Compared to other senses, very little is known about taste. In a recent study (Crouzet, S. M., Busch, N. A., & Ohla, K. (2015). Taste quality decoding parallels taste sensations. Current Biology, 25(7), 890-896.), we used mulitvariate pattern analysis of single-trial EEG data to investigate which information about a taste is represented in taste-evoked brain responses.
In everyday language, “taste” is often used in to describe a multisensory sensation that involves taste proper, but also other sensations such as olfaction and somatosensation (think of texture and temperature). By contrast, when we talk about taste in chemosensory research, we refer specifically to the sense that is mediated by dedicated gustatory receptors, mostly on the tongue.
Taste is a peculiar sense. One aspect in which it differs from other senses is the categorical structure of gustatory phenomenology. For example, we could describe our phenomenology of having a cup of coffee as “I see the cup”, and “it smells like coffee”, and “it tastes bitter”. Thus, when we describe our perception in other senses, we usually refer to the object evoking this perception, but we describe taste only with a categorical label: bitter, sour, sweet, salty, or umami (savory). These categories are also referred to as “taste qualities”. Therefore, one important research question in taste research is to clarify how these taste qualities are represented in the human cortex.
Unraveling the neural code underlying taste quality perception remains a major challenge in gustatory research. This is due, in part, to the fact that chemical stimuli delivered into the mouth are notoriously difficult to control with respect to their physical properties, i.e., place of stimulation and onset/offset. Most of our current understanding of the cortical areas involved in human taste perception is based on neuroimaging techniques that are relatively forgiving to imprecise stimulus onset, such as functional magnetic resonance imaging (fMRI) or positron emission tomography (PET). By comparison, only few studies so far have measured EEG and thus little is known about the temporal dynamics of the neural representation of taste (see Ohla, Busch, & Lundstrom, 2012).
A fundamental question that needs to be addressed in taste research is what these neural responses mean – which information is encoded in the signal? What does the gustatory system tell itself and the rest of the brain about the taste and how are these responses related to subjective taste perception? This question is difficult to address with conventional, univariate event-related potential (ERP) analyses. For instance, several studies have demonstrated that the amplitude of the gustatory-evoked ERP is dependent on the intensity of the gustatory stimulus (Ohla, Toepel, le Coutre, & Hudry, 2010; Tzieropoulos, Rytz, Hudry, & le Coutre, 2013). Does this imply that the neuronal processes underlying this ERP response are used by the brain to code intensity, rather than, say, taste quality? Likewise, a study comparing ERPs evoked by different tastants may demonstrate amplitude differences between tastes, but does this imply that the brain uses the underlying neural processes to represent taste category? Generally speaking, univariate ERP analyses test whether the ERP amplitude is bigger in condition A than in condition B. To study whether a neural signal is involved in coding a given feature, an alternative avenue is to test whether the neural signal contains information about the feature. If so, it should be possible to analyze the data recorded on a given trial and decide based on these data which feature was presented on that trial. This approach is called decoding (popularized under the term “brain reading”). The reasoning is that if a neural signal allows us to decode information about a feature, it is likely that the brain uses the same neural signal for coding this feature.
Thus, to address the question whether the taste-evoked EEG response codes information about taste quality rather than other taste features such as intensity or pleasantness, we used time-resolved multivariate pattern analysis (MVPA) to evaluate whether the single-trial, instantaneous topographical pattern of electrophysiological activity carries information about taste quality (Crouzet, Busch, & Ohla, 2015). MVPA leverages information in the topographical pattern on single trials in single subjects, thereby allowing to directly relate on a single-trial basis brain responses with subsequent behavior. Therefore, MVPA in humans offers the opportunity to relate this information to the subjective perception reported by the participants.
Figure 1: Event-Related Responses to Different Tastes Exhibited Differences in Electric Field Strength and Distribution (A) Schematic of an experimental trial. Atomized tastants (indicated in black) were embedded in a regular stream of water sprays (gray). (B) Global field power (GFP) for each taste category (averaged across participants). The time period during which the GFP differed from pre-stimulus levels is marked with a gray line for all tastes and with colored lines for individual tastes. Only p < 0.05 lasting for at least 100 ms are shown. (C) Periods of significant topographical differences (global map dissimilarity) between taste categories are indicated in black. The top row depicts the main effect of taste categories (only p < 0.05 lasting for > 100 ms are shown); subsequent rows represent all pairwise comparisons: salty versus sweet, salty versus sour, salty versus bitter, sweet versus sour, sweet versus bitter, and sour versus bitter (p < 0.05 for > 30 ms). (D) Estimates of neural sources underlying the initial GFP-normalized taste-evoked responses (P1) include the frontal operculum and insula (predominantly of the left hemisphere), the bilateral superior temporal gyrus, and the cuneus for all tastes. (Reproduced with permission from (Crouzet et al., 2015))