Dynamic representation of time in brain states

Abstract

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.Humans and non-human animals are able to estimate temporal intervals across a wide range of scales 1,2 . Intervals ranging from hundreds of milliseconds to seconds are especially critical for sensory and motor processing, learning and cognition. On this scale, the theoretical dominant models are based on the existence of an internal clock, consisting of a pulse-emitting oscillator and an accumulator that counts the pulses 3-5 . Electrophysiological evidence for this model consists mainly in ramping activity as a possible correlate of the accumulation of pulses, and has been found using invasive recordings in brain regions as prefrontal, parietal and motor areas. In human electroencephalography (EEG), it has been suggested that the contingent negative variation (CNV), a slow cortical potential of developing negative polarity, could be a reflection of such processes, given its similarity with the hypothesised characteristics of an accumulation process 6 . However, in both cases (invasive recordings and human EEG) it is not clear whether ramping activity is coding time or using temporal information to anticipate or react to events 7 . Moreover, the existence of an internal clock has been criticised based on behavioural findings and for being biologically unrealistic 8 . For this reason, a number of alternate models of timing, which take into account neural data, have been put forward as biologically-plausible explanatory candidates, such as state-dependent networks models 9 . For this class of models, neural circuits would be inherently capable of temporal processing as a result of the complexity of cortical networks coupled with the presence of time-dependent neuronal properties 8 . In this view, neural systems can take advantage of the temporal evolution of their states, caused by the variation in neural and synaptic properties. When activated, a neural system would follow a unique trajectory through its state space. Thus, by adapting networks to read out specific activity patterns, they could be tuned to discriminate temporal intervals 9 . Ho...

A common representation of time across visual and auditory modalities

“…In a recent study, we have shown that multivariate pattern analysis (MVPA) can reveal spatiotemporal dynamics of human brain activity related to temporal processing 14 . Multivariate approaches can take advantage of small differences in the signal across electrodes that might not be detectable using classical EEG methods.…”

Temporal metacognition as the decoding of self-generated brain dynamics

“…This design enabled to address the possibility of internal timing or duration being explicitly available to awareness through self-referential metacognition (Block, 1995;. Because current neuroscientific models posit that internal dynamics in timing are mediated by oscillatory or statedependent network dynamics (Laje & Buonomano, 2013;Karmarkar & Buonomano, 2007;Buhusi & Meck, 2005;Merchant et al, 2013;Allman et al, 2014;Gu et al, 2015;van Wassenhove, 2016;Bueno et al, 2017), we combined magneto-and electroencephalography (M/EEG) to quantify the dynamics of oscillatory brain responses when participants engaged in self-generated and self-assessed timing. Using a temporal production task to assess metacognition provided several paradigmatic and conceptual benefits.…”

Dissociating decisional and temporal information in interval categorisation

“…In previous works, we have shown that time-related information was decodable from pre-offset EEG signals in temporal reproduction [Barne et al, 2018] and temporal categorisation tasks [Bueno et al, 2017]. However, because in our previous categorisation task there was only one reference interval [Bueno et al, 2017], time and decision information were intrinsically correlated. In the present study, we show again that it is possible to decode time-related information from within each condition.…”

“…Responses were collected via a response box with 9 buttons (DirectIN High Speed Button; Empirisoft). The task consisted of a computerised "shoot the target" task adapted from Guilhardi et al [2010] and Bueno et al [2017].…”

“…As in Bueno et al [2017], the task consisted of two types of trials. Regular trials (480 trials, figure 1A) started with the presentation of a target (a bulls-eye with a 1.5 visual degree radius, red and black) at the left hemifield of the screen (background RGB-colour 150;150;150) and a "gun sight" (an empty circle with 0.5 visual degree radius) at the centre of the screen.…”