used in the application of horizontal calibrations for cases of high-incidence angle and/or high albedo surfaces.

The dissection of phylogenetic and environmental components in biological evolution is one of the main themes of general biology. Here we propose an approach to this theme relying upon the comparison between a phylogenetic oriented metrics spanning the hemoglobin beta chains of different fishes and a more physiologically oriented metrics defining the same sequences in terms of the dynamical features of their hydrophobic distributions. By analyzing the set of sequences more similar to the Gadus morhua (Atlantic cod) hemoglobin beta chain, we were able to give a proof of concept of the possibility to discriminate the phylogenetic and environmental (evolutive convergence) components by the comparative analysis of the Clustal W (phylogenetics first) and Recurrence Quantification Analysis (physiology first) metrics in which the sequences were embedded. The use of a molecular system like hemoglobin playing a crucial role in fishes adaptation to environmental cues allowed us to span different levels of biological variability by means of the same paradigm. Starting from the reconstruction of the general taxonomy of vertebrate groups we went down to the exploitation of the peculiar role played by Met55Val and Lys62Ala polymorphisms in the beta1 hemoglobin chain of the Atlantic cod able to influence the geographical distribution of its various stocks.

Mountain sites experience enhanced UV radiation levels due to the concurrent effects of shorter radiation path-length, low aerosol load and high reflectivity of the snow surfaces. This study was encouraged by the possibility to collect original data of personal dose on a specific anatomical site (erythemally effective UV dose on the forehead) of two groups of volunteers (ski instructors and skiers) in the mountainous areas of Italy (the Alpine site of La Thuile-Les Suches in Valle d'Aosta region). Personal doses were assessed using polysulphone dosimetry. Exposure Ratio (ER), defined as the ratio between the personal dose and the corresponding ambient dose (i.e. erythemally weighted dose received by a horizontal surface) during the same exposure period was taken into account. In addition measuring skin colours as biological markers of individual response to UV exposure, was also carried out on the forearm and cheek of each volunteer before and after exposure. The median ER, taking into account the whole sample, is 0.60 in winter, with a range of 0.29 to 1.46, and 1.02 in spring, ranging from 0.46 to 1.72. No differences in ERs were found between skiers and instructors in spring while in winter skiers experienced lower values. Regarding skin colorimetric parameters the main result was that both skiers and instructors had on average significantly lower values of luminance after exposure i.e.~they became darker. It was found that the use of sunscreen and individual skin photo-type did not produce significant variations in ER across instructor/skier group by day and by seasons (p>0.05). It seems that sunscreen use only at the beginning of the exposure or in a few cases a couple of times during exposure (at difference with the specific instructions sheets), was not sufficient to change significantly skin colorimetric parameters across participants. In conclusion UV personal doses on the ski-fields are often significantly higher than those on horizontal surfaces and consistently more intense respect to personal doses received by sunbathers on the beach in central Italy (ER range: 0.09–0.42). Given the high levels of exposure observed in the present study, specific public health warnings with regards to the efficacy of sun-protection behaviours (proper application and re-application of sunscreen and protective measures such as hats and sun glasses) should be adopted.

Self-sustained oscillations are perhaps the most studied objects in science. The accomplishment of such a task reliably and accurately requires the presence of specific control mechanisms to face the presence of variable and largely unpredictable environmental stimuli and noise. Self-sustained oscillations of transcript abundance are, in fact, widespread and are not limited to the reproductive cycle but are also observed during circadian rhythms, metabolic cycles, developmental cycles and so on. To date, much of the literature has focused on the transcriptional machinery underlying control of the basic timing of transcript abundance. However, mRNA abundance is known to be regulated at the post-transcriptional level also and the relative contribution of the two mechanisms to gene-expression programmes is currently a major challenge in molecular biology. Here, we review recent results showing the relevance of the post-transcriptional regulation layer and present a statistical reanalysis of the yeast metabolic cycle using publicly available gene-expression and RNA-binding data. Taken together, the recent theoretical and experimental developments reviewed and the results of our reanalysis strongly indicate that regulation of mRNA stability is a widespread, phase-specific and finely tuned mechanism for the multi-layer control of gene expression needed to achieve high flexibility and adaptability to external and internal signals.

The present work intends to evaluate the dynamics of the cerebral networks during the preparation and the execution of the foot movement. In order to achieve this objective, we have used mathematical tools capable of estimating the cortical activity via high-resolution EEG techniques. Afterwards we estimated, the instantaneous relationships occurring among the time-series of sixteen regions of interest (ROIs) in the Alpha (7-12 Hz) and Beta (13-29 Hz) band through the adaptive multivariate autoregressive models. Eventually, we evaluated the weighted-topology of the cerebral networks by calculating some theoretical graph indexes. The results show that the main structural changes are encoded in the highest spectral contents (Beta band). In particular, during the execution of the foot movement the cingulate motor areas (CM) work as network "hubs" presenting a large amount of outgoing links to the other ROIs. Moreover, the connectivity pattern changes its structure according to the different temporal stages of the task. In particular, the communication between the ROIs reaches its highest level of efficiency during the preparation of the foot movement, as revealed by the "small-world" property of the network, which is characterized by the presence of abundant clustering connections combined with short average distances between the cortical areas.

We describe a set of computational tools able to estimate cortical activity and connectivity from high-resolution EEG and fMRI recordings in humans. These methods comprise the estimation of cortical activity using realistic geometry head volume conductor models and distributed cortical source models, followed by the evaluation of cortical connectivity between regions of interest coincident with the Brodmann areas via the use of Partial Directed Coherence. Connectivity patterns estimated on the cortical surface in different frequency bands are then imaged and interpreted with measures based on graph theory. These computational tools were applied on a set of EEG and fMRI data from a Stroop task to demonstrate the potential of the proposed approach. The present findings suggest that the methodology is able to identify differences in functional connectivity patterns elicited by different experimental tasks or conditions.

Static hemodynamic or neuroelectric images of brain regions activated during particular tasks do not convey the information of how these regions communicate to each other. Cortical connectivity estimation aims at describing these interactions as connectivity patterns which hold the direction and strength of the information flow between cortical areas. In this study, we attempted to estimate the causality between distributed cortical systems during a movement volition task in preparation for execution of simple movements by a group of normal healthy subjects and by a group of Spinal Cord Injured (SCI) patients. To estimate the causality between the spatial distributed patterns of cortical activity in the frequency domain, we applied a series of processing steps on the recorded EEG data. From the high-resolution EEG recordings we estimated the cortical waveforms for the regions of interest (ROIs), each representing a selected sensor group population. The solutions of the linear inverse problem returned a series of cortical waveforms for each ROI considered and for each trial analyzed. For each subject, the cortical waveforms were then subjected to Independent Component Analysis (ICA) pre-processing. The independent components obtained by the application of the ThinICA algorithm were further processed by a Partial Directed Coherence algorithm, in order to extract the causality between spatial cortical patterns of the estimated data. The source-target cortical dependencies found in the group of normal subjects were relatively similar in all frequency bands analyzed. For the normal subjects we observed a common source pattern in an ensemble of cortical areas including the right parietal and right lip primary motor areas and bilaterally the primary foot and posterior SMA areas. The target of this cortical network, in the Granger-sense of causality, was shown to be a smaller network composed mostly by the primary foot motor areas and the posterior SMA bilaterally. In the case of the SCI population, both the source and the target cortical patterns had larger sizes than in the normal population. The source cortical areas included always the primary foot and lip motor areas, often bilaterally. In addition, the right parietal area and the bilateral premotor area 6 were also involved. Again, the patterns remained substantially stable across the different frequency bands analyzed. The target cortical patterns observed in the SCI population had larger extensions when compared to the normal ones, since in most cases they involved the bilateral activation of the primary foot movement areas as well as the SMA, the primary lip areas and the parietal cortical areas.