A neural marker of rapid discrimination of facial expression in 3.5- and 7-month-old infants

Rhythmic visual stimulation as a window into early brain development: A systematic review

Rhythmic visual stimulation (RVS), the periodic presentation of visual stimuli to elicit a rhythmic brain response, is increasingly applied to reveal insights into early neurocognitive development. Our systematic review identified 69 studies applying RVS in 0- to 6-year-olds. RVS has long been used to study the development of the visual system and applications have more recently been expanded to uncover higher cognitive functions in the developing brain, including overt and covert attention, face and object perception, numeral cognition, and predictive processing. These insights are owed to the unique benefits of RVS, such as the targeted frequency and stimulus-specific neural responses, as well as a remarkable signal-to-noise ratio. Yet, neural mechanisms underlying the RVS response are still poorly understood. We discuss critical challenges and avenues for future research, and the unique potentials the method holds. With this review, we provide a resource for researchers interested in the breadth of developmental RVS research and hope to inspire the future use of this cutting-edge method in developmental cognitive neuroscience.

Automatic Brain Categorization of Discrete Auditory Emotion Expressions

Seamlessly extracting emotional information from voices is crucial for efficient interpersonal communication. However, it remains unclear how the brain categorizes vocal expressions of emotion beyond the processing of their acoustic features. In our study, we developed a new approach combining electroencephalographic recordings (EEG) in humans with a frequency-tagging paradigm to 'tag' automatic neural responses to specific categories of emotion expressions. Participants were presented with a periodic stream of heterogeneous non-verbal emotional vocalizations belonging to five emotion categories: anger, disgust, fear, happiness and sadness at 2.5 Hz (stimuli length of 350 ms with a 50 ms silent gap between stimuli). Importantly, unknown to the participant, a specific emotion category appeared at a target presentation rate of 0.83 Hz that would elicit an additional response in the EEG spectrum only if the brain discriminates the target emotion category from other emotion categories and generalizes across heterogeneous exemplars of the target emotion category. Stimuli were matched across emotion categories for harmonicity-to-noise ratio, spectral center of gravity and pitch. Additionally, participants were presented with a scrambled version of the stimuli with identical spectral content and periodicity but disrupted intelligibility. Both types of sequences had comparable envelopes and early auditory peripheral processing computed via the simulation of the cochlear response. We observed that in addition to the responses at the general presentation frequency (2.5 Hz) in both intact and scrambled sequences, a greater peak in the EEG spectrum at the target emotion presentation rate (0.83 Hz) and its harmonics emerged in the intact sequence in comparison to the scrambled sequence. The greater response at the target frequency in the intact sequence, together with our stimuli matching procedure, suggest that the categorical brain response elicited by a specific emotion is at least partially independent from the low-level acoustic features of the sounds. Moreover, responses at the fearful and happy vocalizations presentation rates elicited different topographies and different temporal dynamics, suggesting that different discrete emotions are represented differently in the brain. Our paradigm revealed the brain's ability to automatically categorize non-verbal vocal emotion expressions objectively (at a predefined frequency of interest), behavior-free, rapidly (in few minutes of recording time) and robustly (with a high signal-to-noise ratio), making it a useful tool to study vocal emotion processing and auditory categorization in general and in populations where behavioral assessments are more challenging.

Frequency tagging with infants: The visual oddball paradigm

Combining frequency tagging with electroencephalography (EEG) provides excellent opportunities for developmental research and is increasingly employed as a powerful tool in cognitive neuroscience within the last decade. In particular, the visual oddball paradigm has been employed to elucidate face and object categorization and intermodal influences on visual perception. Still, EEG research with infants poses special challenges that require consideration and adaptations of analyses. These challenges include limits to attentional capacity, variation in looking times, and presence of artefacts in the EEG signal. Moreover, potential differences between age-groups must be carefully evaluated. This manuscript evaluates challenges theoretically and empirically by (1) a systematic review of frequency tagging studies employing the oddball paradigm and (2) combining and re-analyzing data from seven-month-old infants (N = 124, 59 females) collected in a categorization task with artifical, unfamiliar stimuli. Specifically, different criteria for sequence retention and selection of harmonics, the influence of bins considered for baseline correction and the relation between fast periodic visual stimulation (FPVS) responses and looking time are analyzed. Overall, evidence indicates that analysis decisions should be tailored based on age-group to optimally capture the observed signal. Recommendations for infant frequency tagging studies are developed to aid researchers in selecting appropriate stimulation and analysis strategies in future work.