Biology subjects

Soddu, A.

Publications and source records attributed to Soddu, A..

5 recordsLinked to original sources

bioRxiv2026

Assessing whole-cortex excitability from electromagnetic brain signals

Cortical excitability, the propensity of neural circuits to respond to internal or external perturbations, is a fundamental property of brain functioning, shaped by local microcircuitry, large-scale networks, and neurochemical architecture. In humans, excitability is inferred from multiple indirect metrics derived from spontaneous and stimulus-driven electromagnetic activity, yet it remains unclear whether these measures reflect a common underlying construct or distinct physiological processes. Here, we systematically compared ten previously validated excitability metrics using whole-head magnetoencephalography (MEG) recorded at rest and during 40 Hz auditory stimulation in a large sample of healthy adults. The measures spanned stimulus-driven synchronization, spectral power, 1/f activity (hereafter defined as aperiodic), signal complexity, long-range temporal correlations, and phase-gamma synchronization. Hierarchical clustering revealed six separable excitability dimensions with limited redundancy, demonstrating that cortical excitability is inherently multidimensional. Aperiodic and alpha-band measures showed the strongest mutual coupling and the furthest spatial correspondence to stimulus-related responses, whereas temporal, complexity, and synchronization-based metrics were largely independent. The similarity between measures varied across cortical regions and functional networks, with maximal cluster separability in integrative and internally driven regions. These regions included orbitofrontal, temporal, anterior cingulate, and default mode areas, as well as visual and somatomotor networks. Finally, excitability dimensions showed distinct relationships with cortical morphology and neurotransmitter receptor density, implicating heterogeneous neurobiological substrates. Together, these findings provide a unified framework for interpreting excitability metrics and highlight the need for multimodal approaches when probing cortical excitability in health and disease.

neuroscience↗

bioRxiv2025

Rate of functional network maturity and the role of environmental factors

The developmental period from childhood to adolescence is marked by significant changes to the functional properties of the brain that support various aspects of higher-level cognition. Environmental factors such as socioeconomic status and adversity can have an outsized influence on neurocognitive development. However, not all environmental factors have the same influence on cognitive and brain development. In the current study, we examined the differential influences of SES (i.e., parental education and neighbourhood safety) and adversity on the maturation rate of functional networks in children and adolescents. Using resting-state fMRI data, independent component analysis with dual regression was computed to identify six networks (Default Mode Network (DMN), Left Executive Control Network (ECN), Right ECN, Hippocampal (HPC), Salience, and Sensorimotor networks) of interest in children and adolescents aged 7 to 15 (N=216, acquired from the Healthy Brain Network). A neural maturity index was generated based on the degree of similarity between the spatial configuration of the six networks in each youth brain to that of an adult template (1243 total, with a mean age of 26; independently by sex). Regression analyses were used to determine the association between neural maturity, social-cognitive abilities and environmental factors such as parental education, neighbourhood safety and number of negative life events (adversity). We found one sensory (sensorimotor) and two association (default mode and executive control) networks matured faster than other networks. Only the rate of maturity of the DMN and HPC were associated with environmental factors. Maturity of the DMN was associated with less adversity and better social cognitive ability, whereas maturity of the HPC network was associated with younger participants with higher IQs. Moreover, these effects were stronger in females than males. Our results highlight the importance of examining the unique contributions of distinct dimensions of childhood environments on neurocognitive development.

neuroscience↗

bioRxiv2021

CALIPER: A software for blood-free parametric Patlak mapping using PET/MRI input function.

Routine clinical use of absolute PET quantification techniques is limited by the need for serial arterial blood sampling for input function and more importantly by the lack of automated pharmacokinetic analysis tools that can be readily implemented in clinic with minimal effort. PET/MRI provides the ability for absolute quantification of PET probes without the need for serial arterial blood sampling using image-derived input functions (IDIFs). Here we introduce caliPER, a modular and scalable software for simplified pharmacokinetic modelling of PET probes with irreversible uptake or binding based on PET/MR IDIFs and Patlak Plot analysis. caliPER generates regional values or parametric maps of net influx rate (Ki) using reconstructed dynamic PET images and anatomical MRI aligned to PET for IDIF vessel delineation. We evaluated the performance of caliPER for blood-free region-based and pixel-wise Patlak analyses of [18F] FDG by comparing caliPER IDIF to serial arterial blood input functions and its application in imaging brain glucose hypometabolism in Frontotemporal dementia. IDIFs corrected for partial volume errors including spill-out and spill-in effects were similar to arterial blood input functions with a general bias of around 6-8%, even for arteries <5 mm. The Ki and cerebral metabolic rate of glucose estimated using caliPER IDIF were similar to estimates using arterial blood sampling (<2%) and within limits of whole brain values reported in literature. Overall, caliPER is a promising tool for irreversible PET tracer quantification and can simplify the ability to perform parametric analysis in clinical settings without the need for blood sampling. HighlightsO_LIcaliPER is an adaptable image processing software for extracting image-derived input functions and generating parametric maps of irreversible PET tracer uptake. C_LIO_LIAnatomical (T1-weighted/T2-weighted/time-of-flight angiography) MRI carefully aligned to PET provides a robust approach for delineation of vessels on PET, eliminating the need for serial blood sampling for input functions. C_LIO_LIApplication of caliPER in modelling glucose uptake in patients with Frontotemporal dementia, demonstrates the feasibility of absolute quantification of cerebral metabolic rate of glucose in clinical populations. C_LI

bioinformatics↗

bioRxiv2019

Cognition across the lifespan: Aging and gender differences

Maintaining cognitive health across the lifespan has been the focus of a multi-billion-dollar industry. In order to guide treatment and interventions, a clear understanding of the way that proficiency in different cognitive domains develops and declines across the lifespan is necessary. Additionally, there are gender differences in a range of other factors, such as anxiety and substance use, that are also known to affect cognition, although the scale of this interaction is unknown. Our objective was to assess differences in cognitive function across the lifespan in men and women in a large, representative sample. Leveraging online cognitive testing, a sample of 18,902 men and women ranging in age from 12-69 matched on socio-demographic factors were studied. Segmented regression was used to model three cognitive domains - short-term memory, verbal abilities, and reasoning. Gender differences in all three domains were minimal; however, after broadening the sample in terms of socio-demographic factors, gender differences appeared. These results suggest that cognition across the lifespan differs for men and women, but is greatly influenced by environmental factors. We discuss these findings within a framework that describes gender differences in cognition as likely guided by a complex interplay between biology and environment.

neuroscience↗

bioRxiv2019

The emergence of integrated information, complexity, andconsciousness at criticality

Using the critical Ising model of the brain, integrated information as a measure of consciousness is measured in toy models of generic neural networks. Monte Carlo simulations are run on 159 random weighted networks analogous to small 5-node neural network motifs. The integrated information generated by this sample of small Ising models is measured across the model parameter space. It is observed that integrated information, as a type of order parameter not unlike a concept like magnetism, undergoes a phase transition at the critical point in the model. This critical point is demarcated by the peaks of the generalized susceptibility of integrated information, a point where the consciousness of the system is maximally susceptible to perturbations and on the boundary between an ordered and disordered form. This study adds further evidence to support that the emergence of consciousness coincides with the more universal patterns of self-organized criticality, evolution, the emergence of complexity, and the integration of complex systems.\n\nAuthor summaryUnderstanding consciousness through a scientific and mathematical language is slowly coming into reach and so testing and grounding these emerging ideas onto empirical observations and known systems is a first step to properly framing this ancient problem. This paper in particular explores the Integrated Information Theory of Consciousness framed within the physics of the Ising model to understand how and when consciousness, or integrated information, can arise in simple dynamical systems. The emergence of consciousness is treated like the emergence of other classical macroscopic observables in physics such as magnetism and understood as a dynamical phase of matter. Our findings show that the sensitivity of consciousness in a complex system is maximized when the system is undergoing a phase transition, also known as a critical point. This result, combined with a body of evidence highlighting the privelaged state of critical systems suggests that, like many other complex phenomenon, consciousness may simply follow from/emerge out of the tendency of a system to self-organize to criticality.

neuroscience↗