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The history of mathematics provides several examples of the use of fingers to count or calculate. These observations converge with developmental data showing that fingers play a critical role in the acquisition of arithmetic knowledge. Further studies evidenced specific interference of finger movements with arithmetic problem solving in adults, raising the question of whether or not finger and number manipulations rely on common brain areas. In the present study, functional magnetic resonance imaging (fMRI) was used to investigate the possible overlap between the brain areas involved in mental arithmetic and those involved in finger discrimination. Solving subtraction and multiplication problems was found to increase cerebral activation bilaterally in the horizontal part of the intraparietal sulcus (hIPS) and in the posterior part of the superior parietal lobule (PSPL). Finger discrimination was associated with increased activity in a bilateral occipito-parieto-precentral network extending from the extrastriate body area to the primary somatosensory and motor cortices. A conjunction analysis showed common areas for mental arithmetic and finger representation in the hIPS and PSPL bilaterally. Voxelwise correlations further showed that finger discrimination and mental arithmetic induced a similar pattern of activity within the parietal areas only. Pattern similarity was more important for the left than for the right hIPS and for subtraction than for multiplication. These findings provide the first evidence that the brain circuits involved in finger representation also underlie arithmetic operations in adults. ► Mental arithmetic and finger discrimination rely on common parietal areas in adults. ► Parietal activation induced by finger discrimination is not hand-specific. ► Voxelwise correlations between tasks are used to explore further the neural overlap. ► Neural overlap varies as a function of hemisphere and arithmetic operation. ► Finger representations might offer a support for arithmetic operations.

Transcranial direct current stimulation (tDCS) has the potential to modulate spatial attention by enhancing the activity in one hemisphere relative to the other. This study aims to inform neurorehabilitation strategies for spatial attention disorders by investigating the impact of tDCS on the performance of healthy participants. Unlike prior research that focused on visual detection, we extended the investigation to visual search and visual imagery using computerized neuropsychological tests. Forty-eight participants had to actively search for targets in space (visual search) and notice differences between two mental images (visual imagery). Anodal stimulation was administered over the left parietal cortex for half of the participants and over the right parietal cortex for the other half. The results showed that tDCS modulated spatial attention in visual search but not in visual imagery. In the sham condition, visual search was characterized by a leftward bias in the selection of the first target and a left asymmetry in the overall spatial distribution of cancelled targets. Parietal tDCS modulated the initial leftward bias, enhancing it (more lateral) during right anodal stimulation and reducing it (more central) during left anodal stimulation. However, this effect was not reflected in the spatial distribution of the cancelled targets. The overall visual search performance marginally improved during right anodal stimulation, as evidenced by a greater percentage of cancelled targets compared to sham. Finally, the results revealed no left-right asymmetries in the visual imagery task, either after sham or anodal stimulation. The specific effect of parietal tDCS on the initiation of visual search offers a new perspective for targeted neurorehabilitation strategies and provides further insight into the different sensitivity of visual search measures classically used in brain-lesioned patients.

What mechanisms underlie facial expression recognition? A popular hypothesis holds that efficient facial expression recognition cannot be achieved by visual analysis alone but additionally requires a mechanism of motor simulation — an unconscious, covert imitation of the observed facial postures and movements. Here, we first discuss why this hypothesis does not necessarily follow from extant empirical evidence. Next, we report experimental evidence against the central premise of this view: we demonstrate that individuals can achieve normotypical efficient facial expression recognition despite a congenital absence of relevant facial motor representations and, therefore, unaided by motor simulation. This underscores the need to reconsider the role of motor simulation in facial expression recognition.

Skilled tool use and object manipulation critically relies on the ability to scale anticipatorily the grip force (GF) in relation to object dynamics. This predictive behaviour entails that the nervous system is able to store, and then select, the appropriate internal representation of common object dynamics, allowing GF to be applied in parallel with the arm motor commands. Although psychophysical studies have provided strong evidence supporting the existence of internal representations of object dynamics, known as \"internal models\", their neural correlates are still debated. Because functional neuroimaging studies have repeatedly designated the supplementary motor area (SMA) as a possible candidate involved in internal model implementation, we used repetitive transcranial magnetic stimulation (rTMS) to interfere with the normal functioning of left or right SMA in healthy participants performing a grip-lift task with either hand. TMS applied over the left, but not right, SMA yielded an increase in both GF and GF rate, irrespective of the hand used to perform the task, and only when TMS was delivered 130-180 ms before the fingers contacted the object. We also found that both left and right SMA rTMS led to a decrease in preload phase durations for contralateral hand movements. The present study suggests that left SMA is a crucial node in the network processing the internal representation of object dynamics although further experiments are required to rule out that TMS does not affect the GF gain. The present finding also further substantiates the left hemisphere dominance in scaling GF.

This paper aims to highlight the new research and significant advances in our understanding of links between coastal habitat quality/quantity/diversity and the diversity of fisheries species and other mobile aquatic species (hereafter nekton) that use them within coastal landscapes. This topic is quite diverse owing to the myriad of habitat types found in coastal marine waters and the variety of life history strategies fisheries species and nekton use in these environments. Thus, we focus our review on five selective but relevant topics, habitat templates, essential fish habitat, habitat mosaics/habitat connectivity, transitory/ephemeral habitat, and the emerging/maturing approaches to the study of fish-habitat systems as a roadmap to its development. We have highlighted selected important contributions in the progress made on each topic to better identify and quantify landscape scale interactions between living biota and structured habitats set within a dynamic landscape.

Machine-learning diagnostic systems are widely used to detect abnormal conditions in electrical equipment. Training robust and accurate diagnostic systems is challenging because only small databases of abnormal-condition data are available. However, the performance of the diagnostic systems depends on the quantity and quality of the data. The training database can be augmented utilizing data augmentation techniques that generate synthetic data to improve diagnostic performance. However, existing data augmentation techniques are generic methods that do not include additional information in the synthetic data. In this paper, we develop a model-based data augmentation technique integrating computer-implementable electromechanical models. Synthetic normal- and abnormal-condition data are generated with an electromechanical model and a stochastic parameter value sampling method. The model-based data augmentation is showcased to detect an abnormal condition of a distribution transformer. First, the synthetic data are compared with the measurements to verify the synthetic data. Then, ML-based diagnostic systems are created using model-based data augmentation and are compared with state-of-the-art diagnostic systems. It is shown that using the model-based data augmentation results in an improved accuracy compared to state-of-the-art diagnostic systems. This holds especially true when only a small abnormal-condition database is available.

Objective: Neuropsychological studies suggest that the ability to compensate for the presence of spatial neglect highly depends on the attentional resources a patient can rely on. The present research aimed to study neglect in situations where attentional resources are limited due to multitasking. Method: We examined two patients more than 3 years after a right-hemispheric stroke. Both had received neuropsychological rehabilitation for left neglect and did not show any impairment in standard tests. We used a dual-task paradigm combining a peripheral target detection task with a central shape recognition task. Peripheral targets could appear in left/right positions but also in lower/upper positions. Results: In patient #1, dual-task condition exacerbated left neglect and extinction. Patient #2 did not show any sign of neglect along the horizontal axis, but omitted half of the lower targets when they were presented simultaneously with upper targets under dual-task condition. This behavior reflects altitudinal extinction as the detection of single targets appearing either in upper or lower position was preserved. Conclusion: The present findings show that dual-tasking is a sensitive tool for the quantitative and qualitative assessment of spatial attention deficits, which are often overlooked by standard methods, especially in chronic stage. (JINS, 2019, 25, 644–653)

Prospective judgments about one’s capability to perform an action are assumed to involve mental simulation of the action. Previous studies of motor imagery suggest this simulation is supported by a large fronto-parietal network including the motor system. Experiment 1 used fMRI to assess the contribution of this fronto-parietal network to judgments about one’s capacity to grasp objects of different sizes between index and thumb. The neural network underlying prospective graspability judgments overlapped the fronto-parietal network involved in explicit motor imagery of grasping. However, shared areas were located in the right hemisphere, outside the motor cortex, and were also activated during perceptual length judgments, suggesting a contribution to object size estimate rather than motor simulation. Experiment 2 used TMS over the motor cortex to probe transient excitability changes undetected with fMRI. Results show that graspability judgments elicited a selective increase of excitability in the thumb and index muscles, which was maximal before the object display and intermediate during the judgment. Together, these findings suggest that prospective action judgments do not rely on the motor system to simulate the action per se but to refresh the memory of one’s maximal grip aperture and facilitate its comparison with object size in right fronto-parietal areas.

Background The Bioinformatics Resource Manager (BRM) is a web-based tool developed to facilitate identifier conversion and data integration for Homo sapiens (human), Mus musculus (mouse), Rattus norvegicus (rat), Danio rerio (zebrafish), and Macaca mulatta (macaque), as well as perform orthologous conversions among the supported species. In addition to providing a robust means of identifier conversion, BRM also incorporates a suite of microRNA (miRNA)-target databases upon which to query target genes or to perform reverse target lookups using gene identifiers. Results BRM has the capability to perform cross-species identifier lookups across common identifier types, directly integrate datasets across platform or species by performing identifier retrievals in the background, and retrieve miRNA targets from multiple databases simultaneously and integrate the resulting gene targets with experimental mRNA data. Here we use workflows provided in BRM to integrate RNA sequencing data across species to identify common biomarkers of exposure after treatment of human lung cells and zebrafish to benzo[ a ]pyrene (BAP). We further use the miRNA Target workflow to experimentally determine the role of miRNAs as regulators of BAP toxicity and identify the predicted functional consequences of miRNA-target regulation in our system. The output from BRM can easily and directly be uploaded to freely available visualization tools for further analysis. From these examples, we were able to identify an important role for several miRNAs as potential regulators of BAP toxicity in human lung cells associated with cell migration, cell communication, cell junction assembly and regulation of cell death. Conclusions Overall, BRM provides bioinformatics tools to assist biologists having minimal programming skills with analysis and integration of high-content omics’ data from various transcriptomic and proteomic platforms. BRM workflows were developed in Java and other open-source technologies and are served publicly using Apache Tomcat at https://cbb.pnnl.gov/brm/ .

Two cryptic species of haploporid digeneans belonging in Saccocoelioides are described from Costa Rica: one from a poeciliid fish, Poecilia gillii, and the other from a characid fish, Astyanax aeneus. Traditional morphological features are examined and found to be largely inefficient for differentiating among the new species and 20 New World congeners. Comparison of ribosomal DNA sequences among the 2 new species, 2 North American, 4 Middle American, and 3 South American species of Saccocoelioides, including the type-species Saccocoelioides nanii from Argentina and Saccocoelioides sogandaresi from Texas, is effective in differentiating among these species. A Bayesian inference analysis is conducted using a concatenated alignment of the same 2 ribosomal gene regions from 35 species belonging in the Haploporoidea and rooted by the atractotrematid Isorchis anomalus. The analysis provides stronger support for a close relationship between species in Saccocoelioides and Intromugil; thus, Intromugil is transferred from the Waretrematinae to the Chalcinotrematinae. Additionally, interrelationships among 11 species of Saccocoelioides are resolved and reveal a distinct genetic rift suggesting the presence of 2 distinct lineages within the genus, 1 containing the type-species and the other containing a group of species that more closely resemble other genera in the subfamily. Taxonomy of Saccocoelioides is discussed, and observations made during the present study justify taking several taxonomic actions: new combinations are proposed for Saccocoelioides tilapiae n. comb., formerly in the now-defunct Culuwiya, and Saccocoelioides ruedasueltensis n. comb., formerly in Chalcinotrema; Saccocoelioides guaporense nomen novem is proposed for Lecithobotrioides elongatus; Saccocoelioides papernai is considered a junior subjective synonym of Saccocoelioides overstreeti; Saccocoelioides godoyi is considered a junior subjective synonym of Saccocoelioides szidati; Saccocoelioides magnorchis and Saccocoelioides saccodontis are considered species inquirendae; and Saccocoelioides adelae is considered a nomen nudum. Four new hosts are reported for Saccocoelioides cichlidorum: Amphilophus lyonsi, Amatitlania nigrofasciatus, Amatitlania septemfasciatus, and Hypsophrys nicaraguensis. Molecular data call into question some existing species identifications in Saccocoelioides and reveal that molecular tools combined with traditional taxonomy are required for accurately identifying species in the genus. Twenty-two species of Saccocoelioides are formally accepted, but it is noted that as new molecular data become available, some of these species may be transferred to other genera in the subfamily.