Abstract
In her new book, Time Will Tell, Mari Riess Jones composes a major score for psychological time: a matured and enriched version of an intellectual journey started in 1976, when Jones, taking the auditory perspective of attention and memory, argued that time was a foundational dimension of the (human) mind (M. R. Jones, 1976). Since her description of the Dynamic Attending Theory known as DAT, Jones has nourished the thinking of many scholars, who have in turn enriched the original framework computationally (Large & Jones, 1999) but also empirically, spanning psychology, neurosciences, or musicology (Bella et al., 2009; Besle et al., 2011; Lakatos et al., 2008; Nobre & Van Ede, 2018; Nozaradan et al., 2011; Patel, 2010; Schön & Tillmann, 2015; Schroeder et al., 2010).
From its inception, DAT has emphasized the dynamic aspects of attention in time: In a tunable brain, the temporal architecture defined by endogenous rhythms provides a self-sustained, stable, yet adaptive attractor-like hierarchical structure onto which external rhythms map. The refined theoretical framework laid out in the first chapters together with a wealth of empirical considerations provide a great amount of falsifiable arguments, such as the central role of involuntary and voluntary temporal expectation (implicit and explicit timing, respectively), the possible ecological invalidity of current work on time perception, or the interaction between internal and external rhythms.
For the reader specifically interested in the awareness of time, Jones highlights useful differences between interval timing as proposed in the Scalar Expectancy Theory (SET), or attention to time, and context-based stimulus timing as proposed in DAT, that is attention in time. Jones notes that time intervals are coded independently in SET, whereas they are context-dependent in DAT or, that while SET relies on a pacemaker/counter, neural oscillations varying in frequency and strength are deemed sufficient for DAT.
In DAT, neural oscillations functionally implement an endogenous temporal architecture. The proposed classification of specific oscillatory frequency bands (i.e., alpha pulses are “inhibitory,” beta oscillations for “attending” and gamma for “reactive”) may be overzealous, as recently argued by Buzsáki (2019), but it has the merits of highlighting the needs for more research. In other words, if the functional role of neural oscillations is to link temporal predictions and message carrying networks with cognitive functions (Bastos et al., 2012; Engel et al., 2001; Fries, 2015; Singer, 1999), can we find dynamics that show human specificity?
Across chapters, it becomes clear that a great strength of DAT is the unifying framework it offers for a wide range of phenomena on different time scales, from relatively slow speech envelopes or musical meter to the fast frequencies accounting for pitch percepts. Whether the corresponding empirical observations, such as phase-entrainment of slow neural oscillations (Henry & Obleser, 2012), and (sub-) cortical frequency-following responses (Coffey et al., 2019) truly share the postulated implementation on the neurophysiological level requires more research. Throughout the book, novel observations are enriching the arguments, such as the amodality of time. Rhythm in one modality can improve (implicit) timing in the other, and this can be observed in attentional selection cross-modally (Kösem & van Wassenhove, 2012) as supported by neurophysiological signatures of entrainment in both animals (Lakatos et al., 2008) and humans (Luo & Poeppel, 2007). Jones also introduces the aging hypothesis, which states that individually preferred frequency ranges, so-called attractors, slow down over the life span, proposedly explaining hearing preferences, and potential impairments in older listeners.
In Part II, the domain generality of the DAT is brought to life by providing theoretical considerations and empirical evidence of how humans engage with music and speech on the basis of adaptive entrainment, mainly, transient mode locking of driven-to-driving rhythms. Jones details DAT with respect to music, an ideal case study of hierarchical metrical predictions for auditory processing, on the basis of which she differentiates innate attraction to rhythmicity from acquired meter perception. She also highlights recent advances in oscillatory-based speech models (Giraud & Poeppel, 2012) and stresses the crucial importance of innate brain rhythms (hidden attractors) interfacing with the linguistic system for speech timing and learning. The concluding speculations in the very last chapter expand the previously outlined concepts of entrainment to nonhuman species from crickets to birds to whales, whose vocalizations seem to inhabit specific temporal niches wherein synchrony conveys inter-individual communication. The chapter ends with the critical consideration of technologically induced rhythms, not well matched with human attractor profiles, and their possible detrimental effects on the human cognitive system.
There remain some important difficulties faced by DAT. For instance, current quantifications of neural oscillations are oversimplification of brain activity (Cole & Voytek, 2017), an issue raised early on by seminal electroencephalogram work (Jasper, 1948). In short, oscillations are not regular sinusoids but triangular-shaped, an important detail for time research. In addition, recent work suggests that neural oscillations do not show strong stationarity but rather bursting profiles (S. R. Jones, 2016), which may nevertheless fit the proposal of a metric system attuned to environmental rhythms. Yet, and consistent with Jones’s proposal, entrained oscillations can show nonstationarity of their phase response, driving the awareness of event order in a sequence (Kösem et al., 2014), suggesting that an endogenous temporal architecture can maintain and tune its properties despite varying exogenous event structures (van Wassenhove, 2016). Also consistent with Jones’s proposal is the observation that time is implicit to all tasks as temporal statics are automatically coded in the brain likely driven by oscillatory activity (Cravo et al., 2011; Herbst et al., 2018; Herbst & Obleser, 2019).
Considering that Time Will Tell provides a very rich and detailed account of the importance of the time dimension as a foundational structuring dimension of the mind, the section summaries that pace each chapter provide an extremely limpid and helpful thread throughout the book. In light of this richness, the absence of seminal work (Pöppel, 1972, 1997) on the importance of neural oscillations in timing is perhaps regrettable insofar as theoretical (dis)similarities could have been helpful to the reader. Those who do not consider cyclic time as a sine qua non condition for brain functions may be convinced otherwise or fed with specifics to argument against. Conversely, those already convinced by the foundational importance of cyclic time in biology will realize that a lot of work remains to be achieved to counteract some of the simplifying assumptions in the field. In sum, Time Will Tell provides intellectual openness with no sacrificing of a clear theoretical positioning, which will surely feed much-needed empirical work on the complex issue of time of the mind. Of course, only Time Will Tell.