I see what you mean: Theta power increases are involved in the retrieval of lexical semantic information

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Abstract

An influential hypothesis regarding the neural basis of the mental lexicon is that semantic representations are neurally implemented as distributed networks carrying sensory, motor and/or more abstract functional information. This work investigates whether the semantic properties of words partly determine the topography of such networks.

Subjects performed a visual lexical decision task while their EEG was recorded. We compared the EEG responses to nouns with either visual semantic properties (VIS, referring to colors and shapes) or with auditory semantic properties (AUD, referring to sounds).

A time–frequency analysis of the EEG revealed power increases in the theta (4–7 Hz) and lower-beta (13–18 Hz) frequency bands, and an early power increase and subsequent decrease for the alpha (8–12 Hz) band. In the theta band we observed a double dissociation: temporal electrodes showed larger theta power increases in the AUD condition, while occipital leads showed larger theta responses in the VIS condition.

The results support the notion that semantic representations are stored in functional networks with a topography that reflects the semantic properties of the stored items, and provide further evidence that oscillatory brain dynamics in the theta frequency range are functionally related to the retrieval of lexical semantic information.

Introduction

It has been proposed repeatedly that semantic representations of words, and objects, are neurally implemented in distributed networks carrying sensory, motor and/or more abstract functional information (e.g., Damasio, 1990, Farah and McClelland, 1991, Warrington and McCarthy, 1987, Warrington and Shallice, 1984). A more specific hypothesis is that the exact topology of such networks is at least partly determined by the semantic properties of the word or object concept (Martin and Chao, 2001, Pulvermueller, 1999, Pulvermueller, 2001). This contrasts with the view put forward by others (e.g., Devlin et al., 2002, Tyler and Moss, 2001, Tyler et al., 2000) that semantic representations are stored in a distributed network in which there is no neural specificity as a function of semantic property.

According to the first view, manipulable objects such as tools are strongly linked to motor behavior, and therefore their representational networks should comprise a significant amount of neurons in motor cortex. Animals, which are most of the time (visually) perceived rather than manipulated, should be represented by networks that partly reside in visual cortex. Given anatomically confined lesions/damage to neural tissue, the topographical distinction between the representations of both categories is likely to lead to selective damage to the representations in one category. Support for this view comes from a large number of neuropsychological studies (see Forde and Humphreys, 1999, Saffran and Sholl, 1999 for reviews), that have shown the existence of category-specific semantic impairments in patients, for instance a relatively selective impairment for naming/recognizing animals as opposed to tools, or—less frequently—vice versa. These findings are at least compatible with the view that the semantic properties of words or objects partly determine the topography of their neural representation (although they can be interpreted in different ways, e.g., Tyler & Moss, 2001).

More direct support comes from a number of hemodynamic neuroimaging studies. In a PET experiment, Martin et al. (Martin, Haxby, Lalonde, Wiggs, & Ungerleider, 1995) found that generation of color words selectively activated a region in the ventral temporal lobe just anterior to the area involved in the perception of color, whereas generation of action words activated a region in the middle temporal gyrus just anterior to the area involved in the perception of motion. In another PET study (Martin, Wiggs, Ungerleider, & Haxby, 1996), these authors showed that naming pictures of tools activated premotor areas, while naming pictures of animals activated medial occipital areas. Within the language domain, a recent fMRI study (Hauk, Johnsrude, & Pulvermueller, 2004) showed that the visual presentation of verbs related to the execution of face, arm and leg movements (e.g., to lick, to pick and to kick) differentially activated areas in the motor cortex that were adjacent to or overlapping with the areas that were activated during actual movements of the corresponding body parts. Similarly, recent fMRI data (Vitali et al., 2005) show different effective connectivity patterns for viewing tools vs. animals, with tools engaging areas in frontal and premotor areas, and animals engaging visual association areas. It should be noted however that other studies failed to find such semantically specific activations during semantic processing (e.g., Noppeney & Price, 2002).

Together, the available data largely support the view that spatially distributed functional networks form the basis of semantic representations, and that the topographies of these networks correspond to the semantic properties of individual items. However, in order to answer the question of how such functional networks are formed, one has to gain insight into the temporal dynamics of their activation. Here, we present EEG data showing that oscillatory neuronal dynamics in the theta frequency range are involved in the activation of functional networks with semantically specific topography.

The temporal dynamics of neuronal activity can be investigated with neuroimaging methods that yield high temporal resolution such as EEG or MEG. While some studies have investigated the scalp topography of event-related potentials (ERPs) elicited by the presentation of different categories of words (Hauk and Pulvermueller, 2004, Pulvermueller et al., 2001), the oscillatory dynamics of EEG and MEG data presumably provide another window on the dynamic formation of functional networks. The reason for this is that an (indirect) link can be made between changes in neuronal synchrony on the one hand, and changes in the oscillatory activity that is present in scalp-recorded EEG and MEG on the other hand. The amplitude (or power) of oscillatory activity is indicative of synchronization changes because the synchronization of local groups of neurons, the activities of which are picked up by one and the same sensor, will result in larger EEG/MEG amplitudes for that sensor. It follows that local changes in synchrony of oscillatory firing patterns lead to changes in amplitude (or power) of rhythmic EEG/MEG activity at the single-trial level. The phase of EEG/MEG oscillations is important because synchronization of oscillatory firing patterns between spatially distant neuronal populations lead to increases in coherence, or in phase synchronization, between two (or more) concurrently measured EEG or MEG signals (Bastiaansen and Hagoort, 2003, Singer, 1999, Varela et al., 2001, see Pulvermueller, 1999 for arguments of how this mechanism applies to the representation of lexical semantics).

In sum, a topographical analysis of event-related changes of either power or coherence in oscillatory EEG or MEG activity during language processing tasks would be informative in establishing whether synchronous functional networks with distinct scalp topographies constitute the representation of different categories of words. A few studies have provided data that speak to this issue. In a number of studies aimed at characterizing EEG coherence changes elicited by different word categories, Weiss and colleagues (see Weiss & Mueller, 2003 for review) found different coherence patterns in the lower-beta frequency range (roughly 13–18 Hz) between concrete and abstract nouns, and between concrete nouns and verbs. However, the authors did not attempt to relate coherence topography to semantic properties in these studies. A study by Pulvermueller (Pulvermueller, Lutzenberger, & Preissl, 1999) did attempt to relate semantic properties to the scalp topography of EEG power changes. In a lexical decision task, nouns were contrasted with verbs, assuming that nouns are perception-related and should therefore have a relatively larger neuronal representations in occipital cortex, while verbs are action-related and should have representational network elements in motor cortex. The authors found power decreases in the gamma frequency range compared to baseline, that were smaller for verbs than for nouns at central electrodes, but smaller for nouns than for verbs over occipital electrodes. These data were interpreted to reflect different network topographies that followed the semantic properties of the stimuli.

Other studies have related semantic memory operations to power changes in the alpha frequency band (for review, see Klimesch, 1999). It should be noted however, that in most of these studies, the term semantic memory is used in the sense of declarative (as opposed to episodic) memory. In language comprehension theories however, the term semantic is used in a more narrow sense, referring to the meaning aspect of words (as opposed to syntax, phonology etc.). In the remainder of this paper, we will use the term semantic to refer to the more narrow, psycholinguistically defined process of attributing meaning to linguistic material. However, some studies do address semantic processing in this more narrow sense (e.g., Klimesch et al., 1997a, Klimesch et al., 1997b, Rohm et al., 2001). Generally, the results of these studies support the notion that semantic processing is indeed related to power decreases in the upper alpha band (roughly 10–12 Hz).

We further pursue the issue of whether words with different semantic properties are neurally represented in topographically distinct functional networks, by taking a different approach in constructing stimulus material. Rather than relying on a correlation between semantic features and specific word classes, we constructed two sets of nouns, one referring exclusively to colors and shapes, and the other referring exclusively to sounds. Thus, one set of stimuli only contained nouns with visual semantic properties, while the other set only contained nouns with auditory semantic properties. While their EEG was measured, subjects performed a visual lexical decision task, in which we contrasted the ‘visual’ nouns with the ‘auditory’ nouns (note that both were presented to the subjects in the visual modality). Given our hypothesis, the former set of nouns should activate a network with a relatively large component in the visual cortex, whereas the latter set should lead to the emergence of a network that extends into auditory cortex. Because event-related changes in power reflect changes in local synchrony, while event-related changes in phase coherence between different sensors reflect changes in long-range synchrony (Bastiaansen and Hagoort, 2003, Varela et al., 2001) we expected these local differences in network topography to be expressed as differential power increases over auditory and visual areas. More specifically, we expected EEG power to be larger over the auditory cortex following words with auditory semantic properties compared to words with visual semantic properties, while the opposite pattern was expected over the visual cortex. On the basis of the existing literature on oscillatory EEG/MEG dynamics during language processing, we hypothesized this differential power increase to be manifest in one (or more) of the following frequency bands: theta (4–7 Hz; based on Bastiaansen et al., 2002b, Bastiaansen et al., 2002c, Hagoort et al., 2004), alpha (8–12 Hz; based on the studies reviewed in Klimesch, 1999), lower-beta (13–18 Hz; based on the studies reviewed in Weiss & Mueller, 2003) or gamma (above 30 Hz; based on Hagoort et al., 2004, Pulvermueller et al., 1996, Pulvermueller et al., 1999).

Section snippets

Subjects

Sixteen students (4 male) from the Radboud University Nijmegen (aged 21–36 years), were paid for their participation after having given informed consent in writing, according to the Declaration of Helsinki. All were native Dutch speakers with normal or corrected-to-normal vision. They were right-handed, as assessed by a self-report. None of the participants had any neurological impairment, neurological trauma, and none used neuroleptics.

Stimulus material

The item set that is critical for the present study

ERP data

Fig. 1 shows the time-course of the ERPs elicited by the AUD and VIS words at representative channels.

A negative component is observed, with a (grand-average) peak at 400 ms after word onset. We identify this component as the classical N400. This is confirmed by the postcentral topographical distribution (Fig. 2a). A slight difference in scalp topography appears to be present between the two conditions, with the VIS words eliciting slightly more negativity at frontal channels than the AUD words

Discussion

We investigated event-related potentials (ERPs) and oscillatory brain dynamics of the EEG while subjects performed a visual lexical decision task. In agreement with our hypotheses, we found power increases in the theta band (4–7 Hz) and in the lower beta range (13–18 Hz). We also found the expected power decrease in the alpha (8–12 Hz) frequency range. However, in contrast to previous studies no evidence was found for power in- or decreases in the gamma frequency band.

The most striking finding of

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