Brain responses and looking behavior during audiovisual speech integration in infants predict auditory speech comprehension in the second year of life

The use of visual cues during the processing of audiovisual (AV) speech is known to be less efficient in children and adults with language difficulties and difficulties are known to be more prevalent in children from low-income populations. In the present study, we followed an economically diverse group of thirty-seven infants longitudinally from 6–9 months to 14–16 months of age. We used eye-tracking to examine whether individual differences in visual attention during AV processing of speech in 6–9 month old infants, particularly when processing congruent and incongruent auditory and visual speech cues, might be indicative of their later language development. Twenty-two of these 6–9 month old infants also participated in an event-related potential (ERP) AV task within the same experimental session. Language development was then followed-up at the age of 14–16 months, using two measures of language development, the Preschool Language Scale and the Oxford Communicative Development Inventory. The results show that those infants who were less efficient in auditory speech processing at the age of 6–9 months had lower receptive language scores at 14–16 months. A correlational analysis revealed that the pattern of face scanning and ERP responses to audiovisually incongruent stimuli at 6–9 months were both significantly associated with language development at 14–16 months. These findings add to the understanding of individual differences in neural signatures of AV processing and associated looking behavior in infants.

Brain responses to audiovisual speech mismatch in infants are associated with individual differences in looking behaviour

Research on audiovisual speech integration has reported high levels of individual variability, especially among young infants. In the present study we tested the hypothesis that this variability results from individual differences in the maturation of audiovisual speech processing during infancy. A developmental shift in selective attention to audiovisual speech has been demonstrated between 6 and 9 months with an increase in the time spent looking to articulating mouths as compared to eyes (Lewkowicz & Hansen-Tift. (2012) Proc. Natl Acad. Sci. USA, 109, 1431–1436; Tomalski et al. (2012) Eur. J. Dev. Psychol., 1–14). In the present study we tested whether these changes in behavioural maturational level are associated with differences in brain responses to audiovisual speech across this age range. We measured high-density event-related potentials (ERPs) in response to videos of audiovisually matching and mismatched syllables /ba/ and /ga/, and subsequently examined visual scanning of the same stimuli with eye-tracking. There were no clear age-specific changes in ERPs, but the amplitude of audiovisual mismatch response (AVMMR) to the combination of visual /ba/ and auditory /ga/ was strongly negatively associated with looking time to the mouth in the same condition. These results have significant implications for our understanding of individual differences in neural signatures of audiovisual speech processing in infants, suggesting that they are not strictly related to chronological age but instead associated with the maturation of looking behaviour, and develop at individual rates in the second half of the first year of life.

Spiking neural network connectivity and its potential for temporal sensory processing and variable binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well-understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modeling of neural circuits found in the brain.

Spiking Neural Network Connectivity and its Potential for Temporal Sensory Processing and Variable Binding

The most biologically-inspired artificial neurons are those of the third generation, and are termed spiking neurons, as individual pulses or spikes are the means by which stimuli are communicated. In essence, a spike is a short-term change in electrical potential and is the basis of communication between biological neurons. Unlike previous generations of artificial neurons, spiking neurons operate in the temporal domain, and exploit time as a resource in their computation. In 1952, Alan Lloyd Hodgkin and Andrew Huxley produced the first model of a spiking neuron; their model describes the complex electro-chemical process that enables spikes to propagate through, and hence be communicated by, spiking neurons. Since this time, improvements in experimental procedures in neurobiology, particularly with in vivo experiments, have provided an increasingly more complex understanding of biological neurons. For example, it is now well understood that the propagation of spikes between neurons requires neurotransmitter, which is typically of limited supply. When the supply is exhausted neurons become unresponsive. The morphology of neurons, number of receptor sites, amongst many other factors, means that neurons consume the supply of neurotransmitter at different rates. This in turn produces variations over time in the responsiveness of neurons, yielding various computational capabilities. Such improvements in the understanding of the biological neuron have culminated in a wide range of different neuron models, ranging from the computationally efficient to the biologically realistic. These models enable the modelling of neural circuits found in the brain. In recent years, much of the focus in neuron modelling has moved to the study of the connectivity of spiking neural networks. Spiking neural networks provide a vehicle to understand from a computational perspective, aspects of the brain’s neural circuitry. This understanding can then be used to tackle some of the historically intractable issues with artificial neurons, such as scalability and lack of variable binding. Current knowledge of feed-forward, lateral, and recurrent connectivity of spiking neurons, and the interplay between excitatory and inhibitory neurons is beginning to shed light on these issues, by improved understanding of the temporal processing capabilities and synchronous behaviour of biological neurons. This research topic aims to amalgamate current research aimed at tackling these phenomena.

More than just a problem with faces: Altered body perception in a group of congenital prosopagnosics

It has been estimated that one out of forty people in the general population suffer from congenital prosopagnosia (CP), a neurodevelopmental disorder characterized by difficulty identifying people by their faces. CP involves impairment in recognising faces, although the perception of non-face stimuli may also be impaired. Given that social interaction does not only depend on face processing, but also the processing of bodies, it is of theoretical importance to ascertain whether CP is also characterised by body perception impairments. Here, we tested eleven CPs and eleven matched control participants on the Body Identity Recognition Task (BIRT), a forced-choice match-to-sample task, using stimuli that require processing of body, not clothing, specific features. Results indicated that the group of CPs was as accurate as controls on the BIRT, which is in line with the lack of body perception complaints by CPs. However the CPs were slower than controls, and when accuracy and response times were combined into inverse efficiency scores (IES), the group of CPs were impaired, suggesting that the CPs could be using more effortful cognitive mechanisms to be as accurate as controls. In conclusion, our findings demonstrate CP may not generally be limited to face processing difficulties, but may also extend to body perception

Observed bodies generate object-based spatial codes

Contemporary studies of spatial and social cognition frequently use human figures as stimuli. The interpretation of such studies may be complicated by spatial compatibility effects that emerge when researchers employ spatial responses, and participants spontaneously code spatial relationships about an observed body. Yet, the nature of these spatial codes – whether they are location- or object-based, and coded from the perspective of the observer or the figure – has not been determined. Here, we investigated this issue by exploring spatial compatibility effects arising for objects held by a visually presented whole-bodied schematic human figure. In three experiments, participants responded to the colour of the object held in the figure’s left or right hand, using left or right key presses. Left-right compatibility effects were found relative to the participant’s egocentric perspective, rather than the figure’s. These effects occurred even when the figure was rotated by 90 degrees to the left or to the right, and the coloured objects were aligned with the participant’s midline. These findings are consistent with spontaneous spatial coding from the participant’s perspective and relative to the normal upright orientation of the body. This evidence for object-based spatial coding implies that the domain general cognitive mechanisms that result in spatial compatibility effects may contribute to certain spatial perspective-taking and social cognition phenomena.