Brain Imaging Technologies Research Articles

Trajectory of Terminal Lucidity Phenomenon: Systematic Review

Terminal lucidity is a phenomenon characterized by the sudden reappearance of cognitive clarity in patients with severe cognitive impairment, such as dementia, near death. This systematic study aims to examine various aspects of the terminal lucidity phenomenon, from biological mechanisms, psychosocial impacts, to spiritual dimensions, especially through the lens of an Islamic perspective. The study was conducted using the Systematic Literature Review (SLR) approach according to the PRISMA guidelines, with an analysis of 82 open access articles from 2015 to 2024. The selection process included screening of titles, abstracts, and full texts, resulting in 40 articles that met the inclusion and exclusion criteria. The results of the analysis revealed that although biological mechanisms such as changes in neurotransmitters and brain electrical activity require further study, the terminal lucidity phenomenon has important implications for palliative care. This moment of clarity provides an opportunity for patients to communicate meaningfully and for families to say goodbye with hope. In addition to the medical aspect, terminal lucidity also reflects a significant spiritual dimension, where Islamic values interpret this phenomenon as divine intervention and a moment of final forgiveness. The findings of this study emphasize the need for a holistic approach that integrates emotional support, physical care, and spiritual guidance in end-of-life counseling. Further research is recommended to investigate the pharmacological mechanisms and the use of brain imaging technology to deepen the understanding of this phenomenon, so that the quality of patient care at the end of life can continue to be improved. This study makes an important contribution to expanding the multidisciplinary understanding of terminal lucidity and encourages the development of holistic palliative care guidelines, so that medical, psychosocial, and spiritual interventions can be optimized to accompany patients and their families to achieve a better quality of life.

SYSTEMIC LITERATURE REVIEW: NEUROLINGUISTICS IN LANGUAGE PROCESSING IN CHILDREN WITH AUTISM SPECTRUM DISORDER (ASD)

Neurolinguistic research on language processing in children with autism spectrum disorder (ASD) has progressed markedly in the last ten years. The variability in research methodologies and results frequently hinders the formation of a holistic comprehension of advancements in this domain. This study is to do a comprehensive literature review to summarize and evaluate publication trends, principal subjects, and commonly employed methodologies in neurolinguistic research focused on language processing in children with ASD. This analysis also indicates underexplored research areas and gaps that can inform future investigations. This research used a Systematic Literature Review (SLR) methodology in accordance with PRISMA criteria to examine academic papers from many databases, including Google Scholar and Scopus. The research identifies numerous significant trends, such as heightened focus on lexical and semantic perception impairments, the application of brain imaging technology, and linguistics-based therapies. These findings are anticipated to provide a reference for more targeted future study and facilitate the development of therapies designed to improve language skills in children with ASD.

CVR-BBI: an open-source VR platform for multi-user collaborative brain to brain interfaces.

As brain imaging and neurofeedback technologies advance, the brain-to-brain interface (BBI) has emerged as an innovative field, enabling in-depth exploration of cross-brain information exchange and enhancing our understanding of collaborative intelligence. However, no open-source virtual reality (VR) platform currently supports the rapid and efficient configuration of multi-user, collaborative BBIs. To address this gap, we introduce the Collaborative Virtual Reality Brain-to-Brain Interface (CVR-BBI), an open-source platform consisting of a client and server. The CVR-BBI client enables users to participate in collaborative experiments, collect electroencephalogram (EEG) data, and manage interactive multisensory stimuli within the VR environment. Meanwhile, the CVR-BBI server manages multi-user collaboration paradigms, and performs real-time analysis of the EEG data. We evaluated the CVR-BBI platform using the SSVEP paradigm and observed that collaborative decoding outperformed individual decoding, validating the platform's effectiveness in collaborative settings. The CVR-BBI offers a pioneering platform that facilitates the development of innovative BBI applications within collaborative VR environments, thereby enhancing the understanding of brain collaboration and cognition. CVR-BBI is released as an open-source platform, with its source code being available at https://github.com/DILIU1/CVR-BBI.

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.

Neuroethical issues in adopting brain imaging for personalized chronic pain management: Attitudes of people with lived experience of chronic pain

ABSTRACT Background Pain is an individual and subjective experience that places a burden on individuals to convince others they have pain. Brain imaging technologies can potentially inform pain management but raise neuroethical questions. Aims We examined the degree of endorsement and concerns of adults in Canada with chronic pain regarding the use of brain imaging to detect and treat chronic pain in six areas: new brain imaging technologies, brain data privacy, stigma, treatment, objective representations of pain, and dismissing pain self-reports. Results An online survey was completed by 349 Canadian adults living with chronic pain. Most respondents were open to using brain imaging for diagnostics, prediction, and therapeutic decision making (>90%). More than half of respondents felt that a brain scan would give them more confidence in their diagnosis and treatment plans and that health care providers would be more likely to believe they had chronic pain. However, they worried that brain scans could be used to dismiss their pain self-report. Most respondents felt there were policies to protect their brain data, but 40% were concerned about privacy and brain scan use against them by their employers/insurers. Although most respondents felt that a brain scan could represent their pain and suffering, 80% disagreed that their pain is only real if seen in a brain scan. Conclusions People with chronic pain recognize the potential benefits of brain imaging but are concerned about data security and dismissal of their self-reported pain. Our data align with previous recommendations to use brain imaging as an adjunct to pain self-reports but not as a replacement for the same.

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.

Research hotspots and trends of neuroimaging in social anxiety: a CiteSpace bibliometric analysis based on Web of Science and Scopus database.

This study focused on the research hotspots and development trends of the neuroimaging of social anxiety (SA) in the past 25 years. We selected 1,305 studies on SA neuroimaging from the Web of Science and Scopus from January 1998 to December 2023. CiteSpace was used to analyze the number of published articles visually, cited references, cooperation among authors and institutions, co-occurrence of keywords, clustering of keywords, burst of keywords, and time zone of co-occurring keywords. A total of 1,305 articles were included, and the annual number of articles published over nearly 25 years showed the overall trend is on the rise. The analysis of author and institutional collaboration reveals that most authors collaborate closely. Among them, the team led by Pine, Daniel S published 59 articles, making it the most central team. Harvard University is identified as the most central institution in this network. The research hotspots can be categorized into four areas: research techniques, cognitive processing research areas, core brain regions and brain networks, and the neural predictors of treatment outcomes in SA. The most recent burst keywords are "cognitive behavioral therapy," "systematic review," "machine learning," "major clinical study," "transcranial direct current stimulation," "depression," and "outcome assessment," which provided clues on research frontiers. Based on the burst map and keyword time zone map, it appears that exploring the activity of brain regions involved in cognitive processing, such as face processing and attentional bias, as well as the comorbidity of SA and depression, through brain imaging technology, using brain signals as predictors of treatment outcomes in SA. This study conducted a comprehensive, objective, and visual analysis of publications, and revealed hot topics and trends concerning the study of the brain mechanism of SA from 1998 to 2023. This work might assist researchers in identifying new insights on potential collaborators and institutions, hot topics, and research directions.

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.