Biology subjects

Valenza, G.

Publications and source records attributed to Valenza, G..

7 recordsLinked to original sources

bioRxiv2024

Impaired functional brain-heart interplay sustains emotion dysregulation in depressed individuals

Depression is a leading worldwide cause of mental disorders and disability, strongly affecting emotional processing and regulation. Its dysfunctional psycho-physiological dynamics may be part of the a nervous-system-wise symptomatology, impacting not only patients psyche but also significantly influencing functional cardiovascular dynamics. Therefore, depression serves as an exemplary pathological manifestation of the dysfunctional interaction between the central and autonomic nervous systems. While recent literature has been developing specific techniques to quantify such interactions, often referred to as functional Brain-Heart Interplay (BHI), the quantitative role of BHI dynamics in depression is largely unknown. This study aims to experimentally unveil BHI patterns specific to emotional regulation and processing in subjects exhibiting depressive symptoms compared to healthy controls. Results were gathered from a cohort of 72 individuals and indicate that depressive symptoms are associated with a continuous efferent central-to-peripheral hyperactivity and an afferent peripheral-to-central hypoactivity. This hypoactivity appears to be specific to negative emotional processing. This study offers novel insights into the systemic investigation of the neuro-physiological bases of depression.

neuroscience↗

bioRxiv2022

Directed Functional Connectivity by Variational Cross-mapping of Psychophysiological Variables

Understanding the functional connectivity between different brain regions is vital for improving our comprehension of neural processing and cognition. While directed functional connectivity methods can provide us with statistical estimates of information exchange between regions, classic exploratory methods may not capture the nonlinear temporal effects that are observed in fMRI-BOLD data during task-evoked neural activity. To address this limitation, we propose a novel methodology that leverages variational cross-mapping analysis, inspired by psychophysiological interactions, to identify directional influence between connected regions of interest. Our approach can help uncover previously unknown patterns of information exchange and account for nonlinear effects, making it a valuable addition to the toolkit of researchers studying brain function. We demonstrate the effectiveness of our method using simulated neurovascular signals and publicly available fMRI data from 680 human participants performing an emotional face processing task. Our results suggest information flows from the occipital face area to the superior temporal sulcus and the fusiform face area, and additionally from the superior temporal sulcus to the fusiform gyrus. These findings are consistent with previously documented effective connectivity findings in face processing and provide new insights into the exploratory analyses of non-linear directed connectivity for task-evoked data. Overall, our findings contribute to advancing our understanding of directed functional connectivity in the brain and demonstrate the potential of our method to uncover previously unknown patterns of information exchange. Author summaryThe advent of large datasets has made it possible for many research groups to explore functional connectivity between different brain regions. The ability to assess directed connectivity between multiple regions from task-evoked neural responses could potentially uncover connections that were not previously hypothesized based on available data. However, classic methods for exploring task-evoked effects often rely on specific assumptions that are frequently violated by the data, such as nonlinearity, stationarity, and separability of cause from effect. Recent studies have attempted to address these issues using sliding window approaches or parameterized forward causal models, but these methods have limitations such as fixed contextual effect windows or restricted search space for forward models. To overcome these challenges, we propose a Bayesian non-parametric cross-mapping method that can address non-linearity and separability while using specially designed covariance functions to address non-stationarity. We demonstrate through simulations that our proposed method can detect pair-wise interacting neural populations with high sensitivity and specificity, and accurately infer changes in connections between tasks in both acyclical and cyclical neural networks. We also show that our method can replicate known connectivity findings about emotional face processing in a publicly available dataset. Thus, our method represents a promising exploratory connectivity tool for cognitive and behavioral neurosciences.

neuroscience↗

bioRxiv2022

Dynamic fluctuations in ascending heart-to-brain modulations under mental stress elicitation

Dynamical information exchange between central and autonomic nervous systems, as referred to functional brain-heart interplay, occurs during emotional and physical arousal. It is well documented that physical and mental stress lead to sympathetic activation. Nevertheless, the role of autonomic inputs in nervous-system-wise communication under mental stress is yet unknown. In this study, we estimated the causal and bidirectional neural modulations between EEG oscillations and peripheral sympathetic and parasympathetic activities using a recently proposed computational framework for a functional brain-heart interplay assessment, namely the sympathovagal synthetic data generation model. Mental stress was elicited in 37 healthy volunteers by increasing their cognitive demands throughout three tasks associated with increased stress levels. Stress elicitation induced an increased variability in sympathovagal markers, as well as increased variability in the directional brain-heart interplay. The observed heart-to-brain interplay was primarily from sympathetic activity targeting a wide range of EEG oscillations, whereas variability in the efferent direction seemed mainly related to EEG oscillations in the gamma band. These findings extend current knowledge on stress physiology, which mainly referred to top-down neural dynamics. Our results suggest that mental stress may not cause an increase in sympathetic activity exclusively as it initiates a dynamic fluctuation within brain-body networks including bidirectional interactions at a brain-heart level. We conclude that directional brain-heart interplay measurements may provide suitable biomarkers for a quantitative stress assessment and bodily feedback may modulate the perceived stress caused by increased cognitive demand.

neuroscience↗

bioRxiv2022

Nonlinear Neural Patterns Are Revealed In High Frequency fNIRS Analysis

Vasomotor tone has a direct implication in oxygen transport to neural tissue, and its dynamics are known to be under constant control from feedback loops with visceral signals, such as sympathovagal interactions. Functional Near Infrared Spectroscopy (fNIRS) offers a nuanced measure of hemoglobin concentration that also comprises high frequencies, though most fNIRS literature studies traditional frequency ranges of hemodynamics (< 0.2 Hz). Linear theory of the hemodynamic response function supports this low frequency band, but we hypothesize that nonlinear effects elicited from the complex system sustaining vasomotor tone presents itself in higher frequencies. To characterize these effects, we investigate how plausible modulation of autoregulatory effects impact aforementioned high frequency components of fNIRS through simulations of mechanistic hemodynamic models. Then, we compare representational similarities between fast (0.2 Hz to 0.6 Hz) and slow (< 0.2 Hz) wave fNIRS to demonstrate that representations acquired through nonlinear analysis are distinct between the frequency bands, whereas when using linear time-domain analysis they are not. Furthermore, by comparing topoplots of significant detectors using nonlinear random vector correlation methods (distance correlation), we demonstrate through a 2nd level group analysis that the median concentrations acquired by fNIRS are independent when analyzing the nonlinearity of their dynamics in their fast and slow component, while they are dependent when utilizing linear time-domain analysis. This study not only provides motivation for researchers to also include higher frequency components in their analysis, but also provides motivation to explore nonlinear effects, e.g. topological entropy. The results of this study motivate future research to explore the nonlinear autoregulatory impacts of regional blood flow and hemoglobin concentrations. Author summaryConventionally, hemodynamic response from induced neural metabolic demand is studied as a slow signal, i.e < 0.2 Hz. Though this may be justified in linear analysis of hemodynamics, vascular mechanics nonlinearly transform the neural metabolic demand to hemodynamic response, where a nonlinear spectral profile may show higher frequency responses. Higher frequency ranges may give insight into local vascular dynamics, particularly their reflection of autoregulatory phenomena, hypothesized to be controlled by sympathovagal feedback loops, thus opening a new avenue for studying brain-body interactions. Functional near infrared spectroscopy (fNIRS) offers a method with high temporal resolution (10 Hz) for observing these effects in hemoglobin concentrations. In this study, we utilize stochastic dynamical simulations of plausible autoregulatory phenomena and an open fNIRS dataset to study differences of fast and slow wave neurovascular representations. We demonstrate that, while linear time-domain analysis provides similar representations of fast and slow wave activity, representations derived from nonlinear methods are not. Furthermore, we show how stress tasks, which may elicit autonomic activity, further desynchronizes nonlinear activity between fast and slow wave signals compared to a non-stress inducing task, demonstrating unique high frequency neurovascular phenomena that is mediated by stress processing.

neuroscience↗

bioRxiv2022

Effects of neural monitoring and control of visceral signals on heart rate, respiration rate, and frontal hemodynamics

Recent studies have established that cardiac and respiratory phases can modulate perception and related neural dynamics. While heart rate and respiratory sinus arrhythmia possibly affect interoception biomarkers, such as heartbeat-evoked potentials, the relative changes in heart rate and cardiorespiratory dynamics in interoceptive processes have not yet been investigated. In this study, we investigated the variation in heart and breathing rates, as well as higher functional dynamics including cardiorespiratory correlation and frontal hemodynamics measured with fNIRS, during a heartbeat counting task. To further investigate the functional physiology linked to changes in vagal activity caused by specific breathing rates, we performed the heartbeat counting task together with a controlled breathing rate task. The results demonstrate that focusing on heartbeats decreases breathing and heart rates in comparison, which may be part of the physiological mechanisms related to "listening" to the heart, the focus of attention, and self-awareness. Focusing on heartbeats was also observed to increase frontal connectivity, supporting the role of frontal structures in the neural monitoring of visceral inputs. However, cardiorespiratory correlation is affected by both heartbeats counting and controlled breathing tasks. Based on these results, we concluded that variations in heart and breathing rates are confounding factors in the assessment of interoceptive abilities and relative fluctuations in breathing and heart rates should be considered to be a mode of covariate measurement of interoceptive processes.

neuroscience↗

bioRxiv2021

Cardiac sympathovagal activity initiates a functional brain-body response to emotional processing

A century-long debate on bodily states and emotions persists. While the involvement of bodily activity in emotion physiology is widely recognized, the specificity and causal role of such activity related to brain dynamics has not yet been demonstrated. We hypothesize that the peripheral neural monitoring and control of cardiovascular activity prompts and sustains brain dynamics during an emotional experience, so these afferent inputs are processed by the brain by triggering a concurrent efferent information transfer to the body. To this end, we investigated the functional brain-heart interplay under emotion elicitation in publicly available data from 62 healthy participants using a computational model based on synthetic data generation of EEG and ECG signals. Our findings show that sympathovagal activity plays a leading and causal role in initiating the emotional response, in which ascending modulations from vagal activity precede neural dynamics and correlate to the reported level of arousal. The subsequent dynamic interplay observed between the central and autonomic nervous systems sustains emotional processing. These findings should be particularly revealing for the psychophysiology and neuroscience of emotions. SignificanceWe investigate the temporal dynamics of brain and cardiac activities in healthy subjects who underwent an emotional elicitation through videos. We demonstrate that, within the first few seconds, emotional stimuli modulate the heart activity, which in turn stimulate an emotion-specific cortical response in the brain. Then, the conscious emotional experience is sustained by a bidirectional brain-heart interplay and information exchange. Moreover, the perceived intensity of an emotional stimulus is predicted by the intensity of neural control regulating the heart activity. These findings may constitute the fundamental knowledge linking neurophysiology and psychiatric disorders, including the link between depressive symptoms and cardiovascular disorders.

neuroscience↗

bioRxiv2020

Use of Bioelectric Impedance Analysis (BIA) as a new method to detect prostate cancer

BackgroundTo determine the accuracy of a novel BIA test endorectal probe. MethodsOne hundred-forty consecutive patient candidates to prostate biopsy and 40 healthy volunteers were selected (NCT03428087). Total PSA and PSA density (PSAD) determinations, digital rectal examination (DRE), and the BIA test were analysed in patients and controls. A 16 cores trans rectal prostate biopsy was performed on all patients with clinical suspicion of PCa after a multiparametric MRI (mMRI) test. The study endpoints were to determine accuracy of BIA test in comparison to PSA, PSAD levels, and mMRI and obtain PCa prediction in candidates to prostate biopsy by BIA test. The Mann-Withney U test, the Wilkoxon rank test, and Holm-Bonferronis method were adopted for statistical analyses, and a computational approach was also applied to differentiate patients with PCa from those with benign disease (BPH). ResultsCombined DRE, TRUS, PSA, and PSAD alone failed to satisfactorily discern patients with PCa from those with BPH (62.86% of discrimination accuracy) and mMRI PIRADS [≥]3 showed a sensitivity of 83% and a specificity of 59%. The accuracy in discerning PCa and BPH increased up to 75% by BIA test (sensitivity 63.33% and specificity 83.75%). ConclusionsThe BIA test is a simple, promising, cheap, and reliable test for PCa non-invasive diagnosis. The novel finger probe may improve PCa detection also in patients with low-risk PCa, thus reducing the need of useless biopsies.

biophysics↗