Function estimation: Quantifying individual differences of hand-drawn functions.

Graphical perception is an important part of the scientific endeavour, and the interpretation of graphical information is increasingly important among educated consumers of popular media, who are often presented with graphs of data in support of different policy positions. However, graphs are multidimensional and data in graphs are comprised not only of overall global trends but also local perturbations. We presented a novel function estimation task in which scatterplots of noisy data that varied in the number of data points, the scale of the data, and the true generating function were shown to observers. 170 psychology undergraduates with mixed experience of mathematical functions were asked to draw the function that they believe generated the data. Our results indicated not only a general influence of various aspects of the presented graph (e.g., increasing the number of data points results in smoother generated functions) but also clear individual differences, with some observers tending to generate functions that track the local changes in the data and others following global trends in the data.

Measuring the perception and metacognition of time.

The ability of humans to identify and reproduce short time intervals (in the region of a second) may be affected by many factors ranging from the gender and personality of the individual observer, through the attentional state, to the precise spatiotemporal structure of the stimulus. The relative roles of these very different factors are a challenge to describe and define; several methodological approaches have been used to achieve this to varying degrees of success. Here we describe and model the results of a paradigm affording not only a first-order measurement of the perceived duration of an interval but also a second-order metacognitive judgement of perceived time. This approach, we argue, expands the form of the data generally collected in duration-judgements and allows more detailed comparison of psychophysical behavior to the underlying theory. We also describe a hierarchical Bayesian measurement model that performs a quantitative analysis of the trial-by-trial data calculating the variability of the temporal estimates and the metacognitive judgments allowing direct comparison between an actual and an ideal observer. We fit the model to data collected for judgements of 750 ms (bisecting 1500 ms) and 1500 ms (bisecting 3000 ms) intervals across three stimulus modalities (visual, audio, and audiovisual). This enhanced form of data on a given interval judgement and the ability to track its progression on a trial-by-trial basis offers a way of looking at the different roles that subject-based, task-based and stimulus-based factors have on the perception of time.

Perceptual Grouping Explains Similarities in Constellations Across Cultures.

Cultures around the world organize stars into constellations, or asterisms, and these groupings are often considered to be arbitrary and culture specific. Yet there are striking similarities in asterisms across cultures, and groupings such as Orion, the Big Dipper, the Pleiades, and the Southern Cross are widely recognized across many different cultures. Psychologists have informally suggested that these shared patterns are explained by Gestalt laws of grouping, but there have been no systematic attempts to catalog asterisms that recur across cultures or to explain the perceptual basis of these groupings. Here, we compiled data from 27 cultures around the world and found that a simple computational model of perceptual grouping accounts for many of the recurring cross-cultural asterisms. Our results suggest that basic perceptual principles account for more of the structure of asterisms across cultures than previously acknowledged and highlight ways in which specific cultures depart from this shared baseline.

Metastudies for robust tests of theory.

We describe and demonstrate an empirical strategy useful for discovering and replicating empirical effects in psychological science. The method involves the design of a metastudy, in which many independent experimental variables-that may be moderators of an empirical effect-are indiscriminately randomized. Radical randomization yields rich datasets that can be used to test the robustness of an empirical claim to some of the vagaries and idiosyncrasies of experimental protocols and enhances the generalizability of these claims. The strategy is made feasible by advances in hierarchical Bayesian modeling that allow for the pooling of information across unlike experiments and designs and is proposed here as a gold standard for replication research and exploratory research. The practical feasibility of the strategy is demonstrated with a replication of a study on subliminal priming.

An Optimized Method for the Proteomic Analysis of Low Volumes of Cell Culture Media and the Secretome: The Application and the Demonstration of Altered Protein Expression in iPSC-Derived Neuronal Cell Lines from Parkinson's Disease Patients.

Traditionally, cell culture medium in iPSC-derived cell work is not the main focus of the research and often is considered as just "food for cells". We demonstrate that by manipulation of the media and optimized methodology, it is possible to use this solution to study the proteins that the cell secretes (the "secretome"). This is particularly useful in the study of iPSC-derived neurons, which require long culture time. We demonstrate that media can be used to model diseases with optimized incubation and sampling times. The ability not to sacrifice cells allows significant cost and research benefits. In this manuscript we describe an optimized method for the analysis of the cell media from iPSC-derived neuronal lines from control and Parkinson's disease patients. We have evaluated the use of standard and supplement B27-free cell media as well as five different sample preparation techniques for proteomic analysis of the cell secretome. Mass spectral analysis of culture media allowed for the identification of >500 proteins, in 500 µL of media, which is less volume than reported previously (20-40 mL). Using shorter incubation times and our optimized methodology, we describe the use of this technique to study and describe potential disease mechanisms in Parkinson's disease.

Conversion Mechanism of Soluble Alkylamide Precursors for the Synthesis of Colloidal Nitride Nanomaterials.

There are few molecular precursors that chemically convert to nitride nanomaterials, which severely limits the development of this important class of materials. Alkylamides are soluble and stable nitride precursors that can be based on the same primary amines that are often used in colloidal nanomaterial synthesis, but their conversion involves the breaking of stable C-N bonds through a mechanism that remained unknown up to now. A critical aspect of this conversion mechanism is uncovered here, involving a prelimary step whereby alkylamides are oxidized to N-alkylimines to yield NH2- amide species that are postulated to be the actual reactive precursors in the formation of indium nitride nanomaterials. Interestingly, this step also involves the concomitant reduction of indium(III) to In(0) nanodroplets, which consequently catalyze the growth of InN nanomaterials. The elucidation of the origin of the surprising reactivity of otherwise stable molecular precursors opens the door to the development of new solution-phase approaches for the synthesis of nitride materials.

Replication is already mainstream: Lessons from small-N designs.

Replication is already mainstream in areas of psychology that use small-N designs. Replication failures often result from weak theory, weak measurement, and weak control over error variance. These are hallmarks of phenomenon-based research with sparse data. Small-N designs, which focus on understanding processes, treat the individual rather than the experiment as the unit of replication and largely circumvent these problems.

Once more with feeling: Normative data for the aha experience in insight and noninsight problems.

Despite the presumed ability of insight problems to elicit the subjective feeling of insight, as well as the use of so-called insight problems to investigate this phenomenon for over 100 years, no research has collected normative data regarding the ability of insight problems to actually elicit the feeling of insight in a given individual. The work described in this article provides an overview of both classic and contemporary problems used to examine the construct of insight and presents normative data on the success rate, mean time to solution, and mean rating of aha experience for each problem and task type. We suggest using these data in future work as a reference for selecting problems on the basis of their ability to elicit an aha experience.

Multiplex High-Throughput Targeted Proteomic Assay To Identify Induced Pluripotent Stem Cells.

Induced pluripotent stem cells have great potential as a human model system in regenerative medicine, disease modeling, and drug screening. However, their use in medical research is hampered by laborious reprogramming procedures that yield low numbers of induced pluripotent stem cells. For further applications in research, only the best, competent clones should be used. The standard assays for pluripotency are based on genomic approaches, which take up to 1 week to perform and incur significant cost. Therefore, there is a need for a rapid and cost-effective assay able to distinguish between pluripotent and nonpluripotent cells. Here, we describe a novel multiplexed, high-throughput, and sensitive peptide-based multiple reaction monitoring mass spectrometry assay, allowing for the identification and absolute quantitation of multiple core transcription factors and pluripotency markers. This assay provides simpler and high-throughput classification into either pluripotent or nonpluripotent cells in 7 min analysis while being more cost-effective than conventional genomic tests.

α-Synuclein binds to the ER-mitochondria tethering protein VAPB to disrupt Ca2+ homeostasis and mitochondrial ATP production.

α-Synuclein is strongly linked to Parkinson's disease but the molecular targets for its toxicity are not fully clear. However, many neuronal functions damaged in Parkinson's disease are regulated by signalling between the endoplasmic reticulum (ER) and mitochondria. This signalling involves close physical associations between the two organelles that are mediated by binding of the integral ER protein vesicle-associated membrane protein-associated protein B (VAPB) to the outer mitochondrial membrane protein, protein tyrosine phosphatase-interacting protein 51 (PTPIP51). VAPB and PTPIP51 thus act as a scaffold to tether the two organelles. Here we show that α-synuclein binds to VAPB and that overexpression of wild-type and familial Parkinson's disease mutant α-synuclein disrupt the VAPB-PTPIP51 tethers to loosen ER-mitochondria associations. This disruption to the VAPB-PTPIP51 tethers is also seen in neurons derived from induced pluripotent stem cells from familial Parkinson's disease patients harbouring pathogenic triplication of the α-synuclein gene. We also show that the α-synuclein induced loosening of ER-mitochondria contacts is accompanied by disruption to Ca2+ exchange between the two organelles and mitochondrial ATP production. Such disruptions are likely to be particularly damaging to neurons that are heavily dependent on correct Ca2+ signaling and ATP.

Mutations in SLC25A22: hyperprolinaemia, vacuolated fibroblasts and presentation with developmental delay.

Mutations in SLC25A22 are known to cause neonatal epileptic encephalopathy and migrating partial seizures in infancy. Using whole exome sequencing we identified four novel SLC25A22 mutations in six children from three families. Five patients presented clinical features similar to those in the literature including hypotonia, refractory neonatal-onset seizures and developmental delay. However, the sixth patients presented atypically with isolated developmental delay, developing late-onset (absence) seizures only at 7 years of age. Abnormal metabolite levels have not been documented in the nine patients described previously. One patient in our series was referred to the metabolic clinic because of persistent hyperprolinaemia and another three had raised plasma proline when tested. Analysis of the post-prandial plasma amino acid response in one patient showed abnormally high concentrations of several amino acids. This suggested that, in the fed state, when amino acids are the preferred fuel for the liver, trans-deamination of amino acids requires transportation of glutamate into liver mitochondria by SLC25A22 for deamination by glutamate dehydrogenase; SLC25A22 is an important mitochondrial glutamate transporter in liver as well as in brain. Electron microscopy of patient fibroblasts demonstrated widespread vacuolation containing neutral and phospho-lipids as demonstrated by Oil Red O and Sudan Black tinctorial staining; this might be explained by impaired activity of the proline/pyrroline-5-carboxylate (P5C) shuttle if SLC25A22 transports pyrroline-5-carboxylate/glutamate-γ-semialdehyde as well as glutamate.

Set size slope still does not distinguish parallel from serial search.

Much of the evidence for theories in visual search (including Hulleman & Olivers' [H&O's]) comes from inferences made using changes in mean RT as a function of the number of items in a display. We have known for more than 40 years that these inferences are based on flawed reasoning and obscured by model mimicry. Here we describe a method that avoids these problems.

Statistical analyses of the resilience function.

The extent to which distracting information influences decisions can be informative about the nature of the underlying cognitive and perceptual processes. In a recent paper, a response time-based measure for quantifying the degree of interference (or facilitation) from distracting information termed resilience was introduced. Despite using a statistical measure, the analysis was limited to qualitative comparisons between different model predictions. In this paper, we demonstrate how statistical procedures from workload capacity analysis can be applied to the new resilience functions. In particular, we present an approach to null-hypothesis testing of resilience functions and a method based on functional principal components analysis for analyzing differences in the functional form of the resilience functions across participants and conditions.

Sequence-sensitive exemplar and decision-bound accounts of speeded-classification performance in a modified Garner-tasks paradigm.

Among the most fundamental results in the area of perceptual classification are the "correlated facilitation" and "filtering interference" effects observed in Garner's (1974) speeded categorization tasks: In the case of integral-dimension stimuli, relative to a control task, single-dimension classification is faster when there is correlated variation along a second dimension, but slower when there is orthogonal variation that cannot be filtered out (e.g., by attention). These fundamental effects may result from participants' use of a trial-by-trial bypass strategy in the control and correlated tasks: The observer changes the previous category response whenever the stimulus changes, and maintains responses if the stimulus repeats. Here we conduct modified versions of the Garner tasks that eliminate the availability of a pure bypass strategy. The fundamental facilitation and interference effects remain, but are still largely explainable in terms of pronounced sequential effects in all tasks. We develop sequence-sensitive versions of exemplar-retrieval and decision-bound models aimed at capturing the detailed, trial-by-trial response-time distribution data. The models combine assumptions involving: (i) strengthened perceptual/memory representations of stimuli that repeat across consecutive trials, and (ii) a bias to change category responses on trials in which the stimulus changes. These models can predict our observed effects and provide a more complete account of the underlying bases of performance in our modified Garner tasks.

PTEN depletion decreases disease severity and modestly prolongs survival in a mouse model of spinal muscular atrophy.

Spinal muscular atrophy (SMA) is the second most common genetic cause of death in childhood. However, no effective treatment is available to halt disease progression. SMA is caused by mutations in the survival motor neuron 1 (SMN1) gene. We previously reported that PTEN depletion leads to an increase in survival of SMN-deficient motor neurons. Here, we aimed to establish the impact of PTEN modulation in an SMA mouse model in vivo. Initial experiments using intramuscular delivery of adeno-associated vector serotype 6 (AAV6) expressing shRNA against PTEN in an established mouse model of severe SMA (SMNΔ7) demonstrated the ability to ameliorate the severity of neuromuscular junction pathology. Subsequently, we developed self-complementary AAV9 expressing siPTEN (scAAV9-siPTEN) to allow evaluation of the effect of systemic suppression of PTEN on the disease course of SMA in vivo. Treatment with a single injection of scAAV9-siPTEN at postnatal day 1 resulted in a modest threefold extension of the lifespan of SMNΔ7 mice, increasing mean survival to 30 days, compared to 10 days in untreated mice. Our data revealed that systemic PTEN depletion is an important disease modifier in SMNΔ7 mice, and therapies aimed at lowering PTEN expression may therefore offer a potential therapeutic strategy for SMA.

Activation in the neural network responsible for categorization and recognition reflects parameter changes.

According to various influential formal models of cognition, perceptual categorization and old-new recognition recruit the same memory system. By contrast, the prevailing view in the cognitive neuroscience literature is that separate neural systems mediate perceptual categorization and recognition. A direct form of evidence is that separate brain regions are activated when observers engage in categorization and recognition tasks involving the same types of stimuli. However, even if the same memory-based comparison processes underlie categorization and recognition, one would not expect to see identical patterns of brain activity across the tasks; the reason is that observers would adjust parameter settings (e.g., vary criterion settings) across the tasks to satisfy the different task goals. In this fMRI study, we conducted categorization and recognition tasks in which stimulus conditions were held constant, and in which observers were induced to vary hypothesized parameter settings across conditions. A formal exemplar model was fitted to the data to track the changes in parameters to help interpret the fMRI results. We observed systematic effects of changes in parameters on patterns of brain activity, which were interpretable in terms of differing forms of evidence accumulation that resulted from the changed parameter settings. After controlling for stimulus and parameter-related differences, we found little evidence that categorization and recognition recruit separate memory systems.

Visual Perception Principles in Constellation Creation.

Many cultures share common constellations and common narratives about the stars in the night sky. Previous research has shown that this overlap in asterisms, minimal star groupings inside constellations, is clearly present across 27 distinct culture groups and can be explained in part by properties of individual stars (brightness) and properties of pairs of stars (proximity) (Kemp, Hamacher, Little, & Cropper, 2022). The same work, however, found no evidence that properties of triples (angle) and quadruples (good continuation) predicted constellation formation. We developed a behavioral experiment to explore how individuals form constellations under conditions that reduce cultural learning. We found that participants independently selected and connected similar stars, and that their responses were predicted by two properties of triples (angle and even spacing) in addition to the properties of brightness and proximity supported by previous work. Our findings lend further evidence to the theory that commonality of constellations across cultures is not a result of shared human history but rather stems from shared human nature.

Characterization of two human induced pluripotent stem cell lines derived from Batten disease patient fibroblasts harbouring CLN5 mutations.

The neuronal ceroid lipofuscinoses (NCLs) are a group of common inherited neurodegenerative disorders of childhood. All forms of NCLs are life-limiting with no curative treatments. Most of the 13 NCL genes encode proteins residing in endolysosomal pathways, such as CLN5, a potential lysosomal enzyme. Two induced pluripotent stem cell lines (hiPSCs) were generated from skin fibroblasts of CLN5 disease patients via non-integrating Sendai virus reprogramming. They demonstrate typical stem cell morphology, express pluripotency markers, exhibit trilineage differentiation potential and also successfully differentiate into neurons. These hiPSCs represent a potential resource to model CLN5 disease in a human context and investigate potential therapies.

Maximal mutual information, not minimal entropy, for escaping the "Dark Room".

A behavioral drive directed solely at minimizing prediction error would cause an agent to seek out states of unchanging, and thus easily predictable, sensory inputs (such as a dark room). The default to an evolutionarily encoded prior to avoid such untenable behaviors is unsatisfying. We suggest an alternate information theoretic interpretation to address this dilemma.

Fluency Profiling System: an automated system for analyzing the temporal properties of speech.

The temporal characteristics of speech can be captured by examining the distributions of the durations of measurable speech components, namely speech segment durations and pause durations. However, several barriers prevent the easy analysis of pause durations: The first problem is that natural speech is noisy, and although recording contrived speech minimizes this problem, it also discards diagnostic information about cognitive processes inherent in the longer pauses associated with natural speech. The second issue concerns setting the distribution threshold, and consists of the problem of appropriately classifying pause segments as either short pauses reflecting articulation or long pauses reflecting cognitive processing, while minimizing the overall classification error rate. This article describes a fully automated system for determining the locations of speech-pause transitions and estimating the temporal parameters of both speech and pause distributions in natural speech. We use the properties of Gaussian mixture models at several stages of the analysis, in order to identify theoretical components of the data distributions, to classify speech components, to compute durations, and to calculate the relevant statistics.