Brain Imaging Technologies Research Articles

The future of quantum technologies for brain imaging.

The neurosciences have pioneered the use of quantum technologies for sensing and imaging the brain. Next-generation technologies promise routes towards low-cost, wearable imaging devices with high spatial and temporal resolution.

Maternal Nutrition during Pregnancy and Offspring Brain Development: Insights from Neuroimaging.

Maternal nutrition during pregnancy is known to be important for offspring growth and health and has also been increasingly recognized for shaping offspring brain development. On the other hand, recent advancements in brain imaging technology have provided unprecedented insights into fetal, neonatal, and pediatric brain morphometry and function. This review synthesizes the current literature regarding the impact of maternal nutrition on offspring brain development, with a specific focus on findings from neuroimaging studies. The diverse effects of maternal nutrients intake or status during pregnancy on neurodevelopmental outcomes in children are discussed. Neuroimaging evidence showed associations between maternal nutrition such as food categories, macronutrients, and micronutrients including vitamins and minerals during pregnancy and child brain imaging features measured using imaging techniques such as ultrasound, magnetic resonance imaging (MRI), electroencephalography (EEG), and magnetoencephalography (MEG). This review demonstrates the capability of neuroimaging in characterizing how maternal nutrition during pregnancy impacts structure and function of the developing brain that may further influence long-term neuropsychological, cognitive, and behavioral outcomes in children. It aims to inspire future research utilizing neuroimaging to deepen our understanding of the critical impacts of maternal nutrition during pregnancy on offspring brain development.

Artistic Education in Jerzy Vetulani’s Perspective: A Comparative Analysis With Irena Wojnar’s Polish Concept of Aesthetic Education

RESEARCH OBJECTIVE: This article aims to present the anthropological, aesthetic, and pedagogical foundations of Jerzy Vetulani’s postulate of artistic education and compare it with Irena Wojnar’s concept of aesthetic education. THE RESEARCH PROBLEM AND METHODS: The research questions are: What are the anthropological, aesthetic, and pedagogical foundations of Vetulani’s postulate of artistic education? Is there a similarity between Vetulani’s postulate and Wojnar’s proposal of education through art? To achieve these objectives, the content analysis method based on Karolina Szczepaniak’s model was used. THE PROCESS OF ARGUMENTATION: Starting with Vetulani’s neurobiological views, the article first presents art as a defining characteristic of homo sapiens and a key activator of the human brain, especially its cognitive functions. It then discusses the pedagogical assumptions of Vetulani’s postulate. The comparison between Vetulani’s and Wojnar’s concepts is made by examining their anthropological assumptions and the role of art in human development. RESEARCH RESULTS: According to Vetulani, the relationship between humans and art is bio- logically determined, with art being essential for achieving full humanity. Both Vetulani and Wojnar view humans as inherently open to art, which plays a significant role in the upbringing process. CONCLUSIONS, RECOMMENDATIONS, AND APPLICABLE VALUE OF RESEARCH: Vetulani and Wojnar both emphasize the importance of art in human education. Brain imaging technology can enhance traditional aesthetic education. Activating the brain’s cognitive functions through art, particularly cognitive attention as highlighted by Vetulani, can be beneficial in treating common concentration disorders in children and adolescents.

Naturalistic approach to investigate the neural correlates of a laundry cycle with and without fragrance.

Advancements in brain imaging technologies have facilitated the development of "real-world" experimental scenarios. In this study, participants engaged in a household chore - completing a laundry cycle - while their frontal lobe brain activity was monitored using fNIRS. Participants completed this twice using both fragranced and unfragranced detergent, to explore if fNIRS is able to identify any differences in brain activity in response to subtle changes in stimuli. Analysis was conducted using Automatic IDentification of functional Events (AIDE) software and fNIRS correlation-based signal improvement (CBSI). Results indicated that brain activity, particularly in the right frontopolar and occasionally the left dorsolateral prefrontal cortex, was more pronounced and frequent with the unfragranced detergent than the fragranced. This suggests that completing tasks in an environment where a pleasant and relaxing fragrance is present might be less effortful compared to an odourless environment.

EXPLORING THE ROLE OF NEUROMARKETING IN CONSUMER DECISION-MAKING

This research delves into the emerging field of neuromarketing, examining its role in understanding consumer decision-making processes. Neuromarketing integrates neuroscience principles with marketing strategies to uncover the subconscious factors that influence consumer behavior. Through techniques such as brain imaging technologies, biometric measurements, and implicit association tests, marketers can gain insights into the emotional and cognitive processes that drive purchasing decisions. This study highlights the significance of emotional engagement, memory recall, and decision fatigue in shaping consumer choices. By exploring how emotional connections enhance brand loyalty and the role of memory in brand preference, the research underscores the importance of crafting effective marketing campaigns that resonate with consumers on a deeper level. The findings address the challenges posed by decision fatigue in today’s complex marketplace, emphasizing the need for simplified choices to facilitate consumer decision-making. This research aims to provide a comprehensive understanding of how neuromarketing can inform marketing strategies, fostering more meaningful connections between brands and consumers while promoting ethical considerations in the application of neuroscience in marketing practices.

Integrative approach of omics and imaging data to discover new insights for understanding brain diseases.

Treatments that can completely resolve brain diseases have yet to be discovered. Omics is a novel technology that allows researchers to understand the molecular pathways underlying brain diseases. Multiple omics, including genomics, transcriptomics and proteomics, and brain imaging technologies, such as MRI, PET and EEG, have contributed to brain disease-related therapeutic target detection. However, new treatment discovery remains challenging. We focused on establishing brain multi-molecular maps using an integrative approach of omics and imaging to provide insights into brain disease diagnosis and treatment. This approach requires precise data collection using omics and imaging technologies, data processing and normalization. Incorporating a brain molecular map with the advanced technologies through artificial intelligence will help establish a system for brain disease diagnosis and treatment through regulation at the molecular level.

Photoacoustic imaging in brain disorders: Current progress and clinical applications

AbstractOver the past few decades, the number of patients with neurological diseases has increased significantly, posing huge challenges and opportunities for the development of brain imaging technology. As a hybrid imaging method combining optical excitation and acoustic detection techniques, photoacoustic tomography (PAT), has experienced rapid development, due to high optical contrast and spatial resolution at depth inside tissues. With the development of lasers, ultrasonic detectors, and data computations, PAT has been widely applied for the diagnosis of oncology, dermatosis, etc. However, the energy of light and ultrasound would be greatly attenuated while penetrating the skull, due to the reflection, absorption, and scattering effects, resulting in limited application of PAT in brain imaging. In this review, we summarized the achievements of PAT and its application in the detection of brain diseases including glioma, stroke, traumatic brain injury, Alzheimer's disease, epilepsy, and Parkinson's disease. Moreover, various PAT systems and multi‐modality photoacoustic imaging are introduced for potential clinical applications. Finally, the challenges and current limitations of PAT for further brain imaging are also discussed.

Changes in temporal lobe activation during a sound stimulation task in patients with sensorineural tinnitus: a multi-channel near-infrared spectroscopy study

BackgroundThe subjective sign of a serious pandemic in human work and life is mathematical neural tinnitus. fNIRS (functional near-infrared spectroscopy) is a new non-invasive brain imaging technology for studying the neurological activity of the human cerebral cortex. It is based on neural coupling effects. This research uses the fNIRS approach to detect differences in the neurological activity of the cerebral skin in the sound stimulation mission in order to better discriminate between the sensational neurological tinnitus.MethodsIn the fNIRS brain imaging method, 14 sensorineural tinnitus sufferers and 14 healthy controls listened to varied noise and quiet for fNIRS data collection. Linear fitting was employed in MATLAB to eliminate slow drifts during preprocessing and event-related design analysis. The false discovery rate (FDR) procedure was applied in IBM SPSS Statistics 26.0 to control the false positive rate in multiple comparison analyses.ResultsWhen the ill group and the healthy control group were stimulated by pink noise, there was a significant difference in blood oxygen concentration (P < 0.05), and the healthy control group exhibited a high activation, according to the fNIRS measurement data. The blood oxygen concentration level in the patient group was dramatically enhanced after one month of acupuncture therapy under the identical stimulation task settings, and it was favorably connected with the levels of THI and TEQ scales.ConclusionsUsing sensorineural tinnitus illness as an example, fNIRS technology has the potential to disclose future pathological study on subjective diseases throughout time. Other clinical disorders involving the temporal lobe and adjacent brain areas may also be examined, in addition to tinnitus-related brain alterations.

Multiparametric Brain Hemodynamics Imaging Using a Combined Ultrafast Ultrasound and Photoacoustic System.

Studying brain-wide hemodynamic responses to different stimuli at high spatiotemporal resolutions can help gain new insights into the mechanisms of neuro- diseases and -disorders. Nonetheless, this task is challenging, primarily due to the complexity of neurovascular coupling, which encompasses interdependent hemodynamic parameters including cerebral blood volume (CBV), cerebral blood flow (CBF), and cerebral oxygen saturation (SO2). The current brain imaging technologies exhibit inherent limitations in resolution, sensitivity, and imaging depth, restricting their capacity to comprehensively capture the intricacies of cerebral functions. To address this, a multimodal functional ultrasound and photoacoustic (fUSPA) imaging platform is reported, which integrates ultrafast ultrasound and multispectral photoacoustic imaging methods in a compact head-mountable device, to quantitatively map individual dynamics of CBV, CBF, and SO2 as well as contrast agent enhanced brain imaging at high spatiotemporal resolutions. Following systematic characterization, the fUSPA system is applied to study brain-wide cerebrovascular reactivity (CVR) at single-vessel resolution via relative changes in CBV, CBF, and SO2 in response to hypercapnia stimulation. These results show that cortical veins and arteries exhibit differences in CVR in the stimulated state and consistent anti-correlation in CBV oscillations during the resting state, demonstrating the multiparametric fUSPA system's unique capabilities in investigating complex mechanisms of brain functions.

Paediatric hydrocephalus.

Hydrocephalus is classically considered as a failure of cerebrospinal fluid (CSF) homeostasis that results in the active expansion of the cerebral ventricles. Infants with hydrocephalus can present with progressive increases in head circumference whereas older children often present with signs and symptoms of elevated intracranial pressure. Congenital hydrocephalus is present at or near birth and some cases have been linked to gene mutations that disrupt brain morphogenesis and alter the biomechanics of the CSF-brain interface. Acquired hydrocephalus can develop at any time after birth, is often caused by central nervous system infection or haemorrhage and has been associated with blockage of CSF pathways and inflammation-dependent dysregulation of CSF secretion and clearance. Treatments for hydrocephalus mainly include surgical CSF shunting or endoscopic third ventriculostomy with or without choroid plexus cauterization. In utero treatment of fetal hydrocephalus is possible via surgical closure of associated neural tube defects. Long-term outcomes for children with hydrocephalus vary widely and depend on intrinsic (genetic) and extrinsic factors. Advances in genomics, brain imaging and other technologies are beginning to refine the definition of hydrocephalus, increase precision of prognostication and identify nonsurgical treatment strategies.

Udo Dannlowski: Brain structure and function in the long-term course of mental disorders

Udo Dannlowski is a psychiatrist, psychologist, and translational neuroimaging researcher whose work intersects clinical psychiatry, genetics, data science, and systems neuroscience. His academic endeavors are driven by a commitment to unraveling the complex biological and genetic mechanisms underlying long-term disease trajectories of affective disorders, including depression and anxiety. Dannlowski's use of brain imaging technologies, such as multimodal MRI, to explore the structural and functional anomalies in patients with these disorders in longitudinal cohorts over several years of follow-up with machine learning techniques has significantly advanced our understanding of brain mechanisms in mental disorders. Dannlowski is recognized for contributing to psychiatry and neuroscience, substantially impacting theoretical understanding and clinical practice. Since 2019, he has been heading the Institute for Translational Psychiatry in Münster, Germany, together with the clinical Section for Transition Psychiatry at the Department for Mental Health. We are privileged to present the Genomic Press interview with Professor Dannlowski, who has offered to share insights from his esteemed career and personal experiences for our readers' benefit.

The parallax: The possible errors in the quantification of human decision-making behavior in the experiment of neuroeconomics-A perspective from psychoanalysis.

With the development of neuroscience and technology, economics, which focuses on the selection and decision-making of human behavior, has also entered the field of neuroeconomics. Based on rational biological humans, neuroeconomics assumes that humans are rational biological individuals and behaviors of biological humans can be monitored and quantified in the nervous system through brain imaging technologies such as functional MRI and positron emission tomography. As an emerging discipline, neuroeconomics inevitably encounters obstacles in methodology and epistemology, showing excessive constraints in its understanding of rationality and facing basic conceptual disputes on the theoretical basis of "clear uncertainty monism." In neuroeconomics experiments, measurability will inevitably be traced back to quantification, but when faced with a complex and ever-changing social field, what can be predicted is only probability rather than behavior. Not all human behaviors and decisions can be quantified. Therefore, such research may be biased. Psychoanalysis, a major branch of psychology that is quite similar to neuroeconomics research in subject and object, can greatly correct these basic concepts. Seen from the perspective of psychoanalysis, the existence of these unquantifiable things conversely plays a decisive role and cannot be ignored. This article analyzes the core rational behavior detection of neuroeconomics from the perspective of psychoanalysis and proposes suggestions from the epistemology and methodology of experimental design as well as basic concept discrimination and so forth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Deciphering the Mysteries of Aromatic Incentive of Lemongrass Essential Oil Inhalation on Brain Activities in Healthy Adults

With the rapid advancement in brain science and imaging technology, there is a growing interest in investigating the connection between aromatherapy and its effects on the brain. This study employs Quantitative Electroencephalography (QEEG) to examine the impacts of exposure to the fragrance of lemongrass essential oil (LEO) on specific brain regions. The objective is to assess the influence of inhaling the scent of LEO on EEG patterns in awake, healthy adult females using power spectral analysis. In this experimental study, 30 healthy adult female participants were exposed to a water mist as a control after baseline recordings. Subsequently, participants inhaled LEO aromatic mist diffused into the room air, and their brain activity was recorded. Data from specific scalp electrode readings were analyzed using the Wilcoxon Matched-Pairs Signed Rank Test. The results revealed a significant increase in the relative power of alpha waves in the prefrontal, frontal and occipital regions, accompanied by heightened theta power and decreased beta power. These results suggests that the inhalation of LEO oil modulates brainwave activities, inducing relaxing effects on the brain.

Investigation of Medical Image Technology Based on Big Data Neuroscience in Exercise Rehabilitation.

The purpose of this article is to combine the functional information of CT images with the anatomical and soft tissue information of MRI through image fusion technology, providing more detailed information for rehabilitation treatment and thus providing a scientific basis for clinical applications and better training plans. In this paper, functional brain imaging technology combining CT (computed tomography) and MRI (magnetic resonance imaging) was used for image fusion, and SURF (accelerated robust feature) feature points of images were extracted. In this study, 40 patients with mild and moderate closed traumatic brain injury admitted to the rehabilitation department of a rehabilitation center from 2018 to 2022 were selected as the research objects. Compared with using only CT images and MRI images for brain injury diagnosis, the fusion image had a higher detection rate of abnormal brain injury diagnosis, with a detection rate of 97.5%. When using fused images for the diagnosis of abnormal brain injury, the patient's exercise rehabilitation effect was better. CT and MRI image fusion technology had a high diagnostic accuracy for brain injury, which could timely guide doctors in determining exercise rehabilitation plans and help improve the effectiveness of patient exercise rehabilitation.

M2DC: A Meta-Learning Framework for Generalizable Diagnostic Classification of Major Depressive Disorder.

Psychiatric diseases are bringing heavy burdens for both individual health and social stability. The accurate and timely diagnosis of the diseases is essential for effective treatment and intervention. Thanks to the rapid development of brain imaging technology and machine learning algorithms, diagnostic classification of psychiatric diseases can be achieved based on brain images. However, due to divergences in scanning machines or parameters, the generalization capability of diagnostic classification models has always been an issue. We propose Meta-learning with Meta batch normalization and Distance Constraint (M2DC) for training diagnostic classification models. The framework can simulate the train-test domain shift situation and promote intra-class cohesion, as well as inter-class separation, which can lead to clearer classification margins and more generalizable models. To better encode dynamic brain graphs, we propose a concatenated spatiotemporal attention graph isomorphism network (CSTAGIN) as the backbone. The network is trained for the diagnostic classification of major depressive disorder (MDD) based on multi-site brain graphs. Extensive experiments on brain images from over 3261 subjects show that models trained by M2DC achieve the best performance on cross-site diagnostic classification tasks compared to various contemporary domain generalization methods and SOTA studies. The proposed M2DC is by far the first framework for multi-source closed-set domain generalizable training of diagnostic classification models for MDD and the trained models can be applied to reliable auxiliary diagnosis on novel data.

CE Workshop 05: Technology and Cognition: Examining new trends and opportunities for neuropsychology

Abstract &amp; Learning Objectives:Advances in technologies continue to offer new opportunities for understanding brain functioning and brain-behavior interactions. The clinical application of these technologies continues to require the understanding of both the benefits and limitations of integrating these novel methodologies. This workshop will provide an overview of several emerging and established technologies in neuropsychological assessment and rehabilitation. This will include discussion of portable brain imaging technologies, neuromodulation technologies, virtual reality simulation and various brain-computer interface devices. In addition, we will discuss how clinical application of these novel devices offer opportunities for growing knowledge in new areas of analysis (i.e., machine learning analysis) and interdisciplinary collaborations. Upon conclusion of this course, learners will be able to: 1.Identify 3 technologies that are currently employed in neuropsychological research2.Assess the strengths and weakness of novel technologies for brain-behavior interface3.Examine current clinical applications of neuromodulation technologies and portable brain-imaging technologies

Differential features of early childhood motor skill development and working memory processing: evidence from fNIRS.

The study investigated the differential characteristics associated with motor skill development and working memory processing during early childhood, thereby providing insights for understanding motor learning and cognitive development in young children. In total, 101 preschool children (age: 4-6 years) were recruited for this study. The motor skill development level and the working memory capacity of the children were assessed using the MOBAK Motor Development Assessment Scale and a block task paradigm, respectively. Functional near-infrared spectroscopy brain imaging technology was used to monitor hemodynamic signals in the prefrontal cortex (PFC) of the children while they completed different memory tasks. MATLAB software and the Homer2 plugin were used to calculate the oxygenated hemoglobin (Oxy-Hb) concentration in relevant brain regions during the tasks. (1) The low motor skill group exhibited significantly lower accuracy during the three-memory load condition than during the two-memory load condition. Under both two-memory and three-memory load conditions, the high motor skill group exhibited significantly higher accuracy than the low motor skill group. (2) Significant differences in the Oxy-Hb concentration were observed in the left dorsolateral PFC (L-DLPFC), and right and left triangular part of the Broca's area (R-PTBA and L-PTBA, respectively) between the two memory difficulty levels for the high motor skill group. The Oxy-Hb concentration was significantly higher during the three-memory load condition than during the two-memory load condition. Under the two-memory load condition, the high motor skill group exhibited significantly higher Oxy-Hb concentration in the L-DLPFC and L-PTBA regions than in the low motor skill group. Under the three-memory load condition, the high motor skill group exhibited significantly higher Oxy-Hb concentration in the L-DLPFC, R-PTBA, and L-PTBA regions than the low motor skill group. A close association was observed between the motor skill levels and working memory in young children, with higher motor skill levels being associated with more pronounced brain activation patterns during working memory tasks.

The Intersections of Artificial Intelligence, Brain Imaging Tools and Diagnostics for Neurodegenerative Diseases

This paper explores the fascinating topics of artificial intelligence (AI), brain imaging tools, and diagnostics for neurodegenerative diseases. By examining the advancements in AI algorithms and their integration with cutting-edge brain imaging technologies, this publication displays the potential of these approaches to revolutionize the diagnoses and understanding of neurodegenerative disorders. Through an analysis of recent studies, this paper highlights the significant progress made by utilizing AI-powered tools, enhancing the accuracy, efficiency, and early detection of conditions such as Alzheimer's, Parkinson's, and Huntington's diseases. Ultimately, this research underscores the transformative role that AI and brain imaging can play in the field of neurodegenerative disease diagnostics, paving the way for improved patient care and better outcomes.&#x0D; In addition to exploring the current state of AI and brain imaging tools in neurodegenerative disease diagnostics, my paper also dives into the potential future applications and challenges in this rapidly evolving field. It discusses the ethics of AI-driven diagnostic methods, emphasizing the importance of ensuring patient privacy, informed consent, and equitable access to these technologies.

Research on the effects of gaming on the brain

In recent decades, with the help of computer brain imaging technology and other advanced science and technology, a wealth of research achievements has been made in brain science related to games. These achievements explain the deep mechanism of games and provide scientific theoretical basis for the application of games. This paper analyses the effects of games on the brain. On the one hand, it focuses on the analysis and discussion of the positive effects on the brain in four aspects, including games make the brain excited, become more intelligent, improve agility skills, and improve observation. On the other hand, it summarizes the negative effects of excessive games on the brain, including the structural changes of the brain, mental malaise and brain stunting. In the end, the paper summarizes and summarizes the full text.

Diagnosis of motor function injury based on near-infrared spectroscopy brain imaging (fNIRS) technology

Most clinical stroke patients may have difficulty moving, affecting their self-care ability and quality of life, and causing serious interference with the normal life and work of other family members. At present, in clinical literature, researchers provide functional training for patients with motor disorders through repeated and effective training, which can ultimately effectively promote the recovery of limb function. Therefore, the near-infrared spectroscopy imaging technology (fNIRS) used in this study combines the diagnosis of sports injury with the mechanism of brain function. FNIRS technology has many advantages, such as fast, and non-invasive, and has shown great value in detecting brain activity. Therefore, it has become a promising method in the biomedical field, especially in the field of brain science. Based on the clinical effects of sports injury treatment, fNIRS technology is used to detect the hemodynamic changes of hemoglobin circulation in the patient's brain tissue during training, and to detect the brain activity mechanism in the exercise mechanism, providing a basis for the clinical application of this method.