Presentations

Abstract

When talking, speakers continuously monitor the auditory feedback of their own voice to control and inform speech production processes. When speakers are provided with auditory feedback that is perturbed in real time, most of them compensate for this by opposing the feedback perturbation. For example, when speakers hear themselves at a higher pitch than intended, they would compensate by lowering their pitch. However, sometimes speakers follow the perturbation instead (i.e., raising their pitch in response to higher-than-expected pitch). Current theoretical frameworks cannot account for following responses. In the current study, we performed two experiments to investigate whether the state of the speech production system at perturbation onset may determine what type of response (opposing or following) is given. Participants vocalized while the pitch in their auditory feedback was briefly (500 ms) perturbed in half of the vocalizations. None of the participants were aware of these manipulations. Subsequently, we analyzed the pitch contour of the participants’ vocalizations. The results suggest that whether a perturbation-related response is opposing or following unexpected feedback depends on ongoing fluctuations of the production system: It initially responds by doing the opposite of what it was doing. In addition, the results show that all speakers show both following and opposing responses, although the distribution of response types varies across individuals. Both the interaction with ongoing fluctuations and the non-trivial number of following responses suggest that current speech production models are inadequate. More generally, the current study indicates that looking beyond the average response can lead to a more complete view on the nature of feedback processing in motor control. Future work should explore whether the direction of feedback-based control in domains outside of speech production will also be conditional on the state of the motor system at the time of the perturbation.

Abstract

When talking, speakers continuously monitor and use the auditory feedback of their own voice to control and inform speech production processes. Auditory feedback processing has been studied using perturbed auditory feedback. When speakers are provided with auditory feedback that is perturbed in real time, most of them compensate for this by opposing the feedback perturbation. For example, when speakers hear themselves at a higher pitch than intended, they would compensate by lowering their pitch. However, sometimes speakers follow the perturbation instead (i.e., raising their pitch in response to higher-than-expected pitch). Although most past studies observe some following responses, current theoretical frameworks cannot account for following responses. In addition, recent experimental work has suggested that following responses may be more common than has been assumed to date.
In the current study, we performed two experiments (N = 39 and N = 24) to investigate whether the state of the speech production system at perturbation onset may determine what type of response (opposing or following) is given. Participants vocalized while they tried to match a target pitch level. Meanwhile, the pitch in their auditory feedback was briefly (500 ms) perturbed in half of the vocalizations, increasing or decreasing pitch by 25 cents. None of the participants were aware of these manipulations. Subsequently, we analyzed the pitch contour of the participants’ vocalizations.
The results suggest that whether a perturbation-related response is opposing or following unexpected feedback depends on ongoing fluctuations of the production system: It initially responds by doing the opposite of what it was doing. In addition, the results show that all speakers show both following and opposing responses, although the distribution of response types varies across individuals.
Both the interaction with ongoing fluctuations of the speech system and the non-trivial proportion of following responses suggest that current production models are inadequate: They need to account for why responses to unexpected sensory feedback depend on the production-system’s state at the time of perturbation. More generally, the current study indicates that looking beyond the average response can lead to a more complete view on the nature of feedback processing in motor control. Future work should explore whether the direction of feedback-based control in domains outside of speech production will also be conditional on the state of the motor system at the time of the perturbation.

Abstract

One of the most daunting tasks of a listener is to map a continuous auditory stream onto known speech sound categories and lexical items. A major issue with this mapping problem is the variability in the acoustic realizations of sound categories, both within and across speakers. Past research has suggested listeners may use various sources of information, such as lexical knowledge or visual cues (e.g., lip-reading) to recalibrate these speech categories to the current speaker. Previous studies have focused on audiovisual recalibration of consonant categories. The present study explores whether vowel categorization, which is known to show less sharply defined category boundaries, also benefit from visual cues.
Participants were exposed to videos of a speaker pronouncing one out of two vowels (Dutch vowels /e/ and /ø/), paired with audio that was ambiguous between the two vowels. The most ambiguous vowel token was determined on an individual basis by a categorization task at the beginning of the experiment. In one group of participants, this auditory token was paired with a video of an /e/ articulation, in the other group with an /ø/ video. After exposure to these videos, it was found in an audio-only categorization task that participants had adapted their categorization behavior as a function of the video exposure. The group that was exposed to /e/ videos showed a reduction of /ø/ classifications, suggesting they had recalibrated their vowel categories based on the available visual information. These results show that listeners indeed use visual information to recalibrate vowel categories, which is in line with previous work on audiovisual recalibration in consonant categories, and lexically-guided recalibration in both vowels and consonants.
In addition, a secondary aim of the current study was to explore individual variability in audiovisual recalibration. Phoneme categories vary not only in terms of boundary location, but also in terms of boundary sharpness, or how strictly categories are distinguished. The present study explores whether this sharpness is associated with the amount of audiovisual recalibration. The results tentatively support that a fuzzy boundary is associated with stronger recalibration, suggesting that listeners’ category sharpness may be related to the weight they assign to visual information in audiovisual speech perception. If listeners with fuzzy boundaries assign more weight to visual cues, given that vowel categories have less sharp boundaries than consonants, there ought to be audiovisual recalibration for vowels as well. This is exactly what was found in the current study.

Abstract

The classroom is designed to teach children cultural inventions for which the brain is not evolutionary designed. Hence the
classroom environment has to implement cultural reycling of neuronal maps. To do this effectively it has to recruit existing neural
infrastructure. Therefore, teaching programmes have to be tailored to the possibilities and limitations of available neural architecture.
An example in case is reading, a cultural invention of a few thousand years old. Orthographies and reading methods need
to use visual cortex areas in the most optimal way. I will discuss how the characteristics of different orthographies are tailored
to the possibilities of complex cells in visual cortex. In addition, different reading methods will be evaluated in the light of our
understanding of human brain organization. I will argue that a systematic investigation of culture-brain relations is much needed
for optimizing the optimal environment.

Abstract

Dyslexia is a learning disorder caused primarily by a phonological processing deficit. So far, few studies have examined whether dyslexia deficits extend to syntactic processing. We investigated how dyslexic children process syntactic structures. In a self-paced reading syntactic priming paradigm, the passive voice was repeated in mini-blocks of five sentences. These were mixed with an equal number of filler mini-blocks (actives, intransitives); the verb was repeated within all mini-blocks. The data of 20 dyslexic children (Mean(age)=12,8), native speakers of Brazilian Portuguese, were compared to that of 25 non-dyslexic children (Mean(age)=10,4 years). A repeated-measures ANOVA on reading times for the verb revealed a significant sentence repetition (p<.001) and group by sentence repetition effect (p<.001). Dyslexics demonstrated priming effects between all consecutive passive voice repetitions (all p<.05), whereas reading times for controls differed only between the first and second passive (p<.001). For active sentences, dyslexics showed priming effects only between the first and second sentences (p<.05) while controls did not show any significant effect, suggesting that the effects for passives are not solely due to the verb being repeated, but at least in part due to the repeated syntactic structure. These findings thus reveal syntactic processing differences between dyslexic and non-dyslexic children.

Abstract

In certain situations, human listeners have more difficulty in understanding speech in a multi-talker environment than in the presence of non-intelligible noise. The costs of speech-in-speech masking have been attributed to informational masking, i.e. to the competing processing of the target and the distractor speech’s information. It remains unclear what kind of information is competing, as intelligible speech and unintelligible speech-like signals (e.g. reversed, noise-vocoded, and foreign speech) differ both in linguistic content and in acoustic information. Thus, intelligible speech could be a stronger distractor than unintelligible speech because it presents closer acoustic information to the target speech, or because it carries competing linguistic information. In this study, we intended to isolate the linguistic component of speech-in-speech masking and we tested its influence on the comprehension of target speech. To do so, 24 participants performed a dichotic listening task in which the interfering stimuli consisted of 4-band noise-vocoded sentences that could become intelligible through training. The experiment included three steps: first, the participants were instructed to report the clear target speech from a mixture of one clear speech channel and one unintelligible noise-vocoded speech channel; second, they were trained on the interfering noise-vocoded sentences so that they became intelligible; third, they performed the dichotic listening task again. Crucially, before and after training, the distractor speech had the same acoustic features but not the same linguistic information. We thus predicted that the distracting noise-vocoded signal would interfere more with target speech comprehension after training than before training. To control for practice/fatigue effects, we used additional 2-band noise-vocoded sentences, which participants were not trained on, as interfering signals in the dichotic listening tasks. We expected that performance on these trials would not change after training, or would change less than that on trials with trained 4-band noise-vocoded sentences. Performance was measured under three SNR conditions: 0, -3, and -6 dB. The behavioral results are consistent with our predictions. The 4-band noise-vocoded signal interfered more with the comprehension of target speech after training (i.e. when it was intelligible) compared to before training (i.e. when it was unintelligible), but only at SNR -3dB. Crucially, the comprehension of the target speech did not change after training when the interfering signals consisted of unintelligible 2-band noise-vocoded speech sounds, ruling out a fatigue effect. In line with previous studies, the present results show that intelligible distractors interfere more with the processing of target speech. These findings further suggest that speech-in-speech interference originates, to a certain extent, from the parallel processing of competing linguistic content. A magnetoencephalography study with the same design is currently being performed, to specifically investigate the neural origins of informational masking.

Abstract

Integrating sentence meaning over time requires memory ranging from milliseconds (words) to seconds (sentences) and minutes (discourse). How do transient events like action potentials in the human language system support memory at these different temporal scales? Here we investigate the nature of processing memory in a neurobiologically motivated model of sentence comprehension. The model was a recurrent, sparsely connected network of spiking neurons. Synaptic weights were created randomly and there was no adaptation or learning. As input the network received word sequences generated from construction grammar templates and their syntactic alternations (e.g., active/passive transitives, transfer datives, caused motion). The language environment had various features such as tense, aspect, noun/verb number agreement, and pronouns which created positional variation in the input. Similar to natural speech, word durations varied between 50ms and 0.5s of real, physical time depending on their length. The model's task was to incrementally interpret these word sequences in terms of semantic roles. There were 8 target roles (e.g., Agent, Patient, Recipient) and the language generated roughly 1,2m distinct utterances from which a sequence of 10,000 words was randomly selected and filtered through the network. A set of readout neurons was then calibrated by means of logistic regression to decode the internal network dynamics onto the target semantic roles. In order to accomplish the role assignment task, network states had to encode and maintain past information from multiple cues that could occur several words apart. To probe the circuit's memory capacity, we compared models where network connectivity, the shape of synaptic currents, and properties of neuronal adaptation were systematically manipulated. We found that task-relevant memory could be derived from a mechanism of neuronal spike-rate adaptation, modelled as a conductance that hyperpolarized the membrane following a spike and relaxed to baseline exponentially with a fixed time-constant. By acting directly on the membrane potential it provided processing memory that allowed the system to successfully interpret its sentence input. Near optimal performance was also observed when an exponential decay model of post-synaptic currents was added into the circuit, with time-constants approximating excitatory NMDA and inhibitory GABA-B receptor dynamics. Thus, the information flow was extended over time, creating memory characteristics comparable to spike-rate adaptation. Recurrent connectivity, in contrast, only played a limited role in maintaining information; an acyclic version of the recurrent circuit achieved similar accuracy. This indicates that random recurrent connectivity at the modelled spatial scale did not contribute additional processing memory to the task. Taken together, these results suggest that memory for language might be provided by activity-silent dynamic processes rather than the active replay of past input as in storage-and-retrieval models of working memory. Furthermore, memory in biological networks can take multiple forms on a continuum of time-scales. Therefore, the development of neurobiologically realistic, causal models will be critical for our understanding of the role of memory in language processing.

Abstract

Institute of Adaptive and Neural Computation, School of Informatics, University of Edinburgh, UK

Abstract

An important aspect of L2 speech learning is the interaction between speech production and perception. One way to study this interaction is to provide speakers with altered auditory feedback to investigate how unexpected auditory feedback affects subsequent speech production. Although it is generally well established that speakers on average compensate for auditory feedback perturbations, even when unaware of the manipulation, the neural correlates of responses to perturbed auditory feedback are not well understood. In the present study, we provided speakers with auditory feedback that was intermittently pitch-shifted, while we measured the speaker’s neural activity using magneto-encephalography (MEG). Participants were instructed to vocalize the Dutch vowel /e/ while they tried to match the pitch of a short tone. During vocalization, participants received auditory feedback through headphones. In half of the trials, the pitch in the feedback signal was shifted by -25 cents, starting at a jittered delay after speech onset and lasting for 500ms. Trials with perturbed feedback and control trials (with normal feedback) were in random order. Post-experiment questionnaires showed that none of the participants was aware of the pitch manipulation. Behaviorally, the results show that participants on average compensated for the auditory feedback by shifting the pitch of their speech in the opposite (upward) direction. This suggests that even though participants were not aware of the pitch shift, they automatically compensate for the unexpected feedback signal. The MEG results show a right-lateralized response to both onset and offset of the pitch perturbation during speaking. We suggest this response relates to detection of the mismatch between the predicted and perceived feedback signals, which could subsequently drive behavioral adjustments. These results are in line with recent models of speech motor control and provide further insights into the neural correlates of speech production and speech feedback processing.

Abstract

Speech production is one of the most complex motor skills, and involves close interaction between perceptual and motor systems. One way to investigate this interaction is to provide speakers with manipulated auditory feedback during speech production. Using this paradigm, investigators have started to identify a neural network that underlies auditory feedback processing and monitoring during speech production. However, to date, still little is known about the neural mechanisms that underlie feedback processing. The present study set out to shed more light on the neural correlates of processing auditory feedback. Participants (N = 39) were seated in an MEG scanner and were asked to vocalize the vowel /e/continuously throughout each trial (of 4 s) while trying to match a pre-specified pitch target of 4, 8 or 11 semitones above the participants’ baseline pitch level. They received auditory feedback through ear plugs. In half of the trials, the pitch in the auditory feedback was unexpectedly manipulated (raised by 25 cents) for 500 ms, starting between 500ms and 1500ms after speech onset. In the other trials, feedback was normal throughout the trial. In a second block of trials, participants listened passively to recordings of the auditory feedback they received during vocalization in the first block. Even though none of the participants reported being aware of any feedback perturbations, behavioral responses showed that participants on average compensated for the feedback perturbation by decreasing the pitch in their vocalizations, starting at about 100ms after perturbation onset until about 100 ms after perturbation offset. MEG data was analyzed, time-locked to the onset of the feedback perturbation in the perturbation trials, and to matched time-points in the control trials. A cluster-based permutation test showed that the event-related field responses differed between the perturbation and the control condition. This difference was mainly driven by an ERF response peaking at about 100ms after perturbation onset and a larger response after perturbation offset. Both these were localized to sensorimotor cortices, with the effect being larger in the right hemisphere. These results are in line with previous reports of right-lateralized pitch processing. In the passive listening condition, we found no differences between the perturbation and the control trials. This suggests that the ERF responses were not merely driven by the pitch change in the auditory input and hence instead reflect speech production processes. We suggest the observed ERF responses in sensorimotor cortex are an index of the mismatch between the self-generated forward model prediction of auditory input and the incoming auditory signal.

Abstract

Speech production is one of the most complex motor skills, and involves close interaction between perceptual and motor systems. One way to investigate this interaction is to provide speakers with manipulated auditory feedback during speech production. Using this paradigm, investigators have started to identify a neural network that underlies auditory feedback processing and monitoring during speech production. However, to date, still little is known about the neural mechanisms that underlie feedback processing. The present study set out to shed more light on the neural correlates of processing auditory feedback. Participants (N = 39) were seated in an MEG scanner and were asked to vocalize the vowel /e/continuously throughout each trial (of 4 s) while trying to match a pre-specified pitch target of 4, 8 or 11 semitones above the participants’ baseline pitch level. They received auditory feedback through ear plugs. In half of the trials, the pitch in the auditory feedback was unexpectedly manipulated (raised by 25 cents) for 500 ms, starting between 500ms and 1500ms after speech onset. In the other trials, feedback was normal throughout the trial. In a second block of trials, participants listened passively to recordings of the auditory feedback they received during vocalization in the first block. Even though none of the participants reported being aware of any feedback perturbations, behavioral responses showed that participants on average compensated for the feedback perturbation by decreasing the pitch in their vocalizations, starting at about 100ms after perturbation onset until about 100 ms after perturbation offset. MEG data was analyzed, time-locked to the onset of the feedback perturbation in the perturbation trials, and to matched time-points in the control trials. A cluster-based permutation test showed that the event-related field responses differed between the perturbation and the control condition. This difference was mainly driven by an ERF response peaking at about 100ms after perturbation onset and a larger response after perturbation offset. Both these were localized to sensorimotor cortices, with the effect being larger in the right hemisphere. These results are in line with previous reports of right-lateralized pitch processing. In the passive listening condition, we found no differences between the perturbation and the control trials. This suggests that the ERF responses were not merely driven by the pitch change in the auditory input and hence instead reflect speech production processes. We suggest the observed ERF responses in sensorimotor cortex are an index of the mismatch between the self-generated forward model prediction of auditory input and the incoming auditory signal.

Abstract

Speakers and listeners do more than exchanging propositional content. They try to get things done with their utterances. For speakers this requires planning of utterances with knowledge about the listener in mind, whereas listeners need to make inferences that go beyond simulating sensorimotor aspects of propositional content. For example, the statement "It is hot in here" will usually not be answered with a statement of the kind "Yes, indeed it is 32 degrees Celsius", but rather with the answer "I will open the window", since the listener infers the speaker's intention behind her statement. I will discuss a series of studies that identify the network of brain regions involved in audience design and inferring speaker meaning. Likewise for indirect replies that require conversational implicatures, as in A: "Did you like my talk?" to which B replies: "It is hard to give a good presentation." I will show that in these cases the core language network needs to be extended with brain systems providing the necessary inferential machinery

Abstract

Adapting your grammatical preferences to match that of your interlocutor, a phenomenon known as structural priming, can be influenced by the social opinion you have of your interlocutor. However, the direction and reliability of this effect is unclear as different studies have reported seemingly contrary results. When investigating something as abstract as social opinion, there are numerous differences between the studies that could be causing the differing results. We have operationalized social opinion as the ratings of favorability for a wide range of different avatars in a virtual reality study. This way we can accurately determine how the strength of the structural priming effect changes with differing social opinions. . Our results show an inverted U-shaped curve in passive structure repetition as a function of favorability: the participants showed the largest priming effects for the avatar with average favorability ratings, with a decrease when interacting with the least- or most-favorable avatars. This result suggests that the relationship between social opinion and priming magnitude may not be a linear one, contrary to what the literature has been assuming. Instead there is 'happy medium' which evokes the highest priming effect and on either side of this ideal is a decrease in priming

Abstract

Syntactic priming, the phenomenon in which participants adopt the linguistic behaviour of their partner, is widely used in psycholinguistics to investigate syntactic operations. Although the phenomenon of syntactic priming is well documented, the memory system that supports the retention of this syntactic information long enough to influence future utterances, is not as widely investigated. We aim to shed light on this issue by assessing 17 patients with Korsakoff?s amnesia on an active-passive syntactic priming task and compare their performance to controls matched in age, education and premorbid intelligence. Patients with Korsakoff's amnesia display deficits in all subdomains of declarative memory, yet their implicit learning remains intact, making them an ideal patient group to use in this study. In line with the hypothesis that syntactic priming relies on procedural memory, the patient group showed strong priming tendencies (12.6% passive structure repetition). Our control group didn't show a priming tendency, presumably due to cognitive interference between declarative and non-declarative memory systems. To verify the absence of the effect in the controls, we ran an independent group of 54 participants on the same paradigm that also showed no priming effect. The results are further discussed in relation to amnesia, aging and compensatory mechanisms

Abstract

Syntactic priming, the phenomenon in which participants adopt the linguistic behaviour of their partner, is widely used in psycholinguistics to investigate syntactic operations. Although the phenomenon of syntactic priming is well documented, the memory system that supports the retention of this syntactic information long enough to influence future utterances, is not as widely investigated. We aim to shed light on this issue by assessing 17 patients with Korsakoff’s amnesia on an active-passive syntactic priming task and compare their performance to controls matched in age, education and premorbid intelligence. Patients with Korsakoff's amnesia display deficits in all subdomains of declarative memory, yet their implicit learning remains intact, making them an ideal patient group to use in this study. We used the traffic-light design for the syntactic priming task: the actors in the prime trial photos were colour-coded and the participants were instructed to name the 'green' actor before the 'red' actor in the picture. This way we can control which syntactic structure the participant uses to describe the photo. For target trials, the photos were grey-scale so there was no bias towards one structure over another. This set-up allows us to ensure the primes are properly encoded. In addition to the priming task, we also measured declarative memory, implicit learning ability, and verbal IQ from all participants. Memory tests supported the claim that our 17 patients did have a severely impaired declarative memory system, yet a functional implicit/procedural one. The control group showed no deficit in any of the control measurements. In line with the hypothesis that syntactic priming relies on procedural memory, the patient group showed strong priming tendencies (12.6% passive structure repetition). Unexpectedly, our healthy control group did not show a priming tendency. In order to verify the absence of a syntactic priming effect in the healthy controls, we ran an independent group of 54 participants with the exact same paradigm. The results replicated the earlier findings such that there was no priming effect compared to baseline. This lack of priming ability in the healthy older population could be due to cognitive interference between declarative and non-declarative memory systems, which increases as we get older (mean age of the control group is 62 years).

Abstract

Research into the interaction between attention and language has mainly focused on how language
influences attention. But how does attention influence language
?
Considering we are constantly
bombarded with attention grabbing stimuli unrelated to the conversation we are conducting, this is
certainly an interesting topic of investigation. In this study we aim to uncover how limiting attentional
resources influences
language behaviour. We focus on syntactic priming: a task which captures how
participants adapt their syntactic choices to their partner. Participants simultaneously conducted a
motion
-
object tracking (MOT) task, a task commonly used to tax attentional re
sources. We thus
measured participants
’
ability to process syntax while their attention is not
-
, slightly
-
, or overly
-
taxed.
We observed an inverted U
-
shaped curve on priming magnitude when conducting the MOT task
concurrently with prime sentences, but no
effect when conducted with target sentences. Our results
illustrate how, during the prime phase of the syntactic priming task, attention differentially affects
syntactic processing whereas during the target phase there is no effect of attention on language
behaviour. We explain these results in terms of the implicit learning necessary to prime and how
different levels of attention taxation can either impair or enhance the way language is encoded

Abstract

Speech segmentation requires flexible mechanisms to remain robust to features such as speech rate and pronunciation. Recent hypotheses suggest that low-frequency neural oscillations entrain to ongoing syllabic and phrasal rates, and that neural entrainment provides a speech-rate invariant means to discretize linguistic tokens from the acoustic signal. How this mechanism functionally operates remains unclear. Here, we test the hypothesis that neural entrainment reflects temporal predictive mechanisms. It implies that neural entrainment is built on the dynamics of past speech information: the brain would internalize the rhythm of preceding speech to parse the ongoing acoustic signal at optimal time points. A direct prediction is that ongoing neural oscillatory activity should match the rate of preceding speech even if the stimulation changes, for instance when the speech rate suddenly increases or decreases. Crucially, the persistence of neural entrainment to past speech rate should modulate speech perception. We performed an MEG experiment in which native Dutch speakers listened to sentences with varying speech rates. The beginning of the sentence (carrier window) was either presented at a fast or a slow speech rate, while the last three words (target window) were displayed at an intermediate rate across trials. Participants had to report the perception of the last word of the sentence, which was ambiguous with regards to its vowel duration (short vowel /ɑ/ – long vowel /aː/ contrast). MEG data was analyzed in source space using beamformer methods. Consistent with previous behavioral reports, the perception of the ambiguous target word was influenced by the past speech rate; participants reported more /aː/ percepts after a fast speech rate, and more /ɑ/ after a slow speech rate. During the carrier window, neural oscillations efficiently tracked the dynamics of the speech envelope. During the target window, we observed oscillatory activity that corresponded in frequency to the preceding speech rate. Traces of neural entrainment to the past speech rate were significantly observed in medial prefrontal areas. Right superior temporal cortex also showed persisting oscillatory activity which correlated with the observed perceptual biases: participants whose perception was more influenced by the manipulation in speech rate also showed stronger remaining neural oscillatory patterns. The results show that neural entrainment lasts after rhythmic stimulation. The findings further provide empirical support for oscillatory models of speech processing, suggesting that neural oscillations actively encode temporal predictions for speech comprehension.

Abstract

The kiki-bouba effect, where people map round shapes onto round sounds (such as [b] and [o]) and spiky shapes onto “spiky” sounds (such as [i] and [k]), is the most famous example of sound symbolism. Many behavioural variations have been reported since Köhler’s (1929) original experiments. These studies examine orthography (Cuskley, Simner, & Kirby, 2015), literacy (Bremner et al., 2013), and developmental disorders (Drijvers, Zaadnoordijk, & Dingemanse, 2015; Occelli, Esposito, Venuti, Arduino, & Zampini, 2013). Some studies have suggested that the cross-modal associations between linguistic sound and physical form in the kiki-bouba effect are quasi-synaesthetic (Maurer, Pathman, & Mondloch, 2006; Ramachandran & Hubbard, 2001). However, there is a surprising lack of neuroimaging data in the literature that explain how these cross-modal associations occur (with the exceptions of Kovic et al. (2010)and Asano et al. (2015)). We presented 24 participants with randomly generated spiky or round figures and 16 synthesised, reduplicated CVCV (vowels: [i] and [o], consonants: [f], [v], [t], [d], [s], [z], [k], and [g]) nonwords based on Cuskley et al. (2015). This resulted in 16 nonwords across four conditions: full match, vowel match, consonant match, and full mismatch. Participants were asked to rate on a scale of 1 to 7 how well the nonword fit the shape it was presented with. EEG was recorded throughout, with epochs timelocked to the auditory onset of the nonword. There were significant behavioural effects of condition (p<0.0001). Bonferroni t-tests show participants rated full match more highly than full mismatch nonwords. However, there was no reflection of this behavioural effect in the ERP waveforms. One possible reason for the absence of an ERP effect is that this effect may jitter over a broad latency range. Currently oscillatory effects are being analysed, since these are less dependent on precise time-locking to the triggering events.