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How timing behavior is altered in different neurodevelopmental and neurodegenerative disorders is a contemporary research question. Genetic murine models (GMM) that offer high construct validity also serve as useful tools to investigate this question. But the literature on timing behavior of different GMMs largely remains to be consolidated. The current paper addresses this gap by reviewing studies that have been conducted with GMMs of neurodevelopmental (e.g. ADHD, schizophrenia, autism spectrum disorder), neurodegenerative disorders (e.g., Alzheimer's disease, Huntington's disease) as well as circadian and other mutant lines. The review focuses on those studies that specifically utilized the peak interval procedure to improve the comparability of findings both within and between different disease models. The reviewed studies revealed timing deficits that are characteristic of different disorders. Specifically, Huntington's disease models had weaker temporal control over the termination of their anticipatory responses, Alzheimer's disease models had earlier timed responses, schizophrenia models had weaker temporal control, circadian mutants had shifted timed responses consistent with shifts in the circadian periods. The differences in timing behavior were less consistent for other conditions such as attention deficit and hyperactivity disorder and mutations related to intellectual disability. We discuss the implications of these findings for the neural basis of an internal stopwatch. Finally, we make methodological recommendations for future research for improving the comparability of the timing behavior across different murine models.

Decision-making is one of the cognitive domains which has been under-investigated in animal models of cognitive aging along with its neurobiological correlates. This study investigated the latent variables of the decision process using the hierarchical drift-diffusion model (HDDM). Neurobiological correlates of these processes were examined via immunohistochemistry. Young (n = 11, 4 months old), adult (n = 10, 10 months old), and old (n = 10, 18 months old) mice were tested in a perceptual decision-making task (i.e. two-alternative forced-choice; 2AFC). Observed data showed that there was an age-dependent decrease in the accuracy rate of old mice while response times were comparable between age groups. HDDM results revealed that age-dependent accuracy difference was a result of a decrease in the quality of evidence integration during decision-making. Significant positive correlations observed between evidence integration rate and the number of tyrosine hydroxylase positive (TH+) neurons in the ventral tegmental area (VTA) and axon terminals in dorsomedial striatum (DMS) suggest that decrease in the quality of evidence integration in aging is related to decreased function of mesocortical and nigrostriatal dopamine.

We investigated interval timing behavior of 10-month-old male and female 3xTg-AD mice compared with their B6129F2/J wild type controls using the peak interval procedure with a 15 s target interval. Multiple parameters reflecting different aspects of timing performance were extracted from steady-state anticipatory nose-poking behavior using two different approaches: single trial analyses and average response curve analyses. These measures can dissociate the differences in performance due to distortions in the interval timing ability or to motivational decline (i.e. apathy); both of which have been reported in Alzheimer patients. We found that the interval timing ability of male and female 3xTg-AD mice did not differ from wild-type controls. However, in measures reflecting motivational state, we found significant sex differences regardless of genotype. Specifically, female mice initiated anticipatory responding later in the trial and had lower response amplitudes than males. Although our findings can also be interpreted in terms of differences in temporal control for response initiation, they more strongly suggest the effect of differential incentive motivation between sexes on timing behavior in these mice.

Individuals with autism spectrum disorder (ASD) have difficulties in social interactions. The cognitive domains that support these interactions include perceptual decision-making, timing, and error-monitoring, which enable one to appropriately understand and react to the other individual in communicative settings. This study constitutes a comprehensive exploration of decision-making and interval timing in ASD as well as the first investigation of error-monitoring abilities of individuals with ASD regarding their performance in the corresponding domains. We found that children with ASD fared similar to typically developing (TD) children in their first-order task performance in two-alternative forced choice perceptual decision-making and temporal reproduction tasks as well as the secondary tasks (signal detection and free finger tapping tasks). Yet, they had a deficit in error-monitoring in both tasks where their accuracy did not predict their confidence ratings, which was the case for the TD group. The difference between ASD and TD groups was limited to error-monitoring performance. This study attests to a circumscribed impairment in error-monitoring in individuals with ASD, which may partially underlie their social interaction problems. This difficulty in cognitively evaluating one's own performance may also relate to theory of mind deficits reported for individuals with ASD, where they struggle in understanding the mental states and intentions of others. This novel finding holds the potential to inform effective interventions for individuals with ASD that can target this error-monitoring ability to have broad-ranging effects in multiple domains involved in communication and social interaction. Autism Res 2019, 12: 239-248 © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Decision-making, timing, and error-monitoring are three of many abilities that underlie smooth social interactions. To date, these domains have been only investigated separately, but given their interactive role in social interactions that are impaired in ASD, we conducted the first study to investigate them together. Children with ASD were as successful as typically developing children in their task performances, but unlike them, were unaware of their errors in both decision-making and timing tasks. This deficit that is limited to error-monitoring can contribute to unraveling the unique cognitive signature of ASD and to formulating interventions with positive implications in multiple domains.

Error monitoring has recently been discovered to have informationally rich foundations in the timing domain. Based on the common properties of magnitude-based representations, we hypothesized that judgments on the direction and the magnitude of errors would also reflect their objective counterparts in the numerosity domain. In two experiments, we presented fast sequences of "beeps" with random interstimulus intervals and asked participants to stop the sequence when they thought the target count (7, 11, or 19) had been reached. Participants then judged how close to the target they stopped the sequence, and whether their response undershot or overshot the target. Individual linear regression fits as well as the linear mixed model with a fixed effect of reproduced numerosity on confidence ratings, and participants as independent random effects on the intercept and the slope, revealed significant positive slopes for all the target numerosities. Our results suggest that humans can keep track of the direction and degree of errors in the estimation of discrete quantities, pointing at a numerical-error-monitoring ability.

As we age, there is a wide range of changes in motor, sensory, cognitive, and temporal processing due to alterations in the functioning of the central nervous and musculoskeletal systems. Specifically, aging is associated with degradations in gait; altered processing of the individual sensory systems; modifications in executive control, memory, and attention; and changes in temporal processing. These age-related alterations are often inter-related and have been suggested to result from shared neural substrates. Additionally, the overlap between these brain areas and those controlling walking raises the possibility of facilitating performance in several tasks by introducing protocols that can efficiently target all four domains. Attempts to counteract these negative effects of normal aging have been focusing on research to prevent falls and/or enhance cognitive processes, while ignoring the potential multisensory benefits accompanying old age. Research shows that the aging brain tends to increasingly rely on multisensory integration to compensate for degradations in individual sensory systems and for altered neural functioning. This review covers the age-related changes in the above-mentioned domains and the potential to exploit the benefits associated with multisensory integration in aging so as to improve one's mobility and enhance sensory, cognitive, and temporal processing.

Timing is an integral part of physical activities. Walking as a routine form of physical activity might affect interval timing primarily in two different ways within the pacemaker–accumulator timing-theoretic framework: (1) by increasing the speed of the pacemaker due to its physiological effects; (2) by decreasing attention to time and consequently slowing the rate of temporal integration by serving as a secondary task. In order to elucidate the effect of movement on subjective time, in two different experiments we employed a temporal reproduction task conducted on the treadmill under four different encoding–decoding conditions: (1) encoding and reproducing (decoding) the duration while standing (rest); (2) encoding the duration at rest and reproducing it while moving: (3) both encoding and reproducing the duration while moving; and (4) encoding the duration while moving and reproducing it at rest. In the first experiment, participants were tested either in the 4 or the 8 km/h movement condition, whereas in the second experiment a larger sample was tested only in the 4 km/h movement condition. Data were de-trended to control for long-term performance drifts. In Experiment 1, overall durations encoded at rest and reproduced during motion were under-reproduced whereas durations encoded during motion and reproduced at rest were over-reproduced only in the 8 km/h condition. In Experiment 2, the same results were observed in the 4 km/h condition with a larger sample size. These effects on timing behavior provide support for the clock speed-driven effect of movement and contradicts the predictions of attention-based mediation.

Many perceptual decisions are inevitably subject to the tradeoff between speed and accuracy of choices (SAT). Sequential sampling models attribute this ubiquitous relation to random noise in the sensory evidence accumulation process, and assume that SAT is adaptively modulated by altering the decision thresholds at which the level of integrated evidence should reach for making a choice. Although, neuroimaging studies have shown a relationship between right presupplementary motor area (pre-SMA) activity and threshold setting, only a limited number of brain stimulation studies aimed at establishing the causal link, results of which were inconsistent. Additionally, these studies were limited in scope as they only examined the effect of pre-SMA activity unidirectionally through experimentally inhibiting the neural activity in this region. The current study aims to investigate the predictions of the striatal theory of SAT by experimentally assessing the modulatory effect of right pre-SMA on threshold setting bi-directionally. To this end, we applied both offline inhibition and excitation to the right pre-SMA utilizing transcranial magnetic stimulation in a within-subjects design and tested participants on a Random Dot Motion Task. Decision thresholds were estimated using the Hierarchical Drift Diffusion Model. Findings of our planned comparisons showed that right pre-SMA inhibition leads to significantly higher, whereas right pre-SMA excitation leads to significantly lower thresholds without showing any effects on the evidence integration process itself.

How do animals adapt their behaviors to changing conditions? This question relates to the debate between associative versus representational/computational approaches in cognitive science. An influential line of research that has significantly shaped the conceptual development of animal learning over decades has primarily focused on the role of associative dynamics with little-to-no ascription of representational/combinatorial capacities. The common assumption of these models is that behavioral adjustments are incremental and they result from updating of associations based on actions and their outcomes, without encoding the critical information serving as the determinant(s) of such contingencies (e.g., time in interval schedules, number in ratio schedules). On the other hand, an independent line of research provides evidence for behavioral phenomena that cannot be readily accounted for by the conventional associationist approach. In this paper, we will review different sets of findings particularly in the area of interval timing that suggest the ability of animals to make swift spontaneous computations on subjective quantities and incorporate them into their behavior. Findings of these studies constitute empirical challenges for the associationist approaches to behavioral flexibility. We argue that interval timing is a fertile ground for the formulation of critical tests of different theoretical approaches to animal behavior.

The linguistic category-advantage in color perception refers to better discrimination performance for stimuli that belong to different categories (e.g., green vs. blue) than equidistant stimuli from the same category (e.g., blue). Despite the robust nature of category-advantage in color perception, the related cognitive and neural mechanisms are not fully understood. Some views attribute this effect to early alteration of visual processing of color while others attribute it to post-perceptual conceptual processing. The current study investigated the causal role of the left anterior temporal lobe (ATL), as a post-perceptual semantic hub, in categorical color perception. We modulated the activity of the left ATL via cathodal tDCS or sham stimulation (within-subject) while participants were discriminating between successive presentations of color patches. Without stimulation, we found a category-advantage effect in both accuracy and response times. The inhibition of left ATL eliminated the category-advantage effect in terms of RTs but not accuracies. Our results point at the causal role of ATL in categorical color perception and provide indirect support for a post-perceptual processing account of this robust phenomenon.

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at ) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects., NIH National Institute of Mental Health (NIMH)

Previous work revealed that humans can keep track of the direction and degree of errors in their temporal and numerical reproductions/estimations. Given the behavioral and psychophysical commonalities to various magnitudes and the implication of an overlapping neuroanatomical locus for their representation, we hypothesized that participants would capture the direction of errors and confidence ratings would track the magnitude of errors in line-length reproductions. In two experiments, participants reproduced various target lengths as accurately as possible, and reported the direction of their errors and provided confidence ratings for their reproductions. The isolated analysis of these two second-order judgments showed that participants can correctly report the direction of errors in their line-length reproductions and subjective confidence decreases as the magnitude of errors increases. These results show that humans can robustly keep track of the direction of errors in their line-length reproductions and their subjective confidence corroborates the magnitude of these errors., Turkish Academy of Sciences (Turkish Academy of Sciences (TÜBA)-GEBiP) The Young Scientist Award Programme; Science Academy of Turkey (BAGEP) The Young Scientist Award Programme

To characterize differences between different state-related brain networks, statistical graph theory approaches have been employed to identify informative, topological properties. However, dynamical properties have been studied little in this regard. Our goal here was to introduce spectral graph theory as a reliable approach to determine dynamic properties of functional brain networks and to find how topological versus dynamical features differentiate between such networks. To this goal, 45 participants performed no task with eyes open (EO) or closed (EC) while electroencephalography data were recorded. These data were used to create weighted adjacency matrices for each condition (rest state EO and rest state EC). Then, using the spectral graph theory approach and Shannon entropy, we identified dynamical properties for weighted graphs, and we compared these features with topological aspects of graphs. The results showed that spectral graph theory can distinguish different state-dependent neural networks with different synchronies. On the other hand, correlation analysis indicated that although dynamical and topological properties of random networks are completely independent, these network features can be related in the case of brain generated graphs. In conclusion, the spectral graph theory approach can be used to make inferences about various state-related brain networks, for healthy and clinical populations.Author SummeryBy considering functional communications across different brain regions, a complex network is achieved that is known as functional brain network. Topologically, this network is constructed by different nodes (activity of brain regions or signals over recording electrodes) and different edges (similarity, correlation or phase difference between nodes). Paths, clusters, hubs, and centrality of nodes are examples of topological properties of these networks. However, synchrony and stability of functional brain networks can not be revealed by consideration of topological properties. Alternatively, spectral graph theory (SGT) can demonstrate the dynamic, synchrony and stability of graphs. But this approach has been studied little in brain network analysis. Here, we employed SGT, as well as topological methods, to investigate which approaches are more reliable to find differences between distinct state-related brain networks. On the other hand, we investigated correlations between topology and dynamic in different type of networks (brain generated and random networks). We found that SGT measures can clearly distinguish between distinct state-related brain networks and it can reveal synchrony and complexity of these networks. Also, results show that although dynamic and topology of random-generated graph are completely independent, these properties exhibit several correlations in the case of functional brain networks.

Investigations in the temporal estimation domain are quite vast in the range of milliseconds, seconds, and minutes. This study aimed to determine the psychophysical function that best describes long-range time interval estimation and evaluate the effect of numerals in duration presentation on the form of this function. Participants indicated on a line the magnitude of time intervals presented either as a number + time-unit (e.g., "9 months"; Group I), unitless numerals (e.g., "9"; Group II), or tagged future personal events (e.g., "Wedding"; Group III). The horizontal line was labeled rightward ("Very short" = > "Very long") or leftward ("Very long" = > "Very short") for Group I and II, but only rightward for Group III. None of the linear, power, logistic or logarithmic functions provided the best fit to the individual participant data in more than 50% of participants for any group. Individual power exponents were different only between the tagged personal events (Group III) and the other two groups. When the same analysis was repeated for the aggregated data, power functions provided a better fit than other tested functions in all groups with a difference in the power function parameters again between the tagged personal events and the other groups. A non-linear mixed effects analysis indicated a difference in the power function exponent between Group III and the other groups, but not between Group I and II. No effect of scale directionality was found in neither of the experiments in which scale direction was included as independent variable. These results suggest that the judgment of intervals in a number + time-unit presentation invoke, at least in part, processing mechanisms other than those used for time-domain. Consequently, we propose the use of event-tagged assessment for characterizing long-range interval representation. We also recommend that analyses in this field should not be restricted to aggregated data given the qualitative variation between participants., Capes; International Graduate School ABINEP; Frontiers

Age-related neurobiological and cognitive alterations suggest that interval timing (as a related function) is also altered in aging, which can, in turn, disrupt timing-dependent functions. We investigated alterations in interval timing with aging and accompanying neurobiological changes. We tested 4-6, 10-12, and 18-20 month-old mice on the dual peak interval procedure. Results revealed a specific deficit in the termination of timed responses (stop-times). The decision processes contributed more to timing variability (vs. clock/memory process) in the aged mice. We observed age-dependent reductions in the number of dopaminergic neurons in the VTA and SNc, cholinergic neurons in the medial septum/diagonal band (MS/DB) complex, and density of dopaminergic axon terminals in the DLS/DMS. Negative correlations were found between the number of dopaminergic neurons in the VTA and stop times, and the number of cholinergic neurons in MS/DB complex and the acquisition of stop times. Our results point at age-dependent changes in the decisional components of interval timing and the role of dopaminergic and cholinergic functions in these behavioral alterations. (C) 2020 Elsevier Inc. All rights reserved.

How interval timing is affected by aging constitutes one of the contemporary research questions. There is however a limited number of studies that investigate this research question in animal models of aging. The current study investigated how temporal decision-making is affected by aging. Initially, we trained young (2-3 month-old) and old C57BL/6J male mice (18-19 month-old) independently with short (3 s) and long (9 s) intervals by signaling, in each trial, the hopper associated with the interval that is in effect in that trial. The probability of short and long trials was manipulated (0.25 or 0.75) for different animals in each age group. During testing, both hoppers were illuminated, and thus active trial type was not differentiated. We expected mice to spontaneously combine the independently acquired time interval-location-probability information to adaptively guide their timing behavior in test trials. This adaptive ability and the resultant timing behavior were analyzed and compared between the age groups. Both young and old mice indeed adjusted their timing behavior in an abrupt fashion based on the independently acquired temporal-spatial-probabilistic information. The core timing ability of old mice was also intact. However, old mice had difficulty in terminating an ongoing timed response when the probability for the short trial was higher and this difference disappeared in the group that was exposed to a lower probability of short trials. These results suggest an inhibition problem in old mice as reflected through the threshold modulation process in timed decisions, which is cognitively penetrable to the probabilistic information., Scientific and Technological Research Council of Turkey (TÜBİTAK); Scientific and Technological Research Council of Turkey (TÜBİTAK) National Scholarship Program; Turkish Academy of Sciences GEBIP-2015 award; Suna Kıraç Library

Error monitoring refers to the ability to monitor one's own task performance without explicit feedback. This ability is studied typically in two-alternative forced-choice (2AFC) paradigms. Recent research showed that humans can also keep track of the magnitude and direction of errors in different magnitude domains (e.g., numerosity, duration, length). Based on the evidence that suggests a shared mechanism for magnitude representations, we aimed to investigate whether metric error monitoring ability is commonly governed across different magnitude domains. Participants reproduced/estimated temporal, numerical, and spatial magnitudes after which they rated their confidence regarding first order task performance and judged the direction of their reproduction/estimation errors. Participants were also tested in a 2AFC perceptual decision task and provided confidence ratings regarding their decisions. Results showed that variability in reproductions/estimations and metric error monitoring ability, as measured by combining confidence and error direction judgements, were positively related across temporal, spatial, and numerical domains. Metacognitive sensitivity in these metric domains was also positively associated with each other but not with metacognitive sensitivity in the 2AFC perceptual decision task. In conclusion, the current findings point at a general metric error monitoring ability that is shared across different metric domains with limited generalizability to perceptual decision-making.

Pro-inflammatory cytokines have been shown to be associated with the development of seizures in the WAG/Rij rat model of absence epilepsy. Importantly, WAG/Rij rats also exhibit cognitive deficits and depression-like behaviors. It is possible that pro-inflammatory cytokines mediate these comorbid conditions of absence epilepsy given their well-established effects on cognition and affective responses. The current study investigated the potential therapeutic effect of etanercept (tumor necrosis factor inhibitor) on cognitive impairment, depression-like behavior, and spike-wave discharges (SWDs) typically observed in the WAG/Rij rats. Eight-month-old male WAG/Rij rats and Wistar controls were tested in Morris water maze (MWM), passive avoidance (PA), forced swimming, sucrose preference, and locomotor activity tests, and electroencephalogram (EEG) recordings were taken from a separate group of WAG/Rij rats after 8 weeks of etanercept or vehicle treatment. Consistent with earlier work, WAG/Rij rats exhibited cognitive deficits and depression-like behavior. From these, the cognitive deficits and despair-like behavior were rescued by etanercept administration, which also reduced the frequency of SWDs without affecting their duration. Our results support the hypothesis that pro-inflammatory cytokines mediate the absence seizures and comorbid symptoms of absence epilepsy.

Timing uncertainty is a critical component of temporal decision-making, as it determines the decision strategies that maximize reward rate. However, little is known about the biological substrates of timing uncertainty. In this study, we report that the CA3 subregion of the ventral hippocampus (vCA3), a relatively unexplored area in timing, is critical in regulating timing uncertainty that informs temporal decision making. Using a variant of the differential reinforcement of low rates of responding (DRL) task that incorporates differential levels of approach-avoidance conflict, rats were trained to wait a minimum of 6 s to earn a reward that was paired with varying durations of foot shock. Post-training chemogenetic inhibition of the vCA3 reduced timing uncertainty without affecting mean wait times, irrespective of the level of conflict experienced. Simulations based on the information-processing variant of scalar expectancy theory (SET) revealed that the vCA3 may be important in modulating decision threshold or switch closure latency variability. © 2021 The Author(s)The neural substrate of timing uncertainty, an inherent component of optimal temporal decision making, is not well known. Using a temporal decision-making task combined with chemogenetics, Çavdaroğlu et al. demonstrate that pyramidal cells in the CA3 subregion of the ventral hippocampus are important in modulating timing uncertainty., Natural Sciences and Engineering Research Council of Canada (NSERC)

On the basis of experimental data, long-range time representation has been proposed to follow a highly compressed power function, which has been hypothesized to explain the time inconsistency found in financial discount rate preferences. The aim of this study was to evaluate how well linear and power function models explain empirical data from individual participants tested in different procedural settings. The line paradigm was used in five different procedural variations with 35 adult participants. Data aggregated over the participants showed that fitted linear functions explained more than 98% of the variance in all procedures. A linear regression fit also outperformed a power model fit for the aggregated data. An individual-participant-based analysis showed better fits of a linear model to the data of 14 participants; better fits of a power function with an exponent β > 1 to the data of 12 participants; and better fits of a power function with β < 1 to the data of the remaining nine participants. Of the 35 volunteers, the null hypothesis β = 1 was rejected for 20. The dispersion of the individual β values was approximated well by a normal distribution. These results suggest that, on average, humans perceive long-range time intervals not in a highly compressed, biased manner, but rather in a linear pattern. However, individuals differ considerably in their subjective time scales. This contribution sheds new light on the average and individual psychophysical functions of long-range time representation, and suggests that any attribution of deviation from exponential discount rates in intertemporal choice to the compressed nature of subjective time must entail the characterization of subjective time on an individual-participant basis.

Optimal performance in temporal decisions requires the integration of timing uncertainty with environmental statistics such as probability or cost functions. Reward maximization under response deadlines constitutes one of the most stringent examples of these problems. The current study investigated whether and how mice can optimize their timing behavior in a complex experimental setting under a response deadline in which reward maximization required the integration of timing uncertainty with a geometrically increasing probability/decreasing cost function. Mice optimized their performance under seconds-long response deadlines when the underlying function was reward probability but approached this level of performance when the underlying function was reward cost, only under the assumption of logarithmically scaled subjective costs. The same subjects were then tested in a timed response inhibition task characterized by response rules that conflicted with the initial task, not responding earlier than a schedule as opposed to not missing the deadline. Irrespective of original test groups, mice optimized the timing of their inhibitory control in the second experiment. These results provide strong support for the ubiquity of optimal temporal risk assessment in mice.

Forming temporal expectations plays an instrumental role for the optimization of behavior and allocation of attentional resources. Although the effects of temporal expectations on visual attention are well-established, the question of whether temporal predictions modulate the behavioral outputs of the autonomic nervous system such as the pupillary response remains unanswered. Therefore, this study aimed to obtain an online measure of pupil size while human participants were asked to differentiate between visual targets presented after varying time intervals since trial onset. Specifically, we manipulated temporal predictability in the presentation of target stimuli consisting of letters which appeared after either a short or long delay duration (1.5 vs. 3 s) in the majority of trials (75%) within different test blocks. In the remaining trials (25%), no target stimulus was present to investigate the trajectory of preparatory pupillary response under a low level of temporal uncertainty. The results revealed that the rate of preparatory pupillary response was contingent upon the time of target appearance such that pupils dilated at a higher rate when the targets were expected to appear after a shorter as compared to a longer delay period irrespective of target presence. The finding that pupil size can track temporal regularities and exhibit differential preparatory response between different delay conditions points to the existence of a distributed neural network subserving temporal information processing which is crucial for cognitive functioning and goal-directed behavior.

There is growing evidence that alterations in reward rates modify timing behavior demonstrating the role of motivational factors in interval timing behavior. This study aimed to investigate the effects of manipulations of rewards and penalties on temporal bisection performance in humans. Participants were trained to classify experienced time intervals as short or long based on the reference durations. Two groups of participants were tested under three different bias conditions in which either the relative reward magnitude or penalty associated with correct or incorrect categorizations of short and long reference durations was manipulated. Participants adapted their choice behavior (i.e., psychometric functions shifted) based on these payoff manipulations in directions predicted by reward maximization. The signal detection theory-based analysis of the data revealed that payoff contingencies affected the response bias parameter (B″) without altering participants' sensitivity (A') to temporal distances. Finally, the response time (RT) analysis showed that short categorization RTs increased, whereas long categorization RTs decreased as a function of stimulus durations. However, overall RTs did not exhibit any modulation in response to payoff manipulations. Taken together, this study provides additional support for the effects of motivational variables on temporal decision-making.

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.

Stimulus properties are known to affect duration judgments. In this study, we tested the effect of motion coherence levels in randomly moving dots on the perceived duration of these stimuli. In Experiments 1 and 2 we tested participants on a temporal reproduction task, using stimuli with varying degrees of motion coherence as the to-be-timed stimuli. Our results in both experiments showed that increasing motion coherence from the encoded (i.e. the first) to the reproduced (i.e. the second) stimulus leads to longer reproduction times. These effects were primarily additive in nature, and their magnitude increased with the difference between the coherence levels in the encoding versus reproduction (decoding) phases. This effect was not mirrored when there was a decrease in motion coherence. Experiment 3 tested if the differential number of exploratory saccadic eye-movements during encoding and reproduction predicted these effects. The behavioral findings of Experiment 1 and 2 were replicated in the third experiment, and the change in the number of eye movements from encoding to reproduction predicted the reproduction time when there was an increase in motion coherence. These results are explained by the effect of attention on the latency to initiate temporal integration that is only manifested when there is an increase in the level of motion coherence.

The fundamental assumption of pacemaker accumulator models of interval timing is that timed behavior relies on the accumulation of brain-derived clock signals. Following this theoretical tradition, a recent series of interval timing models has formulated the processing dynamics of timing behavior within the drift-diffusion decision theoretic framework, which has been traditionally applied to explain accuracy and response times in perceptual decision making. The generative processes assumed by these models and their key features can be implemented by neural populations given simple assumptions, and their predictions have received recent support from electrophysiological studies. This paper discusses the conceptual links of the diffusion model of interval timing to other prominent timing models and interprets recent electrophysiological evidence in relation to its predictions.

Temporal information processing in the seconds-to-minutes range is disrupted in patients with Alzheimer's disease (AD). In this study, we investigated the timing behavior of the 5xFAD mouse model of AD in the peak interval (PI) procedure. Nine-month-old female mice were trained with sucrose solution reinforcement for their first response after a fixed-interval (FI) and tested in the inter-mixed non-reinforced PI trials that lasted longer than FI. Timing performance indices were estimated from steady-state timed anticipatory nose-poking responses in the PI trials. We found that the time of maximal reward expectancy (peak time) of the 5xFAD mice was significantly earlier than that of the wild-type (WT) controls with no differences in other indices of timing performance. These behavioral differences corroborate the findings of previous studies on the disruption of temporal associative memory abilities of 5xFAD mice and can be accounted for by the scalar timing theory based on altered long-term memory consolidation of temporal information in the 5xFAD mice. This is the first study to directly show an interval timing phenotype in a genetic mouse model of AD.

Humans and animals do not only keep track of time intervals but they can also make decisions about durations. Temporal bisection is a psychophysical task that is widely used to assess the latter ability via categorization of durations as short or long. Many existing models of performance in temporal bisection primarily account for choice proportions and tend to overlook the associated response times. We propose a time-cell neural network that implements both interval timing and temporal categorization. The proposed model can keep track of time intervals based on lurching wave activity, it can learn the reference durations along with their association with different categorization responses, and finally, it can carry out the comparison of arbitrary intermediate durations to the reference durations. We compared the model's predictions about choice behavior and response times to the empirical data previously gathered from rats. We showed that this time-cell neural network can predict the canonical behavioral signatures of temporal bisection performance. Specifically, (a) the proposed model can account for the sigmoidal relationship between the probability of the long choices and the test durations, (b) the superposition of choice functions on a relative time scale, (c) the localization of the point of subjective equality at the geometric mean of the reference durations, and (d) the differential modulation of short and long categorization response times as a function of the test durations.

Many organisms can time intervals flexibly on average with high accuracy but substantial variability between the trials. One of the core psychophysical features of interval timing functions relates to the signatures of this timing variability; for a given individual, the standard deviation of timed responses/time estimates is nearly proportional to their central tendency (scalar property). Many studies have aimed at elucidating the neural basis of interval timing based on the neurocomputational principles in a fashion that would explain the scalar property. Recent experimental evidence shows that there is indeed a specialized neural system for timekeeping. This system, referred to as the “time cells,” is composed of a group of neurons that fire sequentially as a function of elapsed time. Importantly, the time interval between consecutively firing time cell ensembles has been shown to increase with more elapsed time. However, when the subjective time is calculated by adding the distributions of time intervals between these sequentially firing time cell ensembles, the standard deviation would be compressed by the square root function. In light of this information the question becomes, “How should the signaling between the sequentially firing time cell ensembles be for the resulting variability to increase linearly with time as required by the scalar property?” We developed a simplified model of time cells that offers a mechanism for the synaptic communication of the sequentially firing neurons to address this ubiquitous property of interval timing. The model is composed of a single layer of time cells formulated in the form of integrate-and-fire neurons with feed-forward excitatory connections. The resulting behavior is simple neural wave activity. When this model is simulated with noisy conductances, the standard deviation of the time cell spike times increases proportionally to the mean of the spike-times. We demonstrate that this statistical property of the model outcomes is robustly observed even when the values of the key model parameters are varied., American University of the Middle East

Recent studies have shown that participants can keep track of the magnitude and direction of their errors while reproducing target intervals (Akdogan & Balci, 2017) and producing numerosities with sequentially presented auditory stimuli (Duyan & Balci, 2018). Although the latter work demonstrated that error judgments were driven by the number rather than the total duration of sequential stimulus presentations, the number and duration of stimuli are inevitably correlated in sequential presentations. This correlation empirically limits the purity of the characterization of "numerical error monitoring". The current work expanded the scope of numerical error monitoring as a form of "metric error monitoring" to numerical estimation based on simultaneously presented array of stimuli to control for temporal correlates. Our results show that numerical error monitoring ability applies to magnitude estimation in these more controlled experimental scenarios underlining its ubiquitous nature.

Previous studies showed that rats and pigeons can count their responses, and the resultant count-based judgments exhibit the scalar property (also known as Weber's Law), a psychophysical property that also characterizes interval-timing behavior. Animals were found to take a nearly normative account of these well-established endogenous uncertainty characteristics in their time-based decision-making. On the other hand, no study has yet tested the implications of scalar property of numerosity representations for reward-rate maximization in count-based decision-making. The current study tested mice on a task that required them to press one lever for a minimum number of times before pressing the second lever to collect the armed reward (fixed consecutive number schedule, FCN). Fewer than necessary number of responses reset the response count without reinforcement, whereas emitting responses at least for the minimum number of times reset the response counter with reinforcement. Each mouse was tested with three different FCN schedules (FCN10, FCN20, FCN40). The number of responses emitted on the first lever before pressing the second lever constituted the main unit of analysis. Our findings for the first time showed that mice count their responses with scalar property. We then defined the reward-rate maximizing numerical decision strategies in this task based on the subject-based estimates of the endogenous counting uncertainty. Our results showed that mice learn to maximize the reward-rate by incorporating the uncertainty in their numerosity judgments into their count-based decisions. Our findings extend the scope of optimal temporal risk-assessment to the domain of count-based decision-making.

One of the critical factors that guide choice behavior is the prior bias of the decisionmaker with respect to different options, namely, the relative readiness by which the decision-maker opts for a specific choice. Although previous neuroimaging work has shown decision bias related activity in the orbitofrontal cortex, intraparietal sulcus (IPS) and dorsolateral prefrontal cortex, in a recent work by Javadi et al. (2015), primary motor cortex was also implicated. By applying transcranial direct current stimulation (tDCS), they have revealed a causal role of the primary motor cortex excitability in the induction of response time (RT) differences and decision bias in the form of choice probability. The current study aimed to replicate these recent findings with an experimental design that contained a sham group to increase experimental control and an additional testing phase to investigate the possible after-effects of tDCS. The conventional decision outputs such as choice proportion and RT were analyzed along with the theorydriven estimates of choice bias and non-decision related components of RTs (e. g., motor implementation speed of choices made). None of the statistical comparisons favored the alternative hypotheses over the null hypotheses. Consequently, previous findings regarding the effect of primary motor cortex excitability on choice bias and response times could not be replicated with a more controlled experimental design that is recommended for tDCS studies (Horvath et al., 2015). This empirical discrepancy between the two studies adds to the evidence demonstrating inconsistent effects of tDCS in establishing causal relationships between cortical excitability and motor behavior., Turkish Academy of Sciences (TÜBA)

The physical properties of events are known to modulate perceived time. This study tested the effect of different quantitative (walking speed) and qualitative (walking-forward vs. walking-backward) features of observed motion on time perception in three complementary experiments. Participants were tested in the temporal discrimination (bisection) task, in which they were asked to categorize durations of walking animations as "short" or "long." We predicted the faster observed walking to speed up temporal integration and thereby to shift the point of subjective equality leftward, and this effect to increase monotonically with increasing walking speed. To this end, we tested participants with two different ranges of walking speeds in Experiment 1 and 2 and observed a parametric effect of walking speed on perceived time irrespective of the direction of walking (forward vs. rewound forward walking). Experiment 3 contained a more plausible backward walking animation compared to the rewound walking animation used in Experiments 1 and 2 (as validated based on independent subjective ratings). The effect of walking-speed and the lack of the effect of walking direction on perceived time were replicated in Experiment 3. Our results suggest a strong link between the speed but not the direction of perceived biological motion and subjective time., New Agendas for the Study of Time; Turkish Academy of Sciences (TÜBA) (Turkish Academy of Sciences) GEBIP 2015

Elucidation of the neural correlates of time perception constitutes an important research topic in cognitive neuroscience. The focus to date has been on durations in the millisecond to seconds range, but here we used electroencephalography (EEG) to examine brain functional connectivity during much longer durations (i.e., 15 min). For this purpose, we conducted an initial exploratory experiment followed by a confirmatory experiment. Our results showed that those participants who overestimated time exhibited lower activity of beta (1830 Hz) at several electrode sites. Furthermore, graph theoretical analysis indicated significant differences in the beta range (15-30 Hz) between those that overestimated and underestimated time. Participants who underestimated time showed higher clustering coefficient compared to those that overestimated time. We discuss our results in terms of two aspects. FFT results, as a linear approach, are discussed within localized/dedicated models (i.e., scalar timing model). Second, non-localized properties of psychological interval timing (as emphasized by intrinsic models) are addressed and discussed based on results derived from graph theory. Results suggested that although beta amplitude in central regions (related to activity of BG-thalamocortical pathway as a dedicated module) is important in relation to timing mechanisms, the properties of functional activity of brain networks; such as the segregation of beta network, are also crucial for time perception. These results may suggest subjective time may be created by vector units instead of scalar ticks., NA

Rahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

Animals use estimates of time intervals to adaptively guide their anticipatory actions. New research on mice shows that photostimulation of the neural pathway that coordinates drinking behavior delays subsequent anticipatory responses by pausing/resetting the internal stopwatch.

Circadian clock is known to adapt to environmental changes and can significantly influence cognitive and physiological functions. In this work, we report specific behavioral, cognitive, and sleep homeostatic defects in the after hours (Afh) circadian mouse mutant, which is characterized by lengthened circadian period. We found that the circadian timing irregularities in Afh mice resulted in higher interval timing uncertainty and suboptimal decisions due to incapability of processing probabilities. Our phenotypic observations further suggested that Afh mutants failed to exhibit the necessary phenotypic plasticity for adapting to temporal changes at multiple time scales (seconds-to-minutes to circadian). These behavioral effects of Afh mutation were complemented by the specific disruption of the Per/Cry circadian regulatory complex in brain regions that govern food anticipatory behaviors, sleep, and timing. We derive statistical predictions, which indicate that circadian clock and sleep are complementary processes in controlling behavioral/cognitive performance during 24 hrs. The results of this study have pivotal implications for understanding how the circadian clock modulates sleep and behavior., Russian Science Foundation

Decisions are made based on the integration of available evidence. The noise in evidence accumulation leads to a particular speed-accuracy tradeoff in decision-making, which can be modulated and optimized by adaptive decision threshold setting. Given the effect of pre-SMA activity on striatal excitability, we hypothesized that the inhibition of pre-SMA would lead to higher decision thresholds and an increased accuracy bias. We used offline continuous theta burst stimulation to assess the effect of transient inhibition of the right pre-SMA on the decision processes in a free-response two-alternative forced-choice task within the drift diffusion model framework. Participants became more cautious and set higher decision thresholds following right pre-SMA inhibition compared with inhibition of the control site (vertex). Increased decision thresholds were accompanied by an accuracy bias with no effects on post-error choice behavior. Participants also exhibited higher drift rates as a result of pre-SMA inhibition compared with the vertex inhibition. These results, in line with the striatal theory of speed-accuracy tradeoff, provide evidence for the functional role of pre-SMA activity in decision threshold modulation. Our results also suggest that pre-SMA might be a part of the brain network associated with the sensory evidence integration., Turkish Academy of Sciences (TÜBA) (Turkish Academy of Sciences)-GEBIP award

Temporal judgments regarding a target interval typically produce a nearly normally distributed reproduction times centered on the target with substantial variance. This phenomenon indicates that the majority of our temporal judgments are deviations from the target times, which are assumed to originate from the underlying timing uncertainty. Although humans were found to adapt their decisions in response to timing uncertainty, we do not know if they can accurately judge the direction and degree of their temporal errors. In this study, we asked participants to reproduce durations as accurately as possible. After each reproduction, participants were asked to retrospectively rate their confidence in their temporal estimates and to judge if their response time was earlier or later than the target interval. The results revealed that human participants are aware of both the direction and magnitude of their timing errors, pointing at an informationally rich temporal error monitoring ability. We further show that a sequential diffusion process can account for the detection of direction of errors as well as the qualitative features of the relationship of objective temporal errors with subjective confidence ratings and associated response times. (PsycINFO Database Record

WOS: 000389088600005, PubMed ID: 27690351, Background: Decision-making in Obsessive Compulsive Disorder has typically been investigated in the adult population. Computational approaches have recently started to get integrated into these studies. However, decision-making research in pediatric OCD populations is scarce. Methods: We investigated latent decision processes in 21 medication-free pediatric OCD patients and 23 healthy control participants. We hypothesized that OCD patients would be more cautious and less efficient in evidence accumulation than controls in a two alternative forced choice (2AFC) task. Results: Pediatric OCD patients were less efficient than controls in accumulating perceptual evidence and showed a tendency to be more cautious. In comparison to post-correct decisions, OCD patients increased decision thresholds after erroneous decisions, whereas healthy controls decreased decision thresholds. These changes were coupled with weaker evidence accumulation after errors in both groups. Limitations: The small sample size limited the power of the study. Conclusions: Our results demonstrate poorer decision-making performance in pediatric OCD patients at the level of latent processes, specifically in terms of evidence accumulation. (C) 2016 Elsevier B.V. All rights reserved., Turkish Academy of Sciences, We would like to thank Hakan Karsilar for his help on the DMDT code; Elif Akin for her help in recruiting participants; Aysu Hazar for her help with data collection. This work was supported by the Turkish Academy of Sciences under grant GEBIP 2015 to Fuat Balci. The sponsor had no role, in study design; in the collection, analysis or interpretation of data; in the writing of the report; or in the decision to submit the article for publication.

Author(s): Brunner, Daniela; Balci, Fuat; Kabitzke, Patricia; Hill, Heather | Abstract: These guidelines follow the recommendation of a number of external bodies to regulate the use of animals in research. They can be used both for transparency in publication, and in this sense they extend what is being requested by journals, or for regulatory or funding institutions, to request information prior, during, or after funding, and to ensure adherence to regulations.This checklist focuses on the use of rodents in research. Other species (such as marine mammals, primates, or invertebrates) will be covered in future separated checklists.This checklist is based on and extends the following guidelines: Animals in Research Ethical Guidelines, Guidance for the Description of Animal Research in Scientific Publications, Animals Welfare Act, and ARRIVE guidelines.

Animals can shape their timed behaviors based on experienced probabilistic relations in a nearly optimal fashion. On the other hand, it is not clear if they adopt these timed decisions by making computations based on previously learnt task parameters (time intervals, locations, and probabilities) or if they gradually develop their decisions based on trial and error. To address this question, we tested mice in the timed-switching task, which required them to anticipate when (after a short or long delay) and at which of the two delay locations a reward would be presented. The probability of short trials differed between test groups in two experiments. Critically, we first trained mice on relevant task parameters by signaling the active trial with a discriminative stimulus and delivered the corresponding reward after the associated delay without any response requirement (without inducing switching behavior). During the test phase, both options were presented simultaneously to characterize the emergence and temporal characteristics of the switching behavior. Mice exhibited timed-switching behavior starting from the first few test trials, and their performance remained stable throughout testing in the majority of the conditions. Furthermore, as the probability of the short trial increased, mice waited longer before switching from the short to long location (experiment 1). These behavioral adjustments were in directions predicted by reward maximization. These results suggest that rather than gradually adjusting their time-dependent choice behavior, mice abruptly adopted temporal decision strategies by directly integrating their previous knowledge of task parameters into their timed behavior, supporting the model-based representational account of temporal risk assessment., Scientific and Technological Research Council of Turkey (TÜBİTAK)

Introduction: Obsessive compulsive disorder (OCD) is occasionally characterized by decision-making deficits. Compared to the isolated analysis of the choice and response times, characterizing decision outputs at the level of latent processes can be a more powerful approach in revealing differences, even in subclinical cases. We hypothesized that participants with higher obsessive compulsive (OC) features would set their decision thresholds higher and thus make more cautious decisions. Method: We used a perceptual two-alternative forced-choice (2AFC) task (dot motion discrimination) to test this hypothesis in a non-clinical sample ( N = 74). We fitted the data with the diffusion model and evaluated the optimality of decision outputs. We also conducted exploratory analyses to reveal which subscales best predicted the differences at the level of latent decision processes. Results: Higher OC total scores in Maudsley and Padua scales significantly predicted higher threshold settings (cautiousness). The follow-up exploratory analyses with subscale scores showed that checking and rumination tendencies predicted higher threshold settings whereas washing tendency predicted faster non-decision times. Conclusions: Our primary results showed that participants with higher degrees of OC features exhibit more cautious decision making. Our exploratory analyses also revealed distinctions based on different types of OC features in both controlled (cautiousness in decision making) and automatic (faster non-decision times) elements of the decision process.

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.

In the temporal bisection task, participants classify experienced stimulus durations as short or long based on their temporal similarity to previously learned reference durations. Temporal decision making in this task should be influenced by the experienced probabilities of the reference durations for adaptiveness. In this study, we tested the temporal bisection performance of mice (Mus musculus) under different short and long reference duration probability conditions implemented across two experimental phases. In Phase 1, the proportion of reference durations (compared to probe durations) was 0.5, whereas in Phase 2 it was increased to 0.8 to further examine the adjustment of choice behavior with more frequent reference duration presentations (under higher reinforcement rate). Our findings suggest that mice developed adaptive biases in their choice behaviors. These adjustments in choice behavior were nearly optimal as the mice maximized their gain to a great extent which required them to monitor stimulus probabilities as well as the level of variability in their temporal judgments. We further found that short but not long categorization response times were sensitive to stimulus probability manipulations, which in turn suggests an asymmetry between short and long categorizations. Finally, we investigated the latent decision processes underlying the bias manifested in subjects' choice behavior within the diffusion model framework. Our results revealed that probabilistic information influenced the starting point and the rate of evidence accumulation process. Overall, the stimulus probability effects on choice behavior were modulated by the reinforcement rate. Our findings illustrate that mice can adapt their temporal behaviors with respect to the probabilistic contingencies in the environment.

Classic psychological models of interval timing track time by counting – or integrating – pulses emitted by a stochastic pulse generator. However, the neural plausibility of this approach has frequently been questioned, despite the key role played by neural integrators in well-supported models of perceptual decision-making. Although response times on the order of 1–2 s are routinely observed in the decision-making domain, tuning an integrator's parameters precisely enough to time intervals of much greater duration strikes many researchers as implausible. Behavioral and physiological data from timing tasks nonetheless frequently appear consistent with such precision. In this article, we propose that chains of integrators constructed from mechanisms exhibiting a range of intrinsic time constants (ranging from slow protein synthesis processes to rapidly ramping neural firing rates) may be used collectively to perform robust interval timing over a broad range of durations. Since the 1960s, many psychological models have exploited Poisson-like firing rates of cortical neurons to account for variability in measured behavior Luce (1986). They have also typically applied counters to these spike trains to achieve behavioral functionality (e.g., counting spikes up to a threshold to trigger a timed behavior). In this respect, such models embody the notion that counting, or integration, is as easy for the brain as it is for a digital timer – a notion that strikes many neuroscientists as implausible. We hypothesize that the level of robust integration needed to model interval timing in this way over many orders of temporal magnitude (from fractions of a second to many minutes) can be achieved by physical spike generators and counters with a range of intrinsic spike rates and time constants. Unlike perfect integration, leaky integration is known to be a fundamental feature of brain function: for example, it is exhibited by voltage dynamics on an individual neuron's capacitive membrane. Equation 1 is a stochastic differential equation that decomposes how a leaky integrator with time constant τ and output x(t) responds to deterministic inputs I(t) (the dt term) combined with additive white noise (the dW term): τ⋅dx=(I−x)⋅dt+c⋅dW. (1) The x-value of a deterministic (c = 0) leaky integrator jumps at the time of a large transient input I, then decays exponentially back to 0 as e−t/τ if I remains 0 thereafter. Small τ implies large jumps and rapid decay in x(t); x is likewise highly responsive to noise when it is included (c > 0). Although individual membrane potentials reset to a baseline level after conversion into an action potential, populations of neurons are thought capable of continuously representing a leaky integrator's state using a firing rate code Shadlen and Newsome (1994). Recurrent connections within such a model population produce reverberating activity that emulates a leaky integrator with a large time constant. Any leaky integrator's leakiness can in fact be completely canceled by recurrent self--excitation, in which the output of a leaky integrator is added to its inputs. In this way, x disappears from the first term on the righthand side of Equation 1, implying that x(t) is the integral of I(t). This balancing is the basis of one form of neural integrator model e.g., Seung (1996), and it is fundamental to the design of analog electronic integrators. When noise is included, Equation 1 defines a stochastic integrator, implying that x(t) is a drift–diffusion process – a process that forms the basis of an influential model of two-alternative decision-making (Ratcliff and Rouder, 1998). What troubles some researchers is the level of precision-tuning required for self-excitation to cancel the leak: if self-excitation replaces x in the righthand side of Equation 1, not by zero, but by kx, with k ≠ 0, then the system will remain leaky (k > 0) or become unstable (k

Huntington's disease (HD) is a progressive neurodegenerative disease marked by psychiatric and motor problems. Recently, these findings have been extended to deficits in sleep and circadian function that can be observed in HD patients and in HD mouse models, with abnormal sleep patterns correlating with symptom severity in patients. Here, we studied the behavior of the BAC HD mouse model using an 24/7 automated system; the results indicate significant lengthening of the circadian period in the mutant mice. These results reinforce previous findings in HD models and symptomatic HD patients, indicating that circadian dysfunction is a core feature of HD. Abstract Huntington's disease (HD) is a progressive neurodegenerative disease marked by psychiatric and motor problems. Recently, these findings have been extended to deficits in sleep and circadian function that can be observed in HD patients and in HD mouse models, with abnormal sleep patterns correlating with symptom severity in patients. Here, we studied the behavior of the BAC HD mouse model using an 24/7 automated system; the results indicate significant lengthening of the circadian period in the mutant mice. These results reinforce previous findings in HD models and symptomatic HD patients, indicating that circadian dysfunction is a core feature of HD. Abstract Huntington's disease (HD) is a progressive neurodegenerative disease marked by psychiatric and motor problems. Recently, these findings have been extended to deficits in sleep and circadian function that can be observed in HD patients and in HD mouse models, with abnormal sleep patterns correlating with symptom severity in patients. Here, we studied the behavior of the BAC HD mouse model using an 24/7 automated system; the results indicate significant lengthening of the circadian period in the mutant mice. These results reinforce previous findings in HD models and symptomatic HD patients, indicating that circadian dysfunction is a core feature of HD.

Time is an essential feature of most decisions, because the reward earned from decisions frequently depends on the temporal statistics of the environment (e.g., on whether deci- sions must be made under deadlines). Accordingly, evolution appears to have favored a mechanism that predicts intervals in the seconds to minutes range with high accuracy on average, but significant variability from trial to trial. Importantly, the subjective sense of time that results is sufficiently imprecise that maximizing rewards in decision-making can require substantial behavioral adjustments (e.g., accumulating less evidence for a decision in order to beat a deadline). Reward maximization in many daily decisions therefore requires optimal temporal risk assessment. Here, we review the temporal decision-making litera- ture, conduct secondary analyses of relevant published datasets, and analyze the results of a new experiment. The paper is organized in three parts. In the first part, we review literature and analyze existing data suggesting that animals take account of their inherent behavioral variability (their “endogenous timing uncertainty”) in temporal decision-making. In the second part, we review literature that quantitatively demonstrates nearly optimal temporal risk assessment with sub-second and supra-second intervals using perceptual tasks (with humans and mice) and motor timing tasks (with humans). We supplement this section with original research that tested human and rat performance on a task that requires finding the optimal balance between two time-dependent quantities for reward maximization. This optimal balance in turn depends on the level of timing uncertainty. Cor- roborating the reviewed literature, humans and rats exhibited nearly optimal temporal risk assessment in this task. In the third section, we discuss the role of timing uncertainty in reward maximization in two-choice perceptual decision-making tasks and review literature that implicates timing uncertainty as an important factor in performance quality. Together, these studies strongly support the hypothesis that animals take normative account of their endogenous timing uncertainty. By incorporating the psychophysics of interval timing into the study of reward maximization, our approach bridges empirical and theoretical gaps between the interval timing and decision-making literatures., FP7 Marie Curie; National Institute of Mental Health; Air Force Research Laboratory; European project COST ISCH

The majority of two-alternative forced choice (2AFC) psychophysics studies have examined speed-accuracy trade-offs either in free-response or fixed viewing time paradigms with no hard time constraints on responding. Under response deadlines, reward maximization requires participants to modulate decision thresholds over the course of a trial such that when the deadline arrives a response is ensured despite the possible reduction of accuracy to the chance level. Importantly, this normative threshold collapsing process should take account not only of the deadline time but also the participants’ level of timing uncertainty about the deadline. For instance, for a given level of timing uncertainty participants facing a more stringent deadline and for a given deadline participants with higher timing uncertainty should start collapsing thresholds earlier within a trial(Frazier, P., & Yu, A. J. (2008). Sequential hypothesis testing under stochastic deadlines.Advances In Neural Information Processing Systems, 20, 465-472). We tested human participants in random dot motion discrimination task in three different conditions: free-response paradigm and with two different response deadlines (800 and 1000 ms). We also quantified the level of timing uncertainty using two different temporal reproduction tasks. Micro speed-accuracy trade-off curves suggested that participants might have collapsed thresholds within a trial when facing a response deadline; however, observed performance diverged markedly from optimality. Participants did not take account of either response deadline times or their timing uncertainty. Our findings define a limit on the optimal temporal risk assessment performance of humans. We also consider other possible sources of observed reduction in accuracy as response times approach the deadline, through simulations of data using empirical model parameters., NA