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Introduction: Habituation and novelty detection are two fundamental and widely studied neurocognitive processes. Whilst neural responses to repetitive and novel sensory input have been well-documented across a range of neuroimaging modalities, it is not yet fully understood how well these different modalities are able to describe consistent neural response patterns. This is particularly true for infants and young children, as different assessment modalities might show differential sensitivity to underlying neural processes across age. Thus far, many neurodevelopmental studies are limited in either sample size, longitudinal scope or breadth of measures employed, impeding investigations of how well common developmental trends can be captured via different methods.
Method: This study assessed habituation and novelty detection in N = 204 infants using EEG and fNIRS measured in two separate paradigms, but within the same study visit, at 1, 5 and 18 months of age in an infant cohort in rural Gambia. EEG was acquired during an auditory oddball paradigm during which infants were presented with Frequent, Infrequent and Trial Unique sounds. In the fNIRS paradigm, infants were familiarised to a sentence of infant-directed speech, novelty detection was assessed via a change in speaker. Indices for habituation and novelty detection were extracted for both EEG and NIRS RESULTS: We found evidence for weak to medium positive correlations between responses on the fNIRS and the EEG paradigms for indices of both habituation and novelty detection at most age points. Habituation indices correlated across modalities at 1 month and 5 months but not 18 months of age, and novelty responses were significantly correlated at 5 months and 18 months, but not at 1 month. Infants who showed robust habituation responses also showed robust novelty responses across both assessment modalities.
Discussion: This study is the first to examine concurrent correlations across two neuroimaging modalities across several longitudinal age points. Examining habituation and novelty detection, we show that despite the use of two different testing modalities, stimuli and timescale, it is possible to extract common neural metrics across a wide age range in infants. We suggest that these positive correlations might be strongest at times of greatest developmental change.
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http://dx.doi.org/10.1016/j.neuroimage.2023.120153 | DOI Listing |
Prog Mol Biol Transl Sci
September 2025
School of Forensic Science, National Forensic Sciences University, Gandhinagar, Gujarat, India.
Ingestible biosensors are a mix of advanced biomedical engineering, digital health and precision pharmacotherapy. These miniaturised electronic devices are encapsulated in biocompatible materials, which operate within gastrointestinal (GI) tract. This enables real-time monitoring of pharmacological and physiological parameters.
View Article and Find Full Text PDFMar Life Sci Technol
August 2025
State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240 China.
Unlabelled: Traditional cultivation methods with defined growth media can only isolate and cultivate a small number of microbes. However, much higher microbial diversity has been detected by cultivation-independent tools from a range of natural ecosystems. These represent a large unexplored pool of potentially novel taxa.
View Article and Find Full Text PDFRep Pract Oncol Radiother
August 2025
University Teaching Department, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
Background: Cervical cancer (CC) is a leading cause of cancer-related deaths worldwide, emphasizing the need for accurate and efficient diagnostic tools. Traditional methods of cervical cell classification are time-consuming and susceptible to human error, highlighting the need for automated solutions.
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Front Microbiol
August 2025
BIOASTER, Lyon, France.
We propose an innovative technology to classify the Mechanism of Action (MoA) of antimicrobials and predict their novelty, called HoloMoA. Our rapid, robust, affordable and versatile tool is based on the combination of time-lapse Digital Inline Holographic Microscopy (DIHM) and Deep Learning (DL). In combination with hologram reconstruction.
View Article and Find Full Text PDFAnal Chim Acta
November 2025
Key Laboratory of Analytical Science and Technology of Hebei Province, College of Chemistry and Materials Science, Hebei University, Baoding, 071002, PR China; Engineering Research Center of Ecological Safety and Conservation in Beijing-Tianjin-Hebei (Xiong'an New Area) of Ministry of Education, Bao
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