87 research outputs found

    fNIRS complexity analysis for the assessment of motor imagery and mental arithmetic tasks

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    Conventional methods for analyzing functional near-infrared spectroscopy (fNIRS) signals primarily focus on characterizing linear dynamics of the underlying metabolic processes. Nevertheless, linear analysis may underrepresent the true physiological processes that fully characterizes the complex and nonlinear metabolic activity sustaining brain function. Although there have been recent attempts to characterize nonlinearities in fNIRS signals in various experimental protocols, to our knowledge there has yet to be a study that evaluates the utility of complex characterizations of fNIRS in comparison to standard methods, such as the mean value of hemoglobin. Thus, the aim of this study was to investigate the entropy of hemoglobin concentration time series obtained from fNIRS signals and perform a comparitive analysis with standard mean hemoglobin analysis of functional activation. Publicly available data from 29 subjects performing motor imagery and mental arithmetics tasks were exploited for the purpose of this study. The experimental results show that entropy analysis on fNIRS signals may potentially uncover meaningful activation areas that enrich and complement the set identified through a traditional linear analysis

    Uncovering hemispheric asymmetry and directed oscillatory brain-heart interplay in anxiety processing: an fMRI study

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    Brain-heart interactions (BHI) are critical for generating and processing emotions, including anxiety. Understanding specific neural correlates would be instrumental for greater comprehension and potential therapeutic interventions of anxiety disorders. While prior work has implicated the pontine structure as a central processor in cardiac regulation in anxiety, the distributed nature of anxiety processing across the cortex remains elusive. To address this, we performed a whole-brain-heart analysis using the full frequency directed transfer function to study resting-state spectral differences in BHI between high and low anxiety groups undergoing fMRI scans. Our findings revealed a hemispheric asymmetry in low-frequency interplay (0.05 Hz - 0.15 Hz) characterized by ascending BHI to the left insula and descending BHI from the right insula. Furthermore, we provide evidence supporting the “pacemaker hypothesis”, highlighting the pons’ function in regulating cardiac activity. Higher frequency interplay (0.2 Hz - 0.4Hz) demonstrate a preference for ascending interactions, particularly towards ventral prefrontal cortical activity in high anxiety groups, suggesting the heart’s role in triggering a cognitive response to regulate anxiety. These findings highlight the impact of anxiety on BHI, contributing to a better understanding of its effect on the resting-state fMRI signal, with further implications for potential therapeutic interventions in treating anxiety disorders

    Nonlinear neural patterns are revealed in high frequency functional near infrared spectroscopy analysis

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    Functional Near Infrared Spectroscopy (fNIRS) is a useful tool for measuring hemoglobin concentration. Linear theory of the hemodynamic response function supports low frequency analysis (<0.2 Hz). However, we hypothesized that nonlinearities, arising from the complex neurovascular interactions sustaining vasomotor tone, may be revealed in higher frequency components of fNIRS signals. To test this hypothesis, we simulated nonlinear hemodynamic models to explore how blood flow autoregulation changes may alter evoked neurovascular signals in high frequencies. Next, we analyzed experimental fNIRS data to compare neural representations between fast (0.2–0.6 Hz) and slow (<0.2 Hz) waves, demonstrating that only nonlinear representations quantified by sample entropy are distinct between these frequency bands. Finally, we performed group-level distance correlation analysis to show that the cortical distribution of activity is independent only in the nonlinear analysis of fast and slow waves. Our study highlights the importance of analyzing nonlinear higher frequency effects seen in fNIRS for a comprehensive analysis of cortical neurovascular activity. Furthermore, it motivates further exploration of the nonlinear dynamics driving regional blood flow and hemoglobin concentration

    Multivariate Pattern Analysis of Entropy estimates in Fast- and Slow-Wave Functional Near Infrared Spectroscopy: A Preliminary Cognitive Stress study

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    Functional near infrared spectroscopy (fNIRS) is a modality that can measure shallow cortical brain signals and also contains pulsatile oscillations that originate from heartbeat dynamics. In particular, while fNIRS slow waves (0 Hz to 0.6 Hz) refer to the standard hemodynamic signal, fast-wave (0.8 Hz to 3 Hz) fNIRS signals refer to cardiac oscillations. Using a cognitive stress experiment paradigm with mental arithmetic, the aim of this study was to assess differences in cortical activity when using slow-wave or fast-wave fNIRS signals. Furthermore, we aimed to see whether fNIRS fast and slow waves provide different information to discriminate mental arithmetic tasks from baseline. We used data from 10 healthy subjects from an open dataset performing mental arithmetic tasks and assessed fNIRS signals using mean values in the time domain, as well as complexity estimates including sample, fuzzy, and distribution entropy. A searchlight representational similarity analysis with pairwise t-test group analysis was performed to compare the representational dissimilarity matrices of each searchlight center. We found significant representational differences between fNIRS fast and slow waves for all complexity estimates, at different brain regions. On the other hand, no statistical differences were observed for mean values. We conclude that entropy analysis of fNIRS data may be more sensitive than traditional methods like mean analysis at detecting the additional information provided by fast-wave signals for discriminating mental arithmetic tasks and warrants further research

    Complexity Analysis on Functional-Near Infrared Spectroscopy Time Series: A Preliminary Study on Mental Arithmetic

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    It is well known that physiological systems show complex and nonlinear behaviours. In spite of that, functional near-infrared spectroscopy (fNIRS) is usually analyzed in the time and frequency domains with the assumption that metabolic activity is generated from a linear system. To leverage the full information provided by fNIRS signals, in this study we investigate topological entropy in fNIRS series collected from 10 healthy subjects during mental mental arithmetic task. While sample entropy and fuzzy entropy were used to estimate time series irregularity, distribution entropy was used to estimate time series complexity. Our findings show that entropy estimates may provide complementary characterization of fNIRS dynamics with respect to reference time domain measurements. This finding paves the way to further investigate functional activation in fNIRS in different case studies using nonlinear and complexity system theory

    The design and in vivo testing of a locally stiffness-matched porous scaffold

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    An increasing volume of work supports utilising the mechanobiology of bone for bone ingrowth into a porous scaffold. However, typically during in vivo testing of implants, the mechanical properties of the bone being replaced are not quantified. Consequently there remains inconsistencies in the literature regarding ‘optimum’ pore size and porosity for bone ingrowth. It is also difficult to compare ingrowth results between studies and to translate in vivo animal testing to human subjects without understanding the mechanical environment. This study presents a clinically applicable approach to determining local bone mechanical properties and design of a scaffold with similar properties. The performance of the scaffold was investigated in vivo in an ovine model. The density, modulus and strength of trabecular bone from the medial femoral condyle from ovine bones was characterised and power-law relationships were established. A porous titanium scaffold, intended to maintain bone mechanical homeostasis, was additively manufactured and implanted into the medial femoral condyle of 6 ewes. The stiffness of the scaffold varied throughout the heterogeneous structure and matched the stiffness variation of bone at the surgical site. Bone ingrowth into the scaffold was 10.73 ± 2.97% after 6 weeks. Fine woven bone, in the interior of the scaffold, and intense formations of more developed woven bone overlaid with lamellar bone at the implant periphery were observed. The workflow presented will allow future in vivo testing to test specific bone strains on bone ingrowth in response to a scaffold and allow for better translation from in vivo testing to commercial implants

    Statistical shape modelling of the thoracic spine for the development of pedicle screw insertion guides

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    Spinal fixation and fusion are surgical procedures undertaken to restore stability in the spine and restrict painful or degenerative motion. Malpositioning of pedicle screws during these procedures can result in major neurological and vascular damage. Patient-specific surgical guides offer clear benefits, reducing malposition rates by up to 25%. However, they suffer from long lead times and the manufacturing process is dependent on third-party specialists. The development of a standard set of surgical guides may eliminate the issues with the manufacturing process. To evaluate the feasibility of this option, a statistical shape model (SSM) was created and used to analyse the morphological variations of the T4–T6 vertebrae in a population of 90 specimens from the Visible Korean Human dataset (50 females and 40 males). The first three principal components, representing 39.7% of the variance within the population, were analysed. The model showed high variability in the transverse process (~ 4 mm) and spinous process (~ 4 mm) and relatively low variation (< 1 mm) in the vertebral lamina. For a Korean population, a standardised set of surgical guides would likely need to align with the lamina where the variance in the population is lower. It is recommended that this standard set of surgical guides should accommodate pedicle screw diameters of 3.5–6 mm and transverse pedicle screw angles of 3.5°–12.4°

    Characterization of ICRISAT-bred Pearl Millet Restorer Parents

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    Pearl millet [Pennisetum glaucum (L) R. Br.], primarily grown for grain production on more than 26 m ha in the arid and semi-arid tropical (SAT) regions of Asia and Africa, is a highly nutritious cereal crop with wide agro- ecological adaptation. India, the largest producer of this crop at the global level, cultivates pearl millet on about >9 million ha contributing to more than 90% area of the crop in the Asian region. It is a highly cross pollinated crop, and single-cross hybrids generally give 20-30% more yield than open pollinated varieties (Rai et al. 2006). With the availability of commercially exploitable cytoplasmic-nuclear male sterility (CMS) systems in pearl millet, the national agricultural research system (NARS) and the private seed sector in India focused their breeding programs on hybrid development. This led to the development and adoption of a diverse range and large number of hybrids (> 80 in 2011) and now occupying > 4.5 m ha area, which is about half the total pearl millet area being cultivated in India (Rai et al. 2006). ICRISAT also aligned its breeding program to developing promising hybrid parental lines in order to support the Asian pearl millet hybrid program..
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