Biology subjects

McGettigan, C.

Publications and source records attributed to McGettigan, C..

4 recordsLinked to original sources

bioRxiv2026

Decoding the ''bouba-kiki'' effect in early visual cortex

The "bouba-kiki" effect, or sound symbolism, is the non-arbitrary mapping between speech sounds and visual shapes, in which words like "bouba" are consistently associated with round shapes, and "kiki" with spiky shapes. Despite robust behavioral evidence for sound symbolic associations, it is still unclear whether they are a linguistic epiphenomenon or manifest themselves as distinct sensory representations in the human brain. Using fMRI and multivariate pattern analyses, we show that, in the absence of visual input, round and spiky sound symbolic words elicit distinct neural representations, not only in auditory and speech processing regions, but also in parietal and even early visual cortex including V1. These neural representations correlate with behavioural shape judgements of sound-symbolic words, as revealed by representational similarity analyses. Our findings suggest a potential functional mechanism for sound symbolism: phonological features of sound symbolic words are represented in auditory and speech processing regions and linked to cross-modal shape representations in parietal and early visual regions, which in turn lead to sound symbolic perceptual judgements. Thus, our results provide evidence for a neural mechanism underlying the "bouba-kiki" effect in the human brain.

neuroscience↗

bioRxiv2020

FFA and OFA encode distinct types of face identity information

Faces of different people elicit distinct functional MRI (fMRI) patterns in several face-selective brain regions. Here we used representational similarity analysis to investigate what type of identity-distinguishing information is encoded in three face-selective regions: fusiform face area (FFA), occipital face area (OFA), and posterior superior temporal sulcus (pSTS). We used fMRI to measure brain activity patterns elicited by naturalistic videos of famous face identities, and compared their representational distances in each region with models of the differences between identities. Models included low-level to high-level image-computable properties and complex human-rated properties. We found that the FFA representation reflected perceived face similarity, social traits, and gender, and was well accounted for by the OpenFace model (deep neural network, trained to cluster faces by identity). The OFA encoded low-level image-based properties (pixel-wise and Gabor-jet dissimilarities). Our results suggest that, although FFA and OFA can both discriminate between identities, the FFA representation is further removed from the image, encoding higher-level perceptual and social face information.

neuroscience↗

bioRxiv2018

Faces and voices in the brain: a modality-general person-identity representation in superior temporal sulcus

Face-selective and voice-selective brain regions have been shown to represent face-identity and voice-identity, respectively. Here we investigated whether there are modality-general person-identity representations in the brain that can be driven by either a face or a voice, and that invariantly represent naturalistically varying face and voice tokens of the same identity. According to two distinct models, such representations could exist either in multimodal brain regions (Campanella and Belin, 2007) or in face-selective brain regions via direct coupling between face- and voice-selective regions (von Kriegstein et al., 2005). To test the predictions of these two models, we used fMRI to measure brain activity patterns elicited by the faces and voices of familiar people in multimodal, face-selective and voice-selective brain regions. We used representational similarity analysis (RSA) to compare the representational geometries of face- and voice-elicited person-identities, and to investigate the degree to which pattern discriminants for pairs of identities generalise from one modality to the other. We found no matching geometries for faces and voices in any brain regions. However, we showed crossmodal generalisation of the pattern discriminants in the multimodal right posterior superior temporal sulcus (rpSTS), suggesting a modality-general person-identity representation in this region. Importantly, the rpSTS showed invariant representations of face- and voice-identities, in that discriminants were trained and tested on independent face videos (different viewpoint, lighting, background) and voice recordings (different vocalizations). Our findings support the Multimodal Processing Model, which proposes that face and voice information is integrated in multimodal brain regions.\n\nSignificance statementIt is possible to identify a familiar person either by looking at their face or by listening to their voice. Using fMRI and representational similarity analysis (RSA) we show that the right posterior superior sulcus (rpSTS), a multimodal brain region that responds to both faces and voices, contains representations that can distinguish between familiar people independently of whether we are looking at their face or listening to their voice. Crucially, these representations generalised across different particular face videos and voice recordings. Our findings suggest that identity information from visual and auditory processing systems is combined and integrated in the multimodal rpSTS region.

neuroscience↗

bioRxiv2017

Distinct neural systems for the production of communicative vocal behaviors

Vocalizations are the production of sounds by the coordinated activity of up to eighty respiratory and laryngeal muscles. Whilst voiced acts, modified by the upper vocal tract (tongue, jaw, lip and palate) are central to the production of human speech, they are also central to the production of emotional vocalizations such as sounds of disgust, anger, laughter and crying. Evidence suggests that the speech and emotional vocalizations may comprise distinct classes of vocal movements: patients with speech production deficits are often able to produce emotional vocalizations. In addition to this, the ontogeny of the two articulations is largely distinct, with some culturally universal emotional vocalizations emerging soon after birth and human speech being a culture specific, highly learnt motor act, which must develop to some degree before a critical period in development. Here we investigate the motor pathways underlying these two classes of vocal movements for the first time by directly comparing BOLD responses during production of speech and non-speech vocal movements. Using functional magnetic resonance imaging, we report distinct patterns of activity in both subcortical and cortical regions (putamen and bilateral inferior frontal and parietal cortices) during the production of emotional vocalizations compared to speech production. In contrast we show that responses in primary sensorimotor regions do not differ during the production of speech and emotional vocalizations, suggesting partially overlapping, and partially non-overlapping neural structures for the motor control of these two classes of movement. In addition to this we report that responses in auditory cortices are distinct during the production of speech and non-speech vocalizations, suggesting that feedback control of speech and emotional vocalizations are distinct. These data provide novel evidence for the presence of dual pathways for the neural control of complex articulatory movements in humans. These findings are discussed in relation to the clinical and primate literature of vocal motor control.\n\nSignificance StatementThis work marks the first evidence in healthy humans for dual routes to vocal behaviors. Clinical evidence suggests that patients unable to produce speech may still be able to produce other vocal behaviors that employ the same set of effectors. Here we demonstrate that the production of different classes of vocal behavior is associated with overlapping and distinct networks of activity. Moreover, we show that auditory processing that occurs during the production of these movements may be distinct, suggesting that feedback may be used differently for these distinct classes of vocal movement.

neuroscience↗