Early posterior negativity indicates time dilation by arousal

We investigated whether Early Posterior Negativity (EPN) indicated the subjective dilation of time when judging the duration of arousing stimuli. Participants performed a visual temporal bisection task along with high-level and low-level arousing auditory stimuli, while we simultaneously recorded EEG. In accordance with previous studies, arousing stimuli were temporally overestimated and led to higher EPN amplitude. Yet, we observed that time dilation and EPN amplitude were significantly correlated and this effect cannot be explained by confounds from stimulus valence. We interpret our findings in terms of the pacemaker–accumulator model of human timing, and suggest that EPN indicates an arousal-based increasing of the speed of our mental clock.

Interval Timing and Motivation are Dissociable when Interval-Initiating Responses are Discriminable from Target Responses

Data have accumulated suggesting that motivation and timing are correlated processes, yet few studies have tested whether motivation and timing are procedurally dissociable. This may be attributed to the fact that the most common framework in which to study timing, the pacemaker-accumulator model, does not readily suggest a route by which to dissociate motivation and timing. In contrast, the behavioral systems framework suggests that motivation and timing could be dissociated if subjects were trained in response-initiated (RI) interval-timing procedures rather than in common externally-initiated (EI) procedures. RI procedures were predicted to enhance temporal control and yield timing performance robust to fluctuations in motivation. Experiment 1 tested this hypothesis by training rats to either initiate switch-timing trials with a single press on the lever associated with the shorter FI schedule (SL-RI), or wait for switch-timing trials to be initiated (EI). Motivation was varied through pre-feeding. SL-RI and EI rats showed similar levels of temporal control and sensitivity to pre-feeding in their switch-timing performance. Experiment 2 tested a revised RI hypothesis, the discriminative-RI hypothesis, which predicts that as the trial-initiating response becomes progressively different from target responses, motivation and timing are increasingly dissociated. This experiment replicated Experiment 1 and added a trial-initiating condition in which a nose-poke into a nose port (NP-RI) initiated trials. As predicted, the sensitivity of switching-timing performance to pre-feeding scaled such that EI > SL-RI > NP-RI. These data suggest that it is possible to dissociate timing and motivation, challenging the notion that these processes are correlated.

Influence of Hydraulic Accumulator Performance on the Hydraulic Hybrid Powertrain

Owing to its high power density, hydraulic hybrid is considered as an effective approach to reducing the fuel consumption of heavy duty vehicles. A gas-charged hydraulic accumulator serves as the power buffer, storing and releasing hydraulic power through gas. An accurate hydraulic accumulator model is crucial to predict its actual performance. There are two widely used accumulator models: isothermal and adiabatic models. Neither of these models are practical to reflect its real performance in the hydraulic hybrid system. Therefore, the influence of an accumulator model considering thermal hysteresis on a hydraulic hybrid wheel loader has been studied in this paper. The difference of three accumulator models (isothermal, adiabatic and energy balance) has been identified. A dynamic simulation model of the hydraulic hybrid wheel loader has been developed. The fuel consumptions of the hydraulic hybrid wheel loader with three accumulator models has been compared. The influence of heat transfer coefficient of the accumulator housing has also been studied.

Neurally constrained modeling of speed-accuracy tradeoff during visual search: gated accumulation of modulated evidence

Stochastic accumulator models account for response times and errors in perceptual decision making by assuming a noisy accumulation of perceptual evidence to a threshold. Previously, we explained saccade visual search decision making by macaque monkeys with a stochastic multiaccumulator model in which accumulation was driven by a gated feed-forward integration to threshold of spike trains from visually responsive neurons in frontal eye field that signal stimulus salience. This neurally constrained model quantitatively accounted for response times and errors in visual search for a target among varying numbers of distractors and replicated the dynamics of presaccadic movement neurons hypothesized to instantiate evidence accumulation. This modeling framework suggested strategic control over gate or over threshold as two potential mechanisms to accomplish speed-accuracy tradeoff (SAT). Here, we show that our gated accumulator model framework can account for visual search performance under SAT instructions observed in a milestone neurophysiological study of frontal eye field. This framework captured key elements of saccade search performance, through observed modulations of neural input, as well as flexible combinations of gate and threshold parameters necessary to explain differences in SAT strategy across monkeys. However, the trajectories of the model accumulators deviated from the dynamics of most presaccadic movement neurons. These findings demonstrate that traditional theoretical accounts of SAT are incomplete descriptions of the underlying neural adjustments that accomplish SAT, offer a novel mechanistic account of decision-making mechanisms during speed-accuracy tradeoff, and highlight questions regarding the identity of model and neural accumulators. NEW & NOTEWORTHY A gated accumulator model is used to elucidate neurocomputational mechanisms of speed-accuracy tradeoff. Whereas canonical stochastic accumulators adjust strategy only through variation of an accumulation threshold, we demonstrate that strategic adjustments are accomplished by flexible combinations of both modulation of the evidence representation and adaptation of accumulator gate and threshold. The results indicate how model-based cognitive neuroscience can translate between abstract cognitive models of performance and neural mechanisms of speed-accuracy tradeoff.