Neurophysiological Mechanisms of Word Meaning Acquisition

Repetition suppression is typically observed in PET/ fMRI experiments when spoken words or pseudowords are presented repeatedly during relatively active involvement of subjects into the experimental procedure (Steve Majerus et al., 2005; Paulesu et al., 2009).

Yet EEG studies dedicated to passive word learning reported no substantial ERP suppression for words and pseudowords even after 150 stimulus presentations (Kimppa et al., 2015; Shtyrov, 2011). Kimppa et al., 2015 reported that after attentive passive listening at least to words there still was a small decline of ERP amplitude, while there was an enhancement for pseudowords. Similar results were obtained within oddball paradigm (Shtyrov et al., 2010); Yue et al., 2014).

The absence of habituation effect for pseudowords in the EEG studies indicates that episodic passive listening was not sufficient to provide an exhaustive pseudoword familiarization leading to further response diminution. However relative ERP enhancement especially during attentive listening to pseudowords evidence initial stage of phoneme concatenation into Gestalt-like phonological representation. Early time windows, where ERP to pseudowords differed from ERPs to words (about 100-200 ms) also corresponds to the P200 latency component reported for word form recognition (Stevens, 2002; Fiederichi, 2002).

Taking this into account, we can assume that the active experimental task speeds up word learning processes in subjects. A strong repetition suppression observed in the current study to both types of pseudoword stimuli (`words' and `distractors') may be a consequence of an active learning procedure similar to operant conditioning. We will discuss the procedural differences of the current experiment from previous studies below.

5.3 Differential effect explanation

Although in the current study strong repetition suppression was observed for both stimulus types, the suppression for `words' associated with action was less than for `distractors'. We can consider this to be a result of superposition of two effects - a nonspecific repetition suppression, and a more specific repetition enhancement to words that acquired meaning through the associative learning procedure. The latter effect seems to be similar to findings obtained by Hawkins, Astle, and Rastl (2015), who demonstrated that pseudowords induced relatively higher MMN response if they were associated with pictures. Our data speaks in favor of hypothesis that semantic stimulates processes of phoneme concatenation and strengthens word-form representation. The time window and the effect are similar to results reported by Fargier et. al (2014) and Franзois et al. (2017).

In terms of operant conditioning, `words' utilized in the current procedure may be considered as stimuli relevant to behavior (i.e. sound-guided behavior), while `distractors' lack such relevance. Kato, Gillet, and Isaacson (2015) studied changes in habituation dynamics to familiarized sound stimuli which acquired behavioral relevance. The study reported increase of pyramidal cells response to the stimuli after training with reinforcement. Moreover, the study by Beitel, Schreiner, Cheung, Wang, & Merzenich (2003) evidenced that behavioral plasticity mechanisms also caused response decrements to task distractors thus providing target-distractor perceptive contrast. These findings altogether may provide a likely explanation of the differences in dynamics for `words' and `distractors' in the current experiment.

Importantly, acoustic word recognition can be understood as a sensory detection of relatively complex spectrotemporal acoustic patterns, i.e. of phoneme concatenations (DeWitt & Rauschecker, 2012; Hickok & Poeppel, 2007). From a neurobiological point of view, this is a routine detection of certain stimulus features bound together; as far as the auditory system concerns, detection of increasingly complex stimulus features is performed hierarchically throughout the auditory cortices, from the core primary auditory cortex to belt and further to parabelt auditory areas (Baumann & Schlangen, 2013; Poremba et al., 2003).

The mechanism that underlies the effects observed may be related to a well-studied phenomenon of receptive field tuning. A series of studies evidenced sensory plasticity in auditory cortex that occurs as a result of stimulus importance learning (see Weinberger (2004) for review). It was discovered that receptive fields of the auditory cortex neurons attune to features of reinforced stimuli (e.g. pitch/frequency) with consequent reduction of response on non-conditioned stimuli (Edeline, Pham, & Weinberger, 1993). As a result, while strong habituation was observed for non-conditioned stimuli, the overall response to conditioned stimuli was enhanced. This kind of plasticity was observed both for classical and for operant conditioning (Bakin & Weinberger, 1990, 2005; Bakin, South, & Weinberger, 1996) with either negative or positive reinforcement (Kisley & Gerstein, 2001). Remarkably, neural tuning was reported to occur after a rather short period of learning not exceeding few hours (Edeline et al., 1993; Galvбn & Weinberger, 2002) and proved to last for weeks (Weinberger, Javid, & Lepan, 2006). Remarkably, the same effects were observed in humans (Bitterman, Mukamel, Malach, Fried, & Nelken, 2008; Molchan, Sunderland, McIntosh, Herscovitch, & Schreurs, 2006). The phenomena are known as memory/experience induced plasticity.

Importantly, after learning procedure we observed relative response enhancement to `words' within speech areas commonly discussed in modern literature (e.g., Hickok Poeppel 2015; Hagoort, 2015; Berwick, Friederici, Chomsky and Bolhuis, 2013). The activation enhancement for words observed within the articulatory network (STS and Broca's complex) may evidence word-specific phonological tuning for efficient detection of target `words'. Current findings can be understood that semantic learning triggered a process essentially similar to receptive field tuning, and this process may be one of the principal mechanisms of meaningful word learning.

5.4 Timing of the effects

The time interval, during which a significant differential effect was observed, began at about 150 ms after disambiguation point and lasted till about 360 ms. Importantly the reported timespan covered both phonologic and semantic analyses according to a hierarchical pattern-recognition scheme (DeWitt & Rauschecker, 2012; Riesenhuber & Poggio, 2002).

ERP studies dedicated to word processing distinguish two components N200 and N400. According to Friedrich and Friederici's review (2010), categorization processes are related to N200 component (150-250 ms), while latency of semantic access for words is 300-600 ms after stimulus onset (Hagoort, Brown, & Groothusen, 1993; Halgren et al., 2002; Kutas & Federmeier, 2010). Both components are sensitive to repetitive presentations of words: the decline in amplitude was observed in the course of repetitive presentations (Dittinger, Chobert, Ziegler, & Besson, 2017). It seems that repetitive presentation facilitates both categorization (i.e. word-form representation recall) and semantic access. In other words, associative neuronal network activated previously will automatically capture subsequent stimuli with no additional widespread search and additional restoration of phonological form and semantic information. Yet studies dedicated to passive word learning and perception reported for existence of earlier time interval, which might evidence that the initial stage of categorization between words and non-words starts about 100 ms (Kimppa et al., 2015, MacGregor et al., 2012), more traditional N200 and N400 intervals were also reported as related to words-pseudowords contrasting.

The beginning of the interval obtained overlapped with the timing of effects reported in several EEG studies (Kimppa et. al, 2015; Shtyrov et al., 2011; Yue et al. (2014); Baart & Samuel, 2015) during passive exposure to words and pseudowords; this is compatible with the explanation that phonological familiarization, leading to formation of a phoneme concatenation detector, was involved in the effect observed. Findings of an EEG study, which involved active semantic learning, were also confined to a rather early time interval of 130-180 ms, since the study focused exclusively on changes in phonological representations induced by semantic acquisition Hawkins, Astle, and Rastl (2015).

Yet, the interval reported in the current study extended into much later latencies than those typically reported in EEG studies involving phonological effects of learning, which may be the consequence of an active procedure of semantic word learning used in the current study. At least two EEG studies addressed semantic aspect of auditory word learning more directly, both of them using some version of active associative learning. Fargier et. al 2014 found significant effects of word learning in a 100-400 msec post-word onset interval. Although this was an a priori chosen interval, it closely resembles the time interval obtained in the current study. (Franзois et al., 2017) specifically addressed the N400 effect and found an increase in N400 amplitude as a result of semantic learning.

As we will discuss in the next section, brain regions revealed in the current study, demonstrated a succession of processing stages, with phonological analysis at low-tier speech areas in the beginning and throughout the time interval, and with semantic analysis in higher-tier speech areas added at the end of the time interval under analysis.

5.5 Brain regions

Using data-driven approach, we identified a widespread network of cortical areas that were involved in word meaning acquisition. These included both low-tier areas involved in phonological processing, which were active during the whole interval of analysis (approximately 150-360 ms after disambiguation point), and higher-tier areas, involved in semantic processing, which were active during the later part of time interval under analysis (at about 300 ms and later).

5.5.1 Left anterior temporal cortex

At the initial part of the time interval reported here, aSTS-aMTG region was observed, activation spread was observed at later time frames toward temporal pole. STS is considered to perform the spectrotemporal analysis (Hickok & Poeppel, 2007) and initial steps of word recognition (Scott & Johnsrude, 2003; Scott & Wise, 2004). Recent meta-analysis introduced functional dissociation between aSTG most strongly associated with auditory word-form processing, and aSTS involved in semantic processing (DeWitt & Rauschecker, 2012). Thus, the spread of activation within this region evidences successive involvement of high-order semantical areas; during later stage of word processing we observed activation within temporal pole - the cortical area which was reported to be involved in quick acquisition of word-picture associations and recollection (together with temporoparietal, premotor, and prefrontal regions), see Majerus et al., (2005); Mestres-Missй et al. (2007); Paulesu et al. (2009); Sharon et al.( 2011). Animal studies evidence involvement of monkey left temporal pole in specialized processing of species-specific calls Poremba et al.(2003).

5.5.2 Broca's complex

We observed long-lasting widespread activation of Broca's complex (insular circular sulci in combination with pIFG, triangular gyrus and ventral prefrontal cortex). This finding evidences active involvement of the articulatory system. In turn, Broca's complex and STS form phonological-articulation loop lateralized in the left hemisphere (Budisavljevic et al., 2017; Clerget, Badets, Duquй, & Olivier, 2011; Hillis et al., 2004). Phonological-articulation loop is supposed to provide integration between articulatory sensory-motor experience during word learning, speech perception and production.

Several studies reported activation of articulation-related parts of motor (Pulvermьller, 2005) and premotor cortex (Broca's complex) during passive listening to phonemes or words (Wilson, Saygin, Sereno, & Iacoboni, 2004). According to (Majerus et al., 2006), the inferior and premotor frontal cortices, as well as insula are consistently activated during verbal short-term memory tasks, and they are responsible for reintroducing the to-be-recalled information into the phonological storage via subvocal articulatory rehearsal, thus refreshing decaying short-term memory traces. Indeed, the activity the speech areas involved in phonological processing persisted throughout the whole interval under analysis - continuing to be active at the time when semantic processing may have started. This finding may be related to keeping the phonological pattern in short-term memory. Additionally, recurrent activation at the phonological level is very likely to be continued during semantic analysis, since higher levels of sensory analysis are known to recurrently communicate with lower levels as a principal of refining detection of complex features within the sensory signal (Bullier, 2001; Di Lollo, 2012) and is compatible with the hierarchical predictive coding model (Rao, Ballard, 1999).

Another explanation of articulatory loop function comes from Lieberman's motor theory of speech perception. According to it, perception of word-like sounds is based on replaying of corresponding articulatory movements that could produce similar sounds (Liberman &Mattingly, 1985; Venezia et al., 2016). Functional role of this motor-activation was described in a body of TMS studies conducted by D'Ausilio et al. (D'Ausilio, Bufalari, Salmas, & Fadiga, 2012; D'Ausilio et al., 2009). These studies reported that activation in articulatory motor regions helped to process noisy auditory inputs, which were difficult to perceive. The task used in the current study was rather difficult, since it required participants to distinguish between many novel pseudowords with similar phonemic structure. Thus, articulatory rehearsal might be essential for effective word processing in the current word-learning task.

5.5.3 Insula

Widespread insula activation should be emphasized. As long as insula is reported to be a multifunctional region essential for both low-level and high-level information processing, there are several explanations for intensive activation of this region in response to pseudowords associated with meaning.

Insula is often included into `salience network', the function of which is to identify the most relevant stimuli among multiple competing internal and external stimuli (Seeley et al., 2007). The body of available empirical studies suggests that one of the functions of the anterior insula is to integrate external sensory information with internal emotional and bodily state signals to coordinate brain network dynamics (Uddin, Nomi, Hйbert-Seropian, Ghaziri, & Boucher, 2017).

It is possible that insula plays crucial role for word memory traces and association formation. However, insula is also reported to be a part of an automatic path that deals with overlearned or routine activities such as repeating words (Augustine, 1996) and specifically activates during processing of learnt stimulus (Van Turennout, Ellmore, & Martin, 2000).

Recently, insula was supposed to be a functional hub for classical and non-classical language areas. Insula is reported to play a crucial role for both speech perception/production and semantic processes (Oh, Duerden, & Pang, 2014). Insula receives cortical projections from the auditory cortex, temporal pole, superior temporal cortex, and the temporal operculum. In addition, the insular cortex is known to have bidirectional connections with the inferior frontal gyrus (IFG) (Augustine, 1985).

Strong insular activation that we observed shows that insula is essential for word processing orchestration: it seems that insula accumulates and redirects sensory-motor information for successful word processing and learning.

5.5.4 Intraparietal sulcus

A number of studies have suggested a dissociation between semantic and phonological processing within regions of the IPS (e.g. Butterworth, 2002; Dehaene & Cohen, 1997; Holloway, Price, & Ansari, 2010). Posterior and anterior intraparietal regions are reported to be involved in generalizing information from gestures and auditory input during speech production (Piazza, Pinel, Le Bihan, & Dehaene, 2007). These behaviour may be explained by increased spatial attention, a process in which (intra)parietal regions are known to be also involved (Corbetta & Shulman, 2002). Similar conclusion was made by Majerus et al. (2006) during verbal (and non-verbal) STM tasks. This study also reported functionally connectivity between IPS and areas in the temporal lobe subtending phonological and orthographic processing. It is likely that depending on the type of information that needs to be maintained, the IPS will steer attentional resources towards the neural substrates that are specialized in the initial processing of the given type of information.

5.5.5 Spatiotemporal pattern

Judging by the cortical locations obtained, the network observed was formed to meet the requirements for successful task performance, specifically to provide for (1) effective discrimination between the pseudowords, (2) recollection of corresponding motor representations, and (3) initiation of an appropriate action. These functions correspond to general requirements for sufficient language processing - memory, unification and control (MUC model, according to Hagoort (2015).

The effect was observed in a rather wide set of brain regions. It should be noted that the second passive session was administered almost immediately after the learning sessions, while the whole experiment lasted less than two hours. Thus, even during the second passive session, the pseudowords were still rather novel to the brain in terms of lexical processing (Haier et al., 1992; Van Turennout et al., 2000). In other words, no long-lasting cortical plasticity (or `consolidation' in terms of Davis & Gaskell, 2009; Gaskell & Dumay, 2003) could have taken place, and lexical processing of newly learned pseudowords was not yet optimized, thus activating extensive cortical areas. Later in time, after a longer period of consolidation, the network engaged might become much smaller, and this prediction may be tested in future experiments.

Additionally, it should be noted that we observed initial activation of low-tier brain regions reported for phonological analyses and word-form concatenation. aSTS and insular activation was observed beginning from early time window (144-217 ms). This goes in concordance with hierarchical model of object recognition. At the end of time interval (about 300 ms) we observed spread of activation towards higher-tier speech zones reported for semantic analyzes, specifically, we observed triangular IFG and temporal pole regions. It should be stressed that activation within low-tier regions lasted during semantic interval. It spokes in favor of idea of iterative nature of semantic analyses via recursive addressing to phonological word form representation.



5.5.6 Multimodality

The other important aspect that should be discussed is that word-action pairing induced activation in structures reported as multimodal (Ghazanfar & Schroeder, 2006; Stein & Stanford, 2008).

Studies have shown that anterior and caudal regions of STS have multiple multimodal neuronal populations (Beauchamp, 2005; Bruce, Desimone, & Gross, 2017). Multimodality means that, for example, one and the same neuron can encode both sensorimotor representation (e.g. actions), and sounds associated with the same process/event. Multimodal neurons are actively discussed within cognitive studies dedicated to another area where sound-action association is essential - music learning (Zimmerman & Lahav, 2012). Notably, this block of research works also reported STS and Intraparietal regions. IPS regions are reported to respond to visual, auditory, somatosensory, and vestibular signals to create bimodal and trimodal receptive fields (Avillac, Denиve, Olivier, Pouget, & Duhamel, 2005; Bremmer, Klam, Duhamel, Ben Hamed, & Graf, 2002; Duhamel, Colby, & Goldberg, 1998). Importantly, Beauchamp (2005) found that 23% of neurons responsive to the sight of actions in STS are also responsive to the sounds of those actions. In the context of our experimental procedure it is notable, that Lahav, Saltzman, and Schlaug (2007) observed activation in the IPS during motionless listening to a rehearsed musical piece after learning. These studies implicate the IPS as a brain area involved in auditory memory circuitry - a crucial component for music and, likely, action-word associative learning.

The fact that pseudowords associated with consequent movement induced higher plasticity in auditory cortex comparing to distractors also speak in favor of multimodal learning/neural coding. Similarly, Pantev, Lappe, Herholz, and Trainor (2009) found that multimodal sensorimotor-auditory training in non-musicians resulted in greater plastic changes in auditory cortex than auditory training alone.



Conclusions

In the current study, we were the first implement a trial-and-error semantic word learning procedure, which was essentially similar to operant conditioning, and thus required active participation of the participants in the learning procedure. All participants were behaviorally successful on the task, reaching the accuracy level of 90% and higher. Thus, the “fast mapping” procedure of semantic learning was successful.

Repetitive pseudoword presentation produced strong repetition suppression, which was mostly localized to perisylvian areas, including insula, as well as to temporal and precentral areas. Such a strong repetition suppression was not common for previous EEG studies of word learning. We suppose that the active nature of the learning procedure could have contributed to such a strong repetition suppression effect. Repetition suppression can be understood as a result of formation of overlearnt phonological representations for both types of stimuli used - `words' and `distractors'.

Importantly, we used only novel pseudowords, and our experimental design did not involve presentation of any real words. Thus, the time course of familiarization effect for `words' and `distractors' was equalized and balanced.

Our primary goal was to assess the interaction between effects of stimulus repetition and semantic lexicalization Davis and Gaskell (2009). Thus, we analyzed the `double difference' - a measure of differential effects of repetition of the responses to `words' and `distractors'.

In the current study, we used a purely data-driven approach free of any a priori assumptions.

The analysis of the RMS global mean power produced a statistically significant time interval of approximately 150 - 360 ms after the disambiguation time point, for the left hemisphere only.

Source analysis revealed a widespread network of speech-related cortical areas in the left hemisphere.

The timing and localization of effects observed allow us to suppose that essentially two processes were involved in word learning:

(1) Forced formation of phonological representations (i.e. phoneme concatenation): low-tier speech-related areas, forming a phonological loop, were involved throughout the whole time period of analysis, starting from approximately 150 ms after the disambiguation point.

(2) Semantic acquisition (i.e. mapping of a phonological representation onto semantics): higher-tier speech-related areas were recruited around 300 ms after the disambiguation point and later.



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