The role of human primary motor cortex in the production of skilled finger sequences

Human primary motor cortex (M1) is essential for producing dexterous hand movements. Although distinct subpopulations of neurons are activated during single-finger movements, it remains unknown whetherM1also represents sequences of multiple finger movements. Using novel multivariate functional magnetic resonance imaging (fMRI) analysis techniques and combining evidence from both 3T and 7T fMRI data, we found that after 5 d of intense practice, premotor and parietal areas encoded the different movement sequences. There was little or no evidence for a sequence representation in M1. Instead, activity patterns in M1 could be fully explained by a linear combination of patterns for the constituent individual finger movements, with the strongest weight on the first finger of the sequence. Using passive replay of sequences, we show that this first-finger effect is due to neuronal processes involved in the active execution, rather than to a hemodynamic nonlinearity. These results suggest thatM1receives increased input from areas with sequence representations at the initiation of a sequence, but thatM1activity itself relates to the execution of component finger presses only. These results improve our understanding of the representation of finger sequences in the human neocortex after short-term training and provide important methodological advances for the study of long-term skill development

Pattern component modeling: A flexible approach for understanding the representational structure of brain activity patterns

Representational models specify how complex patterns of neural activity relate to visual stimuli, motor actions, or abstract thoughts. Here we review pattern component modeling (PCM), a practical Bayesian approach for evaluating such models. Similar to encoding models, PCM evaluates the ability of models to predict novel brain activity patterns. In contrast to encoding models, however, the activity of individual voxels across conditions (activity profiles) are not directly fitted. Rather, PCM integrates over all possible activity profiles and computes the marginal likelihood of the data under the activity profile distribution specified by the representational model. By using an analytical expression for the marginal likelihood, PCM allows the fitting of flexible representational models, in which the relative strength and form of the encoded feature spaces can be estimated from the data. We present here a number of different ways in which such flexible representational models can be specified, and how models of different complexity can be compared. We then provide a number of practical examples from our recent work in motor control, ranging from fixed models to more complex non-linear models of brain representations. The code for the fitting and cross-validation of representational models is provided in an open-source software toolbox

The Emotional Self-Efficacy Scale: Adaptation and Validation for Young Adolescents

Emotional self-efficacy (ESE) is an important aspect of emotional functioning, with current measures for children and adolescents focused on the measurement of self-beliefs in relation to the management of emotions. In the present study, we report the psychometric properties of the first adaptation of the Emotional Self-Efficacy Scale for youth (Youth-ESES) that measures additional aspects of ESE, such as perceiving and understanding emotions and helping others modulate their emotions. Participants were 192 young adolescents aged 11 to 13 years from a U.K. state school. They completed the Youth-ESES and measures of ability emotional intelligence (EI) and cognitive ability. Results support the same four-factor structure that has been previously documented using the adult version of the ESES, with the four subscales being largely independent from cognitive ability and only moderately related to ability EI. However, the four subscales were less differentiated in the present study compared with adult data previously published, suggesting that there is a strong general factor underlying young adolescents’ ESE scores. Overall, the results suggest that the adapted Youth-ESES can be reliably used with youth, and that confidence in how a young person feels about his or her emotional functioning remains distinct from emotional skill

Mapping the Integration of Sensory Information across Fingers in Human Sensorimotor Cortex

The integration of somatosensory signals across fingers is essential for dexterous object manipulation. Previous experiments suggest that this integration occurs in neural populations in the primary somatosensory cortex (S1). However, the integration process has not been fully characterized, as previous studies have mainly used 2-finger stimulation paradigms. Here, we addressed this gap by stimulating all 31 single- and multifinger combinations. We measured population-wide activity patterns evoked during finger stimulation in human S1 and primary motor cortex (M1) using 7T fMRI in female and male participants. Using multivariate fMRI analyses, we found clear evidence of unique nonlinear interactions between fingers. In Brodmann area (BA) 3b, interactions predominantly occurred between pairs of neighboring fingers. In BA 2, however, we found equally strong interactions between spatially distant fingers, as well as interactions between finger triplets and quadruplets. We additionally observed strong interactions in the hand area of M1. In both M1 and S1, these nonlinear interactions did not reflect a general suppression of overall activity, suggesting instead that the interactions we observed reflect rich, nonlinear integration of sensory inputs from the fingers. We suggest that this nonlinear finger integration allows for a highly flexible mapping from finger sensory inputs to motor responses that facilitates dexterous object manipulation.SIGNIFICANCE STATEMENT Processing of somatosensory information in primary somatosensory cortex (S1) is essential for dexterous object manipulation. To successfully handle an object, the sensorimotor system needs to detect complex patterns of haptic information, which requires the nonlinear integration of sensory inputs across multiple fingers. Using multivariate fMRI analyses, we characterized brain activity patterns evoked by stimulating all single- and multifinger combinations. We report that progressively stronger multifinger interactions emerge in posterior S1 and in the primary motor cortex (M1), with interactions arising between inputs from neighboring and spatially distant fingers. Our results suggest that S1 and M1 provide the neural substrate necessary to support a flexible mapping from sensory inputs to motor responses of the hand

Development and validation of the WEll-being and Satisfaction of CAREgivers of Children with Diabetes Questionnaire (WE-CARE)

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

A study of factors facilitating continued implementation of educational change.

EducationDoctor of Education (Ed.D.

Disodium (2RS,3SR)-tartrate

The asymmetric unit of the anhydrous title compound, 2Na+·C4H4O6 2−, contains two sodium cations and one tartrate anion. Each sodium ion is six coordinate, with bonding to six O atoms from both the carboxyl­ate and hydroxyl groups of the anion. A three-dimensional coordination network is formed with sodium ions stacking in layers along the c-axis direction. This network is supported by additional O—H⋯O hydrogen bonds

Thermal analysis of organically modified siloxane melting gels

Hybrid melting gels were prepared by a sol–gel process, starting with a mono-substituted siloxane and a disubstituted siloxane, methyltrimethoxysilane (MTES) together with dimethyldimethoxysilane (DMDES). Five gel compositions were prepared with concentrations between 50% MTES–50% DMDES and 75% MTES–25% DMDES (in mol.%)

Adoption of agricultural conservation practices in the United States: Evidence from 35 years of quantitative literature

This is a comprehensive review of all published, quantitative studies focused on adoption of agricultural conservation practices in the United States between 1982 and 2017. This review finds that, taken as a whole, few independent variables have a consistent statistically significant relationship with adoption. Analyses showed that variables positively associated with adoption include the farmer self-identifying primarily as stewardship motivated or otherwise nonfinancially motivated, environmental attitudes, a positive attitude toward the particular program or practice, previous adoption of other conservation practices, seeking and using information, awareness of programs or practices, vulnerable land, greater farm size, higher levels of income and formal education, engaging in marketing arrangements, and positive yield impact expected. Some variables often thought to be important, such as land tenure, did not emerge as consistently important in this cross-study review. Other variables, such as farmers\u27 sense of place, training, presence of institutional conditions supporting adoption, and the role of collective decision making are not measured in enough studies to draw conclusions but potentially have a relationship with adoption decisions. Implications for how to promote conservation adoption and directions for future research are discussed. Because positive attitudes and awareness of conservation programs or practices are positive predictors of adoption, practitioners should share benefits of specific practices and programs and leverage existing practice adoption. Further work to explore relationships between conservation adoption and the role of farmer identity, nuances of land tenure, and the influence of structural factors is needed. Moreover, we suggest that future research should focus on the impact of different messages and avenues of reaching farmers in order to continue to inform conservation practices. Future research should consider both individual and institutional factors that facilitate and constrain adoption

Fatigue in fibromyalgia: a conceptual model informed by patient interviews

Abstract Background Fatigue is increasingly recognized as an important symptom in fibromyalgia (FM). Unknown however is how fatigue is experienced by individuals in the context of FM. We conducted qualitative research in order to better understand aspects of fatigue that might be unique to FM as well as the impact it has on patients' lives. The data obtained informed the development of a conceptual model of fatigue in FM. Methods Open-ended interviews were conducted with 40 individuals with FM (US [n = 20], Germany [n = 10] and France [n = 10]). Transcripts were analyzed using qualitative methods based upon grounded theory to identify key themes and concepts. Results Participants were mostly female (70%) with a mean age of 48.7 years (range: 25-79). Thirty-one individuals (i.e., 77.5%) spontaneously described experiencing tiredness/lack of energy/fatigue due to FM. Participants discussed FM fatigue as being more severe, constant/persistent and unpredictable than normal tiredness. The conceptual model depicts the key elements of fatigue in FM from a patient perspective. This includes: an overwhelming feeling of tiredness (n = 17, 42.5%), not relieved by resting/sleeping (n = 15, 37.5%), not proportional to effort exerted (n = 25, 62.5%), associated with a feeling of weakness/heaviness (n = 20, 50%), interferes with motivation (n = 22, 55%), interferes with desired activities (n = 27, 67.5%), prolongs tasks (n = 15, 37.5%), and makes it difficult to concentrate (n = 21, 52.5%), think clearly (n = 12, 30%) or remember things (n = 9, 22.5%). Conclusion The majority of individuals with FM who participated in this study experience fatigue and describe it as more severe than normal tiredness.http://deepblue.lib.umich.edu/bitstream/2027.42/112483/1/12891_2010_Article_962.pd