Collective learning in schools described: building collective learning capacity

Processes of collective learning are expected to increase the professionalism of teachers and school leaders. Little is known about the processes of collective learning which take place in schools and about the way in which those processes may be improved. This paper describes a research into processes of collective learning at three primary schools. Processes of collective learning are described which took place in small teams in these schools. It is also pointed out which attempts can be made in order to reinforce these processes in the schools mentioned

Centering inclusivity in the design of online conferences: An OHBM-Open Science perspective

As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume

The influence of object-color knowledge on emerging object representations in the brain

The ability to rapidly and accurately recognize complex objects is a crucial function of the human visual system. To recognize an object, we need to bind incoming visual features, such as color and form, together into cohesive neural representations and integrate these with our preexisting knowledge about the world. For some objects, typical color is a central feature for recognition; for example, a banana is typically yellow. Here, we applied multivariate pattern analysis on time-resolved neuroimaging (MEG) data to examine how object-color knowledge affects emerging object representations over time. Our results from 20 participants (11 female) show that the typicality of object-color combinations influences object representations, although not at the initial stages of object and color processing. We find evidence that color decoding peaks later for atypical object-color combinations compared with typical object-color combinations, illustrating the interplay between processing incoming object features and stored object knowledge. Together, these results provide new insights into the integration of incoming visual information with existing conceptual object knowledge. SIGNIFICANCE STATEMENT To recognize objects, we have to be able to bind object features, such as color and shape, into one coherent representation and compare it with stored object knowledge. The MEG data presented here provide novel insights about the integration of incoming visual information with our knowledge about the world. Using color as a model to understand the interaction between seeing and knowing, we show that there is a unique pattern of brain activity for congruently colored objects (e.g., a yellow banana) relative to incongruently colored objects (e.g., a red banana). This effect of object-color knowledge only occurs after single object features are processed, demonstrating that conceptual knowledge is accessed relatively late in the visual processing hierarchy

Detecting mild traumatic brain injury for athletes using SSVEP classification : a case study

Mild traumatic brain injury (mTBI) can have detrimental impacts on the well-being of individuals, especially athletes with millions of injury cases reported per year. Nevertheless, the current assessment and diagnostic tools for mTBI have limitations due to their subjectivity and the lack of accessibility. This study aimed to evaluate the potential of machine learning algorithms in combination with steady-state visual evoked potentials (SSVEP) to provide mTBI diagnoses. The participants of this study included 36 athletes diagnosed with mTBI, aged 17–54, and 400 matched healthy controls without mTBI. Altogether, we extracted 51 SSVEP-based features from the collected observations and transformed them via principal component analysis (PCA) for feature reduction. Several machine learning algorithms were trained and validated using the transformed features for further analysis and comparison. Linear Discriminant Analysis (LDA) was found to be the best-performing classifier with 62 % balanced accuracy and has the potential to improve further with additional data. Overall, the findings of this study indicate that machine learning models have the potentials to be utilized as a diagnostic tool for mTBI when used with SSVEP data

Collective learning in schools described. Building collective learning capacity

Processes of collective learning are expected to increase the professionalism of teachers and school leaders. Little is known about the processes of collective learning which take place in schools and about the way in which those processes may be improved. This paper describes a research into processes of collective learning at three primary schools. Processes of collective learning are described which took place in small teams in these schools. It is also pointed out which attempts can be made in order to reinforce these processes in the schools mentioned

Collective learning in schools described. Building collective learning capacity

Processes of collective learning are expected to increase the professionalism of teachers and school leaders. Little is known about the processes of collective learning which take place in schools and about the way in which those processes may be improved. This paper describes a research into processes of collective learning at three primary schools. Processes of collective learning are described which took place in small teams in these schools. It is also pointed out which attempts can be made in order to reinforce these processes in the schools mentioned

Toward an individualized neural assessment of receptive language in children

Purpose We aimed to develop a noninvasive neural test of language comprehension to use with nonspeaking children for whom standard behavioral testing is unreliable (e.g., minimally verbal autism). Our aims were threefold. First, we sought to establish the sensitivity of two auditory paradigms to elicit neural responses in individual neurotypical children. Second, we aimed to validate the use of a portable and accessible electroencephalography (EEG) system, by comparing its recordings to those of a research-grade system. Third, in light of substantial interindividual variability in individuals' neural responses, we assessed whether multivariate decoding methods could improve sensitivity. Method We tested the sensitivity of two child-friendly covert N400 paradigms. Thirty-one typically developing children listened to identical spoken words that were either strongly predicted by the preceding context or violated lexical-semantic expectations. Context was given by a cue word (Experiment 1) or sentence frame (Experiment 2), and participants either made an overall judgment on word relatedness or counted lexical-semantic violations. We measured EEG concurrently from a research-grade system, Neuroscan's SynAmps2, and an adapted gaming system, Emotiv's EPOC+. Results We found substantial interindividual variability in the timing and topology of N400-like effects. For both paradigms and EEG systems, traditional N400 effects at the expected sensors and time points were statistically significant in around 50% of individuals. Using multivariate analyses, detection rate increased to 88% of individuals for the research-grade system in the sentences paradigm, illustrating the robustness of this method in the face of interindividual variations in topography. Conclusions There was large interindividual variability in neural responses, suggesting interindividual variation in either the cognitive response to lexical-semantic violations and/or the neural substrate of that response. Around half of our neurotypical participants showed the expected N400 effect at the expected location and time points. A low-cost, accessible EEG system provided comparable data for univariate analysis but was not well suited to multivariate decoding. However, multivariate analyses with a research-grade EEG system increased our detection rate to 88% of individuals. This approach provides a strong foundation to establish a neural index of language comprehension in children with limited communication

BioMAV: Bio-inspired intelligence for autonomous flight

Item does not contain fulltextThis paper aims to contribute to research on biologically inspired micro air vehicles in two ways: (i) it explores a novel repertoire of behavioral modules which can be controlled through finite state machines (FSM) and (ii) elementary movement detectors (EMD) are combined with a center/ surround edge detection algorithm to yield improved edge information used for object detection. Both methods will be assessed in the context of the IMAV 2011 pylon challenge.IMAV201

BioMAV: Bio-inspired intelligence for autonomous ?ight

This paper aims to contribute to research on biologically inspired micro air vehicles in two ways: (i) it explores a novel repertoire of behavioral modules which can be controlled through ?nite state machines (FSM) and (ii) elementary movement detectors (EMD) are combined with a center/surround edge detection algorithm to yield improved edge information used for object detection. Both methods will be assessed in the context of the IMAV 2011 pylon challenge