Untangling Trustworthiness and Uncertainty in Science: Implications for Science Education.

This article focuses on uncertainty-ways in which scientists recognize and analyze limits in their studies and conclusions. We distinguish uncertainty from (un)trustworthiness-ways in which scientific reports can be affected by conscious deception or unconscious bias. Scientific journal articles typically include analyses and quantifications of uncertainty in both quantitative forms (e.g., error bars, ranges of predictions, statistical tests) and qualitative forms (e.g., alternate hypotheses, limitations of studies, questions for future research). These analyses of uncertainty are often incorporated into reports from scientific organizations and responsible scientific journalism. We argue that a critical goal of science education should be to help students understand how science may be employed as an uncertain and limited, yet still useful tool for informing decisions about socioscientific problems. When members of the public are insufficiently prepared to understand analyses and quantifications of uncertainty, the consequences are manifest in public skepticism about science and inadequately informed decision-making about socioscientific issues. We describe current design work in science education that includes a worthwhile emphasis on helping students to recognize and leverage uncertainty in their own data and models. Additional important work can enable students to develop proficiency in seeking out and understanding analyses of continuing uncertainty in media accounts of scientific conclusions and predictions.

Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

A Comparison of Conventional and Tri-Polar EEG Electrodes for Decoding Real and Imaginary Finger Movements from One Hand.

The representations of different fingers in the sensorimotor cortex are largely overlapped, which necessitate a good signal-to-noise ratio (SNR) and high spatial resolution to classify individual finger movements from one hand. Electroencephalography (EEG) recorded with disc electrodes has low SNR and poor spatial resolution. The surface Laplacian has been applied to EEG to improve the spatial resolution and selectivity of the surface electrical activity recording. Tri-polar concentric ring electrodes (TCREs) were shown to estimate the Laplacian automatically with better spatial resolution than disc electrodes. For this work, movement-related potentials (MRPs) were recorded from four TCREs and disc electrodes while 13 subjects performed real and imaginary finger movements. The MRP signals recorded with the TCREs have significantly less mutual information and coherence between neighboring locations compared to disc electrodes. The results also show that signals from TCREs generated higher accuracy compared to disc electrodes. It further shows that TCREs using temporal EEG data as features yield an average accuracy of [Formula: see text]% and [Formula: see text]% for real and imaginary finger movements, respectively, which is significantly higher than utilizing EEG spectral power changes in [Formula: see text] and [Formula: see text] bands as features. Similarly, with the disc electrodes, it achieved highest accuracy of [Formula: see text]% and [Formula: see text]% for real and imaginary finger movements, respectively, with temporal EEG data feature.

Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation.

The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics in BCI (also called brain-machine interface) research. Workshops covered foundational topics such as hardware development and signal analysis algorithms, new and imaginative topics such as BCI for virtual reality and multi-brain BCIs, and translational topics such as clinical applications and ethical assumptions of BCI development. BCI research is expanding in the diversity of applications and populations for whom those applications are being developed. BCI applications are moving toward clinical readiness as researchers struggle with the practical considerations to make sure that BCI translational efforts will be successful. This paper summarizes each workshop, providing an overview of the topic of discussion, references for additional information, and identifying future issues for research and development that resulted from the interactions and discussion at the workshop.

Developing an Analytical Framework to Characterize Student Reasoning about Complex Processes.

Real-world processes are complex and require ideas from multiple disciplines to be explained. However, many science courses offer limited opportunities for students to synthesize scientific ideas into coherent explanations. In this study, we investigated how students constructed causal explanations of complex phenomena to better understand the ways they approach this practice. We interviewed 12 undergraduate science majors and asked them to explain real-world phenomena. From these interviews, we developed a characterization framework that described the reasoning patterns we found. In this framework, we identified three explanatory frames that differentiated the kinds of explanations students provided: a colloquial frame, wherein participants activated conceptual resources based on personal experience using everyday language; an emerging mechanistic frame, wherein participants used scientific concepts in semicoherent ways; and a causal mechanistic frame, wherein participants cohesively drew upon scientific conceptual resources to construct mechanistic explanations. Overall, the causal mechanistic frame was the least prevalent frame invoked by students. Instead, many drew on an emerging mechanistic frame and struggled to identify and apply scientific concepts to real-world scenarios. We advocate for incorporating opportunities to reason about real-world phenomena into undergraduate science curricula to provide students with experience integrating scientific concepts to explain real-world phenomena.

Auditory priming improves neural synchronization in auditory-motor entrainment.

Neurophysiological research has shown that auditory and motor systems interact during movement to rhythmic auditory stimuli through a process called entrainment. This study explores the neural oscillations underlying auditory-motor entrainment using electroencephalography. Forty young adults were randomly assigned to one of two control conditions, an auditory-only condition or a motor-only condition, prior to a rhythmic auditory-motor synchronization condition (referred to as combined condition). Participants assigned to the auditory-only condition auditory-first group) listened to 400 trials of auditory stimuli presented every 800 ms, while those in the motor-only condition (motor-first group) were asked to tap rhythmically every 800 ms without any external stimuli. Following their control condition, all participants completed an auditory-motor combined condition that required tapping along with auditory stimuli every 800 ms. As expected, the neural processes for the combined condition for each group were different compared to their respective control condition. Time-frequency analysis of total power at an electrode site on the left central scalp (C3) indicated that the neural oscillations elicited by auditory stimuli, especially in the beta and gamma range, drove the auditory-motor entrainment. For the combined condition, the auditory-first group had significantly lower evoked power for a region of interest representing sensorimotor processing (4-20 Hz) and less total power in a region associated with anticipation and predictive timing (13-16 Hz) than the motor-first group. Thus, the auditory-only condition served as a priming facilitator of the neural processes in the combined condition, more so than the motor-only condition. Results suggest that even brief periods of rhythmic training of the auditory system leads to neural efficiency facilitating the motor system during the process of entrainment. These findings have implications for interventions using rhythmic auditory stimulation.

Workshops of the Sixth International Brain-Computer Interface Meeting: brain-computer interfaces past, present, and future.

The Sixth International Brain-Computer Interface (BCI) Meeting was held 30 May-3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain-machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. BCI research is growing and expanding in the breadth of its applications, the depth of knowledge it can produce, and the practical benefit it can provide both for those with physical impairments and the general public. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and highlighting important issues and calls for action to support future research and development.

Social affiliation and contact patterns among white-tailed deer in disparate landscapes: implications for disease transmission.

In social species, individuals contact members of the same group much more often than those of other groups, particularly for contacts that could directly transmit disease agents. This disparity in contact rates violates the assumptions of simple disease models, hinders disease spread between groups, and could decouple disease transmission from population density. Social behavior of white-tailed deer has important implications for the long-term dynamics and impact of diseases such as bovine tuberculosis and chronic wasting disease (CWD), so expanding our understanding of their social system is important. White-tailed deer form matrilineal groups, which inhabit stable home ranges that overlap somewhat with others-a pattern intermediate between mass-action and strict territoriality. To quantify how group membership affects their contact rates and document the spectrum of social affiliation, we analyzed location data from global positioning system (GPS) collars on female and juvenile white-tailed deer in 2 study areas: near Carbondale in forest-dominated southern Illinois (2002-2006) and near Lake Shelbyville in agriculture-dominated central Illinois (2006-2009). For each deer dyad (i.e., 2 individual deer with sufficient overlapping GPS data), we measured space-use overlap, correlation of movements, direct contact rate (simultaneous GPS locations < 10 m apart), and indirect contact rate (GPS locations < 10 m apart when offset by 1 or 3 days). Direct contact rates were substantially higher for within-group dyads than between-group dyads, but group membership had little apparent effect on indirect contact rates. The group membership effect on direct contact rates was strongest in winter and weakest in summer, with no apparent difference between study areas. Social affiliations were not dichotomous, with some deer dyads showing loose but positive affiliation. Even for obvious within-group dyads, their strength of affiliation fluctuated between years, seasons, and even days. Our findings highlight the poor fit between deer behavior and simple models of disease transmission and, combined with previous infection data, suggest that direct contact is the primary driver of CWD transmission among free-living female and juvenile white-tailed deer.

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

The Fifth International Brain-Computer Interface (BCI) Meeting met June 3-7th, 2013 at the Asilomar Conference Grounds, Pacific Grove, California. The conference included 19 workshops covering topics in brain-computer interface and brain-machine interface research. Topics included translation of BCIs into clinical use, standardization and certification, types of brain activity to use for BCI, recording methods, the effects of plasticity, special interest topics in BCIs applications, and future BCI directions. BCI research is well established and transitioning to practical use to benefit people with physical impairments. At the same time, new applications are being explored, both for people with physical impairments and beyond. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and high-lighting important issues for future research and development.

Connections between student explanations and arguments from evidence about plant growth.

We investigate how students connect explanations and arguments from evidence about plant growth and metabolism-two key practices described by the Next Generation Science Standards. This study reports analyses of interviews with 22 middle and high school students postinstruction, focusing on how their sense-making strategies led them to interpret-or misinterpret-scientific explanations and arguments from evidence. The principles of conservation of matter and energy can provide a framework for making sense of phenomena, but our results show that some students reasoned about plant growth as an action enabled by water, air, sunlight, and soil rather than a process of matter and energy transformation. These students reinterpreted the hypotheses and results of standard investigations of plant growth, such as van Helmont's experiment, to match their own understanding of how plants grow. Only the more advanced students consistently interpreted mass changes in plants or soil as evidence of movement of matter. We also observed that a higher degree of scaffolding during some of the interview questions allowed mid-level students to improve their responses. We describe our progress and challenges developing teaching materials with scaffolding to improve students' understanding of plant growth and metabolism.

On-farm mitigation of transmission of tuberculosis from white-tailed deer to cattle: literature review and recommendations.

The Animal Industry Division of the Michigan Department of Agriculture and Rural Development (MDARD) has been challenged with assisting farmers with modifying farm practices to reduce potential for exposure to Mycobacterium bovis from wildlife to cattle. The MDARD recommendations for on-farm risk mitigation practices were developed from experiences in the US, UK and Ireland and a review of the scientific literature. The objectives of our study were to review the present state of knowledge on M. bovis excretion, transmission, and survival in the environment and the interactions of wildlife and cattle with the intention of determining if the current recommendations by MDARD on farm practices are adequate and to identify additional changes to farm practices that may help to mitigate the risk of transmission. This review will provide agencies with a comprehensive summary of the scientific literature on mitigation of disease transmission between wildlife and cattle and to identify lacunae in published research.

Evaluation of remote delivery of Passive Integrated Transponder (PIT) technology to mark large mammals.

Methods to individually mark and identify free-ranging wildlife without trapping and handling would be useful for a variety of research and management purposes. The use of Passive Integrated Transponder technology could be an efficient method for collecting data for mark-recapture analysis and other strategies for assessing characteristics about populations of various wildlife species. Passive Integrated Transponder tags (PIT) have unique numbered frequencies and have been used to successfully mark and identify mammals. We tested for successful injection of PIT and subsequent functioning of PIT into gelatin blocks using 4 variations of a prototype dart. We then selected the prototype dart that resulted in the least depth of penetration in the gelatin block to assess the ability of PIT to be successfully implanted into muscle tissue of white-tailed deer (Odocoileus virginianus) post-mortem and long-term in live, captive Rocky Mountain elk (Cervus elaphus). The prototype dart with a 12.7 mm (0.5 inch) needle length and no powder charge resulted in the shallowest mean (± SD) penetration depth into gelatin blocks of 27.0 mm (± 5.6 mm) with 2.0 psi setting on the Dan-Inject CO(2)-pressured rifle. Eighty percent of PIT were successfully injected in the muscle mass of white-tailed deer post-mortem with a mean (± SD) penetration depth of 22.2 mm (± 3.8 mm; n = 6). We injected PIT successfully into 13 live, captive elk by remote delivery at about 20 m that remained functional for 7 months. We successfully demonstrated that PIT could be remotely delivered in darts into muscle mass of large mammals and remain functional for >6 months. Although further research is warranted to fully develop the technique, remote delivery of PIT technology to large mammals is possible using prototype implant darts.

Exploring undergraduates' understanding of photosynthesis using diagnostic question clusters.

We present a diagnostic question cluster (DQC) that assesses undergraduates' thinking about photosynthesis. This assessment tool is not designed to identify individual misconceptions. Rather, it is focused on students' abilities to apply basic concepts about photosynthesis by reasoning with a coordinated set of practices based on a few scientific principles: conservation of matter, conservation of energy, and the hierarchical nature of biological systems. Data on students' responses to the cluster items and uses of some of the questions in multiple-choice, multiple-true/false, and essay formats are compared. A cross-over study indicates that the multiple-true/false format shows promise as a machine-gradable format that identifies students who have a mixture of accurate and inaccurate ideas. In addition, interviews with students about their choices on three multiple-choice questions reveal the fragility of students' understanding. Collectively, the data show that many undergraduates lack both a basic understanding of the role of photosynthesis in plant metabolism and the ability to reason with scientific principles when learning new content. Implications for instruction are discussed.

EEG character identification using stimulus sequences designed to maximize mimimal hamming distance.

In this study, we have improved upon the P300 speller Brain-Computer Interface paradigm by introducing a new character encoding method. Our concept in detection of the intended character is not based on a classification of target and nontarget responses, but based on an identifaction of the character which maximize the difference between P300 amplitudes in target and nontarget stimuli. Each bit included in the code corresponds to flashing character, '1', and non-flashing, '0'. Here, the codes were constructed in order to maximize the minimum hamming distance between the characters. Electroencephalography was used to identify the characters using a waveform calculated by adding and subtracting the response of the target and non-target stimulus according the codes respectively. This stimulus presentation method was applied to a 3×3 character matrix, and the results were compared with that of a conventional P300 speller of the same size. Our method reduced the time until the correct character was obtained by 24%.

Critical issues in state-of-the-art brain-computer interface signal processing.

This paper reviews several critical issues facing signal processing for brain-computer interfaces (BCIs) and suggests several recent approaches that should be further examined. The topics were selected based on discussions held during the 4th International BCI Meeting at a workshop organized to review and evaluate the current state of, and issues relevant to, feature extraction and translation of field potentials for BCIs. The topics presented in this paper include the relationship between electroencephalography and electrocorticography, novel features for performance prediction, time-embedded signal representations, phase information, signal non-stationarity, and unsupervised adaptation.

Dissociating the contributions of independent corticostriatal systems to visual categorization learning through the use of reinforcement learning modeling and Granger causality modeling.

We dissociated the contributions to learning of four corticostriatal "loops" (interacting striatal and cortical regions): motor (putamen and motor cortex), visual (posterior caudate and visual cortex), executive (anterior caudate and prefrontal cortex), and motivational (ventral striatum and ventromedial frontal cortex). Subjects learned to categorize individual repeated images into one of two arbitrary categories via trial and error. We identified (1) regions sensitive to correct categorization, categorization learning, and feedback valence; (2) regions sensitive to prediction error (violation of feedback expectancy) and reward prediction (expected feedback associated with category response) using reinforcement learning modeling; and (3) directed influences between regions using Granger causality modeling. Each loop showed a unique pattern of sensitivity to each of these factors. Both the motor and visual loops were involved in acquisition of categorization ability: activity during correct categorization increased across learning and was sensitive to reward prediction. However, the posterior caudate received directed influence from visual cortex, whereas the putamen exerted directed influence on motor cortex. The motivational and executive loops were involved in feedback processing: both regions were sensitive to feedback valence, which interacted with learning across scans. However, the motivational loop activity reflected prediction error, whereas executive loop activity reflected reward prediction, consistent with the executive loop role in integrating reward and action. Granger causality modeling found directed influences between striatal and cortical regions within each loop. Across loops, the motor loop exerted directed influence on the executive loop which is consistent with the role of the executive loop in integrating feedback with stimulus-response history.

Robust reinforcement learning control using integral quadratic constraints for recurrent neural networks.

The applicability of machine learning techniques for feedback control systems is limited by a lack of stability guarantees. Robust control theory offers a framework for analyzing the stability of feedback control loops, but for the integral quadratic constraint (IQC) framework used here, all components are required to be represented as linear, time-invariant systems plus uncertainties with, for IQCs used here, bounded gain. In this paper, the stability of a control loop including a recurrent neural network (NN) is analyzed by replacing the nonlinear and time-varying components of the NN with IQCs on their gain. As a result, a range of the NN's weights is found within which stability is guaranteed. An algorithm is demonstrated for training the recurrent NN using reinforcement learning and guaranteeing stability while learning.

Assessing students' ability to trace matter in dynamic systems in cell biology.

College-level biology courses contain many complex processes that are often taught and learned as detailed narratives. These processes can be better understood by perceiving them as dynamic systems that are governed by common fundamental principles. Conservation of matter is such a principle, and thus tracing matter is an essential step in learning to reason about biological processes. We present here multiple-choice questions that measure students' ability and inclination to trace matter through photosynthesis and cellular respiration. Data associated with each question come from students in a large undergraduate biology course that was undergoing a shift in instructional strategy toward making fundamental principles (such as tracing matter) a central theme. We also present findings from interviews with students in the course. Our data indicate that 1) many students are not using tracing matter as a tool to reason about biological processes, 2) students have particular difficulties tracing matter between systems and have a persistent tendency to interconvert matter and energy, and 3) instructional changes seem to be effective in promoting application of the tracing matter principle. Using these items as diagnostic tools allows instructors to be proactive in addressing students' misconceptions and ineffective reasoning.

BCI Meeting 2005--workshop on BCI signal processing: feature extraction and translation.

This paper describes the outcome of discussions held during the Third International BCI Meeting at a workshop charged with reviewing and evaluating the current state of and issues relevant to brain-computer interface (BCI) feature extraction and translation. The issues discussed include a taxonomy of methods and applications, time-frequency spatial analysis, optimization schemes, the role of insight in analysis, adaptation, and methods for quantifying BCI feedback.

Geometric subspace methods and time-delay embedding for EEG artifact removal and classification.

Generalized singular-value decomposition is used to separate multichannel electroencephalogram (EEG) into components found by optimizing a signal-to-noise quotient. These components are used to filter out artifacts. Short-time principal components analysis of time-delay embedded EEG is used to represent windowed EEG data to classify EEG according to which mental task is being performed. Examples are presented of the filtering of various artifacts and results are shown of classification of EEG from five mental tasks using committees of decision trees.