Complex words are those comprised of multiple morphemes, such as agree+able
. For such words, the base verb (agree
) can combine with a number of affixes (e.g., agree+ment
). An important question in language processing concerns how such morphologically complex words are accessed from the mental lexicon. Much of the behavioral evidence supporting effects of morphological complexity on lexical access comes from the interplay of morphological structure and frequency. It is widely known that an individual word’s frequency of occurrence in the language will affect the speed with which that word can be accessed in a variety of tasks (Forster and Chambers, 1973
; Frederiksen and Kroll, 1976
; Gernsbacher, 1984
; Balota and Chumbley, 1984
; Balota and Chumbley, 1985
). For morphologically complex words, however, the frequency of the word’s surface form (the word as a whole including its particular affix, e.g., agreeable
), as well as the frequency of its base morpheme (that is, the total frequency of all the words containing this component morpheme, e.g., agree
+ agreeable + agreement + disagree
, etc.), both play an important role in processing (see Alegre and Gordon 1999a
, Baayen et al. 1997
; Joanisse and Seidenberg 1999
). These two types of frequencies are known as the surface frequency
(the frequency of a particular word form) and the base frequency
(the frequency of the base morpheme, equivalent to the total frequency of all the words containing this morpheme). The effect of the base frequency on response time is referred to as the base frequency effect
. A number of studies have manipulated surface and base frequency of complex words independently and have shown that each of these variables affects response times for certain types of words (Taft 1979
, Bradley 1980
, Vannest and Boland 1999
, Bertram et al. 2000
). Base frequency effects indicate an influence of morphological complexity on processing; rather than each word containing the base being treated in isolation, the common base across morphologically complex forms affects the processing of all forms sharing that base.
Two types of theoretical accounts have been suggested for the presence/absence of morphological effects in complex word recognition. The classic decomposition view, based on linguistic accounts of rules used for combining morphemes, is that a base frequency effect reflects a process in which complex words are accessed in terms of their component morphemes, which are subsequently combined (Taft 1979
, Bradley 1980
, Burani and Caramazza 1987, Schreuder and Baayen 1995
, Bertram et al. 2000
, Vannest et al. 2002
, Taft 2004). This type of model specifies either obligatory decomposition (Taft 2004) or a dual-system model in which complex words may be represented as separate morphemes, full forms, or both (Burani and Caramazza 1987, Schreuder and Baayen 1995
). An alternative account of these same data (Rueckl, Mikolinski, Raveh, Miner, and Mars, 1997; Joanisse and Seidenberg 1999
, Seidenberg and Gonnerman, 2000; Plaut and Gonnerman, 2000; Gonnerman, Seidenberg and Andersen 2007) is that accessing a complex word also activates all the other words in the lexicon that overlap substantially in phonology and meaning (this will usually turn out to be the same set of words that are morphologically related). In either case, accounts of this behavioral difference predict that morphologically complex words associated with robust behavioral base frequency effects should differ from complex words with no associated base frequency effect, as well as from simple words with no morphological complexity.
In the present study, we examine whether there are specialized regions of the brain that support this processing of morphological relationships among word families (words sharing the same base) or, alternatively, whether this kind of processing is done by the same regions that process monomorphemic words (though perhaps with higher levels of activation).
Derivational Morphology and the Base Frequency Effect
In this study, we focus on a particular subset of complex words in English that has shown varying results in behavioral studies: words with derivational affixes. Derivational affixes (such as English –able mentioned above) alter the meaning and grammatical category of the words to which they apply. Typically, particular derivational affixes apply to only a small set of base words; subsets of words in the same grammatical category often take different derivational morphemes to mark the same grammatical and semantic change. For example, in English, some verb forms become nominals by adding –ion (e.g., observation), while others add -ment (e.g., investment) or any of several other nominalizing affixes. Within this group of affixes, lexical access shows robust differences. On the one hand, some derivational affixes, including English - less, -ness and -able, or Dutch -heid, show effects of base frequency. On the other hand, words containing other derivational affixes, like English -ion, do not show a base frequency effect during word recognition. In keeping with the terminology in this literature, we refer to the former as ‘decomposable’ words and to the latter as ‘whole-words’.
A number of linguistic factors contribute to whether a word shows a base frequency effect or not, suggesting the possibility that the distinction might be graded rather than strictly dichotomous. Phonological properties have been proposed to determine the base frequency effect (Bradley, 1980
). Typically, phonologically neutral affixes (those that do not cause phonological changes to the words they attach to, e.g., agree - agreeable
) show a base frequency effect, whereas non-neutral affixes like -ity
(where there can be phonological interaction between base and affix, e.g., serene – serenity
) do not (Vannest and Boland, 1999
). However, Taft (2004) has demonstrated that the absence of a base frequency effect may not rule out the possibility of explicit representation of individual morphemes (see details below). Moreover, some priming studies show facilitation across the type of word pairs that involve a phonological change (Boudelaa and Marslen-Wilson, 2004), suggesting that their relationship does not go unrecognized. A possible explanation is that a complex word’s semantics is another important linguistic factor (Marslen-Wilson et al. 1994, Feldman et al. 2002, 2004; Bertram et al. 2000b). When the meaning of a complex word can be easily understood from its parts (e.g. adorable
), it is more likely to show a base frequency effect than a word whose meaning is not as clearly derived from its parts (e.g. hospitality
). Such findings, indicating sensitivity to phonological and semantic structure, are consistent with the view that the base frequency effect reflects co-activation of morphological families during lexical access, or a graded effect of the relevant variables, rather than the presence/absence of a decomposition process. Overall, the behavioral literature on derivationally complex words is extensive and has suggested that a number of variables, typically highly correlated with one another, can influence the base frequency effect. In the present work, we limit ourselves to morphologically complex words either known to lead to robust base frequency effects or not, and we ask how the neural network engaged during lexical access of each type of words differs from that supporting simple, monomorphemic words as well as from each other. We also take advantage of the fMRI method to ask whether neural activation reveals any effect of morphological complexity for ‘whole words’ that behavioral measures do not. This study will thus provide a first window on the neural bases of the base frequency effect or lack thereof.
Models of Morphological Processing
As already noted, two types of accounts have been suggested for the presence/absence of morphological effects in complex word recognition. One class of models suggests that most complex words are processed in terms of their component morphemes, which are subsequently checked for compatibility. On this account, base forms of complex words are stored in the lexicon; inflectional or derivational morphemes are added through a compositional process that is reflected in longer reaction times (Niemi et al. 1994
). Full decomposition accounts (Taft 1979
, 2004) assume that complex words are always recognized in terms of component morphemes, and base frequency effects arise from the fact that base forms are activated as part of this process. Taft (2004) suggests that even the absence of a base frequency effect does not indicate that no decomposition process occurs. Rather, properties of particular complex words and the other items that surround them in an experimental context (for example, syntactic category ambiguity of the stem, infrequent combinations of stem and suffix, and a context of nonwords made up of real morphemes) may make the recombination stage slower, masking base frequency effects.
Dual-system models (Burani and Caramazza 1987, Schreuder and Baayen 1995
) also assume that base frequency effects arise from explicit representation of individual morphemes, but if they are frequent enough, full forms are also represented. Factors such as phonological and semantic transparency may influence whether items are stored in their full form versus constructed from separate morphemes (Bertram et al., 2000
). On this account, words with phonologically neutral affixes (such as -able
) are influenced by their individual morphemic components, whereas words with non-neutral affixes like -ion
are accessed as whole units and therefore do not show a base frequency effect (Schreuder and Baayen 1995
, Vannest et al., 2002
However, as mentioned above, base frequency effects for complex words may be accounted for by mechanisms other than a decomposition process during lexical access. Connectionist models of word recognition (see Rueckl et al., 1997; Joanisse and Seidenberg 1999
, Seidenberg and Gonnerman, 2000, Rueckl and Raveh 1999, Raveh 2002) hypothesize that a single mechanism supports recognition of monomorphemic and complex words, without decomposition. According to these models, morphological relationships between words result from overlap in orthographic, phonological and semantic properties of words. For example, Joanisse and Seidenberg (1999)
propose such a model for past tense inflection: regular (-ed
) past tense word forms have a great deal of phonological similarity with their base forms, so phonological similarity can account for why these forms may be accessed together. Irregular past tenses (e.g. go
) do not have as much phonological overlap with their base forms, so that semantic information plays a greater role in accessing these past tenses. In this framework, base frequency effects result from frequency-sensitive connections between base words and complex forms that overlap in varying degrees of orthographic, phonological and semantic similarity. Thus, for example, responses to agreeable
are facilitated by the frequency of agree
more than serenity
is facilitated by serene
, not because agreeable
is accessed as two separate morphemes, but because of the larger degree of orthographic and phonological overlap between agree
. Rueckl and Raveh (1999) showed that a three-layer network model could quickly learn mappings between orthography and semantics when these mappings contained morphological regularities, whereas random form-to-meaning mappings were learned more slowly. The success of this kind of model suggests that morphological relationships among words could indeed emerge without any explicit representation of a morphological process in the lexicon.
Neuroscientific Work on Simple versus Complex Words
While many studies have examined behavioral measures of processing derived words, only a handful of studies have addressed the neural bases of derived word processing. Ito et al. (1996) found that Broca's aphasics have difficulty producing a regular derivational affix in Japanese, but not in producing less productive derived forms; they found the opposite pattern for Wernicke's and transcortical aphasics. Vannest, Polk and Lewis (2005)
used fMRI to assess the participation of Broca’s area and the basal ganglia in processing derived and inflected words. They found that neural activation increased in Broca’s area and the basal ganglia for inflected words and for derived words that show base frequency effects in behavioral studies relative to monomorphemic words, but not for derived words that do not show base frequency effects (that is, derived words hypothesized to be processed as whole wordforms). Whereas these studies highlight the role of the frontal-basal ganglia network in the processing of derived words, not all studies do so. Using a masked priming paradigm with a lexical decision task to examine derived words, Devlin et al. (2004)
found that activation was reduced in the left angular gyrus, left occipitotemporal cortex and the left middle temporal gyrus for base forms when primed with a derivational relative. These same areas were also modulated by semantic and orthographic priming, indicating that the priming from derivational relatives may have been mediated by these factors. Bick, Frost and Goelman (2010)
used a similar paradigm in Hebrew and also found morphological priming effects in left frontal and parietal regions, though only the parietal actvation was affected by semantic transparency. Davis, Meunier and Marslen-Wilson (2004)
failed to find any effect of morphology in a task requiring synonym monitoring of morphologically complex (inflected and derived) vs. simple English words.
The available studies therefore indicate that, to the extent that an effect of morphological complexity can be observed, it is expressed by an increased recruitment of left language areas, especially the frontal-basal ganglia network and the superior temporal sulcus, during the analysis of morphologically complex words as compared to simple words. However, these findings are not entirely consistent in the specific regions involved or in the precise effects found. In the present study we will investigate this question further, by taking advantage of the known effect of word frequency on brain activation (low frequency processes lead to higher brain activation than high frequency, more automatized processes), in combination with the extensive behavioral evidence of base frequency effects for morphologically complex words, to revisit the question of which areas in the language system that may mediate the processing of complex as compared to simple words.
Neuroscientific Work on Word Frequency Effects
Before asking how manipulations of base
frequency might affect neural activation for complex words, it is important to consider what we know about the effects of simple word frequency on neural activation for monomorphemic words. The effect of frequency on neural activation for monomorphemic words has been investigated in a number of studies. The general pattern is increased activation for low frequency words in brain areas associated with lexical processing. Fiez et al. (1999)
, using PET, found increased activation for naming low versus high frequency words in left superior temporal regions, left supplementary motor regions, and left inferior frontal gyrus (where it interacted with spelling/sound regularity). Using fMRI, Keller et al. (2001)
found that reading low as compared with high frequency words in sentence contexts increased activation in a number of regions including the left inferior frontal gyrus, a left superior/middle temporal region, and left and right extrastriate visual cortex; weaker effects were also found in the right hemisphere homologues of these regions. This frequency effect also interacted with sentence complexity (the sentence complexity effect was greater when the sentence contained low frequency words) in left hemisphere language ROI’s. Chee et al. (2003)
, using a semantic judgment task in fMRI, also found increased activation for low relative to high frequency words in the left inferior frontal gyrus, along with a lesser extent of activation in its right hemisphere homologue, and additional areas of activation in the left anterior cingulate and a left inferior temporal region. Fiebach et al. (2002)
, using a lexical decision task in fMRI, also showed increased activation for reading low over high frequency words in the left inferior frontal gyrus, anterior insula bilaterally, and in the caudate nucleus and thalamus bilaterally. Recent studies by Kronbichler et al. (2004) and Hauk et al. (2008) made use of fMRI and a silent reading task and parametric variation in word frequency, examining regions that increased in activation with decreasing frequency. These studies found that middle occipital gyrus (Kronbichler et al., 2004) and fusiform gyrus responded to word frequency, as well as left inferior frontal gyrus (Kronbichler et al., 2004 and Hauk et al., 2008). Hauk et al. (2008) also found a relationship with frequency in the insula bilaterally as well as left and right inferior frontal gyrus.
In sum, then, all studies manipulating word frequency indicate greater recruitment of the brain areas that mediate language processing, whether at the lexical level or at the sentence level, for low frequency as compared to high frequency words.
Rationale for the Present Study
The present study compares complex words with high and low base frequency to simple words with matched high and low surface word frequency. This comparison allows us to ask which brain regions show effects of morphological complexity, both independent of frequency (i.e., a main effect of morphological complexity) and interacting with frequency. Of particular interest is the extent to which those brain areas that show a frequency effect for simple words also show a base frequency effect for complex words. The standard view that complex words are decomposed into morpheme+affix, leading to the base frequency effect in behavioral studies, predicts overlapping brain areas responsive to both types of frequency. Based on the existing literature, these may include inferior frontal gyrus, superior/middle temporal regions, extrastriate visual areas, anterior cingulate, insula bilaterally, caudate nucleus or thalamus. Alternatively, some of these regions, which have previously been found to respond to simple word frequency, may not respond to base frequency. This pattern of results would suggest that frequency and morphological structure interact, and contrary to the classical view of decomposition, that the components of complex words are not processed the same way as simple words. The frequency manipulation included in the present design allow us to characterize and differentiate between those brain areas that may reflect compositional behavior and those that do not.
Importantly, then, our study will investigate the details of neural activation during morphological processing by contrasting complex and simple words. In addition, we will investigate the details of neural activation for morphological complexity by exploiting the fact that not all derived words show a base frequency effect. As described earlier, words with derivational affixes that are less productive, more idiosyncratic in meaning, and change the form of base words to which they attach (e.g. -ion, as in locate ➔ location) do not show the usual base frequency effects correlated with morphological complexity and appear to be processed as whole-word units. We therefore will examine the brain systems that mediate the processing of words that do show base frequency effects in behavioral work (called ‘decomposable’), as well as those that do not (called ‘whole-word’). Note that we choose these terms so as not to single out any property (phonological or semantic transparency, productivity) but to represent a cluster of properties that contribute to the finding that some words show morphological effects while others do not. The behavioral literature has often attempted to assess which of the properties of complex words – their phonological transparency, semantic transparency, productivity, or family size – is responsible for the morphological effects. However, some of these properties (e.g., family size) are systematically related to morphological complexity, and several of these properties are not possible to differentiate perfectly in an fMRI study of real English words (see Methods for more discussion of this point). While we attempt to match or differentiate these properties wherever possible, this is not the main focus of the study; rather, we ask whether the properties of complex words act as a cluster of correlated factors that influence their representation and processing, and perhaps, as we investigate here, the neural mechanisms that underlie this processing.
The proposal that ‘decomposable’ words are decomposed into parts, whereas ‘whole-words’ are processed as whole lexical units, like simple words, predicts a greater recruitment of those brain areas sensitive to morphological complexity for ‘decomposable’ as compared to ‘whole-words’. However, we will also be interested in investigating the extent to which the complex morphological structure of ‘whole-words’ differentiates them nonetheless from simple words. While behavioral evidence has suggested that ‘whole-words’ are no different than simple words, it is possible that patterns of neural activation may reveal a more graded role of morphological complexity than has previously been revealed, with ‘whole-words’ showing activation patterns somewhere in between those of decomposable words and those of simple monomorphemic words, in line with their intermediate morphological status.
Finally, we will analyze our fMRI data with the goal of decoupling the differences in response time to high frequency and low frequency words from differences in fMRI activation. A common finding in fMRI studies is that the level of BOLD signal increases with increased task difficulty, which often corresponds to increases in the time required to perform the task (i.e. longer response times, see Dassonville et al. 1998
, Huettel et al. 2001
, Huettel et al. 2004
). Consequently, it becomes difficult in data analysis to interpret higher BOLD signal in a particular brain region when response times differ between two conditions: is this signal increase due to the relevant cognitive operations involved in the task, or due to perceptual or motor processing that increases with longer response time? Stowe et al. (2004)
, for example, suggest that it may be impossible to separate cognitive/language functions from motor processes in subcortical areas and the cerebellum. In an effort to distinguish differences due to frequency or morphological structure versus response time in our data, a regression analysis will be used to identify the BOLD activation level in various brain regions that vary directly with response times in the task. All further analyses of frequency and morphology effects will be performed after variation due to perceptual and motor increases associated with longer response time is removed, resulting in a more accurate assessment of these effects independent of response preparation/execution times.