Biology subjects

Tachtsidis, I.

Publications and source records attributed to Tachtsidis, I..

7 recordsLinked to original sources

bioRxiv2026

Cerebral hemodynamics and cytochrome c oxidase in hypoxic-ischemic rabbit fetuses

Background: Understanding fetal brain responses to hypoxia-ischemia is of growing interest, as it remains unclear to what extent these responses differ from those of newborns and whether developmental adaptations during gestation contribute to such differences. Materials and methods: Using a combination of broadband near-infrared spectroscopy (bNIRS) and diffuse correlation spectroscopy (DCS), we measured brain microvascular oxygen saturation (StO2), total hemoglobin concentration (THC), relative cerebral blood flow (rCBF), and the oxidation state of cytochrome c oxidase (oxCCO) during an acute ischemic challenge in the brains of five rabbit fetuses in utero. Simultaneous measurements were acquired from four control fetuses located in the contralateral uterine horn. Results: During the hypoxia-ischemia phase, we observed a rapid reduction of CBF (47% +/- 29%) and StO2, (from 64.7% +/- 1.5% at baseline to 40.6% +/- 2.0%) together with an increase of oxCCO (3.7 uM +/- 0.5 uM). Conclusion: The simultaneous increase in oxCCO and decrease in rCBF and StO2 during hypoxia-ischemia reveals a cerebral response pattern that differs from that commonly reported in the newborn brain. These findings support the hypothesis that unique developmental adaptations influence fetal cerebral metabolism during hypoxic-ischemic stress.

neuroscience↗

bioRxiv2026

Prefrontal brain-to-brain synchrony during human group hunting: Evidence from fNIRS hyperscanning

Orca, wolves, chimpanzees and humans share a similarly impressive capacity for group hunting, where individuals coordinate behaviour together to capture prey. Studying hunting behaviours has important implications for understanding how behaviour in group contexts may be indicative of cognitive decline. Despite growing interest in brain circuits for prey capture, the brain regions involved in tracking prey during a hunt and the behaviours in group hunt linked to success remain unclear. Here we combined functional near infrared spectroscopy (fNIRS) and a virtual minecraft world to examine behaviour, brain dynamics and brain synchrony involved in group hunting behaviour. We focused on the prefrontal cortex (PFC) due to its known role in planning and social coordination and recorded from pairs of individuals as they either cooperated to hunt another person (prey) or simply followed another person. Hunters were more successful if they managed to keep a smaller distance to the prey and moved at speeds that were more synchronised with their co-predator. At high-range frequencies for fNIRS (0.1-0.2Hz), we found greater brain-to-brain synchrony in lateral and medial (frontopolar) PFC regions during hunting compared with chance levels. Together, these findings provide insights into what behaviours and brain dynamics associated with successful group hunting.

neuroscience↗

bioRxiv2025

On-skin, micro-lens enabled camera module for speckle contrast optical spectroscopy/tomography

In this paper, we introduce a speckle contrast optical spectroscopy/tomography (SCOS/SCOT) configuration based on an integrated imaging approach exploiting 113 micro-objetives mounted on a commercial CMOS camera that operates without fiber coupling, suitable for direct skin contact measurements and simultaneous multiple source-detector separation acquisitions. This compact system was validated ex vivo on phantoms and in vivo by monitoring the blood flow on the forearm muscle of a healthy human subject. The measurements, performed at multiple source-detector separations and camera exposure times, demonstrate excellent agreement with the theory based on the correlation-diffusion model. In vivo data demonstrate the capability of tracking pulsatile blood flow with a high signal-to-noise ratio (>4 harmonics of the cardiac pulse frequency detected) and sensitivity to small changes in muscle blood flow. This micro-objective array-based design overcomes a key challenge towards wearable SCOS/SCOT devices.

bioengineering↗

bioRxiv2023

Neuroplasticity of speech-in-noise processing in older adults assessed by functional near-infrared spectroscopy (fNIRS)

Functional near-infrared spectroscopy (fNIRS), a non-invasive optical neuroimaging technique that is portable and acoustically silent, has become a promising tool for evaluating auditory brain functions in hearing- vulnerable individuals. This study, for the first time, used fNIRS to evaluate neuroplasticity of speech-in-noise processing in older adults. Ten older adults, most of whom had moderate-to-mild hearing loss, participated in a 4-week speech-in-noise training. Their speech-in-noise performances and fNIRS brain responses to speech (auditory sentences in noise), non-speech (spectrally-rotated speech in noise) and visual (flashing chequerboards) stimuli were evaluated pre- (T0) and post-training (immediately after training, T1; and after a 4-week retention, T2). Behaviourally, speech-in-noise performances were improved after retention (T2 vs. T0) but not immediately after training (T1 vs. T0). Neurally, we intriguingly found brain responses to speech vs. non-speech decreased significantly in the left auditory cortex after retention (T2 vs. T0 and T2 vs. T1) for which we interpret as suppressed processing of background noise during speech listening alongside the significant behavioural improvements. Meanwhile, functional connectivity within and between multiple regions of temporal, parietal and frontal lobes was significantly enhanced in the speech condition after retention (T2 vs. T0). We also found neural changes before the emergence significant behavioural improvements. Compared to pre-training, responses to speech vs. non-speech in the left frontal/prefrontal cortex were decreased significantly both immediately after training (T1 vs. T0) and retention (T2 vs. T0), reflecting possible alleviation of listening efforts. Finally, connectivity was significantly decreased between auditory and higher-level non-auditory (parietal and frontal) cortices in response to visual stimuli immediately after training (T1 vs. T0), indicating decreased cross-modal takeover of speech-related regions during visual processing. The results thus showed that neuroplasticity can be observed not only at the same time, but also before behavioural changes in speech-in- noise perception. To our knowledge, this is the first fNIRS study to evaluate speech-based auditory neuroplasticity in older adults. It thus provides important implications for current research by illustrating the promises of detecting neuroplasticity using fNIRS in hearing-vulnerable individuals.

neuroscience↗

bioRxiv2023

The influence of carbon dioxide on cerebral metabolism and oxygen consumption: combining multimodal monitoring with dynamic systems modelling

Hypercapnia increases cerebral blood flow, but the effect on cerebral metabolism in humans remains incompletely understood. Either increased or reduced oxygen consumption has been predicted from Fick models incorporating cerebral oxygen extraction fraction and cerebral blood flow. Hypercapnia also results in oxidation of cytochrome c oxidase, complex IV of the mitochondrial respiratory chain, implicating a change in cellular metabolism. The aim of this study was to combine systems modelling with non-invasive measurements of cerebral tissue oxygenation, cerebral blood flow, and cytochrome c oxidase redox state to evaluate any metabolic effects of hypercapnia. Cerebral tissue oxygen saturation and cytochrome oxidase redox state were measured with broadband near infrared spectroscopy and cerebral blood flow velocity using transcranial Doppler ultrasound. Data collected during 5-minutes hypercapnia in human volunteers were analyzed using a Fick model to determine changes in brain oxygen consumption and a mathematical model of cerebral hemodynamics and metabolism (BrainSignals) to inform on the potential mechanisms of any observed changes. Systemic physiology - blood pressure, arterial oxygen saturations and end-tidal carbon dioxide - served as model inputs. The extent of the hypercapnic oxidation of cytochrome oxidase required modifications of the BrainSignals model; simulations compared two possible modifications that could cause this oxidation - a decrease in metabolic substrate supply or an increase in metabolic demand. Only the decrease in substrate supply was able to explain both the enzyme redox state changes and the Fick calculated drop in brain oxygen consumption. These modelled outputs are consistent with, but do not prove, previous reports of CO2 inhibition of succinate dehydrogenase, complex II of the mitochondrial respiratory chain. These findings suggest that hypercapnia may have physiologically significant effects suppressing oxidative metabolism in humans and perturbing mitochondrial signaling pathways in health and disease.

physiology↗

bioRxiv2022

Mapping human social brain specialisation beyond the neuron using multimodal imaging in human infants

The specialised regional functionality of the mature human cortex partly emerges through experience-dependent specialisation during early development. Our existing understanding of this process is based on evidence from unitary imaging modalities and has thus focused on isolated changes in spatial or temporal precision of neural or haemodynamic activation alone, giving an incomplete picture of the process. We speculate that neural specialisation of function will be underpinned by better coordinated haemodynamic and metabolic changes in a broader orchestrated physiological response. Thus, we present a harmonised framework in which specialisation is indexed by the emergence of coupling between neuronal activity and vascular supply of oxygen and energy. Here, we combine simultaneous measures of coordinated neural activity (EEG), metabolic rate and oxygenated blood supply (broadband near-infrared spectroscopy) to measure emerging specialisation in the infant brain. In 4-to-7-month-old infants, we show that social processing is accompanied by spatially and temporally specific increases in coupled activation in the temporal-parietal junction, a core hub region of the adult social brain. During non-social processing coupled activation decreased in the same region, indicating specificity to social processing. Coupling was strongest with high frequency brain activity (beta and gamma), consistent with the greater energetic requirements and more localised action of high frequency brain activity. We conclude that functional specialisation of the brain is a coordinated activity across neural, haemodynamic, and metabolic changes, and our ability to measure these simultaneously opens new vistas in understanding how the brain is shaped by its environment.

developmental biology↗

bioRxiv2018

A Bayesian framework for the analysis of systems biology models of the brain

Systems biology models are used to understand complex biological and physiological systems. Interpretation of these models is an important part of developing this understanding. These models are often fit to experimental data in order to understand how the system has produced various phenomena or behaviour that are seen in the data. In this paper, we have outlined a framework that can be used to perform Bayesian analysis of complex systems biology models. In particular, we have focussed on analysing a systems biology of the brain using both simulated and measured data. By using a combination of sensitivity analysis and approximate Bayesian computation, we have shown that it is possible to obtain a more complete understanding of the parameter space as compared to a maximum likelihood estimate based approach. This is done through analysis of simulated and experimental data. NIRS measurements were simulated using the same simulated systemic input data for the model in a healthy and impaired state. By analysing both of these datasets, we show that different parameter spaces can be distinguished and compared between different physiological states or conditions. Finally, we analyse experimental data using the new Bayesian framework and the previous maximum likelihood estimate approach, showing that the Bayesian approach provides a more complete understanding of the parameter space.\n\nAuthor summarySystems biology models are mathematical representations of biological processes that reproduce the overall behaviour of a biological system. They are comprised by a number of parameters representing biological information. We use them to understand the behaviour of biological systems, such as the brain. We do this by fitting the models parameter to observed or simulated data; and by looking at how these values change during the fitting process we investigate the mechanisms controlling the behaviour of our system. We are interested in understanding differences between a healthy and an injured brain. Here we outline a statistical framework that uses a Bayesian approach during the fitting process that can provide us with a distribution of parameters rather than single parameter number. We apply this method when simulating the physiological responses between a healthy and a vascular compromised brain to a drop in oxygenation. We then use experimental data that demonstrates the healthy brain response to an increase in arterial CO2 and fit our brain model predictions to the measurements. In both instances we show that our approach provides more information about the overlap between healthy and unhealthy brain states than a fitting process that provides a single value parameter estimate.

systems biology↗