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Summary Radiological incidental findings (IFs) are previously undetected abnormalities which are unrelated to the original indication for imaging and are unexpectedly discovered. In brain magnetic resonance imaging (MRI), the prevalence of IFs is increasing. By reviewing the literature on IFs in brain MRI performed for research purposes and discussing ethical considerations of IFs, this paper provides an overview of brain IF research results and factors contributing to inconsistencies and considers how the consent process can be improved from an ethical perspective. We found that despite extensive literature regarding IFs in research MRI of the brain, there are major inconsistencies in the reported prevalence, ranging from 1.3% to 99%. Many factors appear to contribute to this broad range: lack of standardised definition, participant demographics variance, heterogenous MRI scanner strength and sequences, reporter variation and results classification. We also found significant discrepancies in the review, consent and clinical communication processes pertaining to the ethical nature of these studies. These findings have implications for future studies, particularly those involving artificial intelligence. Further research, particularly in relation to MRI brain IFs would be useful to explore the generalisability of study results. [ABSTRACT FROM AUTHOR]

The diversity of intrinsic dynamics observed in neurons may enhance the computations implemented in the circuit by enriching network-level emergent properties such as synchronization and phase locking. Large-scale spiking network models of entire brain regions offer a platform to test theories of neural computation and cognitive function, providing useful insights on information processing in the nervous system. However, a systematic in-depth investigation requires network simulations to capture the biological intrinsic diversity of individual neurons at a sufficient level of accuracy. The computationally efficient Izhikevich model can reproduce a wide range of neuronal behaviors qualitatively. Previous studies using optimization techniques, however, were less successful in quantitatively matching experimentally recorded voltage traces. In this article, we present an automated pipeline based on evolutionary algorithms to quantitatively reproduce features of various classes of neuronal spike patterns using the Izhikevich model. Employing experimental data from Hippocampome.org, a comprehensive knowledgebase of neuron types in the rodent hippocampus, we demonstrate that our approach reliably fit Izhikevich models to nine distinct classes of experimentally recorded spike patterns, including delayed spiking, spiking with adaptation, stuttering, and bursting. Importantly, by leveraging the parameter-exploration capabilities of evolutionary algorithms, and by representing qualitative spike pattern class definitions in the error landscape, our approach creates several suitable models for each neuron type, exhibiting appropriate feature variabilities among neurons. Moreover, we demonstrate the flexibility of our methodology by creating multi-compartment Izhikevich models for each neuron type in addition to single-point versions. Although the results presented here focus on hippocampal neuron types, the same strategy is broadly applicable to any neural systems.

Asynchronous evolutionary algorithms are becoming increasingly popular as a means of making full use of many processors while solving computationally expensive search and optimization problems. These algorithms excel at keeping large clusters fully utilized, but may sometimes inefficiently sample an excess of fast‐evaluating solutions at the expense of higher‐quality, slow‐evaluating ones. We have previously introduced a steady‐state parent selection strategy, SWEET ("Selection whilE EvaluaTing"), that sometimes selects individuals that are still being evaluated and allows them to reproduce early. We perform a takeover‐time analysis that confirms that this strategy gives slow‐evaluating individuals that have higher fitnesses an increased ability to multiply in the population. We also find that SWEET appears effective at improving optimization performance on problems in which solution quality is positively correlated with evaluation time. We evaluate our approach on six simulated real‐valued optimization problems and three real‐world applications: an autonomous vehicle controller problem that involves tuning a spiking neural network and two adversarial EA problems. We further evaluate SWEET versus a basic asynchronous process in a simulated setting. We present evidence that SWEET outperforms basic asynchronous processes in a use‐case in which performance is positively correlated with evaluation time, and performs comparably (and often better) than basic asynchronous processes in several use‐cases where performance is negatively correlated with evaluation time. That said, in the cases where performance and evaluation time are negatively correlated the variance of outcomes for SWEET is notably high. [ABSTRACT FROM AUTHOR]

Recent literature has sought to understand the presence of epenthetic vowels after the productions of postvocalic word-final consonants by second language (L2) learners whose first languages (L1s) restrict the presence of obstruents in coda position. Previous models include those in which epenthesis is seen as a strategy to mitigate the effects of coda licensing restrictions in the L1; others see epenthesis as a result of misperception of consonant releases in the L2 as indicating the presence of an additional syllable nucleus. The current study examines segmental identification and syllable counting in inexperienced Korean learners of English as a foreign language. Across stimuli, two effects were found. Increased perceptual epenthesis correlated with increased identification of a segment as voiceless, indicating a joint perception of voicelessness and an epenthetic vowel. Also, rate of epenthesis increased with accuracy of detecting sibilants and coronal segments, sounds characterized by salient consonant noise. Taken together, these results indicate a perceptual mechanism that evaluates segmental content and prosodic structure from an integrated percept. Analyses across individual listeners do not support a model in which perceptual epenthesis is a strategy to increase segmental accuracy; rather, they support models in which both syllable counting and segmental identification are skills that are reflections of increased proficiency in the L2. These results are discussed with respect to models of L2 phonology that rely on the robust encoding of lexical items.

In hearing children, reading skills have been found to be closely related to phonological awareness. We used several standardized tests to investigate the reading and phonological awareness skills of 27 deaf school-age children who were experienced cochlear implant users. Approximately two-thirds of the children performed at or above the level of their hearing peers on the phonological awareness and reading tasks. Reading scores were found to be strongly correlated with measures of phonological awareness. These correlations remained the same when we statistically controlled for potentially confounding demographic variables such as age at testing and speech perception skills. However, these correlations decreased even after we statistically controlled for vocabulary size. This finding suggests that lexicon size is a mediating factor in the relationship between the children's phonological awareness and reading skills, a finding that has also been reported for typically developing hearing children.

This article examines the extent of differences between second language (L2) learners in their abilities to identify L2 consonants and provides evidence for linguistic generalization from one consonant to other consonants. It distinguishes among different sorts of models of the relationship between segments: (a) "segmentally specific models" in which each segment is treated separately and (b) "generalized featural models" in which segments that share features are treated as a group. It also examines (c) "ordered models" in which one segment might rely on another previously existing one. The article presents the results of an experiment with 40 Korean learners of English identifying English obstruents in different prosodic locations, and it examines the pattern of variation in perceptual accuracy across the listeners. Results indicate that manner perception varies from person to person as a unit, regardless of the segment, suggesting a single generalized featural skill. Voicing identification, however, does not vary as a unit across the different prosodic positions, suggesting different skills that are applicable to different prosodic positions and are acquired separately. There is also evidence for an implicational relationship between pairs of segments that differ in markedness, providing some evidence for an ordered model; however, such patterns are not pervasive across different contrasts.