Trial And Error Research Articles

Anterior-Posterior Hippocampal Dynamics Support Working Memory Processing.

The hippocampus is a locus of working memory (WM) with anterior and posterior subregions that differ in their transcriptional and external connectivity patterns. However, the involvement and functional connections between these subregions in WM processing are poorly understood. To address these issues, we recorded intracranial EEG from the anterior and the posterior hippocampi in humans (seven females and seven males) who maintained a set of letters in their WM. We found that WM maintenance was accompanied by elevated low-frequency activity in both the anterior and posterior hippocampus and by increased theta/alpha band (3-12 Hz) phase synchronization between anterior and posterior subregions. Cross-frequency and Granger prediction analyses consistently showed that the correct WM trials were associated with theta/alpha band-coordinated unidirectional influence from the posterior to the anterior hippocampus. In contrast, WM errors were associated with bidirectional interactions between the anterior and posterior hippocampus. These findings imply that theta/alpha band synchrony within the hippocampus may support successful WM via a posterior to anterior influence. A combination of intracranial recording and a fine-grained atlas may be of value in understanding the neural mechanisms of WM processing.SIGNIFICANCE STATEMENT Working memory (WM) is crucial to everyday functioning. The hippocampus has been proposed to be a subcortical node involved in WM processes. Previous studies have suggested that the anterior and posterior hippocampi differ in their external connectivity patterns and gene expression. However, it remains unknown whether and how human hippocampal subregions are recruited and coordinated during WM tasks. Here, by recording intracranial electroencephalography simultaneously from both hippocampal subregions, we found enhanced power in both areas and increased phase synchronization between them. Furthermore, correct WM trials were associated with a unidirectional influence from the posterior to the anterior hippocampus, whereas error trials were correlated with bidirectional interactions. These findings indicate a long-axis specialization in the human hippocampus during WM processing.

Higher-Order Conditioning in the Spatial Domain.

Spatial learning and memory, the processes through which a wide range of living organisms encode, compute, and retrieve information from their environment to perform goal-directed navigation, has been systematically investigated since the early twentieth century to unravel behavioral and neural mechanisms of learning and memory. Early theories about learning to navigate space considered that animals learn through trial and error and develop responses to stimuli that guide them to a goal place. According to a trial-and error learning view, organisms can learn a sequence of motor actions that lead to a goal place, a strategy referred to as response learning, which contrasts with place learning where animals learn locations with respect to an allocentric framework. Place learning has been proposed to produce a mental representation of the environment and the cartesian relations between stimuli within it—which Tolman coined the cognitive map. We propose to revisit some of the best empirical evidence of spatial inference in animals, and then discuss recent attempts to account for spatial inferences within an associative framework as opposed to the traditional cognitive map framework. We will first show how higher-order conditioning can successfully account for inferential goal-directed navigation in a variety of situations and then how vectors derived from path integration can be integrated via higher-order conditioning, resulting in the generation of higher-order vectors that explain novel route taking. Finally, implications to cognitive map theories will be discussed.

The data-processing multiverse of event-related potentials (ERPs): A roadmap for the optimization and standardization of ERP processing and reduction pipelines

In studies of event-related brain potentials (ERPs), numerous decisions about data processing are required to extract ERP scores from continuous data. Unfortunately, the systematic impact of these choices on the data quality and psychometric reliability of ERP scores or even ERP scores themselves is virtually unknown, which is a barrier to the standardization of ERPs. The aim of the present study was to optimize processing pipelines for the error-related negativity (ERN) and error positivity (Pe) by considering a multiverse of data processing choices. A multiverse analysis of a data processing pipeline examines the impact of a large set of different reasonable choices to determine the robustness of effects, such as the impact of different decisions on between-trial standard deviations (i.e., data quality) and between-condition differences (i.e., experimental effects). ERN and Pe data from 298 healthy young adults were used to determine the impact of different methodological choices on data quality and experimental effects (correct vs. error trials) at several key stages: highpass filtering, lowpass filtering, ocular artifact correction, reference, baseline adjustment, scoring sensors, and measurement procedure. This multiverse analysis yielded 3,456 ERN scores and 576 Pe scores per person. An optimized pipeline for ERN included a 15 Hz lowpass filter, ICA-based ocular artifact correction, and a region of interest (ROI) approach to scoring. For Pe, the optimized pipeline included a 0.10 Hz highpass filter, 30 Hz lowpass filter, regression-based ocular artifact correction, a -200 to 0 ms baseline adjustment window, and an ROI approach to scoring. The multiverse approach can be used to optimize pipelines for eventual standardization, which would support efforts toward establishing normative ERP databases. The proposed process of analyzing the data-processing multiverse of ERP scores paves the way for better refinement, identification, and selection of data processing parameters, ultimately improving the precision and utility of ERPs.

Post-error slowing is associated with intelligence

There is considerable evidence showing that people slow down after making an error. The post-error slowing is typically interpreted as the result of adaptation processes raising response criteria in order to avoid future errors. Here we analyze performance results of a previous study examining the relation between intelligence and electrocortical concomitants of mental rotation. Participants performed a hybrid Choice/Go-NoGo task presenting stimuli upright or rotated (60, 120, or 180 degrees) in normal or mirror image. The results showed that low-ability participants responded slower overall and committed more errors—in particular on NoGo trials with 180 degrees rotated stimuli. We selected the error trials and 7 correct Go trials preceding the error trial and 3 correct Go trials following the error trial. The results showed considerable post-error slowing and revealed that this slowing was related to intelligence—low-ability participants showed greater slowing than high-ability participants. This finding was interpreted within the context of diffusion-modeling studies of post-error slowing and may suggest that the rate of evidence accumulation and, possibly, the setting of response thresholds on trials following an error is more vulnerable in low- relative to high-ability individuals.

The orbitofrontal cortex maps future navigational goals

Accurate navigation to a desired goal requires consecutive estimates of spatial relationships between the current position and future destination throughout the journey. Although neurons in the hippocampal formation can represent the position of an animal as well as its nearby trajectories1–7, their role in determining the destination of the animal has been questioned8,9. It is, thus, unclear whether the brain can possess a precise estimate of target location during active environmental exploration. Here we describe neurons in the rat orbitofrontal cortex (OFC) that form spatial representations persistently pointing to the subsequent goal destination of an animal throughout navigation. This destination coding emerges before the onset of navigation, without direct sensory access to a distal goal, and even predicts the incorrect destination of an animal at the beginning of an error trial. Goal representations in the OFC are maintained by destination-specific neural ensemble dynamics, and their brief perturbation at the onset of a journey led to a navigational error. These findings suggest that the OFC is part of the internal goal map of the brain, enabling animals to navigate precisely to a chosen destination that is beyond the range of sensory perception.

Quantitative assessment of self-treated canalith repositioning procedures using inertial measurement unit sensors.

Low success and high recurrence of benign paroxysmal positional vertigo (BPPV) after home-based self-treated Epley and Barbeque (BBQ) roll maneuvers is an important issue. To quantify the cause of low success rate of self-treated Epley and BBQ roll maneuvers and provide a clinically acceptable criterion to guide self-treatment head rotations. Twenty-five participants without active BPPV wore a custom head-mount rotation monitoring device for objective measurements. Self-treatment and specialist-assisted maneuvers were compared for head rotation accuracy. Absolute differences between the head rotation evaluation criteria (American Academy of Otolaryngology guidelines) and measured rotation angles were considered as errors. Self-treatment and specialist-treated errors in maneuvers were compared. Between-trial variations and age effects were evaluated. A significantly large error and between-trial variation occurred in step 4 of the self-treated Epley maneuver, with a considerable error in the second trial. The cumulative error of all steps of self-treated BBQ roll maneuver was significantly large. Age effect occurred only in the self-treated BBQ roll maneuver. Errors in specialist-treated maneuvers ranged from 10 to 20 degrees. Real-time feedback of head movements during simultaneous head-body rotations could increase success rates of self-treatments. Specialist-treated maneuvers can be used as permissible rotation margin criteria.

Analisa Performansi Beberapa Metode Kontroler PID Pada Magnetic Ball

PID controller is a controller that is still widely used in the industrial world. ThePID controller is proven to provide good control performance even though ithas a simple and easy-to-understand algorithm. The important thing in thedesign of this PID controller is to determine the controller parameters or tuning. Project tries to implement advanced PID tuning which involves several tuning methods to get the best performance on a system or plant that is unstable or critically stable, such as controlling the height of a magnetic ball. Some of the methods that will be discussed here are Ziegler-Nichols, Non-control, On Off, Trial Error, and Chien-Hrones-Reswick (C-H-R). From results show that of the five PID Control methods to control the position of the magnetic ball, the best sequential control method is PID Control Trial Error, PID Control On Off, PID Ziegler-Nichols, Chien-Hrones-Reswick Method, and PID Non-Control

Altered theta rhythm and hippocampal-cortical interactions underlie working memory deficits in a hyperglycemia risk factor model of Alzheimer\u2019s disease

Diabetes mellitus is a metabolic disease associated with dysregulated glucose and insulin levels and an increased risk of developing Alzheimer’s disease (AD) later in life. It is thought that chronic hyperglycemia leads to neuroinflammation and tau hyperphosphorylation in the hippocampus leading to cognitive decline, but effects on hippocampal network activity are unknown. A sustained hyperglycemic state was induced in otherwise healthy animals and subjects were then tested on a spatial delayed alternation task while recording from the hippocampus and anterior cingulate cortex (ACC). Hyperglycemic animals performed worse on long delay trials and had multiple electrophysiological differences throughout the task. We found increased delta power and decreased theta power in the hippocampus, which led to altered theta/delta ratios at the end of the delay period. Cross frequency coupling was significantly higher in multiple bands and delay period hippocampus-ACC theta coherence was elevated, revealing hypersynchrony. The highest coherence values appeared long delays on error trials for STZ animals, the opposite of what was observed in controls, where lower delay period coherence was associated with errors. Consistent with previous investigations, we found increases in phosphorylated tau in STZ animals’ hippocampus and cortex, which might account for the observed oscillatory and cognitive changes.

Mirror tracing task in yoga practitioners and non-yoga practitioners: A cross-sectional comparative study

Objectives: The present study compared yoga practitioners with age- and gender-matched yoga naïve persons on performance in a mirror tracing task which involved tracing a star pattern on a sheet of paper while looking at its reflection in a mirror. Materials and Methods: The present cross-sectional study included twenty yoga practitioners of both sexes (15 females; group mean age ± SD; 24.8 ± 3.4 years) and twenty yoga naïve persons (15 females; group mean age ± SD; 24.2 ± 3.8 years) of the same age range. Both groups were assessed for performance in the mirror tracing task in three trials. The distance covered, total errors, and time taken to complete the task were noted. Results: Yoga practitioners made significantly less errors (P < 0.05) in the third trial and covered greater distance in star tracing in the first (P < 0.05) and second (P < 0.05) trials compared to yoga naïve participants. Mann– Whitney U-test was used for all comparisons. Conclusion: Yoga practice may be useful to facilitate learning in the tasks that require better perceptual and motor skills.

Attenuated neuronal and autonomic responses during error processing in anorexia nervosa.

IntroductionAnorexia nervosa (AN) is a severe psychiatric illness with alarming mortality rates. Nevertheless, despite former and recent research results, the etiology of AN is still poorly understood. Of particular interest is that, despite exaggerated response control and increased perfectionism scores, patients with AN seem not to perform better that those unaffected in tasks that require inhibitory control. One reason might be aberrant processing of errors. The objective of our study was thus to obtain further insight into the pathopsychology of AN. We were particularly interested in neuronal and autonomic responses during error processing and their association with behavior.MethodsWe analyzed 16 acute patients suffering from restrictive type AN and 21 healthy controls using functional magnetic resonance imaging (fMRI) with simultaneous physiological recordings during a Go/Nogo response inhibition task. Data were corrected for noise due to cardiac and respiratory influence.ResultsPatients and controls had similarly successful response inhibition in Nogo trials. However, in failed Nogo trials, controls had significantly greater skin conductance responses (SCR) than in correct Nogo trials. Patients did not exhibit elevated SCR to errors. Furthermore, we found significantly increased neuronal responses, especially in the amygdala and hippocampus, in controls compared to patients during error trials. We also found significant positive correlations in controls but not in patients between Nogo performance and activation in the salience network core regions after errors.ConclusionAcute restrictive type AN patients seem to lack neuronal and autonomic responses to errors that might impede a flexible behavior adaption.

Attentional modulation of neural dynamics in tactile perception of complex regional pain syndrome patients.

Body perceptual disturbances are an increasingly acknowledged set of symptoms and possible clinical markers of complex regional pain syndrome (CRPS), but the neurophysiological and neurocognitive changes that underlie them are still far from being clear. We adopted a multivariate and neurodynamical approach to the analysis of EEG modulations evoked by touch to highlight differences between patients and healthy controls, between affected and unaffected side of the body, and between "passive" (i.e., no task demands and equiprobable digit stimulation) and "active" tactile processing (i.e., where a digit discrimination task was administered and spatial probability manipulated). When correct identifications are considered, an early reduction in cortical decodability (28-56 ms) distinguishes CRPS patients from healthy volunteers. However, when error trials are included in the classifier's training, there is an unexpected increased decodability in the CRPS group compared with healthy volunteers (280-320 ms). These group differences in neural processing seemed to be driven by the affected rather than the unaffected side. We corroborated these findings with several exploratory analyses of neural representation dynamics and behavioural modelling, highlighting the need for single participant analyses. Although several limitations impacted the robustness and generalizability of these comparisons, the proposed analytical approach yielded promising insights (as well as possible biomarkers based on neural dynamics) into the relatively unexplored alterations of tactile decision-making and attentional control mechanisms in chronic CRPS.

Predicting the extrudability of complex food materials during 3D printing based on image analysis and gray-box data-driven modelling

Material extrudability is a prerequisite for printing 3D structures with extrusion-based food printing. Food materials with different shear-thinning behaviors were printed to develop predictive models for extrudability. A dataset of 131 unique combinations of materials and printing parameters was collected. Image analysis was employed to rapidly quantify extrudability as determined by mode width, line height and width consistency of line filaments. The relation between the printing pressure and the volumetric flow rate followed a power-law relation, which characterizes the extent of shear-thinning of the food materials. Both regression and classification models were trained and tested using the random forest algorithm. The model performance indicated that extrudability can be predicted with moderate to high accuracy by using rheological measurements and printing parameters as inputs. The predictive workflow developed in this study provides a framework to quantitatively assess and predict extrudability for 3D printing of complex food materials. Industrial relevanceExtrusion-based 3D printing has been applied to customize food designs and can potentially enable personalized nutrition. To achieve this, we need to be able to effectively print complex food materials with high accuracy. Variations in composition and rheological properties of complex food materials make achieving proper extrudability not trivial at this moment, and this limits their applicability to extrusion-based food printing. Here, we developed an image analysis tool to measure line filament extrusion of complex food materials that vary in shear-thinning behaviors. We then built predictive models to estimate material extrudability based on material's shear-thinning properties and printing parameters. Data-driven prediction of material's extrudability can help avoid excessive trial-and error experiments in future.

Machine Learning Guided Design of Single-Phase Hybrid Lead Halide White Phosphors.

Designing new single‐phase white phosphors for solid‐state lighting is a challenging trial–error process as it requires to navigate in a multidimensional space (composition of the host matrix/dopants, experimental conditions, etc.). Thus, no single‐phase white phosphor has ever been reported to exhibit both a high color rendering index (CRI ‐ degree to which objects appear natural under the white illumination) and a tunable correlated color temperature (CCT). In this article, a novel strategy consisting in iterating syntheses, characterizations, and machine learning (ML) models to design such white phosphors is demonstrated. With the guidance of ML models, a series of luminescent hybrid lead halides with ultra‐high color rendering (above 92) mimicking the light of the sunrise/sunset (CCT = 3200 K), morning/afternoon (CCT = 4200 K), midday (CCT = 5500 K), full sun (CCT = 6500K), as well as an overcast sky (CCT = 7000 K) are precisely designed.

Cognitive ocular motor deficits and white matter damage chronically after sports-related concussion.

A history of concussion has been linked to long-term cognitive deficits; however, the neural underpinnings of these abnormalities are poorly understood. This study recruited 26 asymptomatic male Australian footballers with a remote history of concussion (i.e. at least six months since last concussion), and 23 non-collision sport athlete controls with no history of concussion. Participants completed three ocular motor tasks (prosaccade, antisaccade and a cognitively complex switch task) to assess processing speed, inhibitory control and cognitive flexibility, respectively. Diffusion tensor imaging data were acquired using a 3 T MRI scanner, and analysed using tract-based spatial statistics, to investigate white matter abnormalities and how they relate to ocular motor performance. Australian footballers had significantly slower adjusted antisaccade latencies compared to controls (P = 0.035). A significant switch cost (i.e. switch trial error > repeat trial error) was also found on the switch task, with Australian footballers performing increased magnitude of errors on prosaccade switch trials relative to prosaccade repeat trials (P = 0.023). Diffusion tensor imaging analysis found decreased fractional anisotropy, a marker of white matter damage, in major white matter tracts (i.e. corpus callosum, corticospinal tract) in Australian footballers relative to controls. Notably, a larger prosaccade switch cost was significantly related to reduced fractional anisotropy in anterior white matter regions found to connect to the prefrontal cortex (i.e. a key cortical ocular motor centre involved in executive functioning and task switching). Taken together, Australian footballers with a history of concussion have ocular motor deficits indicative of poorer cognitive processing speed and cognitive flexibility, which are related to reduce white matter integrity in regions projecting to important cognitive ocular motor structures. These findings provide novel insights into the neural mechanisms that may underly chronic cognitive impairments in individuals with a history of concussion.

Construction of Virtual Simulation Teaching Platform for Microteaching

In the process of microteaching and training, virtual simulation technology is introduced to solve the problems that the real classroom training of normal school students can’t meet the diversified classroom situations and low tolerance of trial error, and increase the sense of reality and scene of training. Based on modern microteaching theory, instructional design theory and feedback mechanism, a virtual simulation platform of microteaching is constructed, which enables normal school students to conduct training in a flexible and independent manner according to their own needs. Using virtual reality technology and speech recognition technology, a virtual simulation teaching platform is developed, which covers the selection of scenes, the introduction of courseware, the setting of questions, the questioning of students and the emergency treatment. The platform that is applied to the microteaching training course of normal school students’ teaching skills has achieved good results.

Experience-related enhancements in striatal temporal encoding.

Temporal control of action is key for a broad range of behaviors and is disrupted in human diseases such as Parkinson's disease and schizophrenia. A brain structure that is critical for temporal control is the dorsal striatum. Experience and learning can influence dorsal striatal neuronal activity, but it is unknown how these neurons change with experience in contexts which require precise temporal control of movement. We investigated this question by recording from medium spiny neurons (MSNs) via dorsal striatal microelectrode arrays in mice as they gained experience controlling their actions in time. We leveraged an interval timing task optimized for mice which required them to "switch" response ports after enough time had passed without receiving a reward. We report three main results. First, we found that time-related ramping activity and response-related activity increased with task experience. Second, temporal decoding by MSN ensembles improved with experience and was predominantly driven by time-related ramping activity. Finally, we found that a subset of MSNs had differential modulation on error trials. These findings enhance our understanding of dorsal striatal temporal processing by demonstrating how MSN ensembles can evolve with experience. Our results can be linked to temporal habituation and illuminate striatal flexibility during interval timing, which may be relevant for human disease.

Hippocampal place cell sequences differ during correct and error trials in a spatial memory task

Theta rhythms temporally coordinate sequences of hippocampal place cell ensembles during active behaviors, while sharp wave-ripples coordinate place cell sequences during rest. We investigated whether such coordination of hippocampal place cell sequences is disrupted during error trials in a delayed match-to-place task. As a reward location was learned across trials, place cell sequences developed that represented temporally compressed paths to the reward location during the approach to the reward location. Less compressed paths were represented on error trials as an incorrect stop location was approached. During rest periods of correct but not error trials, place cell sequences developed a bias to replay representations of paths ending at the correct reward location. These results support the hypothesis that coordination of place cell sequences by theta rhythms and sharp wave-ripples develops as a reward location is learned and may be important for the successful performance of a spatial memory task.

Temporal Fluctuation of Mood in Gaming Task Modulates Feedback Negativity: EEG Study With Virtual Reality.

Feedback outcomes are generally classified into positive and negative feedback. People often predict a feedback outcome with information that is based on both objective facts and uncertain subjective information, such as a mood. For example, if an action leads to good results consecutively, people performing the action overestimate the behavioral result of the next action. In electroencephalogram measurements, negative feedback evokes negative potential, called feedback negativity, and positive feedback evokes positive potential, called reward positivity. The present study investigated the relationship between the degree of the mood caused by the feedback outcome and the error-related brain potentials. We measured the electroencephalogram activity while the participants played a virtual reality shooting game. The experimental task was to shoot down a cannonball flying toward the player using a handgun. The task difficulty was determined from the size and curve of the flying cannonball. These gaming parameters affected the outcome probability of shooting the target in the game. We also implemented configurations in the game, such as the player’s life points and play times. These configurations affected the outcome magnitude of shooting the target in the game. Moreover, we used the temporal accuracy of shooting in the game as the parameter of the mood. We investigated the relationship between these experimental features and the event-related potentials using the single-trial-based linear mixed-effects model analysis. The feedback negativity was observed at an error trial, and its amplitude was modulated with the outcome probability and the mood. Conversely, reward positivity was observed at hit trials, but its amplitude was modulated with the outcome probability and outcome magnitude. This result suggests that feedback negativity is enhanced according to not only the feedback probability but also the mood that was changed depending on the temporal gaming outcome.

The contributions of entorhinal cortex and hippocampus to error driven learning

Computational models proposed that the medial temporal lobe (MTL) contributes importantly to error-driven learning, though little direct in-vivo evidence for this hypothesis exists. To test this, we recorded in the entorhinal cortex (EC) and hippocampus (HPC) as macaques performed an associative learning task using an error-driven learning strategy, defined as better performance after error relative to correct trials. Error-detection signals were more prominent in the EC relative to HPC. Early in learning hippocampal but not EC neurons signaled error-driven learning by increasing their population stimulus-selectivity following error trials. This same pattern was not seen in another task where error-driven learning was not used. After learning, different populations of cells in both the EC and HPC signaled long-term memory of newly learned associations with enhanced stimulus-selective responses. These results suggest prominent but differential contributions of EC and HPC to learning from errors and a particularly important role of the EC in error-detection.

Computational minimization of over-deposition at corners of trajectories in Laser Metal Deposition

Avoidance of over-deposition at trajectory corners is relevant in Laser Metal Deposition (LMD) for Additive Manufacturing. Currently available LMD hardware only allows constant material feed (g/s). Therefore, gliding speed of the material dispenser is the remaining tuning variable for controlling metal over-deposition at corners. Existing literature reports trial–error physical experiments, addressing only particular corner angles. In response, this manuscript reports the implementation of a voxel-based simulator of the bead geometry, taking into consideration bead profile, dispenser velocity, material feed, and bead curve geometry. We use it to evaluate two constant-feed tailored-velocity strategies for minimizing material over-deposition at corners.