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.

Time encoding migrates from prefrontal cortex to dorsal striatum during learning of a self-timed response duration task.

Although time is a fundamental dimension of life, we do not know how brain areas cooperate to keep track and process time intervals. Notably, analyses of neural activity during learning are rare, mainly because timing tasks usually require training over many days. We investigated how the time encoding evolves when animals learn to time a 1.5 s interval. We designed a novel training protocol where rats go from naive- to proficient-level timing performance within a single session, allowing us to investigate neuronal activity from very early learning stages. We used pharmacological experiments and machine-learning algorithms to evaluate the level of time encoding in the medial prefrontal cortex and the dorsal striatum. Our results show a double dissociation between the medial prefrontal cortex and the dorsal striatum during temporal learning, where the former commits to early learning stages while the latter engages as animals become proficient in the task.

Multimodal resting-state connectivity predicts affective neurofeedback performance.

Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into "connectivity summary scores" (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson's correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = -0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.

Time experience during social distancing: A longitudinal study during the first months of COVID-19 pandemic in Brazil.

Social distancing in response to the COVID-19 pandemic brought several modifications in our daily lives. With these changes, some people have reported alterations in their feelings of how fast time was passing. In this study, we assessed whether and how social distancing and the evolution of the COVID-19 pandemic influenced participants' time awareness and production of time intervals. Participants (n = 3855) filled in the first questionnaire approximately 60 days after the start of social distancing in Brazil and weekly questionnaires for 15 weeks during social distancing. Our results indicate that time was perceived as expanded at the beginning, but this feeling decreased across the weeks. Time awareness was strongly associated with psychological factors such as loneliness, stress, and positive emotions, but not with time production. This relation was shown between participants and within their longitudinal reports. Together, our findings show how emotions are a crucial aspect of how time is felt.

Temporal dynamics of implicit memory underlying serial dependence.

Serial dependence is the effect in which the immediately preceding trial influences participants' responses to the current stimulus. But for how long does this bias last in the absence of interference from other stimuli? Here, we had 20 healthy young adult participants (12 women) perform a coincident timing task using different inter-trial intervals to characterize the serial dependence effect as the time between trials increases. Our results show that serial dependence abruptly decreases from 0.1 s to 1 s inter-trial interval, but it remains pronounced after that for up to 8 s. In addition, participants' response variability slightly decreases over longer intervals. We discuss these results in light of recent models suggesting that serial dependence might rely on a short-term memory trace kept through changes in synaptic weights, which might explain its long duration and apparent stability over time.

Temporal prediction elicits rhythmic preactivation of relevant sensory cortices.

Being able to anticipate events before they happen facilitates stimulus processing. The anticipation of the contents of events is thought to be implemented by the elicitation of prestimulus templates in sensory cortex. In contrast, the anticipation of the timing of events is typically associated with entrainment of neural oscillations. It is so far unknown whether and in which conditions temporal expectations interact with feature-based expectations, and, consequently, whether entrainment modulates the generation of content-specific sensory templates. In this study, we investigated the role of temporal expectations in a sensory discrimination task. We presented participants with rhythmically interleaved visual and auditory streams of relevant and irrelevant stimuli while measuring neural activity using magnetoencephalography. We found no evidence that rhythmic stimulation induced prestimulus feature templates. However, we did observe clear anticipatory rhythmic preactivation of the relevant sensory cortices. This oscillatory activity peaked at behaviourally relevant, in-phase, intervals. Our results suggest that temporal expectations about stimulus features do not behave similarly to explicitly cued, nonrhythmic, expectations, yet elicit a distinct form of modality-specific preactivation.

Post-interval EEG activity is related to task-goals in temporal discrimination.

Studies investigating the neural mechanisms of time perception often measure brain activity while participants perform a temporal task. However, several of these studies are based exclusively on tasks in which time is relevant, making it hard to dissociate activity related to decisions about time from other task-related patterns. In the present study, human participants performed a temporal or color discrimination task of visual stimuli. Participants were informed which magnitude they would have to judge before or after presenting the two stimuli (S1 and S2) in different blocks. Our behavioral results showed, as expected, that performance was better when participants knew beforehand which magnitude they would judge. Electrophysiological data (EEG) was analysed using Linear Discriminant Contrasts (LDC) and a Representational Similarity Analysis (RSA) approach to investigate whether and when information about time and color was encoded. During the presentation of S1, we did not find consistent differences in EEG activity as a function of the task. On the other hand, during S2, we found that temporal and color information was encoded in a task-relevant manner. Taken together, our results suggest that task goals strongly modulate decision-related information in EEG activity.

Subject-independent decoding of affective states using functional near-infrared spectroscopy.

Affective decoding is the inference of human emotional states using brain signal measurements. This approach is crucial to develop new therapeutic approaches for psychiatric rehabilitation, such as affective neurofeedback protocols. To reduce the training duration and optimize the clinical outputs, an ideal clinical neurofeedback could be trained using data from an independent group of volunteers before being used by new patients. Here, we investigated if this subject-independent design of affective decoding can be achieved using functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas. For this purpose, a linear discriminant analysis classifier was first trained in a dataset (49 participants, 24.65±3.23 years) and then tested in a completely independent one (20 participants, 24.00±3.92 years). Significant balanced accuracies between classes were found for positive vs. negative (64.50 ± 12.03%, p<0.01) and negative vs. neutral (68.25 ± 12.97%, p<0.01) affective states discrimination during a reactive block consisting in viewing affective-loaded images. For an active block, in which volunteers were instructed to recollect personal affective experiences, significant accuracy was found for positive vs. neutral affect classification (71.25 ± 18.02%, p<0.01). In this last case, only three fNIRS channels were enough to discriminate between neutral and positive affective states. Although more research is needed, for example focusing on better combinations of features and classifiers, our results highlight fNIRS as a possible technique for subject-independent affective decoding, reaching significant classification accuracies of emotional states using only a few but biologically relevant features.

Prestimulus alpha power is related to the strength of stimulus representation.

Spatial attention can modulate behavioural performance and is associated with several electrophysiological markers. In this study, we used multivariate pattern analysis in electrophysiology data to investigate the effects of covert spatial attention on the quality of stimulus processing and its underlying mechanisms. Our results show that covert spatial attention led to (i) an anticipatory alpha power desynchronization; (ii) enhanced stimuli identity information. Moreover, we found that alpha power fluctuations in anticipation of the relevant stimuli boosted and prolonged the coding of stimulus identity.

Temporal regularity and stimulus control in multiple fixed interval schedules.

In multiple fixed interval schedules of reinforcement, different time intervals are signaled by different environmental stimuli which acquire control over behavior. Previous work has shown that temporal performance is controlled not only by external stimuli but also by temporal aspects of the task, depending on the order in which the different intervals are trained - intermixed across trials or in blocks of several trials. The aim of this study was to further describe the training conditions under which the stimuli acquire control over temporal performance. We manipulated the number of consecutive trials of each fixed interval (FI) per training block (Experiment I) and the number of FIs trained (Experiment II). The results suggest that when trained in blocks of several consecutive trials of the same FI, temporal performance is controlled by temporal regularities across trials and not by the visual stimuli that signal the FIs. One possible account for those data is that the temporal cues overshadow the visual stimuli for the control of temporal performance. Similar results have also been observed with humans, which suggest that temporal regularity overcomes the stimuli in the control of behavior in temporal tasks across species.

Rats can learn a temporal task in a single session.

Fixed interval, peak interval, and temporal bisection procedures have been used to assess cognitive functions and address questions such as how animals perceive, represent, and reproduce time intervals. They have also been extensively used to test the effects of drugs on behavior, and to describe the neural correlates of interval timing. However, those procedures usually require several weeks of training for behavior to stabilize. Here, we investigated a variation of the Differential Reinforcement of Response Duration (DRRD) task with a target time of 1.2 s. We compared three types of training protocols and reported a procedure in which performance by the end of the very first session nearly matches the performance of long-term training. We also showed that the initial distribution of the responses is uni-modal and, as training evolves (and rats improve their performance), a second peak emerges and progressively shifts toward longer times. This one-day training protocol can be used to investigate temporal learning and may be especially useful to electrophysiological and neuropharmacological studies.

Dissociating the sequential dependency of subjective temporal order from subjective simultaneity.

The physical simultaneity between two events can differ from our point of subjective simultaneity (PSS). Studies using simultaneity judgments (SJ) and temporal order judgments (TOJ) tasks have shown that whether two events are reported as simultaneous is highly context-dependent. It has been recently suggested that the interval between the two events in the previous trial can modulate judgments both in SJ and TOJ tasks, an effect named rapid recalibration. In this work, we investigated rapid recalibration in SJ and TOJ tasks and tested whether centering the range of presented intervals on perceived simultaneity modulated this effect. We found a rapid recalibration effect in TOJ, but not in SJ. Moreover, we found that centering the intervals on objective or subjective simultaneity did not change the pattern of results. Interestingly, we also found no correlations between an individual's PSS in TOJ and in SJ tasks, which corroborates other studies in suggesting that these two psychophysical measures may capture different processes.

A common representation of time across visual and auditory modalities.

Humans' and non-human animals' ability to process time on the scale of milliseconds and seconds is essential for adaptive behaviour. A central question of how brains keep track of time is how specific temporal information across different sensory modalities is. In the present study, we show that encoding of temporal intervals in auditory and visual modalities are qualitatively similar. Human participants were instructed to reproduce intervals in the range from 750 ms to 1500 ms marked by auditory or visual stimuli. Our behavioural results suggest that, although participants were more accurate in reproducing intervals marked by auditory stimuli, there was a strong correlation in performance between modalities. Using multivariate pattern analysis in scalp EEG, we show that activity during late periods of the intervals was similar within and between modalities. Critically, we show that a multivariate pattern classifier was able to accurately predict the elapsed interval, even when trained on an interval marked by a stimulus of a different sensory modality. Taken together, our results suggest that, while there are differences in the processing of intervals marked by auditory and visual stimuli, they also share a common neural representation.

The effect of conscious intention to act on the Bereitschaftspotential.

The current study investigated the effect of conscious intention to act on the Bereitschaftspotential. Situations in which the awareness of acting is minimally expressed were generated by asking 16 participants to press a button after performing a mental imagery task based on animal pictures (automatic condition). The affective responses induced by the pictures were controlled by selecting the animals according to different valences, threatening and neutral. The Bereitschaftspotential associated with the button presses was compared to the observed when similar movements were performed under the basic instructions of the self-paced movement paradigm (willed condition). Enhanced Bereitschaftspotential amplitudes were observed in the willed condition with respect to the automatic condition. This effect was manifested as a negative slope at medial frontocentral sites during the last 500 ms before movement onset. The valence of the pictures did not affect the motor preparatory potentials. The results suggest that significant part of the NS' subcomponent of the readiness potential is associated with the attention to-and, presumably, awareness of-intention to move, possibly reflecting cortical activation from supplementary motor areas. Secondarily, our findings supports that the feeling of threat does not influence the Bereitschaftspotential associated with automatic movements. Regarding methodological issues, the behavioural model of spontaneous voluntary movements proposed in automatic condition can benefit investigations on purely motor (or non-cognitive) subcomponents of the Bereitschaftspotential.

Predicting affective valence using cortical hemodynamic signals.

Ascribing affective valence to stimuli or mental states is a fundamental property of human experiences. Recent neuroimaging meta-analyses favor the workspace hypothesis for the neural underpinning of valence, in which both positive and negative values are encoded by overlapping networks but are associated with different patterns of activity. In the present study, we further explored this framework using functional near-infrared spectroscopy (fNIRS) in conjunction with multivariate analyses. We monitored the fronto-temporal and occipital hemodynamic activity of 49 participants during the viewing of affective images (passive condition) and during the imagination of affectively loaded states (active condition). Multivariate decoding techniques were applied to determine whether affective valence is encoded in the cortical areas assessed. Prediction accuracies of 89.90 ± 13.84% and 85.41 ± 14.43% were observed for positive versus neutral comparisons, and of 91.53 ± 13.04% and 81.54 ± 16.05% for negative versus neutral comparisons (passive/active conditions, respectively). Our results are consistent with previous studies using other neuroimaging modalities that support the affective workspace hypothesis and the notion that valence is instantiated by the same network, regardless of whether the affective experience is passively or actively elicited.

Functional near-infrared spectroscopy-based affective neurofeedback: feedback effect, illiteracy phenomena, and whole-connectivity profiles.

Background: Affective neurofeedback constitutes a suitable approach to control abnormal neural activities associated with psychiatric disorders and might consequently relief symptom severity. However, different aspects of neurofeedback remain unclear, such as its neural basis, the performance variation, the feedback effect, among others. Aim: First, we aimed to propose a functional near-infrared spectroscopy (fNIRS)-based affective neurofeedback based on the self-regulation of frontal and occipital networks. Second, we evaluated three different feedback approaches on performance: real, fixed, and random feedback. Third, we investigated different demographic, psychological, and physiological predictors of performance. Approach: Thirty-three healthy participants performed a task whereby an amorphous figure changed its shape according to the elicited affect (positive or neutral). During the task, the participants randomly received three different feedback approaches: real feedback, with no change of the classifier output; fixed feedback, keeping the feedback figure unmodified; and random feedback, where the classifier output was multiplied by an arbitrary value, causing a feedback different than expected by the subject. Then, we applied a multivariate comparison of the whole-connectivity profiles according to the affective states and feedback approaches, as well as during a pretask resting-state block, to predict performance. Results: Participants were able to control this feedback system with 70.00 % ± 24.43 % ( p < 0.01 ) of performance during the real feedback trials. No significant differences were found when comparing the average performances of the feedback approaches. However, the whole functional connectivity profiles presented significant Mahalanobis distances ( p ≪ 0.001 ) when comparing both affective states and all feedback approaches. Finally, task performance was positively correlated to the pretask resting-state whole functional connectivity ( r = 0.512 , p = 0.009 ). Conclusions: Our results suggest that fNIRS might be a feasible tool to develop a neurofeedback system based on the self-regulation of affective networks. This finding enables future investigations using an fNIRS-based affective neurofeedback in psychiatric populations. Furthermore, functional connectivity profiles proved to be a good predictor of performance and suggested an increased effort to maintain task control in the presence of feedback distractors.

Temporal Anticipation Based on Memory.

The fundamental role that our long-term memories play in guiding perception is increasingly recognized, but the functional and neural mechanisms are just beginning to be explored. Although experimental approaches are being developed to investigate the influence of long-term memories on perception, these remain mostly static and neglect their temporal and dynamic nature. Here, we show that our long-term memories can guide attention proactively and dynamically based on learned temporal associations. Across two experiments, we found that detection and discrimination of targets appearing within previously learned contexts are enhanced when the timing of target appearance matches the learned temporal contingency. Neural markers of temporal preparation revealed that the learned temporal associations trigger specific temporal predictions. Our findings emphasize the ecological role that memories play in predicting and preparing perception of anticipated events, calling for revision of the usual conceptualization of contextual associative memory as a reflective and retroactive function.

Dynamic representation of time in brain states.

The ability to process time on the scale of milliseconds and seconds is essential for behaviour. A growing number of studies have started to focus on brain dynamics as a mechanism for temporal encoding. Although there is growing evidence in favour of this view from computational and in vitro studies, there is still a lack of results from experiments in humans. We show that high-dimensional brain states revealed by multivariate pattern analysis of human EEG are correlated to temporal judgements. First, we show that, as participants estimate temporal intervals, the spatiotemporal dynamics of their brain activity are consistent across trials. Second, we present evidence that these dynamics exhibit properties of temporal perception, such as scale invariance. Lastly, we show that it is possible to predict temporal judgements based on brain states. These results show how scalp recordings can reveal the spatiotemporal dynamics of human brain activity related to temporal processing.

Low-frequency cortical oscillations are modulated by temporal prediction and temporal error coding.

Monitoring and updating temporal predictions are critical abilities for adaptive behavior. Here, we investigated whether neural oscillations are related to violation and updating of temporal predictions. Human participants performed an experiment in which they had to generate a target at an expected time point, by pressing a button while taking into account a variable delay between the act and the stimulus occurrence. Our behavioral results showed that participants quickly adapted their temporal predictions in face of an error. Concurrent electrophysiological (EEG) data showed that temporal errors elicited markers that are classically related to error coding. Furthermore, intertrial phase coherence of frontal theta oscillations was modulated by error magnitude, possibly indexing the degree of surprise. Finally, we found that delta phase at stimulus onset was correlated with future behavioral adjustments. Together, our findings suggest that low frequency oscillations play a key role in monitoring and in updating temporal predictions.

Lexical-retrieval and semantic memory in Parkinson's disease: The question of noun and verb dissociation.

The dissociation between the processing of verbs and nouns has been debated in light of the Embodied Cognition Theory (EC). The objective of this paper is to verify how action and verb processing deficits of PD patients are modulated by different tasks with different cognitive demands. Action and object lexical-semantic processing was evaluated in patients with Parkinson's Disease (PD) and cognitively healthy controls through three different tasks (verbal fluency, naming and semantic association). Compared to controls, PD patients presented worse performance in naming actions and in the two semantic association tasks (action/object). Action verbal fluency performance was significantly associated with PD severity whereas object semantic association deficits and noun verbal fluency scores were associated to lower scores in measures of global cognitive functioning. Our data suggest that semantic deficits are related to the type of cognitive processing and this is in the line with more flexible EC accounts.