"Leap before you look": Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30° rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90° rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Electrokinetic transport of CTAB induces multiphasic behavior during capillary adsorption and desorption.

Cationic surfactant coatings (e.g., CTAB) are commonly used in CE to control EOF and thereby improve separation efficiencies. However, our understanding of surfactant adsorption and desorption dynamics under EOF conditions is limited. Here, we apply automated zeta potential analysis to study the adsorption and desorption kinetics of CTAB in a capillary under different transport conditions: diameter, length, voltage alternation pattern and frequency, and applied pressure. In contrast to other studies, we observe slower kinetics at distinct capillary wall zeta potential ranges. Within these ranges, which we call "stagnant regimes," the EOF mobility significantly counteracts the electrophoretic (EP) mobility of CTA+ and hinders the net transport. By constructing a numerical model to compare with our experiments and recasting our experimental data in terms of the net CTA+ transport volume normalized by surface area, we reveal that the EP mobility of CTA+ and the capillary surface-area-to-volume ratio dictate the zeta potential range and the duration of the stagnant regime and thereby govern the overall reaction kinetics. Our results indicate that further transport-oriented studies can significantly aid in the understanding and design of electrokinetic systems utilizing CTAB and other charged surfactants.

The push-pull of serial dependence effects: Attraction to the prior response and repulsion from the prior stimulus.

In the "serial dependence" effect, responses to visual stimuli appear biased toward the last trial's stimulus. However, several kinds of serial dependence exist, with some reflecting prior stimuli and others reflecting prior responses. One-factor analyses consider the prior stimulus alone or the prior response alone and can consider both variables only via separate analyses. We demonstrate that one-factor analyses are potentially misleading and can reach conclusions that are opposite from the truth if both dependencies exist. To address this limitation, we developed two-factor analyses (model comparison with hierarchical Bayesian modeling and an empirical "quadrant analysis"), which consider trial-by-trial combinations of prior response and prior stimulus. Two-factor analyses can tease apart the two dependencies if applied to a sufficiently large dataset. We applied these analyses to a new study and to four previously published studies. When applying a model that included the possibility of both dependencies, there was no evidence of attraction to the prior stimulus in any dataset, but there was evidence of attraction to the prior response in all datasets. Two of the datasets contained sufficient constraint to determine that both dependencies were needed to explain the results. For these datasets, the dependency on the prior stimulus was repulsive rather than attractive. Our results are consistent with the claim that both dependencies exist in most serial dependence studies (the two-dependence model was not ruled out for any dataset) and, furthermore, that the two dependencies work against each other.

Gestalt formation promotes awareness of suppressed visual stimuli during binocular rivalry.

Continuous flash suppression leverages binocular rivalry to render observers unaware of a static image for several seconds. To achieve this effect, rapidly flashing noise masks are presented to the dominant eye while a static stimulus is presented to the non-dominant eye. Eventually "breakthrough" occurs, wherein awareness shifts to the static image shown to the non-dominant eye. We tested the hypothesis that Gestalt formation can promote breakthrough. In two experiments, we presented pacman-shaped objects that might or might not align to form illusory Kanizsa objects. To measure the inception of breakthrough, observers were instructed to press a key at the moment of partial breakthrough. After pressing the key, which stopped the trial, observers reported how many pacmen were seen and where they were located. Supporting the Gestalt hypothesis, breakthrough was faster when the pacmen were aligned and observers more often reported pairs of pacmen if they were aligned. To address whether these effects reflected illusory shape perception, a computational model was applied to the pacman report distributions and breakthrough times for an experiment with four pacmen. A full account of the data required an increased joint probability of reporting all four pacmen, suggesting an influence of a perceived illusory cross.

Nanofluidic diodes based on asymmetric bio-inspired surface coatings in straight glass nanochannels.

In this study, we present nanofluidic diodes fabricated from straight glass nanochannels and functionalized using bio-inspired polydopamine (PDA) and poly-L-lysine (PLL) coatings. The resulting PDA coatings are shown to be asymmetric due to a combination of transport considerations which can be leveraged to provide a measure of control over the effective channel geometry. By subsequently introducing a layer of amine-bearing PLL chains covalently bound to the PDA, we enhance heterogeneities in the charge and ion distributions within the channel and enable significant current rectification between forward-bias and reverse-bias modes; our PDA-PLL-coated channels yielded a rectification ratio greater than 1000 in a 100 nm channel filled with 0.01× phosphate-buffered saline solution (PBS). We further demonstrated that at higher ionic strength conditions, reducing the solution pH increased the number of protonated amines within the PLL layer, amplifying the charge disparities along the channel and leading to greater rectification. As nanofluidic diodes with bipolar surface charge distributions tend to provide superior performance compared to those with a single wall charge polarity, we imposed a more bipolar charge distribution in our devices by partially coating our PDA-PLL-coated channels with negatively charged polyacrylic acid (PAA). These enhanced bipolar channels exhibited greater current rectification than the PDA-PLL-coated channels, reaching rectification ratios in excess of 100 even in more physiologically-relevant 1× PBS solutions. Our fabrication approach and the results herein provide a promising platform from which the scientific community can build upon in the relentless endeavor for improved sensitivity in biosensors and other analytical devices.

A modeling framework for determining modulation of neural-level tuning from non-invasive human fMRI data.

Many neuroscience theories assume that tuning modulation of individual neurons underlies changes in human cognition. However, non-invasive fMRI lacks sufficient resolution to visualize this modulation. To address this limitation, we developed an analysis framework called Inferring Neural Tuning Modulation (INTM) for "peering inside" voxels. Precise specification of neural tuning from the BOLD signal is not possible. Instead, INTM compares theoretical alternatives for the form of neural tuning modulation that might underlie changes in BOLD across experimental conditions. The most likely form is identified via formal model comparison, with assumed parametric Normal tuning functions, followed by a non-parametric check of conclusions. We validated the framework by successfully identifying a well-established form of modulation: visual contrast-induced multiplicative gain for orientation tuned neurons. INTM can be applied to any experimental paradigm testing several points along a continuous feature dimension (e.g., direction of motion, isoluminant hue) across two conditions (e.g., with/without attention, before/after learning).

A visual sense of number emerges from divisive normalization in a simple center-surround convolutional network.

Many species of animals exhibit an intuitive sense of number, suggesting a fundamental neural mechanism for representing numerosity in a visual scene. Recent empirical studies demonstrate that early feedforward visual responses are sensitive to numerosity of a dot array but substantially less so to continuous dimensions orthogonal to numerosity, such as size and spacing of the dots. However, the mechanisms that extract numerosity are unknown. Here, we identified the core neurocomputational principles underlying these effects: (1) center-surround contrast filters; (2) at different spatial scales; with (3) divisive normalization across network units. In an untrained computational model, these principles eliminated sensitivity to size and spacing, making numerosity the main determinant of the neuronal response magnitude. Moreover, a model implementation of these principles explained both well-known and relatively novel illusions of numerosity perception across space and time. This supports the conclusion that the neural structures and feedforward processes that encode numerosity naturally produce visual illusions of numerosity. Taken together, these results identify a set of neurocomputational properties that gives rise to the ubiquity of the number sense in the animal kingdom.

Electrooxidation of Phenol on Polyelectrolyte Modified Carbon Electrodes for Use in Insulin Pump Infusion Sets.

BACKGROUND: Many type 1 diabetes patients using continuous subcutaneous insulin infusion (CSII) suffer from the phenomenon of unexplained hypoglycemia or "site loss." Site loss is hypothesized to be caused by toxic excipients, for example, phenolic compounds within insulin formulations that are used as preservatives and stabilizers. Here, we develop a bioinspired polyelectrolyte-modified carbon electrode for effective electrooxidative removal of phenol from insulin and eventual incorporations into an infusion set of a CSII device. METHODS: We modified a carbon screen printed electrode (SPE) with poly-L-lysine (PLL) to avoid passivation due to polyphenol deposition while still removing phenolic compounds from insulin injections. We characterized these electrodes using scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) and compared their data with data from bare SPEs. Furthermore, we performed electrochemical measurements to determine the extent of passivation, and high-performance liquid chromatography (HPLC) measurements to confirm both the removal of phenol and the integrity of insulin after phenol removal. RESULTS: Voltammetry measurements show that electrode passivation due to polyphenol deposition is reduced by a factor of 2X. HPLC measurements confirm a 10x greater removal of phenol by our modified electrodes relative to bare electrodes. CONCLUSION: Using bioinspired polyelectrolytes to modify a carbon electrode surface aids in the electrooxidation of phenolic compounds from insulin and is a step toward integration within an infusion set for mitigating site loss.

A 'compensatory selection' effect with standardized tests: Lack of correlation between test scores and success is evidence that test scores are predictive of success.

We introduce the statistical concept of 'compensatory selection', which arises when selecting a subset of applicants based on multiple predictors, such as when standardized test scores are used in combination with other predictors required in a school application (e.g., previous grades, references letters, and personal statements). Post-hoc analyses often fail to find a positive correlation between test scores and subsequent success, and this failure is sometimes taken as evidence against the predictive validity of the standardized test. The present analysis reveals that the failure to find a negative correlation indicates that the standardized test is in fact a valid predictor of success. This is due to compensation between predictors during selection: Some students are admitted despite a low test score because their application is exceptional in other respects, while other students are admitted primarily based on a high test score despite weakness in the rest of their application. This compensatory selection process introduces a negative correlation between test scores and other predictors among those admitted (a 'collider bias' or 'Berkson's paradox' effect). If test scores are valid predictors of success, this negative correlation between the predictors counteracts the positive correlation between test scores and success that would have been observed if all applicants were admitted. If test scores are not predictive of success, but were nevertheless used in a compensatory selection process, there would be a spurious negative correlation between test scores and success (i.e., an admitted student with a weak application except for a high test score would be unlikely to succeed). The selection effect that is described here is fundamentally different from the well-known 'restricted range' problem and can powerfully alter results even in situations that accept most applicants.

Real-Time Zeta Potential Analysis of Microchannel Surfaces during Aminosilane Deposition and Exposure Using Current Monitoring.

Surface coatings are extensively used in capillary electrophoresis to increase separation efficiency and resolution. The stability of these coatings across a wide pH range is desirable to achieve repeatable migration times; therefore, a comprehensive understanding of coating degradation timescales is needed. We present a novel platform for automated zeta potential analysis based upon current monitoring that delivers improved time resolution over the existing methods. Using our platform, we measure the zeta potential continuously during aminosilane coating reactions and infer changes in the surface composition. We found that the change in the zeta potential after coating depended on the monomer type and solvent, while its stability was influenced by the coating solvent and exposure pH. Our versatile platform provides an elegant approach for evaluating the molecular composition, reactivity, and stability of surfaces in real time.

Asymmetric Weights and Retrieval Practice in an Autoassociative Neural Network Model of Paired-Associate Learning.

Rizzuto and Kahana (2001) applied an autoassociative Hopfield network to a paired-associate word learning experiment in which (1) participants studied word pairs (e.g., ABSENCE-HOLLOW), (2) were tested in one direction (ABSENCE-?) on a first test, and (3) were tested in the same direction again or in the reverse direction (?-HOLLOW) on a second test. The model contained a correlation parameter to capture the dependence between forward versus backward learning between the two words of a word pair, revealing correlation values close to 1.0 for all participants, consistent with neural network models that use the same weight for communication in both directions between nodes. We addressed several limitations of the model simulations and proposed two new models incorporating retrieval practice learning (e.g., the effect of the first test on the second) that fit the accuracy data more effectively, revealing substantially lower correlation values (average of .45 across participants, with zero correlation for some participants). In addition, we analyzed recall latencies, finding that second test recall was faster in the same direction after a correct first test. Only a model with stochastic retrieval practice learning predicted this effect. In conclusion, recall accuracy and recall latency suggest asymmetric learning, particularly in light of retrieval practice effects.

A neural habituation account of the negative compatibility effect.

The negative compatibility effect (NCE) is the finding of slower reaction times (RTs) to report the direction of a target arrow following a subliminal prime arrow pointed in the same direction. The NCE is commonly thought to reflect automatic response inhibition, and on this assumption, it has recently been used to assess various motor disorders. Here we propose a fundamentally different account of the NCE: one that relates the NCE to a broader class of paradigms that reveal behavioral deficits with repetition priming. We propose that the NCE is a "cognitive aftereffect," as explained with the neural habituation model of Huber and O'Reilly (2003). To identify the underlying perceptual dynamics by reducing the role of response preparation, we developed a novel variant of the NCE task with threshold accuracy rather than RT as the dependent measure. This revealed a transition from positive to negative priming as a function of prime duration, and a second experiment ruled out response priming. The perceptual dynamics of the neural habituation model were fit to these results and then fixed in applying the model to the NCE literature. Application of the model to RTs added a response layer that accumulates response information throughout the trial. With this addition, the model captured results found in the NCE literature that are inconsistent with a response inhibition account. Situations that produce a positive compatibility effect, rather than an NCE, were explained as response priming, whereas NCE effects were explained as a cognitive aftereffect, rooted in perceptual dynamics. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Neural habituation enhances novelty detection: an EEG study of rapidly presented words.

Huber and O'Reilly (2003) proposed that neural habituation aids perceptual processing, separating neural responses to currently viewed objects from recently viewed objects. However, synaptic depression has costs, producing repetition deficits. Prior work confirmed the transition from repetition benefits to deficits with increasing duration of a prime object, but the prediction of enhanced novelty detection was not tested. The current study examined this prediction with a same/different word priming task, using support vector machine (SVM) classification of EEG data, ERP analyses focused on the N400, and dynamic neural network simulations fit to behavioral data to provide a priori predictions of the ERP effects. Subjects made same/different judgements to a response word in relation to an immediately preceding brief target word; prime durations were short (50ms) or long (400ms), and long durations decreased P100/N170 responses to the target word, suggesting that this manipulation increased habituation. Following long duration primes, correct "different" judgments of primed response words increased, evidencing enhanced novelty detection. An SVM classifier predicted trial-by-trial behavior with 66.34% accuracy on held-out data, with greatest predictive power at a time pattern consistent with the N400. The habituation model was augmented with a maintained semantics layer (i.e., working memory) to generate behavior and N400 predictions. A second experiment used response-locked ERPs, confirming the model's assumption that residual activation in working memory is the basis of novelty decisions. These results support the theory that neural habituation enhances novelty detection, and the model assumption that the N400 reflects updating of semantic information in working memory.

Mechanisms of memory: An intermediate level of analysis and organization.

Research in the last five years has made great strides toward mechanistic explanations of how the brain enables memory. This progress builds upon decades of research from two complementary strands: a Levels of Analysis approach and a Levels of Organization approach. We review how research in cognitive psychology and cognitive neuroscience under these two approaches has recently converged on mechanistic, brain-based theories, couched at the optimal level for explaining cognitive phenomena - the intermediate level. Furthermore, novel empirical and data analysis techniques are now providing ways to test these theories' predictions, a crucial step in unraveling the mechanisms of memory.

Frontal cortex tracks surprise separately for different sensory modalities but engages a common inhibitory control mechanism.

The brain constantly generates predictions about the environment to guide action. Unexpected events lead to surprise and can necessitate the modification of ongoing behavior. Surprise can occur for any sensory domain, but it is not clear how these separate surprise signals are integrated to affect motor output. By applying a trial-to-trial Bayesian surprise model to human electroencephalography data recorded during a cross-modal oddball task, we tested whether there are separate predictive models for different sensory modalities (visual, auditory), or whether expectations are integrated across modalities such that surprise in one modality decreases surprise for a subsequent unexpected event in the other modality. We found that while surprise was represented in a common frontal signature across sensory modalities (the fronto-central P3 event-related potential), the single-trial amplitudes of this signature more closely conformed to a model with separate surprise terms for each sensory domain. We then investigated whether surprise-related fronto-central P3 activity indexes the rapid inhibitory control of ongoing behavior after surprise, as suggested by recent theories. Confirming this prediction, the fronto-central P3 amplitude after both auditory and visual unexpected events was highly correlated with the fronto-central P3 found after stop-signals (measured in a separate stop-signal task). Moreover, surprise-related and stopping-related activity loaded onto the same component in a cross-task independent components analysis. Together, these findings suggest that medial frontal cortex maintains separate predictive models for different sensory domains, but engages a common mechanism for inhibitory control of behavior regardless of the source of surprise.

Connecting the dots without top-down knowledge: Evidence for rapidly-learned low-level associations that are independent of object identity.

Knowing the identity of an object can powerfully alter perception. Visual demonstrations of this-such as Gregory's (1970) hidden Dalmatian-affirm the existence of both top-down and bottom-up processing. We consider a third processing pathway: lateral connections between the parts of an object. Lateral associations are assumed by theories of object processing and hierarchical theories of memory, but little evidence attests to them. If they exist, their effects should be observable even in the absence of object identity knowledge. We employed Continuous Flash Suppression (CFS) while participants studied object images, such that visual details were learned without explicit object identification. At test, lateral associations were probed using a part-to-part matching task. We also tested whether part-whole links were facilitated by prior study using a part-naming task, and included another study condition (Word), in which participants saw only an object's written name. The key question was whether CFS study (which provided visual information without identity) would better support part-to-part matching (via lateral associations) whereas Word study (which provided identity without the correct visual form) would better support part-naming (via top-down processing). The predicted dissociation was found and confirmed by state-trace analyses. Thus, lateral part-to-part associations were learned and retrieved independently of object identity representations. This establishes novel links between perception and memory, demonstrating that (a) lateral associations at lower levels of the object identification hierarchy exist and contribute to object processing and (b) these associations are learned via rapid, episodic-like mechanisms previously observed for the high-level, arbitrary relations comprising episodic memories. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Testing the primary and convergent retrieval model of recall: Recall practice produces faster recall success but also faster recall failure.

The primary and convergent retrieval (PCR) model assumes that the act of successful recall not only boosts associations between the item and retrieval cues but additionally strengthens associations within the item (i.e., between the features of an item), speeding the rate of information retrieval from memory. The latter effect is termed intra-item learning and is a unique benefit of recall practice (i.e., the "testing effect"). Prior work confirmed the prediction that recall practice produces faster subsequent recall than restudy practice even if accuracy is higher following restudy. The current study replicated this result, but also examined the downside of recall practice: that after a failure to recall during practice, participants will be faster in their failure to recall on a subsequent recall test. This prediction was confirmed in a multisession cued recall experiment that collected accuracy and recall latency measurements for no practice, recall practice, or restudy, with an immediate or delayed final test. The linear ballistic accumulator model was fit to latency distributions, and model comparison determined that these effects reflect differences in drift rates, as predicted by the PCR model.

A hierarchical Bayesian state trace analysis for assessing monotonicity while factoring out subject, item, and trial level dependencies.

State trace analyses assess the latent dimensionality of a cognitive process by asking whether the means of two dependent variables conform to a monotonic function across a set of conditions. Using an assumption of independence between the measures, recently proposed statistical tests address bivariate measurement error, allowing both frequentist and Bayesian analyses of monotonicity (e.g., Davis-Stober, Morey, Gretton, & Heathcote, 2016; Kalish, Dunn, Burdakov, & Sysoev, 2016). However, inference can be biased by unacknowledged dependencies between measures, particularly when the data are insufficient to overwhelm an incorrect prior assumption of independence. To address this limitation, we developed a hierarchical Bayesian model that explicitly models the separate roles of subject, item, and trial-level dependencies between two measures. Assessment of monotonicity is then performed by fitting separate models that do or do not allow a non-monotonic relation between the condition effects (i.e., same vs. different rank orders). The Widely Applicable Information Criterion (WAIC) and Pseudo Bayesian Model Averaging - cross validation measures of model fit - are used for model comparison, providing an inferential conclusion regarding the dimensionality of the latent psychological space. We validated this new state trace analysis technique using model recovery simulation studies, which assumed different ground truths regarding monotonicity and the direction/magnitude of the subject- and trial-level dependence. We also provide an example application of this new technique to a visual object learning study that compared performance on a visual retrieval task (forced choice part recognition) versus a verbal retrieval task (cued recall).

Does inhibition cause forgetting after selective retrieval? A reanalysis and failure to replicate.

Retrieval practice can produce forgetting, but it remains unclear using only behavioral data whether this forgetting is caused by targeted inhibition versus interference. Therefore, Wimber et al. (2015) used pattern classifier analyses of fMRI data to track individual memories in a novel variant of retrieval induced forgetting. After initial learning, people recalled target images across selective retrieval practice trials, and cortical activity patterns gradually became more similar to those evoked by the target pictures (i.e., pattern enhancement) and less similar to those evoked by competing pictures (i.e., pattern suppression). The key question was whether this inhibition of competing memories would cause forgetting. Wimber et al. found a significant forgetting effect (p<.01) on a subsequent forced choice picture recognition test, with lower accuracy for competitors than for baseline items. Because fMRI data is correlative, a causal interpretation of the data would require, at a minimum, more forgetting following cortical pattern suppression (as occurred for competitors) than cortical pattern enhancement (as occurred for targets). The interaction necessary to reach this conclusion was significant (p=.041). However, reanalyzing the original data revealed that the interaction depended on the decision to code missing responses as equivalent to choosing the wrong picture. Even if missing trials reflected memory failures, at worst they would produce 50/50 guessing, rather than an error every time. Treating these trials as missing, or setting them to chance performance, resulted in no reliable forgetting difference between competitors and targets. Because this might reflect inadequate statistical power, we undertook two replication attempts of the behavioral paradigm, failing both times to observe more forgetting for competitors than targets. In fact, we failed to find any forgetting at all. We conclude that the study of Wimber et al. does not support the conclusion that forgetting is caused by targeted inhibition.