Trial And Error Research Articles

Ameliorative effect of walnut oil against cognitive impairment in Alzheimers type dementia in rodent

Walnut oil (WO), known for abundant polyunsaturated fatty acids and an array of bioactive substances such as tocopherols, phytosterols, squalene, melatonin, and polyphenols, which is endowed with numerous health advantages. The primary objective of this research was to ascertain the impact of WO on cognitive deficits in learning and memory impairment mice caused by scopolamine (SCOP). The Morris water maze and the step-down avoidance test were utilized to assess the memory and learning capabilities. WO notably counteracted the detrimental effects of SCOP on learning and memory in the Morris water maze, as indicated by a reduction in escape latency and swimming distance. Likewise, WO administration led to a notably reduced number of errors in training trial and an increased latency in testing trial when compared to the SCOP group in the step-down avoidance test,. Moreover, WO activated the cholinergic system of the brain by upregulating choline acetyltransferase activity and reducing acetylcholinesterase activity. These results suggest that WO has the potential to protect against memory decline in mice, offering a promising strategy for the prevention of memory-related disorders.

A Scientific Framework for Analyzing the Harmfulness of Trial Errors

A Scientific Framework for Analyzing the Harmfulness of Trial Errors

A robust temporal map of speech monitoring from planning to articulation

Speakers continuously monitor their own speech to optimize fluent production, but the precise timing and underlying variables influencing speech monitoring remain insufficiently understood. Through two EEG experiments, this study aimed to provide a comprehensive temporal map of monitoring processes ranging from speech planning to articulation.In both experiments, participants were primed to switch the consonant onsets of target word pairs read aloud, eliciting speech errors of either lexical or articulatory-phonetic (AP) origin. Experiment I used pairs of the same stimuli words, creating lexical or non-lexical errors when switching initial consonants, with the degree of shared AP features not fully balanced but considered in the analysis. Experiment II followed a similar methodology but used different words in pairs for the lexical and non-lexical conditions, fully orthogonalizing the number of shared AP features.As error probability is higher in trials primed to result in lexical versus non-lexical errors and AP-close compared to AP-distant errors, more monitoring is required for these conditions. Similarly, error trials require more monitoring compared to correct trials. We used high versus low error probability on correct trials and errors versus correct trials as indices of monitoring.Across both experiments, we observed that on correct trials, lexical error probability effects were present during initial stages of speech planning, while AP error probability effects emerged during speech motor preparation. In contrast, error trials showed differences from correct utterances in both early and late speech motor preparation and during articulation. These findings suggest that (a) response conflict on ultimately correct trials does not persist during articulation; (b) the timecourse of response conflict is restricted to the time window during which a given linguistic level is task-relevant (early on for response appropriateness-related variables and later for articulation-relevant variables); and (c) monitoring during the response is primarily triggered by pre-response monitoring failure. These results support that monitoring in language production is temporally distributed and rely on multiple mechanisms.

Precision measurement of rehabilitation interventions-a secondary analysis of motor error in a clinical trial with young children with cerebral palsy.

The delivery of precision medicine in rehabilitation will require not only precise measurement of participant response, but also precise measurement of the "ingredients" of intervention and their dose. As an example, we report the measurement of motor error in two treatment groups from a randomized controlled trial in toddlers (mean age 26.3 months) with cerebral palsy (CP). Our objective was to measure the type and amount of motor error during physical therapy sessions in young children with CP. Participants were stratified by motor function and age and randomly allocated to "conventional" physical therapy that generally prevented falls or to an intervention that encouraged error experience by not preventing falls (experimental group). Baseline motor and cognitive function were measured using the Gross Motor Function Measure-66 (GMFM-66) and Bayley 3 cognitive subscale (B3-C) prior to randomization. Randomly selected video recorded therapy sessions were manually coded to identify losses of balance defined as falls (child contacted floor), rescues (therapist prevented fall) or saves (child recovered their balance independently). Average number of losses of balance per session were higher in the experimental group than the conventional group due to significantly greater falls. Saves were infrequent in both groups but were also significantly higher in the experimental group. Average number of rescues did not differ between groups. In the experimental group, greater frequency of falls was significantly related to GMFM-66. In both groups, greater frequency of saves was related to GMFM-66. Neither total losses of balance per session nor rescues were related to GMFM-66 in either group. There were no significant relationships between losses of balance and baseline cognition in either group, except greater frequency of saves was related to higher cognitive ability in the experimental group. Our observations suggest that motor error experience is lower in toddlers with CP compared to peers with typical development but can be manipulated to higher doses of error during therapy sessions. Future work should investigate the relationship between type and amount of error experience and rehabilitation outcomes, as well as other "ingredients" of rehabilitation therapy. Tools to automate the precise measurement of intervention content are necessary for broad scale implementation.

Sub-threshold neuronal activity and the dynamical regime of cerebral cortex

Cortical neurons exhibit temporally irregular spiking patterns and heterogeneous firing rates. These features arise in model circuits operating in a ‘fluctuation-driven regime’, in which fluctuations in membrane potentials emerge from the network dynamics. However, it is still debated whether the cortex operates in such a regime. We evaluated the fluctuation-driven hypothesis by analyzing spiking and sub-threshold membrane potentials of neurons in the frontal cortex of mice performing a decision-making task. We showed that while standard fluctuation-driven models successfully account for spiking statistics, they fall short in capturing the heterogeneity in sub-threshold activity. This limitation is an inevitable outcome of bombarding single-compartment neurons with a large number of pre-synaptic inputs, thereby clamping the voltage of all neurons to more or less the same average voltage. To address this, we effectively incorporated dendritic morphology into the standard models. Inclusion of dendritic morphology in the neuronal models increased neuronal selectivity and reduced error trials, suggesting a functional role for dendrites during decision-making. Our work suggests that, during decision-making, cortical neurons in high-order cortical areas operate in a fluctuation-driven regime.

A registered report of a two-site study of variations of the flanker task: ERN experimental effects and data quality.

Error-related negativity is a widely used measure of error monitoring, and many projects are independently moving ERN recorded during a flanker task toward standardization, optimization, and eventual clinical application. However, each project uses a different version of the flanker task and tacitly assumes ERN is functionally equivalent across each version. The routine neglect of a rigorous test of this assumption undermines efforts to integrate ERN findings across tasks, optimize and standardize ERN assessment, and widely apply ERN in clinical trials. The purpose of this registered report was to determine whether ERN shows similar experimental effects (correct vs. error trials) and data quality (intraindividual variability) during three commonly used versions of a flanker task. ERN was recorded from 172 participants during three versions of a flanker task across two study sites. ERN scores showed numerical differences between tasks, raising questions about the comparability of ERN findings across studies and tasks. Although ERN scores from all three versions of the flanker task yielded high data quality and internal consistency, one version did outperform the other two in terms of the size of experimental effects and the data quality. Exploratory analyses of the error positivity (Pe) provided tentative support for the other two versions of the task over the paradigm that appeared optimal for ERN. The present study provides a roadmap for how to statistically compare psychometric characteristics of ERP scores across paradigms and gives preliminary recommendations for flanker tasks to use for ERN- and Pe-focused studies.

New disturbance observer-based speed estimator for induction motor

<p>This paper discusses a novel disturbance observer designed as an estimator to determine the rotor speed of an induction motor. This observer is a solution to obtain a simple structure with a small number of compact observer gains. Furthermore, the adaptation law is no longer required to estimate induction motor speed values. This is a machine model-based computation method that uses a stationary reference frame. The nonlinearity problem is solved using an additional state vector in the observer model, which is known as an extended state observer. This approach easily and systematically determines the observer gain by applying the linear quadratic regulator (LQR) method, thereby avoiding time-consuming trial errors. The proposed observer, which was presented in both continuous and discrete forms, was tested using a sensorless V/f- controlled induction motor. The simulation results show that the proposed observer can accurately estimate all states, namely, the rotor flux and stator current; therefore, the proposed estimator provides the speed and electromagnetic torque for a wide operational range of speeds and load torques. It was also shown that the proposed observer was robust to noise and uncertainty in induction motor parameters.</p>

Flexible control of sequence working memory in the macaque frontal cortex

To memorize a sequence, one must serially bind each item to its rank order. How the brain controls a given input to bind its associated order in sequence working memory (SWM) remains unexplored. Here, we investigated the neural representations underlying SWM control using electrophysiological recordings in the frontal cortex of macaque monkeys performing forward and backward SWM tasks. Separate and generalizable low-dimensional subspaces for sensory and memory information were found within the same frontal circuitry, and SWM control was reflected in these neural subspaces' organized dynamics. Each item at each rank was sequentially entered into a common sensory subspace and, depending on forward or backward task requirement, flexibly and timely sent into rank-selective SWM subspaces. Neural activity in these SWM subspaces faithfully predicted the recalled item and order information in single error trials. Thus, compositional neural population codes with well-orchestrated dynamics in frontal cortex support the flexible control of SWM.

Optimal development of apoptotic cells-mimicking liposomes targeting macrophages

Macrophages are multifunctional innate immune cells that play indispensable roles in homeostasis, tissue repair, and immune regulation. However, dysregulated activation of macrophages is implicated in the pathogenesis of various human disorders, making them a potential target for treatment. Through the expression of pattern recognition and scavenger receptors, macrophages exhibit selective uptake of pathogens and apoptotic cells. Consequently, the utilization of drug carriers that mimic pathogenic or apoptotic signals shows potential for targeted delivery to macrophages. In this study, a series of mannosylated or/and phosphatidylserine (PS) -presenting liposomes were developed to target macrophages via the design of experiment (DoE) strategy and the trial-and-error (TaE) approach. The optimal molar ratio for the liposome formulation was DOPC: DSPS: Chol: PEG-PE = 20:60:20:2 based on the results of cellular uptake and cytotoxicity evaluation on RAW 264.7 and THP-1 in vitro. Results from in vivo distribution showed that, in the DSS-induced colitis model and collagen II-induced rheumatoid arthritis model, PS-presenting liposomes (PS-Lipo) showed the highest accumulation in intestine and paws respectively, which holds promising potential for macrophage target therapy since macrophages are abundant at inflammatory sites and contribute to the progression of corresponding diseases. Organs such as the heart, liver, spleen, lung, and kidney did not exhibit histological alterations such as inflammation or necrosis when exposed to PC-presenting liposomes (PC-Lipo) or PS-Lipo. In addition, liposomes demonstrated hemobiocompatibility and no toxicity to liver or kidney for circulation and did not induce metabolic injury in the animals. Thus, the well-designed PS-Lipo demonstrated the most potential for macrophage target therapy.

Initial learning in the brain: From rules to action

Abstract We used fMRI to investigate the neural changes and representational dynamics associated with different learning modes during initial learning and subsequent implementation of previously acquired stimulus-response (S-R) associations. We compared instruction-based learning (INS) and trial-and-error learning (TE) via a third observation-based learning (OBS) condition. This was yoked to the TE condition and shared features with both, the INS and TE conditions. During learning, neural changes were observed in the Frontoparietal and Default Mode Networks across learning modes, consistent with a general decrease in cognitive control demand as learning progresses. INS and TE exhibited condition-specific signal changes, which we interpreted in the context of covert motor preparation during INS, and intentional action and increased cognitive control demand during early TE trials, respectively. Multivariate pattern analysis revealed individual rule information in bilateral prefrontal, premotor, and parietal cortices across learning modes. Most regions revealed consistent representations of individual S-R rules between the learning stage and subsequent implementation stage, regardless of the learning mode. This suggests that initially formed S-R rule representations guide task performance during S-R rule implementation, irrespective of how they are acquired. Finally, within the primary motor and sensory cortices, individual S-R rules were decodable during the learning stage not only when motor responses were overtly executed, as in TE, but also in the absence of overt motor execution, as in INS. This finding substantiates previous claims of covert motor preparatory mechanisms during INS.

A Benchmarking Method to Rank the Performance of Physics-Based Earthquake Simulations

Abstract Physics-based earthquake simulators are an increasingly popular modeling tool in earthquake forecasting for seismic hazard as well as fault rupture behavior studies. Their popularity comes from their ability to overcome completeness limitations of real catalogs, and also because they allow reproducing complex fault rupture and interaction patterns via modeling the physical processes involved in earthquake nucleation and propagation. One important challenge of these models revolves around selecting the physical input parameters that will yield the better similarity to earthquake relationships observed in nature, for instance, the frictional parameters of the rate-and-state law—a and b—or the initial normal and shear stresses. Because of the scarcity of empirical data, such input parameters are often selected by trial–error exploration and predominantly manual model performance analyses, which can overall be time consuming. We present a new benchmarking approach to analyze and rank the relative performance of simultaneous earthquake simulation catalogs by quantitatively scoring their combined fit to three reference function types: (1) earthquake-scaling relationships, (2) the shape of the magnitude–frequency distributions, and (3) the rates of the surface ruptures from paleoseismology or paleoearthquake occurrences. The approach provides an effective and potentially more efficient approximation to easily identify the models and input parameter combinations that fit more closely to earthquake relations and behavior. The approach also facilitates the exhaustive analysis of many input parameter combinations, identifying systematic correlations between parameters and model outputs that can potentially improve the overall understanding of the physics-based models. Finally, we demonstrate how the method results agree with the published findings in other earthquake simulation evaluations, a fact that reinforces its overall usefulness. The model ranking outputs can be useful for subsequent analyses, particularly in seismic hazard applications, such as the selection of appropriate earthquake occurrence rate models and their weighting for a logic tree.

Prefrontal neuronal dynamics in the absence of task execution

Prefrontal cortical activity represents stimuli in working memory tasks in a low-dimensional manifold that transforms over the course of a trial. Such transformations reflect specific cognitive operations, so that, for example, the rotation of stimulus representations is thought to reduce interference by distractor stimuli. Here we show that rotations occur in the low-dimensional activity space of prefrontal neurons in naïve male monkeys (Macaca mulatta), while passively viewing familiar stimuli. Moreover, some aspects of these rotations remain remarkably unchanged after training to perform working memory tasks. Significant training effects are still present in population dynamics, which further distinguish correct and error trials during task execution. Our results reveal automatic functions of prefrontal neural circuits allow transformations that may aid cognitive flexibility.

Highly stable silicon oxycarbide all-solid-state batteries enabled by machined learning accelerated screening of oxides and sulfides electrolytes

Traditional trial–error approach severely limits and restricts rapid development of high-performance anode and electrolytes materials, searching huge parameters space of various anode-solid electrolyte interfaces in an effective and efficient way is the key issue. Here, a novel computational strategy combining machine learning and first-principles is proposed to achieve efficient high-throughput screening of oxides and sulfides electrolytes for highly stable silicon oxycarbide all-solid-state batteries. First-principles calculations demonstrate significant compact of material type and elemental doping on interfacial compatibility between silicon oxycarbide and various electrolytes. By proposing several novel descriptors including interfacial adhesion and formation energies of frozen system with low computation cost, the amounts of demanded trainings data are significantly reduced. Gradient-boosted regression tree model shows low mean absolute errors of 0.09 and high R2 value of 0.99 for the prediction of interface formation energy, demonstrating ultrahigh accuracy and reliability of the algorithm. The present work discovers a series of uninvestigated stable anode-solid electrolytes interfacial couples for further experimental preparation.

Multiscale chemogenetic dissection of fronto-temporal top-down regulation for object memory in primates

Visual object memory is a fundamental element of various cognitive abilities, and the underlying neural mechanisms have been extensively examined especially in the anterior temporal cortex of primates. However, both macroscopic large-scale functional network in which this region is embedded and microscopic neuron-level dynamics of top-down regulation it receives for object memory remains elusive. Here, we identified the orbitofrontal node as a critical partner of the anterior temporal node for object memory by combining whole-brain functional imaging during rest and a short-term object memory task in male macaques. Focal chemogenetic silencing of the identified orbitofrontal node downregulated both the local orbitofrontal and remote anterior temporal nodes during the task, in association with deteriorated mnemonic, but not perceptual, performance. Furthermore, imaging-guided neuronal recordings in the same monkeys during the same task causally revealed that orbitofrontal top-down modulation enhanced stimulus-selective mnemonic signal in individual anterior temporal neurons while leaving bottom-up perceptual signal unchanged. Furthermore, similar activity difference was also observed between correct and mnemonic error trials before silencing, suggesting its behavioral relevance. These multifaceted but convergent results provide a multiscale causal understanding of dynamic top-down regulation of the anterior temporal cortex along the ventral fronto-temporal network underpinning short-term object memory in primates.

No association between error-related ERPs and trait anxiety in a nonclinical sample: Convergence across analytical methods including mass-univariate statistics.

Enhanced error monitoring, as indexed by increased amplitude of the error-related negativity (ERN) event-related potential (ERP) component, has been suggested to reflect a vulnerability neuro-marker of anxiety disorders. Another error-related ERP component is the error positivity (Pe), which reflects late-stage error processing. The associations between heightened ERN and Pe amplitudes and anxiety levels in the nonclinical population have been inconsistent. In this preregistered study, we examined the association between anxiety, ERN, and Pe, using different analytical methods (mass-univariate analyses, MUAs and conventional analyses), self-reported anxiety scales (STAI and STICSA), and trial numbers (all correct trials and equal numbers of correct and error trials). In a sample of 82 healthy adults, both conventional and MUAs demonstrated a robust enhancement of the ERN and Pe to errors relative to the correct-response ERPs. However, the mass-univariate approach additionally unveiled a wider array of electrodes and a longer effect duration for this error enhancement. Across the analytic methods, the results showed a lack of consistent correlation between trait anxiety and error-related ERPs. Findings were not modulated by trial numbers, analyses, or anxiety scales. The present results suggest a lack of enhancement of error monitoring by anxious traits in individuals with subclinical anxiety and those with clinical anxiety but without a clinical diagnosis. Importantly, the absence of such correlation questions the validity of the ERN as a neural marker for anxiety disorders. Future studies that investigate neuro-markers of anxiety may explore alternative task designs and employ robust statistics to provide a more comprehensive understanding of anxiety vulnerability.

Locus coeruleus norepinephrine contributes to visual-spatial attention by selectively enhancing perceptual sensitivity.

Selectively focusing on a behaviorally relevant stimulus while ignoring irrelevant stimuli improves perception. Enhanced neuronal response gain is thought to support attention-related improvements in detection and discrimination. However, understanding of the neuronal pathways regulating perceptual sensitivity remains limited. Here, we report that responses of norepinephrine (NE) neurons in the locus coeruleus (LC) of non-human primates to behaviorally relevant sensory stimuli promote visual discrimination in a spatially selective way. LC-NE neurons spike in response to a visual stimulus appearing in the contralateral hemifield only when that stimulus is attended. This spiking is associated with enhanced behavioral sensitivity, is independent of motor control, and is absent on error trials. Furthermore, optogenetically activating LC-NE neurons selectively improves monkeys' contralateral stimulus detection without affecting motor criteria, supporting NE's causal role in granular cognitive control of selective attention at a cellular level, beyond its known diffuse and non-selective functions.

Awareness of Visual Offset Reduces but Does Not Eliminate Joint Repositioning Errors in Virtual Reality

The present study investigated the effect of visual offset (visuo-proprioceptive mismatch) in joint repositioning task in a three-dimensional virtual reality (VR) environment when participants were instructed to ignore vision. Twenty-five physically healthy young individuals performed shoulder joint position sense test. Repositioning accuracy was tested under two visual conditions, accurate and offset visions, and two instructions, no guidance or ignore vision. In accurate vision trials, the virtual hand of the tested limb seen in VR was congruent with where the participant placed their hand. In the offset vision condition, the virtual hand was seen 8° above or below their actual hand in the vertical plane. Repositioning error (i.e. constant error) in offset vision trials was lower when the participants were instructed to ignore vision compared to when no instruction about the visual offset was given (p < 0.001). However, constant error in offset vision trials was larger than accurate vision trials when the participants tried to ignore vision in both visual conditions (p < 0.001). Our results suggest that humans may be able to down-weight vision to some extent by conscious effort, while the influence of vision is difficult to eliminate when vision is present.

Optogenetic inhibition of the orbitofrontal cortex disrupts inhibitory control during stop-change performance in male rats.

Historically, the orbitofrontal cortex (OFC) has been implicated in a variety of behaviors ranging from reversal learning and inhibitory control to more complex representations of reward value and task space. While modern interpretations of the OFC's function have focused on a role in outcome evaluation, these cognitive processes often require an organism to inhibit a maladaptive response or strategy. Single unit recordings from the OFC in rats performing a stop-change task show that the OFC responds strongly to STOP trials. To investigate the role that the OFC plays in stop-change performance we expressed halorhodopsin (eNpHR3.0) in excitatory neurons in the OFC and tested rats on the stop-change task. Previous work suggests that the OFC differentiates between STOP trials based on trial sequence (i.e., gS trials: STOP trials preceded by a GO versus sS trials: STOP trials preceded by a STOP). We found that yellow light activation of the eNpHR3.0 expressing neurons significantly decreased accuracy only on STOP trials that followed GO trials (gS trials). Further, optogenetic inhibition of OFC speeded reaction times on error trials. This suggests that the OFC plays a role in inhibitory control processes, and that this role needs to be accounted for in modern interpretations of OFC function.Significance Statement The orbitofrontal cortex (OFC) is a highly interconnected brain region thought to be essential for healthy cognitive function. Historically, research has implicated the OFC in the inhibition of inappropriate actions, however, more recent work has focused on its role in guiding value-based decision making. Using a modified version of a canonical inhibitory control task in combination with optogenetics, we show that while important for value-based decision making, disruption of excitatory neurons in the OFC impairs inhibitory control processes as well. This highlights the need for theoretical accounts of OFC function to accommodate its role in both types of cognitive processes.

459. Reducing Errors in Clinical Trials: The Importance of Acknowledging Human Error and Improving Quality Control

459. Reducing Errors in Clinical Trials: The Importance of Acknowledging Human Error and Improving Quality Control

Computational Mechanics for Turbofan Engine Blade Containment Testing: Fan Case Design and Blade Impact Dynamics by Finite Element Simulations

The harsh environment during airplane take-off and flights with complex operating conditions require a high dynamic and impact resistance capability of airplane engines. The design, development, and performance evaluation of new turbofan engines are generally performed through numerical simulations before a full-scale model or prototype experiment for certification. Simulations of fan blade containment tests can reduce trial–error testing and are currently the most convenient and inexpensive alternative for design; however, certification failure is always a risk if the calibration of material models is not correctly applied. This work presents a three-dimensional computational model of a turbofan for designing new engines that meet the certification requirements under the blade containment test. Two calibrated Johnson–Cook plasticity and damage laws for Ti64 are assessed in a simulation of a turbofan blade containment test, demonstrating the ability of the models to be used in the safe design of aircraft engine components subjected to dynamic impact loads with large deformations and adequate damage tolerance.