Time-based Decision Research Articles

Using temperature to analyze the neural basis of a time-based decision.

The basal ganglia are thought to contribute to decision-making and motor control. These functions are critically dependent on timing information, which can be extracted from the evolving state of neural populations in their main input structure, the striatum. However, it is debated whether striatal activity underlies latent, dynamic decision processes or kinematics of overt movement. Here, we measured the impact of temperature on striatal population activity and the behavior of rats, and compared the observed effects with neural activity and behavior collected in multiple versions of a temporal categorization task. Cooling caused dilation, and warming contraction, of both neural activity and patterns of judgment in time, mimicking endogenous decision-related variability in striatal activity. However, temperature did not similarly affect movement kinematics. These data provide compelling evidence that the timecourse of evolving striatal activity dictates the speed of a latent process that is used to guide choices, but not continuous motor control. More broadly, they establish temporal scaling of population activity as a likely neural basis for variability in timing behavior.

Efficient coding of cognitive variables underlies dopamine response and choice behavior.

Reward expectations based on internal knowledge of the external environment are a core component of adaptive behavior. However, internal knowledge may be inaccurate or incomplete due to errors in sensory measurements. Some features of the environment may also be encoded inaccurately to minimize representational costs associated with their processing. In this study, we investigated how reward expectations are affected by features of internal representations by studying behavior and dopaminergic activity while mice make time-based decisions. We show that several possible representations allow a reinforcement learning agent to model animals' overall performance during the task. However, only a small subset of highly compressed representations simultaneously reproduced the co-variability in animals' choice behavior and dopaminergic activity. Strikingly, these representations predict an unusual distribution of response times that closely match animals' behavior. These results inform how constraints of representational efficiency may be expressed in encoding representations of dynamic cognitive variables used for reward-based computations.

Assembly Line Overall Equipment Effectiveness (OEE) Prediction from Human Estimation to Supervised Machine Learning

Nowadays, in the domain of production logistics, one of the most complex planning processes is the accurate forecasting of production and assembly efficiency. In industrial companies, Overall Equipment Effectiveness (OEE) is one of the most common used efficiency measures at semi-automatic assembly lines. Proper estimation supports the right use of resources and more accurate and cost-effective delivery to the customers. This paper presents the prediction of OEE by comparing human prediction with one of the techniques of supervised machine learning through a real-life example. In addition to descriptive statistics, takt time-based decision trees are applied and the target-oriented OEE prediction model is presented. This concept takes into account recent data and assembly line targets with different weights. Using the model, the value of OEE can be predicted with an accuracy of within 1% on a weekly basis, four weeks in advance.

A 32Gb/s Time-Based PAM-4 Transceiver for High-Speed DRAM Interfaces With In-Situ Channel Loss and Bit-Error-Rate Monitors

A digital-intensive four-level pulse amplitude (PAM-4) transceiver featuring a 2-tap time-based decision feedback equalization (TB-DFE) circuit was demonstrated in a 65 nm GP CMOS process. A novel inverter-based differential voltage-to-time converter (DVTC) increases the linearity and dynamic range compared to a prior time-based DFE approach enabling reliable PAM-4 operation. The four-level signal comparison and DFE operation were performed entirely in the time domain using programmable delays and a phase detector (PD). Using an on-chip bit error rate (BER) monitor, we verified a BER less than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−12</sup> while achieving an energy-efficiency of 0.97pJ/b at a 32Gb/s data rate. The transmitter (TX) and receiver (RX) circuits occupy an area of 0.009 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> .

Time-Based Decision Making for Reperfusion in Acute Ischemic Stroke

Decision making in the extended time windows for acute ischemic stroke can be a complex and time-consuming process. The process of making the clinical decision to treat has been compounded by the availability of different imaging modalities. In the setting of acute ischemic stroke, time is of the essence and chances of a good outcome diminish by each passing minute. Navigating the plethora of advanced imaging modalities means that treatment in some cases can be inefficaciously delayed. Time delays and individually based non-programmed decision making can prove challenging for clinicians. Visual aids can assist such decision making aimed at simplifying the use of advanced imaging. Flow charts are one such visual tool that can expedite treatment in this setting. A systematic review of existing literature around imaging modalities based on site of occlusion and time from onset can be used to aid decision making; a more program-based thought process. The use of an acute reperfusion flow chart helping navigate the myriad of imaging modalities can aid the effective treatment of patients.

Racing against the clock: Evidence-based versus time-based decisions.

Classical dynamic theories of decision making assume that responses are triggered by accumulating a threshold amount of information. Recently, there has been a growing appreciation that the passage of time also plays a role in triggering responses. We propose that decision processes are composed of 2 diffusive accumulation mechanisms-1 evidence-based and 1 time-based-that compete in an independent race architecture. We show that this timed racing diffusion model (TRDM) provides a unified, comprehensive, and quantitatively accurate explanation of key decision phenomena-including the effects of implicit and explicit deadlines and the relative speed of correct and error responses under speed-accuracy trade-offs-without requiring additional mechanisms that have been criticized as being ad hoc in theoretical motivation and difficult to estimate, such as trial-to-trial variability parameters, collapsing thresholds, or urgency signals. In contrast, our addition is grounded in a widely validated account of time-estimation performance, enabling the same mechanism to simultaneously account for interval estimation and decision making with an explicit deadline. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Spatial and temporal reasoning with granular computing and three way formal concept analysis

This paper presents and evaluates a method to combine time-based granulation and three-way decisions to support decision makers in understanding and reasoning on the learned granular structures conceptualising spatio-temporal events. The method uses an existing approach to discover periodic events in the data, such as periods of intense traffic in a city, and provides an original approach to conceptualize such events to support decision makers in: (i) better comprehending the causes that lead to the repetition of such events and/or (ii) increasing the awareness of their effects and consequences. The formal concept analysis is the central tool of the proposed method. This tool is used as a guide in the phase of time-based granulation, which relies on the principle of justified granularity, and as a support for reasoning and making three-way decisions. The main contribution of the paper is an effective and simple method for time-based granulation of events, their observation, and interpretation to support decision making. The method is described with an illustrative example and evaluated on a real data set on forest fires, showing how to define a spatio-temporal DSS model to support decisions in environmental monitoring problems.

Corning's cell culture monitoring system enables data-driven decisions for large-scale cell applications by providing remote, real-time monitoring of cell confluence in multi-layered cell culture vessels

Background & Aim There is currently a demand for new technologies to address the challenges associated with large-scale production for the vast number of emerging cell and gene therapy applications. One specific pain point for upstream bioprocess scientists is the inability to effectively monitor processes involving adherent cell types. Today's complex cell culture protocols require scientists to accurately know the confluence level of a vessel to achieve the optimal productivity for a specific process step. Currently, there is no way to remotely monitor the confluence level for each vessel in a production lot in real-time. As a result, scientists are forced to manually interrogate a limited number of surrogate vessels and then make a subjective estimation of the confluence value. This process results in inadequate data that can lead to high variability and suboptimal performance. Methods, Results & Conclusion To address this issue, Corning has invented a novel technology that will enable customers to remotely monitor cell confluence in multi-layered cell culture vessels. The system can capture high-quality cell images and determine accurate machine-generated confluence values. Real-time confluence values are displayed on dashboards that can be accessed remotely by the user. Separate operating environments have been developed for process development and production workstreams. Overall, the Corning technology offers several key advantages over the current process. Most importantly, real-time monitoring of cell confluence will allow scientists to make data-driven decisions, thereby improving the consistency and overall performance of their processes. The current strategy of making time-based decisions is not suitable for today's increasingly complex protocols. The first product to be available will monitor cell confluence in Corning® CellSTACK® cell culture vessels. The system has been used to monitor the growth of several industry-relevant cell lines. For each cell line tested, very strong correlation was observed between the Corning monitoring system and a traditional microscope. Corning's technology addresses a key gap in today's large-scale cell manufacturing process; namely the inability to effectively monitor cell confluence in production-scale vessels. The technology will allow customers to achieve a better fundamental understanding of their processes and make data-driven decisions to improve consistency and overall performance.

Endovascular Thrombectomy for Acute Ischemic Stroke.

To review the current evidence supporting the use of endovascular thrombectomy (EVT) for the treatment of acute ischemic stroke (AIS) due to anterior circulation large vessel occlusion (LVO). Recent advances in AIS management by EVT have led to significant reduction in morbidity and mortality in selected patients with LVO within the anterior circulation. Until recently, use of EVT was strictly based on time criteria, within 4.5 to 12h of symptom onset with many patients presenting with "wake-up" stroke who were not considered for EVT. The positive results of the DAWN and DEFUSE-3 trials have shown benefit in extending the therapeutic window for EVT to 24 and 16h, respectively, after last known normal (LKN) time in the setting of large ischemic penumbra. These trials represent a paradigm shift in contemporary treatment of AIS, changing from a purely time-based decision to treat to an individualized decision based on clinical and radiographic findings of salvageable tissue. Overall, acute stroke management has evolved considerably over the years from intravenous thrombolysis to include EVT, with paralleled improvements in patient selection and thrombectomy devices. Since the results of the DAWN and DEFUSE-3, EVT is now considered the standard of care in select patients with anterior circulation LVO up to 24h from LKN time. Despite these developments, post-stroke disability remains pervasive and further studies are warranted in establishing the role of EVT in posterior circulation and distal vessel occlusions, with need for development of new and effective techniques for revascularization of small vessels.

Choosing the Right Resident: Implications of the New Electronic Emergency Medicine Standardized Letter of Evaluation.

Choosing the Right Resident: Implications of the New Electronic Emergency Medicine Standardized Letter of Evaluation.

A 65-nm 10-Gb/s 10-mm On-Chip Serial Link Featuring a Digital-Intensive Time-Based Decision Feedback Equalizer

A digital-intensive on-chip serial link achieving a 10 Gb/s data rate over a 10-mm interconnect was demonstrated in a 65-nm GP process. A three-tap half-rate feed-forward equalizer was implemented for signal pre-emphasis in the transmitted block. On the receiver (RX) side, a two-tap half-rate time-based decision feedback equalizer was employed to cancel out inter-symbol interference noise. A 215 – 1 pseudorandom binary sequence generator and an in situ bit error rate (BER) monitor were designed for bit stream generation and convenient eye-diagram measurements. The measured energy efficiency of the transmitter and RX was 31.9 and 45.3 fJ/b/mm, respectively, for a data rate of 10 Gb/s. A BER less than 10−12 was verified for an eye width of 0.43 unit interval.

A Time-Based Receiver With 2-Tap Decision Feedback Equalizer for Single-Ended Mobile DRAM Interface

A time-based (TB) receiver (RX) with a 2-tap TB decision feedback equalizer (DFE) is proposed for mobile DRAM interface. The TB RX consists of a voltage-to-time converter (VTC), a TB DFE, and a time comparator. The VTC converts the RX input voltage to a time difference between two VTC outputs by using the difference in clock-to-Q delays between two latches with different input offset voltages. The TB DFE inserts an additional delay to one of the two VTC outputs and bypasses the other VTC output to increase the time opening. The time comparator makes a decision with the first arriving edge of the two outputs of the TB DFE. While the feedback loop delay must be less than 1 UI for proper operation in the conventional voltage-based DFE, the TB DFE allows the feedback loop delay up to 1.43 UI in this paper. A transmitter (TX) transmits a single-ended signal of 200-mV swing by using an n-over-n voltage-mode driver. The transceiver in a 65-nm CMOS process achieves a 12.5 Gb/s with a 0.8-V supply through a 15-inch FR-4 channel of 14-dB loss. The TX and RX chip consume 4.3 and 3.4 mA, respectively. The energy efficiency is 0.49 pJ/b.

Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble

Dynamic financial distress prediction (DFDP) is important for improving corporate financial risk management. However, earlier studies ignore the time weight of samples when constructing ensemble FDP models. This study proposes two new DFDP approaches based on time weighting and Adaboost support vector machine (SVM) ensemble. One is the double expert voting ensemble based on Adaboost-SVM and Timeboost-SVM (DEVE-AT), which externally combines the outputs of an error-based decision expert and a time-based decision expert. The other is Adaboost SVM internally integrated with time weighting (ADASVM-TW), which uses a novel error-time-based sample weight updating function in the Adaboost iteration. These two approaches consider time weighting of samples in constructing Adaboost-based SVM ensemble, and they are more suitable for DFDP in case of financial distress concept drift. Empirical experiment is carried out with sample data of 932 Chinese listed companies’ 7 financial ratios, and time moving process is simulated by dividing the sample data into 13 batches with one year as time step. Experimental results show that both DEVE-AT and ADASVM-TW have significantly better DFDP performance than single SVM, batch-based ensemble with local weighted scheme, Adaboost-SVM and Timeboost-SVM, and they are more suitable for disposing concept drift of financial distress.

Mice and rats fail to integrate exogenous timing noise into their time-based decisions.

Endogenous timing uncertainty results in variability in time-based judgments. In many timing tasks, animals need to incorporate their level of endogenous timing uncertainty into their decisions in order to maximize the reward rate. Although animals have been shown to adopt such optimal behavioral strategies in time-based decisions, whether they can optimize their behavior under exogenous noise is an open question. In this study, we tested mice and rats in a task that required them to space their responses for a minimum duration (DRL task) in different task conditions. In one condition, the minimum wait time was fixed, whereas in other conditions minimum wait time was a Gaussian random variable. Although reward maximization entailed waiting longer with added exogenous timing variability, results indicated that both mice and rats became more impulsive and deviated from optimality with increasing levels of exogenous noise. We introduce a reward-rate-dependent sampling function to SET to account for optimal performance in noiseless and suboptimal performance in noisy environments.

Probabilistic numerical discrimination in mice.

Previous studies showed that both human and non-human animals can discriminate between different quantities (i.e., time intervals, numerosities) with a limited level of precision due to their endogenous/representational uncertainty. In addition, other studies have shown that subjects can modulate their temporal categorization responses adaptively by incorporating information gathered regarding probabilistic contingencies into their time-based decisions. Despite the psychophysical similarities between the interval timing and nonverbal counting functions, the sensitivity of count-based decisions to probabilistic information remains an unanswered question. In the current study, we investigated whether exogenous probabilistic information can be integrated into numerosity-based judgments by mice. In the task employed in this study, reward was presented either after few (i.e., 10) or many (i.e., 20) lever presses, the last of which had to be emitted on the lever associated with the corresponding trial type. In order to investigate the effect of probabilistic information on performance in this task, we manipulated the relative frequency of different trial types across different experimental conditions. We evaluated the behavioral performance of the animals under models that differed in terms of their assumptions regarding the cost of responding (e.g., logarithmically increasing vs. no response cost). Our results showed for the first time that mice could adaptively modulate their count-based decisions based on the experienced probabilistic contingencies in directions predicted by optimality.

Effective Temporal Awareness Support can Hinder Change Detection

Change blindness (CB) – the failure to notice visual changes – is an important source of human errors in managing dynamic multitasking situations, especially when the tempo at which the situation evolves as well as the timeliness of the decisions are critical to performance and to achieving higher order goals. The support of temporal awareness – in the form of a Temporal Overview Display (TOD) – proved successful in promoting time-based decision heuristics and increasing the timeliness of actions. In the present study, we test the impact on CB of a tool that provides an external time-based representation of the situation and its evolution within an air-warfare simulation that requires participants to perform radar-based subtasks. Although the use of the TOD was previously shown beneficial to performance, the tool may come with a drawback as participants missed a greater number of critical changes compared to a control condition. The TOD is associated with an exacerbation of the attentional source of CB as suggested by a higher percentage of fixated undetected changes. The contextual cues essential to detect a change may not be salient enough to be quickly found in the tool, especially when the operator must deal with time pressure, multitasking and multiple other sources of information. Our study highlights the need for a comprehensive approach to system development and evaluation in order to prevent unintended consequences such as higher CB rates.

On Efficiency Loss of Multiclass Traffic Equilibrium Assignment with Elastic Demand

Seeking the upper bound of the efficiency loss in traffic assignment has attracted many scholars’ attentions in the last decade. The existing researches mainly focus on traffic assignment with fixed demand, few on user equilibrium (UE) assignment with elastic demand focus on single user. In this paper, the authors investigate the efficiency loss of multiclass traffic equilibrium assignment (MTEA) with elastic demand. Two decision making criteria are used in this traffic assignment problem, namely, time-based and monetary-based. The variational inequality (VI) models for MTEA under time-based decision criterion and monetary-based decision criterion are formulated. The efficiency loss caused by this two decision criterion is analytically derived and the relations to some network parameters are discussed. It is shown that the upper bound of efficiency loss caused by the time-based assignment depends on the type of link travel time function, the ratio of user benefit and the total social surplus under time-based at traffic equilibrium assignment state. The upper bound of efficiency loss caused by monetary-based assignment depends on the type of link travel time function, the value of time (VOT) of user classes, the ratio of user benefit and the total social surplus under monetary-based at traffic equilibrium assignment state, the ratio of user benefit at system optimum (SO) and the total social surplus at traffic equilibrium state under monetary –based. The numerical tests validate our analytical results.

Time-based reward maximization

Humans and animals time intervals from seconds to minutes with high accuracy but limited precision. Consequently, time-based decisions are inevitably subjected to our endogenous timing uncertainty, and thus require temporal risk assessment. In this study, we tested temporal risk assessment ability of humans when participants had to withhold each subsequent response for a minimum duration to earn reward and each response reset the trial time. Premature responses were not penalized in Experiment 1 but were penalized in Experiment 2. Participants tried to maximize reward within a fixed session time (over eight sessions) by pressing a key. No instructions were provided regarding the task rules/parameters. We evaluated empirical performance within the framework of optimality that was based on the level of endogenous timing uncertainty and the payoff structure. Participants nearly tracked the optimal target inter-response times (IRTs) that changed as a function of the level of timing uncertainty and maximized the reward rate in both experiments. Acquisition of optimal target IRT was rapid and abrupt without any further improvement or worsening. These results constitute an example of optimal temporal risk assessment performance in a task that required finding the optimal trade-off between the 'speed' (timing) and 'accuracy' (reward probability) of timed responses for reward maximization.

Interval Timing and Time-Based Decision Making

EDITORIAL article Front. Integr. Neurosci., 30 March 2012 https://doi.org/10.3389/fnint.2012.00013

Time for Zebrafish

Time for Zebrafish