Biology subjects

Georgieva, S.

Publications and source records attributed to Georgieva, S..

7 recordsLinked to original sources

bioRxiv2025

Distinct developmental changes in linear and nonlinear neural interactions across infancy and adulthood

The development of functional brain connectivity during early life depends on social experience and is best understood in the context of interactions with a caregiver. It is still an open question to what extent distinct modes of functional connectivity dominate in different stages of human brain development, and whether cognitive tasks can differentially modulate them. Using electroencephalography (EEG), we investigated the development of linear and nonlinear functional brain connectivity in infants and adults while they socially interacted. Using simultaneous EEG recordings in parent-infant dyads performing two different experiments (N = 160; 80 adults and 80 infants), we computed functional connectivity capturing distinct dynamics: a linear measure capturing phase synchronization (weighted phase lag index; WPLI), and a nonlinear measure capturing information sharing (weighted symbolic mutual information; WSMI). In both tasks, adults showed higher WSMI than infants, whereas infants showed higher WPLI than adults. Moreover, infant age predicted only task-related connectivity values computed with the nonlinear measure and not with its linear counterpart, suggesting that the information-theoretic measure was more sensitive to developmental changes in task-relevant neural processing. These findings suggest that over development, a shift in dominance from linear to nonlinear modes of brain communication may be essential for supporting emerging higher cognitive abilities, such as precursors to executive function (here, attention shifting) and social decision-making. Further, this work highlights the importance of using nonlinear measures in addition to traditional linear ones, which collectively permit a more robust capture of maturational changes.

neuroscience↗

bioRxiv2023

A Pose-Informed De-Noising Diffusion Model for Adult Naturalistic EEG Signals

Artifact contamination in EEG (electroencephalogram) signals is a significant problem, especially in naturalistic settings where participants can move freely. This contamination stems from various sources like eye movements, muscle activity, sweat, and electrical interference, whose effects differ greatly from each other. Traditional denoising methods, such as Independent Component Analysis, are limited because they assume a linear relationship between the source of the artifacts and the EEG signals, and often require the dominance of one noise source over others. Moreover, these methods need expert knowledge in EEG analysis and lack an objective standard for evaluation. To overcome these challenges, we propose two innovations: Firstly, we introduce the use of "video-estimated" pose coordinates - the x and y positions of different body points (like wrists, eyes, and ankles) - to assist in the EEG denoising process. Secondly, we present a denoising diffusion model, EEG-DDM, that utilizes both the contaminated EEG signals and these pose coordinates to effectively denoise the EEG. Our findings show that incorporating keypoints (pose coordinates) improves denoising performance and helps maintain cross-spatial dependencies in the data. Additionally, we enhance human interpretability of the process by displaying saliency maps generated by our model, which explain the contributions of these keypoints in the denoising process.

neuroscience↗

bioRxiv2023

Effects of alertness on perceptual detection and discrimination

The level of alertness fluctuates throughout the day, exerting modulatory effects on human cognitive processes at any moment. However, our knowledge of how alertness level interacts with specific cognitive demands and perceptual rules of the task is still limited. Here we use perceptual decision-making paradigms to understand how alertness modulates the detection of a stimulus and the capacity to discriminate one stimulus from another. We analyzed data from four different experiments (113 participants in total): 1 - auditory masking detection; 2 - sensorimotor detection; 3 - auditory spatial discrimination; and 4 - auditory phoneme discrimination, and examined the performance of participants during the natural transition from awake (high alertness) to drowsy (low alertness). First, we fitted psychometric functions to the hit rates across different conditions of difficulty for EEG-defined high and low alertness metastable states, respectively. Second, we performed modelling of slope and threshold for the fitted curves as well as signal detection theory measures of perceptual sensitivity (d) and response bias (criterion). We found lower detection and discrimination sensitivity to stimuli as alertness level decreases, signalled by a shallower slope of the sigmoidal curve and a lower d, while the threshold increases slightly and equivalently across experiments during lower alertness. There was no change in the criterion to make the decision during the transition. These results suggest that reduced alertness generally decreases the quality of perceptual decision-making. Zooming in, we observed that the decrease in sensitivity measured by slope was stronger for discrimination than for detection decisions, indicating that lower alertness impairs the precision of decisions in discriminating alternatives more than identifying the presence of a stimulus around the threshold. Taken together, these results suggest that alertness has a common effect on perceptual decision-making and differentially modulates detection and discrimination decisions.

animal behavior and cognition↗

bioRxiv2019

Emotional valence modulates the topology of the parent-infant inter-brain network

Emotional communication between parents and children is crucial during early life, yet little is known about its neural underpinnings. Here, we adopt a dual-brain connectivity approach to assess how emotional valence modulates the parent-infant neural network. Fifteen mothers modelled positive and negative emotions toward pairs of objects during social interaction with their infants (aged 10.3 months) whilst their neural activity was concurrently measured using dual-EEG. Intra-brain and inter-brain network connectivity in the 6-9 Hz (infant Alpha) range was computed during maternal expression of positive and negative emotions using directed (partial directed coherence) and non-directed (phase-locking value) connectivity metrics. Graph theoretical metrics were used to quantify differences in network topology as a function of emotional valence. Inter-brain network indices (Density, Strength and Divisibility) consistently revealed that the integration of parents and childrens neural processes was significantly stronger during maternal demonstrations of positive than negative emotions. Further, directed inter-brain metrics indicated that mother-to-infant directional influences were stronger during the expression of positive than negative emotions. These results suggest that the parent-infant inter-brain network is modulated by the emotional quality and tone of dyadic social interactions, and that inter-brain graph metrics may be successfully applied to examine these changes in interpersonal network topology.

neuroscience↗

bioRxiv2018

Parental neural responsivity to infants visual attention: how mature brains scaffold immature brains during social interaction.

Almost all attention and learning - in particular, most early learning - takes place in social settings. But little is known of how our brains support dynamic social interactions. We recorded dual-EEG from infants and parents during solo play and joint play. During solo play, fluctuations in infants Theta power significantly forward-predicted their subsequent attentional behaviours. But this forwards-predictiveness was lower during joint play than solo play, suggesting that infants endogenous neural control over attention is greater during solo play. Overall, however, infants were more attentive to the objects during joint play. To understand why, we examined how adult brain activity related to infant attention. We found that parents Theta power closely tracked and responded to changes in their infants attention. Further, instances in which parents showed greater neural responsivity were associated with longer sustained attention by infants. Our results offer new insights into how one partner influences another during social interaction.

neuroscience↗

bioRxiv2017

Topographical and spectral signatures of infant and adult movement artifacts in naturalistic EEG

Electroencephalography (EEG) is perhaps the most widely used brain-imaging technique for paediatric populations. However, EEG signals are prone to distortion by motion. Compared to adults, infants motion is both more frequent and less stereotypical yet motion effects on the infant EEG signal are largely undocumented. Here, we present a systematic assessment of naturalistic motion effects on the infant and adult EEG signal. In Study 1, we documented the prevalence of 27 naturally occurring facial and body motions by video-coding five mother-infant pairs during naturalistic play. In Study 2, we elicited a subset of the most common facial, limb and postural motions from one adult and one infant actor while their EEG was recorded. In Study 3, we recorded EEG signals from a larger group of 12 infants whilst they produced the same motions spontaneously. Our findings from Study 2 suggested that adult movements mainly generated increases in spectral power relative to resting state, primarily at peripheral sites and in delta and high-beta frequency bands. In infants, both elicited motions (N=1, Study 2) and spontaneously-occurring motions (N=12, Study 3) produced decreases in theta, alpha and beta power over central regions and increased beta/delta power at peripheral sites. We also observed that infants jaw and upper limb movements generated more pronounced EEG artifacts than lower limb movements. It is intended that this work will inform future development of methods for addressing EEG motion-related artifacts and support wider use of naturalistic paradigms in social and developmental neuroscience.

neuroscience↗

bioRxiv2017

Towards a neuroscientific understanding of play: A neuropsychological coding framework for analysing infant-adult play patterns

During early life, play is a ubiquitous activity, and an individuals propensity for play is positively related to cognitive development and emotional well-being. Play behaviour is diverse and multi-faceted. A challenge for current research is to converge on a common definition and measurement system for play - whether examined at a behavioural, cognitive or neurological level. Combining these different approaches in a multi-level analysis could yield significant advances in understanding the neurocognitive mechanisms of play, and provide the basis for developing biologically-grounded play models. However, there is currently no integrated framework for conducting a multi-level analysis of play that spans brain, cognition and behaviour. The proposed neuropsychological coding framework uses grounded and observable behaviours along three neuropsychological dimensions (sensorimotor, cognitive and socio-emotional), to compute inferences about playful behaviour and related social interactional states. Here, we illustrate the sensitivity and utility of the proposed coding framework using two contrasting dyadic corpora (N=5) of mother-infant object-oriented interactions during experimental conditions that were either conducive (Condition 1) or non-conducive (Condition 2) to the emergence of playful behaviour. We find that the framework accurately identifies the modal form of social interaction as being either playful (Condition 1) or non-playful (Condition 2), and further provides useful insights about differences in the quality of social interaction and temporal synchronicity within the dyad. In conclusion, here, we present a novel neuropsychological framework for analysing the continuous time-evolution of adult-infant play patterns, underpinned by biologically informed state coding along sensorimotor, cognitive and socio-emotional dimensions. We expect that the proposed framework will have wide utility amongst researchers wishing to employ an integrated, multi-level approach to the study of play, and lead towards a greater understanding of the neuroscientific basis of play and may yield insights into a new biologically-grounded taxonomy of play interactions.

neuroscience↗