Pediatric Bone Age Assessment Using Deep Convolutional Neural Networks

Skeletal bone age assessment is a common clinical practice to diagnose endocrine and metabolic disorders in child development. In this paper, we describe a fully automated deep learning approach to the problem of bone age assessment using data from Pediatric Bone Age Challenge organized by RSNA 2017. The dataset for this competition is consisted of 12.6k radiological images of left hand labeled by the bone age and sex of patients. Our approach utilizes several deep learning architectures: U-Net, ResNet-50, and custom VGG-style neural networks trained end-to-end. We use images of whole hands as well as specific parts of a hand for both training and inference. This approach allows us to measure importance of specific hand bones for the automated bone age analysis. We further evaluate performance of the method in the context of skeletal development stages. Our approach outperforms other common methods for bone age assessment.Comment: 14 pages, 9 figure

Modulating motor learning through transcranial direct-current stimulation: An integrative view

Motor learning consists of the ability to improve motor actions through practice playing a major role in the acquisition of skills required for high-performance sports or motor function recovery after brain lesions. During the last decades, it has been reported that transcranial direct-current stimulation (tDCS), consisting in applying weak direct current through the scalp, is able of inducing polarity-specific changes in the excitability of cortical neurons. This low-cost, painless and well-tolerated portable technique has found a wide-spread use in the motor learning domain where it has been successfully applied to enhance motor learning in healthy individuals and for motor recovery after brain lesion as well as in pathological states associated to motor deficits. The main objective of this mini-review is to offer an integrative view about the potential use of tDCS for human motor learning modulation. Furthermore, we introduce the basic mechanisms underlying immediate and long-term effects associated to tDCS along with important considerations about its limitations and progression in recent years

Combining reward and M1 transcranial direct current stimulation enhances the retention of newly learnt sensorimotor mappings

Background: Reward-based feedback given during motor learning has been shown to improve the retention of the behaviour being acquired. Interestingly, applying transcranial direct current stimulation (tDCS) during learning over the primary motor cortex (M1), an area associated with motor retention, also results in enhanced retention of the newly formed motor memories. However, it remains unknown whether combining these distinct interventions result in an additive benefit of motor retention. Methods: We investigated whether combining both interventions while participants learned to account for a visuomotor transformation results in enhanced motor retention (total n = 56; each group n = 14). To determine whether these interventions share common physiological mechanisms underpinning learning, we assessed motor cortical excitability and inhibition (i.e. SICI) on a hand muscle before and after all participants learned the visuomotor rotation using their entire arm and hand. Results: We found that both the Reward-Stim (i.e. reward + tDCS) and Reward-Sham (i.e. reward-only) groups had increased retention at the beginning of the retention phase, indicating an immediate effect of reward on behaviour. However, each intervention on their own did not enhance retention when compared to sham, but rather, only the combination of both reward and tDCS demonstrated prolonged retention. We also found that only the Reward-Stim group had a significant reduction in SICI after exposure to the perturbation. Conclusions: We show that combining both interventions are additive in providing stronger retention of motor adaptation. These results indicate that the reliability and validity of using tDCS within a clinical context may depend on the type of feedback individuals receive when learning a new motor pattern

SICI during changing brain states: Differences in methodology can lead to different conclusions

Background Short-latency intracortical inhibition (SICI) is extensively used to probe GABAergic inhibitory mechanisms in M1. Task-related changes in SICI are presumed to reflect changes in the central excitability of GABAergic pathways. Usually, the level of SICI is evaluated using a single intensity of conditioning stimulus so that inhibition can be compared in different brain states. Objective Here, we show that this approach may sometimes be inadequate since distinct conclusions can be drawn if a different CS intensity is used. Methods We measured SICI using a range of CS intensities at rest and during a warned simple reaction time task. Conclusions Our results show that SICI changes that occurred during the task could be either larger or smaller than at rest depending on the intensity of the CS. These findings indicate that careful interpretation of results are needed when a single intensity of CS is used to measure task-related physiological changes

Bioclimatology, structure, and conservation perspectives of Quercus pyrenaica, Acer opalus subsp. Granatensis, and Corylus avellana deciduous forests on Mediterranean bioclimate in the South-Central part of the Iberian Peninsula

The plant variability in the southern Iberian Peninsula consists of around 3500 different taxa due to its high bioclimatic, geographic, and geological diversity. The deciduous forests in the southern Iberian Peninsula are located in regions with topographies and specific bioclimatic conditions that allow for the survival of taxa that are typical of cooler and wetter bioclimatic regions and therefore represent the relict evidence of colder and more humid paleoclimatic conditions. The floristic composition of 421 samples of deciduous forests in the south-central part of the Iberian Peninsula were analyzed. The ecological importance index (IVI) was calculated, where the most important tree species were Quercuspyrenaica, Aceropalus subsp. Granatensis, and Corylusavellana. These species are uncommon in the south-central part of the Iberian Peninsula, forming forests of little extension. An analysis of the vertical distribution of the species (stratum) shows that the majority of the species of stratum 3 (hemicriptophics, camephytes, geophites, and nanophanerophytes) are characteristic of deciduous forests, and their presence is positively correlated with high values of bioclimatic variables related to humidity and presence of water in the soil (nemoral environments), while they are negatively correlated with high values of bioclimatic variables related to high temperatures, evapotranspiration, and aridity. This work demonstrates that several characteristic deciduous forest taxa are more vulnerable to disappearance due to the loss of their nemoral conditions caused by gaps in the tree or shrub canopy. These gaps lead to an increase in evapotranspiration, excess insolation, and a consequent loss of water and humidity in the microclimatic conditions.info:eu-repo/semantics/publishedVersio

Gesture and speech in maternal input to children with Down's syndrome

Background: Despite recent interest in relationships between maternal gesture and speech and communicative development in typically developing (M) children, little work has examined either speech or gesture in mothers of children with Down's syndrome (DS). Aims: To compare aspects of speech and gesture production by mothers of children with DS with that of mothers of TD children. Methods & Procedures: Participants were five mothers of children with DS (mean chronological age (CA)=47.6 months; mean mental age (MA,)=22.4 months) and five mothers of TD children. To equate for expressive language ability, children in the TD and DS groups were individually matched on the basis of: (1) gender; (2) correspondence between the TD child's chronological age and the DS child's language age; and (3) observed expressive vocabulary size. Each mother-child dyad was videotaped for approximately 30 min during free play. Data analyses focused on: (1) the number and types (speech only, gesture only, mixed) of maternal utterances; (2) the gesture types (deictic, iconic, conventional, emphatic); and (3) for mixed utterances, the structure and the temporal patterning of spoken and gestured components. Outcomes & Results: Relative to mothers of TD children, mothers of children with DS produced significantly fewer utterances overall, but the distribution of utterance types did not differ between the two groups. Relative to mothers of TD children, mothers of children with DS used proportionately more deictic gestures and made more frequent use of SHOWING. Mothers of TD children produced more POINTING gestures. Finally, mothers of children with DS produced a significantly higher proportion of utterances consisting of a single gesture and a single verbal utterance; in contrast to mothers of TD children, more complex structures (one gesture with multiple verbal utterances, one verbal utterance with multiple gestures) were never observed. Within the category of utterances consisting of a gesture and a single verbal utterance, mothers of children with DS tended to produce gestures that were held throughout the complete verbal utterance, while the gestures of mothers of TD children tended to co-occur with only a portion of the utterance. Conclusions: The findings suggest that mothers of children with DS adjust their communication to the developmental status of their child. Results are discussed in terms of the role of gesture in maternal communication and in the regulation of mother-child interaction

LifeCLEF 2016: Multimedia Life Species Identification Challenges

International audienceUsing multimedia identification tools is considered as one of the most promising solutions to help bridge the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g., iSpot, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipment have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching real world requirements. The LifeCLEF lab proposes to evaluate these challenges around 3 tasks related to multimedia information retrieval and fine-grained classification problems in 3 domains. Each task is based on large volumes of real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders to reflect realistic usage scenarios. For each task, we report the methodology, the data sets as well as the results and the main outcom