Biology subjects

Mullin, C.

Publications and source records attributed to Mullin, C..

7 recordsLinked to original sources

bioRxiv2026

Distinct Patterns of Cortical Reorganisation Accompany Behaviour-Specific Development in Freely Behaving Infants

A central premise of developmental neuroscience is that mature behaviour emerges through reciprocal interactions between infants spontaneous actions, neural activity, and environmental experience. Yet, much human neuroimaging research relies on highly controlled, repetitive paradigms designed to minimize behavioural variability, obscuring the very brain-behaviour dynamics that drive developmental change. Here, we introduce a naturalistic functional near-infrared spectroscopy (fNIRS) paradigm that exploits, rather than suppresses, natural variability in infants behaviour to investigate cortical changes associated with behavioural development. Continuous video coding of spontaneous infant behaviour was combined with finite impulse response (FIR) modelling to estimate behaviour-specific hemodynamic responses associated with reach-to-grasp, hand-to-mouth, and vocalization behaviours while accounting for temporally overlapping hemodynamic responses by treating extraneous behaviours as nuisance regressors. From 6 to 13 months of age, reach-to-grasp and vocalizations increased in frequency, while all three behaviours shortened in duration. Critically, developmental changes in cortical activation were behaviour-specific. During reach-to-grasp movements, bilateral posterior parietal activity decreased with age. In contrast, during hand-to-mouth and vocalizations, somatomotor and premotor activity increased with age. Cortical activity was also related to individual variation in the frequency and duration of these behaviours, indicating that cortical recruitment remained coupled to behavioural variation independent of age. These findings reveal behaviour-specific patterns of cortical reorganisation during infant development and establish a methodological framework for linking spontaneous behaviour to cortical activity in freely behaving infants. More broadly, this approach enables direct investigation of cortical development as it unfolds through naturalistic interactions among behaviour, neural activity, and experience. Significance StatementContinuous self-generated interactions with the environment play a critical role in driving infant brain development, yet neuroimaging research often examines infants while sleeping or in highly constrained and repetitive tasks. Here, we show that spontaneous infant behaviour can instead be leveraged to provide the temporal variability needed to resolve behaviour-specific cortical responses in freely behaving infants. By combining continuous behavioural coding with data-driven finite impulse response (FIR) modelling of overlapping hemodynamic responses, we identified behaviour-specific developmental differences in cortical recruitment without tightly constraining the infants behaviour. This novel approach expands developmental neuroimaging beyond sleeping or trial-based paradigms and demonstrates how naturally occurring behavioural variability can become a useful feature of fNIRS experimental design. More broadly, it generates new opportunities to directly test theories of neurobehavioural development in more ecologically valid settings.

neuroscience↗

bioRxiv2025

Reduced inhibition, bursting, and accelerated oscillations drive early hippocampal hyperactivity in Alzheimer's disease

Early hippocampal hyperactivity is a well-documented yet poorly defined phenomenon in Alzheimers disease (AD). While reported in both patients and animal models, its functional manifestations and underlying neurophysiological mechanisms in vivo remain unclear. Here, we address this gap using in vivo high-resolution patch-clamp, high-throughput single-unit, and local field recordings in young amyloidopathy mice, at a stage when A{beta} remains largely soluble. We uncover previously unidentified cellular mechanisms in vivo, characterised by reduced inhibitory synaptic input, hypoactivity of fast-spiking interneurons, and enhanced bursting in pyramidal neurons. At the network level, we reveal accelerated hippocampal oscillations, marked by increased theta and beta power, a departure from the conventional view of oscillation slowing in AD. Mechanistically, this acceleration stems from strengthened synchrony of excitatory currents at higher frequencies and an overall reduction in oscillation-associated inhibitory currents. Our findings provide the first direct in vivo evidence linking early hippocampal hyperactivity to specific synaptic transmission and network dysfunctions, resolving a long-standing ambiguity. Moreover, we propose accelerated oscillations in the hippocampus as a functional biomarker for early AD and a potential therapeutic target for restoring network stability before cognitive decline occurs.

neuroscience↗

bioRxiv2023

Cdc73 protects Notch-induced T-cell leukemia cells from DNA damage and mitochondrial stress

Activated Notch signaling is highly prevalent in T-cell acute lymphoblastic leukemia (T-ALL) but pan-Notch inhibitors were toxic in clinical trials. To find alternative ways to target Notch signals, we investigated Cell division cycle 73 (Cdc73), which is a Notch cofactor and component of transcriptional machinery, a potential target in T-ALL. While we confirmed previous work that CDC73 interacts with NOTCH1, we also found that the interaction in T-ALL was context-dependent and facilitated by the lymphoid transcription factor ETS1. Using mouse models, we showed that Cdc73 is important for Notch-induced T-cell development and T-ALL maintenance. Mechanistically, Cdc73, Ets1, and Notch intersect chromatin at promoters and enhancers to activate oncogenes and genes that are important for DNA repair and oxidative phosphorylation. Consistently, Cdc73 deletion in T-ALL cells induced DNA damage and impaired mitochondrial function. Our data suggests that Cdc73 might promote a gene expression program that was eventually intersected by Notch to mitigate the genotoxic and metabolic stresses of elevated Notch signaling. We also provide mechanistic support for testing inhibitors of DNA repair, oxidative phosphorylation, and transcriptional machinery. Inhibiting pathways like Cdc73 that intersect with Notch at chromatin might constitute a strategy to weaken Notch signals without directly targeting the Notch complex.

cancer biology↗

bioRxiv2020

Emergence of Visual Center-Periphery Spatial Organization in Deep Convolutional Neural Networks

Research at the intersection of computer vision and neuroscience has revealed hierarchical correspondence between layers of deep convolutional neural networks (DCNNs) and cascade of regions along human ventral visual cortex. Recently, studies have uncovered emergence of human interpretable concepts within DCNNs layers trained to identify visual objects and scenes. Here, we asked whether an artificial neural network (with convolutional structure) trained for visual categorization would demonstrate spatial correspondences with human brain regions showing central/peripheral biases. Using representational similarity analysis, we compared activations of convolutional layers of a DCNN trained for object and scene categorization with neural representations in human brain visual regions. Results reveal a brain-like topographical organization in the layers of the DCNN, such that activations of layer-units with central-bias were associated with brain regions with foveal tendencies (e.g. fusiform gyrus), and activations of layer-units with selectivity for image backgrounds were associated with cortical regions showing peripheral preference (e.g. parahippocampal cortex). The emergence of a categorical topographical correspondence between DCNNs and brain regions suggests these models are a good approximation of the perceptual representation generated by biological neural networks.

neuroscience↗

bioRxiv2018

Reliability and Generalizability of Similarity-Based Fusion of MEG and fMRI Data in Human Ventral and Dorsal Visual Streams

To build a representation of what we see, the human brain recruits regions throughout the visual cortex in cascading sequence. Recently, an approach was proposed to evaluate the dynamics of visual perception in high spatiotemporal resolution at the scale of the whole brain. This method combined functional magnetic resonance imaging (fMRI) data with magnetoencephalography (MEG) data using representational similarity analysis and revealed a hierarchical progression from primary visual cortex through the dorsal and ventral streams. To assess the replicability of this method, here we present results of a visual recognition neuro-imaging fusion experiment, and compare them within and across experimental settings. We evaluated the reliability of this method by assessing the consistency of the results under similar test conditions, showing high agreement within participants. We then generalized these results to a separate group of individuals and visual input by comparing them to the fMRI-MEG fusion data of Cichy et al (2016), revealing a highly similar temporal progression recruiting both the dorsal and ventral streams. Together these results are a testament to the reproducibility of the fMRI-MEG fusion approach and allows for the interpretation of these spatiotemporal dynamic in a broader context.

neuroscience↗

bioRxiv2018

The Perceptual Neural Trace of Memorable Unseen Scenes

Some scenes are more memorable than others: they cement in minds with consistencies across observers and time scales. While memory mechanisms are traditionally associated with the end stages of perception, recent behavioral studies suggest that the features driving these memorability effects are extracted early on, and in an automatic fashion. This raises the question: is the neural signal of memorability detectable during early perceptual encoding phases of visual processing? Using the high temporal resolution of magnetoencephalography (MEG), during a rapid serial visual presentation (RSVP) task, we traced the neural temporal signature of memorability across the brain. We found an early and prolonged memorability related signal recruiting a network of regions in both dorsal and ventral streams, detected outside of the constraints of subjective awareness. This enhanced encoding could be the key to successful storage and recognition.

neuroscience↗

bioRxiv2017

Repetitive Transcranial Magnetic Stimulation Increases Phase-Amplitude Coupling

A prominent feature of brain activity with relevance to cognitive processes is Phase-Amplitude Coupling (PAC) between slow and fast oscillatory signals. A newly developed neural mass model of cross-frequency coupling [1] predicts, counter-intuitively, that PAC shows sustained increases after repetitive Transcranial Magnetic Stimulation (rTMS). This is because rTMS leads to simultaneous neuronal firing in distinct regions, thereby enhancing the connectivity that, according to the model, is needed for PAC to be increased. We tested this prediction in healthy human volunteers. Two seconds of 10Hz rTMS were applied to the intraparietal sulcus, temporal-parietal junction, and lateral occipital complex. PAC in the subsequent electro-encephalogram was analyzed for two band pairs, theta-gamma and alpha-gamma, and compared to a sham condition. For all stimulation loci, PAC was higher in both band pairs after rTMS than in the sham condition. These results were found to be conform the model prediction. The perspective for using rTMS to modulate cross-band coupling is discussed.

neuroscience↗