Neural signatures of evidence accumulation in temporal decisions

Distinct brain systems are involved in subjective minute estimation with eyes open or closed: EEG source analysis study

Introduction

Time perception is a fundamental cognitive function, the brain mechanisms of which are not fully understood. Recent electroencephalography (EEG) studies have shown that neural oscillations in specific frequency bands may play a role in this process. In the current study, we sought to investigate how neurophysiological activity of cortical structures relates to subjective time estimations.

Methods

The study sample included 41 healthy volunteers, who were to produce subjective minutes with eyes closed and open by pressing the response button marking the beginning and end of this time interval. High-density EEG was recorded in parallel and the activity of cortical sources within the theta, alpha, and beta frequency bands was analyzed with standardized low-resolution brain electromagnetic tomography.

Results

The results revealed that activity of several cortical structures within the beta-band correlated with the duration of subjective minutes across participants, which highlights the role of the beta-rhythm in supra-second time perception. The sets of involved structures were different depending on eyes being open or closed, while the produced duration did not differ being around 58 s in both conditions. Individual minute correlated with beta power in the left precuneus, left superior parietal lobule, and right superior frontal gyrus (SFG) during eyes-closed sessions, and with that in the caudal anterior cingulate cortex, cuneus, posterior cingulate cortex, parahippocampal gyrus, and right lingual gyrus during the eyes-open condition. Noteworthy, some structures showed tendencies toward opposite correlations between conditions.

Discussion

Taken together, our findings bridge the gap between functional magnetic resonance imaging and EEG time perception studies and suggest reliance on different aspects of subjective experience when judging about time with eyes open or closed.

Direct evidence for logarithmic magnitude representation in the central nervous system

Fechner's law proposes a logarithmic relationship between the physical intensity and perceived magnitude of a stimulus. The principle of logarithmic magnitude representation has been extensively utilized in various theoretical frameworks. Although the neural correlates of Weber's law have been considered as possible evidence for Fechner's law, there is still a lack of direct evidence for a logarithmic representation in the central nervous system. In our study, participants were asked to reproduce the time intervals between two circles and ignore their spatial distances while electroencephalogram (EEG) signals were recorded synchronously. Behavioral results showed that a Bayesian model, which assumes a logarithmic representation of spatiotemporal information, was better at predicting production times than a model relying on a linear representation. The EEG results revealed that P2 and P3b amplitudes increased linearly with the logarithmic transformation of spatiotemporal information, and these event-related potentials were localized in the parietal cortex. Our study provides direct evidence supporting logarithmic magnitude representation in the central nervous system.

Common neural mechanisms supporting time judgements in humans and monkeys

There has been an increasing interest in identifying the biological underpinnings of human time perception, for which purpose research in non-human primates (NHP) is common. Although previous work, based on behaviour, suggests that similar mechanisms support time perception across species, the neural correlates of time estimation in humans and NHP have not been directly compared. In this study, we assess whether brain evoked responses during a time categorization task are similar across species. Specifically, we assess putative differences in post-interval evoked potentials as a function of perceived duration in human EEG (N = 24) and local field potential (LFP) and spike recordings in pre-supplementary motor area (pre-SMA) of one monkey. Event-related potentials (ERPs) differed significantly after the presentation of the temporal interval between "short" and "long" perceived durations in both species, even when the objective duration of the stimuli was the same. Interestingly, the polarity of the reported ERPs was reversed for incorrect trials (i.e., the ERP of a "long" stimulus looked like the ERP of a "short" stimulus when a time categorization error was made). Hence, our results show that post-interval potentials reflect the perceived (rather than the objective) duration of the presented time interval in both NHP and humans. In addition, firing rates in monkey's pre-SMA also differed significantly between short and long perceived durations and were reversed in incorrect trials. Together, our results show that common neural mechanisms support time categorization in NHP and humans, thereby suggesting that NHP are a good model for investigating human time perception.

Influences of temporal and probabilistic expectation on subjective time of emotional stimulus

Subjective time perception can change based on a stimulus's valence and expectancy. Yet, it is unclear how these two factors might interact to shape our sense of how long something lasts. Here, we conducted two experiments examining the effects of temporal and probabilistic expectancy on the perceived duration of images with varying emotional valence. In Experiment 1, we varied the temporal predictive cue with varying stimulus-onset asynchronies (SOAs), while in Experiment 2, we manipulated the cue-emotion probabilistic associations. Our results revealed that stimuli appearing earlier than anticipated were perceived as shorter, whereas less infrequent stimuli seemed to last longer. In addition, negative images were perceived longer than neural ones. However, no significant interaction between expectancy and stimulus valence was observed. We interpret these using the internal clock model, suggesting that while emotional stimuli primarily affect the pacemaker's rhythm through arousal, expectation steers attention, influencing how we register time's passage.

Blocked versus interleaved: How range contexts modulate time perception and its EEG signatures

Accurate time perception is a crucial element in a wide range of cognitive tasks, including decision-making, memory, and motor control. One commonly observed phenomenon is that when given a range of time intervals to consider, people's estimates often cluster around the midpoint of those intervals. Previous studies have suggested that the range of these intervals can also influence our judgments, but the neural mechanisms behind this "range effect" are not yet understood. We used both behavioral tests and electroencephalographic (EEG) measures to understand how the range of sample time intervals affects the accuracy of people's subsequent time estimates. Study participants were exposed to two different setups: In the "blocked-range" (BR) session, short and long intervals were presented in separate blocks, whereas in the "interleaved-range" (IR) session, intervals of various lengths were presented randomly. Our findings indicated that the BR context led to more accurate time estimates compared to the IR context. In terms of EEG data, the BR context resulted in quicker buildup of contingent negative variation (CNV), which also reached higher amplitude levels and dissolved more rapidly during the encoding stage. We also observed an enhanced amplitude in the offset P2 component of the EEG signal. Overall, our results suggest that the variability in time intervals, as defined by their range, influences the neural processes that underlie time estimation.

Humans can infer social preferences from decision speed alone

Humans are known to be capable of inferring hidden preferences and beliefs of their conspecifics when observing their decisions. While observational learning based on choices has been explored extensively, the question of how response times (RT) impact our learning of others' social preferences has received little attention. Yet, while observing choices alone can inform us about the direction of preference, they reveal little about the strength of this preference. In contrast, RT provides a continuous measure of strength of preference with faster responses indicating stronger preferences and slower responses signaling hesitation or uncertainty. Here, we outline a preregistered orthogonal design to investigate the involvement of both choices and RT in learning and inferring other's social preferences. Participants observed other people's behavior in a social preferences task (Dictator Game), seeing either their choices, RT, both, or no information. By coupling behavioral analyses with computational modeling, we show that RT is predictive of social preferences and that observers were able to infer those preferences even when receiving only RT information. Based on these findings, we propose a novel observational reinforcement learning model that closely matches participants' inferences in all relevant conditions. In contrast to previous literature suggesting that, from a Bayesian perspective, people should be able to learn equally well from choices and RT, we show that observers' behavior substantially deviates from this prediction. Our study elucidates a hitherto unknown sophistication in human observational learning but also identifies important limitations to this ability.

Robust inference of causality in high-dimensional dynamical processes from the Information Imbalance of distance ranks

We introduce an approach which allows detecting causal relationships between variables for which the time evolution is available. Causality is assessed by a variational scheme based on the Information Imbalance of distance ranks, a statistical test capable of inferring the relative information content of different distance measures. We test whether the predictability of a putative driven system Y can be improved by incorporating information from a potential driver system X, without explicitly modeling the underlying dynamics and without the need to compute probability densities of the dynamic variables. This framework makes causality detection possible even between high-dimensional systems where only few of the variables are known or measured. Benchmark tests on coupled chaotic dynamical systems demonstrate that our approach outperforms other model-free causality detection methods, successfully handling both unidirectional and bidirectional couplings. We also show that the method can be used to robustly detect causality in human electroencephalography data.

Sensory Drive Modifies Brain Dynamics and the Temporal Integration Window

Perception is suggested to occur in discrete temporal windows, clocked by cycles of neural oscillations. An important testable prediction of this theory is that individuals' peak frequencies of oscillations should correlate with their ability to segregate the appearance of two successive stimuli. An influential study tested this prediction and showed that individual peak frequency of spontaneously occurring alpha (8-12 Hz) correlated with the temporal segregation threshold between two successive flashes of light [Samaha, J., & Postle, B. R. The speed of alpha-band oscillations predicts the temporal resolution of visual perception. Current Biology, 25, 2985-2990, 2015]. However, these findings were recently challenged [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour, 6, 732-742, 2022]. To advance our understanding of the link between oscillations and temporal segregation, we devised a novel experimental approach. Rather than relying entirely on spontaneous brain dynamics, we presented a visual grating before the flash stimuli that is known to induce continuous oscillations in the gamma band (45-65 Hz). By manipulating the contrast of the grating, we found that high contrast induces a stronger gamma response and a shorter temporal segregation threshold, compared to low-contrast trials. In addition, we used a novel tool to characterize sustained oscillations and found that, for half of the participants, both the low- and high-contrast gratings were accompanied by a sustained and phase-locked alpha oscillation. These participants tended to have longer temporal segregation thresholds. Our results suggest that visual stimulus drive, reflected by oscillations in specific bands, is related to the temporal resolution of visual perception.

Time for What? Dissociating Explicit Timing Tasks through Electrophysiological Signatures

Estimating durations between hundreds of milliseconds and seconds is essential for several daily tasks. Explicit timing tasks, which require participants to estimate durations to make a comparison (time for perception) or to reproduce them (time for action), are often used to investigate psychological and neural timing mechanisms. Recent studies have proposed that mechanisms may depend on specific task requirements. In this study, we conducted electroencephalogram (EEG) recordings on human participants as they estimated intervals in different task contexts to investigate the extent to which timing mechanisms depend on the nature of the task. We compared the neural processing of identical visual reference stimuli in two different tasks, in which stimulus durations were either perceptually compared or motorically reproduced in separate experimental blocks. Using multivariate pattern analyses, we could successfully decode the duration and the task of reference stimuli. We found evidence for both overlapping timing mechanisms across tasks as well as recruitment of task-dependent processes for comparing intervals for different purposes. Our findings suggest both core and specialized timing functions are recruited to support explicit timing tasks.

Neurocomputational Models of Interval Timing: Seeing the Forest for the Trees

Extracting temporal regularities and relations from experience/observation is critical for organisms' adaptiveness (communication, foraging, predation, prediction) in their ecological niches. Therefore, it is not surprising that the internal clock that enables the perception of seconds-to-minutes-long intervals (interval timing) is evolutionarily well-preserved across many species of animals. This comparative claim is primarily supported by the fact that the timing behavior of many vertebrates exhibits common statistical signatures (e.g., on-average accuracy, scalar variability, positive skew). These ubiquitous statistical features of timing behaviors serve as empirical benchmarks for modelers in their efforts to unravel the processing dynamics of the internal clock (namely answering how internal clock "ticks"). In this chapter, we introduce prominent (neuro)computational approaches to modeling interval timing at a level that can be understood by general audience. These models include Treisman's pacemaker accumulator model, the information processing variant of scalar expectancy theory, the striatal beat frequency model, behavioral expectancy theory, the learning to time model, the time-adaptive opponent Poisson drift-diffusion model, time cell models, and neural trajectory models. Crucially, we discuss these models within an overarching conceptual framework that categorizes different models as threshold vs. clock-adaptive models and as dedicated clock/ramping vs. emergent time/population code models.

Temporal decision making: it is all about context

Is there sufficient evidence to make a decision, or has enough time passed to justify making a decision? According to Ofir and Landau (2022, Current Biology: CB, 32[18], 4093-4100.e6), these two questions are closely related: brain activity measured by EEG at the offset of stimulus presentation predicts the behavioral temporal decision, being influenced by the current context, and reflecting the relative distance to a decision threshold which is also context dependent.

Intonation Units in Spontaneous Speech Evoke a Neural Response

Spontaneous speech is produced in chunks called intonation units (IUs). IUs are defined by a set of prosodic cues and presumably occur in all human languages. Recent work has shown that across different grammatical and sociocultural conditions IUs form rhythms of ∼1 unit per second. Linguistic theory suggests that IUs pace the flow of information in the discourse. As a result, IUs provide a promising and hitherto unexplored theoretical framework for studying the neural mechanisms of communication. In this article, we identify a neural response unique to the boundary defined by the IU. We measured the EEG of human participants (of either sex), who listened to different speakers recounting an emotional life event. We analyzed the speech stimuli linguistically and modeled the EEG response at word offset using a GLM approach. We find that the EEG response to IU-final words differs from the response to IU-nonfinal words even when equating acoustic boundary strength. Finally, we relate our findings to the body of research on rhythmic brain mechanisms in speech processing. We study the unique contribution of IUs and acoustic boundary strength in predicting delta-band EEG. This analysis suggests that IU-related neural activity, which is tightly linked to the classic Closure Positive Shift (CPS), could be a time-locked component that captures the previously characterized delta-band neural speech tracking.SIGNIFICANCE STATEMENT Linguistic communication is central to human experience, and its neural underpinnings are a topic of much research in recent years. Neuroscientific research has benefited from studying human behavior in naturalistic settings, an endeavor that requires explicit models of complex behavior. Usage-based linguistic theory suggests that spoken language is prosodically structured in intonation units. We reveal that the neural system is attuned to intonation units by explicitly modeling their impact on the EEG response beyond mere acoustics. To our understanding, this is the first time this is demonstrated in spontaneous speech under naturalistic conditions and under a theoretical framework that connects the prosodic chunking of speech, on the one hand, with the flow of information during communication, on the other.

Encoding, working memory, or decision: how feedback modulates time perception

The hypothesis that individuals can accurately represent temporal information within approximately 3 s is the premise of several theoretical models and empirical studies in the field of temporal processing. The significance of accurately representing time within 3 s and the universality of the overestimation contrast dramatically. To clarify whether this overestimation arises from an inability to accurately represent time or a response bias, we systematically examined whether feedback reduces overestimation at the 3 temporal processing stages of timing (encoding), working memory, and decisions proposed by the scalar timing model. Participants reproduced the time interval between 2 circles with or without feedback, while the electroencephalogram (EEG) was synchronously recorded. Behavioral results showed that feedback shortened reproduced times and significantly minimized overestimation. EEG results showed that feedback significantly decreased the amplitude of contingent negative variation (CNV) in the decision stage but did not modulate the CNV amplitude in the encoding stage or the P2-P3b amplitudes in the working memory stage. These results suggest that overestimation arises from response bias when individuals convert an accurate representation of time into behavior. Our study provides electrophysiological evidence to support the conception that short intervals under approximately 3 s can be accurately represented as "temporal gestalt."

Electrophysiological signatures of temporal context in the bisection task

Despite having relatively accurate timing, subjective time can be influenced by various contexts, such as stimulus spacing and sample frequency. Several electroencephalographic (EEG) components have been associated with timing, including the contingent negative variation (CNV), offset P2, and late positive component of timing (LPCt). However, the specific role of these components in the contextual modulation of perceived time remains unclear. In this study, we conducted two temporal bisection experiments to investigate this issue. Participants had to judge whether a test duration was close to a short or long standard. Unbeknownst to them, we manipulated the stimulus spacing (Experiment 1) and sample frequency (Experiment 2) to create short and long contexts while maintaining consistent test ranges and standards across different sessions. The results revealed that the bisection threshold shifted towards the ensemble mean, and both CNV and LPCt were sensitive to context modulation. In the short context, the CNV exhibited an increased climbing rate compared to the long context, whereas the LPCt displayed reduced amplitude and latency. These findings suggest that the CNV represents an expectancy wave preceding a temporal decision process, while the LPCt reflects the decision-making process itself, with both components influenced by the temporal context.

Perceived time expands and contracts within each heartbeat

Perception of passing time can be distorted.¹ Emotional experiences, particularly arousal, can contract or expand experienced duration via their interactions with attentional and sensory processing mechanisms.^2,3 Current models suggest that perceived duration can be encoded from accumulation processes^4,5 and from temporally evolving neural dynamics.^6,7 Yet all neural dynamics and information processing ensue at the backdrop of continuous interoceptive signals originating from within the body. Indeed, phasic fluctuations within the cardiac cycle impact neural and information processing.^{8,9,10,11,12,13,14,15} Here, we show that these momentary cardiac fluctuations distort experienced time and that their effect interacts with subjectively experienced arousal. In a temporal bisection task, durations (200-400 ms) of an emotionally neutral visual shape or auditory tone (experiment 1) or of an image displaying happy or fearful facial expressions (experiment 2) were categorized as short or long.¹⁶ Across both experiments, stimulus presentation was time-locked to systole, when the heart contracts and baroreceptors fire signals to the brain, and to diastole, when the heart relaxes, and baroreceptors are quiescent. When participants judged the duration of emotionally neural stimuli (experiment 1), systole led to temporal contraction, whereas diastole led to temporal expansion. Such cardiac-led distortions were further modulated by the arousal ratings of the perceived facial expressions (experiment 2). At low arousal, systole contracted while diastole expanded time, but as arousal increased, this cardiac-led time distortion disappeared, shifting duration perception toward contraction. Thus, experienced time contracts and expands within each heartbeat-a balance that is disrupted under heightened arousal.