Biology subjects

Mermillod, M.

Publications and source records attributed to Mermillod, M..

8 recordsLinked to original sources

bioRxiv2026

Exploring Healthy Neurocognitive Ageing with Deep Learning Interpretability Methods

Healthy ageing reorganises large-scale functional brain networks. Using resting-state fMRI from 615 adults aged 18 to 88 years in Cam-CAN. We combined raw functional connectivity analyses, graph-theoretical topology, Ridge and MLP age prediction and their attributions in order to understand how functional brain organisation varies with age and relates to cognitive performance. Both models predicted age accurately, with a modest advantage for the MLP. Within-network FC decreased with age, while between-network FC and participation increased. Topological analyses showed increased participation and a redistribution of nodes across connector, provincial, satellite, and peripheral roles. The MLP SmoothGrad attributions emphasised high-participation and weakly specialised nodes, whereas counterfactual tests showed that replacing CON-SMN, CON-DMN and DMN-FPN connections with a young-adult template produced the largest reductions in predicted age. Brain-cognition PLS linked these mechanisms to a broad cognitive-performance axis and a secondary semantic/connectomic axis. Together, these findings suggest that healthy ageing involves a redistribution of functional organisation that extends beyond a single DMN-FPN axis towards a broader DMN-CON-SMN-FPN configuration.

neuroscience↗

bioRxiv2025

Structure-Function Dynamics in Healthy Cognitive Aging: A Graph Signal Processing Approach

Network neuroscience has significantly advanced our understanding of how structural and functional connectivity evolve during healthy neurocognitive aging. Yet, integrative studies linking structural and functional brain organization with cognitive performance remain relatively limited. In this study, we analyzed resting-state functional MRI and diffusion-weighted imaging data from 600 healthy adults aged 18 to 88, drawn from the CamCAN dataset. Using a graph signal processing framework, we investigated how structural connectivity constrains functional brain signals across the adult lifespan. Our results reveal that control and semantic cognitive systems exhibit distinct age-related patterns of structure-function reorganization, potentially reflecting a shift in integrative processing during midlife. Notably, our findings suggest that structurally-coupled sensorimotor integration plays a crucial role for regulating these systems. Until midlife, it accompanies structurally-decoupled activity in transmodal cortices to sustain cognitive control. In parallel, it likely supports the formation of embodied internal models that leverage more structurally-decoupled semantic processes, thus contributing to maintain lexical production skills for longer in older adulthood. Taken together, our study offer new multimodal insights into how sensory-driven processes help reconfigure the healthy aging brain to support controlled semantic cognition.

neuroscience↗

bioRxiv2025

A Neurocognitive Shift in Midlife: Linking Cognitive Flexibility and Functional-Metabolic Adaptation with the SENECA model

Understanding how the older adult brain sustains cognitive flexibility remains a central question in aging research. Here, we analyzed resting-state fMRI data from the population-based CamCAN database (N = 628; age 18-88) and applied structural balance theory to measure functional network energy, a graph-theoretical proxy of network flexibility. In line with the SENECA model, our findings highlight midlife as a critical transition period: network energy is redistributed along the sensory-transmodal hierarchy, shifting from higher-level networks (DMN-FPN) to lower-level networks (SMN, CON, Auditory, Visual, Language). This reorganization (i) helps preserve a global wiring economy across the lifespan, hinting at an allostatic mechanism (i.e., stability through change); and (ii) may support embodied semantic strategies in older adulthood, leveraging more predictive processing to sustain cognitive flexibility at lower costs. Taken together, our study reframes healthy neurocognitive aging as an allostatic process and provides a reference for extending the SENECA model to metabolism and neuropathology.

neuroscience↗

bioRxiv2024

Lifespan Oscillatory Dynamics in Lexical Production: A Population-based MEG Resting-State Analysis

Lexical production remains relatively preserved across the lifespan, but cognitive control demands increase with age to support efficient semantic access. It suggests a domain-general and a language-specific component. Current neurocognitive models suggest the Default Mode Network (DMN) may drive the interplay between these components, impacting the trajectory of production performance with a pivotal shift around midlife. However, the corresponding time-varying architecture still needs clarification. Here, we leveraged MEG resting-state data from healthy adults aged 18-88 from a CamCAN population-based sample. We found that DMN temporal dynamics shift from anterior-ventral to posterior-dorsal states until midlife to mitigate word-finding challenges. Similarly, sensorimotor integration along this posterior path enhances cross-talk with lower-level circuitry as the dynamic information flow with more anterior, higher-order cognitive states gets compromised. It suggests a bottom-up, exploitation-based form of cognitive control in the aging brain, highlighting the interplay between abstraction, control, and perceptive-motor systems in preserving lexical production. HighlightsO_LIMidlife is a pivotal period for time-varying functional connectivity C_LIO_LIDMN activation and deactivation drive the resting-state oscillatory architecture C_LIO_LIEnhanced posterior DMN temporal dynamics mitigates lexical production decline C_LI

neuroscience↗

bioRxiv2024

Dynamics of White Matter Architecture in Lexical Production among Middle-Aged Adults

This study aimed to elucidate the white matter changes associated with lexical production (LP) difficulties that typically emerge in middle age, resulting in increased naming latencies. To delay the onset of LP decline, middle-aged adults may rely on domain-general (DG) and language-specific (LS) compensatory mechanisms as proposed by the LARA model (Lexical Access and Retrieval in Aging). However, our knowledge of the white matter changes supporting these mechanisms remains incomplete. Based on a sample of 155 middle-aged adults from the CAMCAN cohort, we combined dimensionality reduction techniques with multivariate statistical methods to jointly examine the relationships between diffusion-weighted imaging and LP-related neuropsychological data. Our findings (i) show that midlife constitutes a pivotal period marked by a discontinuity in brain structure within distributed networks within dorsal, ventral, and anterior cortico-subcortical pathways, and (ii) reveal that this discontinuity signals a neurocognitive transition around age 53-54, marking the onset of LP decline. Indeed, our results propose that middle-aged adults may initially adopt a "semantic strategy" to compensate for initial LP challenges. Still, this strategy may be compromised when late middle-aged adults (age 55-60) lose the ability to exert cognitive control over semantic representations (i.e., reduced semantic control). In summary, our study advances our comprehension of brain structure changes that underpin the neurocognitive profile of LP in middle age. Specifically, we underscore the importance of considering the interplay between DG and LS processes when studying the trajectory of LP performance in healthy aging. Furthermore, these findings offer valuable insights into identifying predictive biomarkers related to the compensatory dynamics observed in midlife, which can help understand language-related neurodegenerative pathologies. HighlightsO_LIMidlife constitutes a pivotal period characterized by a discontinuity in brain structure. C_LIO_LIEarly middle-aged adults (age 45-55) adopt a "semantic strategy" to facilitate semantic access and sustain lexical production (LP) performances. C_LIO_LILate middle-aged adults (age 55-60) gradually lose the ability to exert cognitive control over semantic representations, marking the onset of LP decline. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/579645v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@85346dorg.highwire.dtl.DTLVardef@13515b7org.highwire.dtl.DTLVardef@24a1fforg.highwire.dtl.DTLVardef@1078f4c_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Modeling the Neurocognitive Dynamics of Language across the Lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that DMN (Default Mode Network) suppression coupled with FPN (Fronto-Parietal Network) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel SENECA model (Synergistic, Economical, Nonlinear, Emergent, Cognitive Aging), integrating connectomic and cognitive dimensions within a complex system perspective. HighlightsO_LILexical production (LP) relies on the interplay between domain-general and semantic processes throughout life. C_LIO_LIDMN (Default Mode Network) suppression cooperates with FPN (Fronto-Parietal Network) integration to maintain LP performance at a minimal cost. C_LIO_LIMidlife marks a neurocognitive shift, with reduced DMN suppression prompting a more cost-efficient compensatory strategy that prioritizes homeostasis over LP performance. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=135 SRC="FIGDIR/small/547510v2_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@85939aorg.highwire.dtl.DTLVardef@19d8bbcorg.highwire.dtl.DTLVardef@40f5e8org.highwire.dtl.DTLVardef@d0713f_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2018

Real-world expectations and their affective value modulate object processing

It is well known that expectations influence how we perceive the world. Yet the neural mechanisms underlying this process remain unclear. Studies about the effects of prior expectations have focused so far on artificial contingencies between simple neutral cues and events. Real-world expectations are however often generated from complex associations between contexts and objects learned over a lifetime. Additionally, these expectations may contain some affective value and recent proposals present conflicting hypotheses about the mechanisms underlying affect in predictions. In this study, we used fMRI to investigate how object processing is influenced by realistic context-based expectations, and how affect impacts these expectations. First, we show that the precuneus, the inferotemporal cortex and the frontal cortex are more active during object recognition when expectations have been elicited a priori, irrespectively of their validity or their affective intensity. This result supports previous hypotheses according to which these brain areas integrate contextual expectations with object sensory information. Notably, these brain areas are different from those responsible for simultaneous context-object interactions, dissociating the two processes. Then, we show that early visual areas, on the contrary, are more active during object recognition when no prior expectation has been elicited by a context. Lastly, BOLD activity was shown to be enhanced in early visual areas when objects are less expected, but only when contexts are neutral; the reverse effect is observed when contexts are affective. This result supports the proposal that affect modulates the weighting of sensory information during predictions. Together, our results help elucidate the neural mechanisms of real-world expectations.

neuroscience↗

bioRxiv2017

From curiosity relief to epistemic surprise: complementary roles of the prefrontal cortex and the ventral striatum in the neural valuation of knowledge

Epistemic curiosity (EC) is a cornerstone of human cognition that contributes to the actualization of our cognitive potential by stimulating a myriad of information-seeking behaviours. Yet, its fundamental relationship with uncertainty remains poorly understood, which limits our ability to predict within- and between-individual variability in the willingness to acquire knowledge. Here, a two-step stochastic trivia quiz designed to induce curiosity and manipulate answer uncertainty provided behavioural and neural evidence for an integrative model of EC inspired from predictive coding. More precisely, our behavioural data indicated an inverse relationship between average surprise and EC levels, which depended upon hemodynamic activity in the rostrolateral prefrontal cortex from one trial to another and from one individual to another. Complementary, the elicitation of epistemic surprise and the relief of acute curiosity states were respectively related to ventromedial prefrontal cortex and ventral striatum activity. Taken together, our results account for the temporal evolution of EC over time, as well as for the interplay of EC, prior knowledge and surprise in controlling memory gain.

neuroscience↗