Progress In Brain Research[JOURNAL]
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200 papers
Models developed to explain the effects of stress on brain and behavior.
Memudu AE, Olukade BA, Nwanama KE … +1 more , Alex GS
Prog Brain Res · 2025 · PMID 40222786 · Publisher ↗
There is an integral relationship between stress, brain function and behavior. Over the year's extensive research has led to the development of various models to explain the intricate intersection between brain and stres...
There is an integral relationship between stress, brain function and behavior. Over the year's extensive research has led to the development of various models to explain the intricate intersection between brain and stress. This chapter delves into some of the theoretical frameworks that explains the neurobiological and behavioral responses to stress using key models of stress such as the allostatic load model, which is the most common model that describes how chronic stress affect brain structure and function resulting in long-term changes in regions such as the hippocampus, amygdala, and prefrontal cortex which phenotypically express as cognitive impairments, emotional dysfunction seen in various forms of neurological disorder. The neuro-endocrine model, follows the glucocorticoid cascade hypothesis, that associates prolonged stress exposure to hippocampal damage and cognitive decline via alteration in the hypothalamic-pituitary-adrenal (HPA) axis and the overproduction of stress hormones like cortisol which can induce hippocampal atrophy, impair learning and memory, and promote depressive-like behaviors. The neurobiological stress model addresses the role of the hypothalamic-pituitary-adrenal (HPA) axis and stress-related neurotransmitters in shaping behavioral responses, emphasizing alterations in neuroplasticity and synaptic function. These models demonstrate how chronic stress can alter neural plasticity, neurotransmitter systems, and synaptic connectivity, affecting behavior and cognitive function. Hence by integrating molecular, neurobiological, and behavioral perspectives, these models offer a comprehensive understanding of how stress alters brain activity and behavior. The chapter further showcase how these models direct the development of medical interventions, shedding light on potential therapies that target the underlying molecular mechanisms of stress-induced brain changes.
Stress and gender differences in brain development.
Asuku AO, Adebayo PO, Ogungbangbe GO
Prog Brain Res · 2025 · PMID 40222785 · Publisher ↗
This chapter investigates the ways in which male and female brains are differently affected by stress during early development, which in turn affects how susceptible each group is to stress-related illnesses. When examin...
This chapter investigates the ways in which male and female brains are differently affected by stress during early development, which in turn affects how susceptible each group is to stress-related illnesses. When examining the structure and function of the brain, gender differences and stress must be taken into account. Male and female brain development differs in response to the prenatal testis's secretion of androgen. It appears that when it comes to responding to stress, encoding memories, feeling emotions, solving specific issues, and making decisions, men and women use distinct areas of the brain. Findings revealed that stress led to specific changes in brain structure and function, with gender-specific differences observed. The prefrontal cortex, the hippocampus, and the amygdala are among the brain regions connected to the stress response. The stress response has been linked to the presentation of numerous mental and psychosomatic conditions. The way men and women respond to stress varies on a biological and psychological level. To gain more insight into the gender differences seen throughout brain development, these disparities must also be investigated. This chapter implies that gender-specific vulnerabilities should be addressed and healthy brain development should be promoted by stress-related interventions.
The stress-immune system axis: Exploring the interplay between stress and immunity.
Raza ML
Prog Brain Res · 2025 · PMID 40222784 · Publisher ↗
The chapter talks about how our body and mind respond to stress and how it affects our immune system. Stress reactions, especially the fight-or-flight reaction, are helpful at first but can be harmful if they last too lo...
The chapter talks about how our body and mind respond to stress and how it affects our immune system. Stress reactions, especially the fight-or-flight reaction, are helpful at first but can be harmful if they last too long. Long-term stress, caused by hormones like cortisol and adrenaline, weakens the immune system and makes people more likely to get sick. Important brain chemicals like serotonin and norepinephrine help control how our immune system works. Also, the connection between our gut and brain is an important way that mental health affects how our immune system functions. Getting older and experiencing stress early in life can affect how our immune system works. Inflammation caused by stress is connected to health issues like heart disease, depression, and autoimmune diseases. There are ways to manage stress, like being mindful and having support from friends, are important for keeping your immune system healthy and lessening harm caused by stress.
Stress-related neurodegenerative diseases: Molecular mechanisms implicated in neurodegeneration and therapeutic strategies.
Azarfarin M, Moradikor N, Salatin S … +2 more , Sarailoo M, Dadkhah M
Prog Brain Res · 2025 · PMID 40222783 · Publisher ↗
Chronic stress is a striking cause of major neurodegenerative diseases disorders (NDDs). These diseases share several common mechanisms regarding to disease pathology, in spite of they have various properties and clinica...
Chronic stress is a striking cause of major neurodegenerative diseases disorders (NDDs). These diseases share several common mechanisms regarding to disease pathology, in spite of they have various properties and clinical manifestations. NDDs are defined by progressive cognitive decline, and stress contribute to the promotion and progression of disease. In addition, various pathways such as production of reactive oxygen species (ROS), mitochondrial dysfunction, and neurodegeneration are the main crucial hallmarks to develop common NDDs, resulting in neuronal cell death. Although the exact mechanisms of NDDs are underexplored, the potential neuroprotective critical role of such therapies in neuronal loss the treatment of NDDs are not clear. In this regard, researchers investigate the neuroprotective effects of targeting underlying cascade to introduce a promising therapeutic option to NDDs. Herein, we provide an overview of the role of non-pharmacological treatments against oxidative stress, mitochondrial symbiosis, and neuroinflammation in NDDs, mainly discussing the music, diet, and exercise effects of targeting pathways.
Mapping brain neural networks in stress brain connectivity.
Wadan AS, Ahmed MA, Moradikor N
Prog Brain Res · 2025 · PMID 40222782 · Publisher ↗
Stress can cause severe damage to the CNS and contribute to an increased risk of neurological and psychiatric disorders. Gaining more insight into the neurobiology of stress is essential to treating neurological disorder...
Stress can cause severe damage to the CNS and contribute to an increased risk of neurological and psychiatric disorders. Gaining more insight into the neurobiology of stress is essential to treating neurological disorders associated with stress, which account for a high percentage of the world's disease burden. However, because of complicated variations in stressor types, stress perception, and preceding exposure to stressors, studying the impacts of stress is challenging. Gender, age, and timing are other crucial variables that can influence the stress response. Behavioral, physiological, genetic, and cellular/molecular neuroscience methodologies have all been widely applied in various research contexts to examine the neurobiological impacts of stress. Furthermore, because these approaches are invasive and hence undesirable or impractical for use in humans, they are frequently challenging to adapt to a therapeutic context. As an alternative to invasive procedures, functional neuroimaging approaches are starting to be developed. We discuss in this chapter brain neural networks under stress brain connection.
Mechanisms underlying stress effects on the brain: Basic concepts and clinical implications.
Saad HA, Marzouk M, Abdelrahman H … +1 more , Moradikor N
Prog Brain Res · 2025 · PMID 40222781 · Publisher ↗
Chronic stress impacts the brain through complex physiological, neurological, and immunological responses. The stress response involves the activation of the sympathetic-adrenal-medullary (SAM) system and the hypothalami...
Chronic stress impacts the brain through complex physiological, neurological, and immunological responses. The stress response involves the activation of the sympathetic-adrenal-medullary (SAM) system and the hypothalamic-pituitary-adrenal (HPA) axis, releasing stress hormones like norepinephrine and cortisol. While these responses are adaptive short-term, chronic stress disrupts homeostasis, increasing the risk of cardiovascular diseases, neurodegenerative disorders, and psychiatric conditions such as depression. This dysregulation is linked to persistent neuroinflammation, oxidative stress, and neurotransmitter imbalances involving dopamine and serotonin, impairing neuroplasticity and leading to structural changes in critical brain areas, such as the hippocampus and prefrontal cortex. Moreover, stress affects gene expression, particularly neuroinflammatory pathways, contributing to long-term cognitive function and emotional regulation alterations. Advancements in neuroimaging and molecular techniques, including MRI, PET, and SPECT, hold promise for identifying biomarkers and better understanding stress-induced brain changes. These insights are critical for developing targeted interventions to mitigate the adverse effects of chronic stress on brain health.
Epigenetic regulation of stress.
Alamoudi MK, Alibrahim NN, Alsaleh AA … +1 more , Raza ML
Prog Brain Res · 2025 · PMID 40222780 · Publisher ↗
Stress can have powerful and lasting effects on our bodies and behavior, partly because it changes how our genes work. These processes, such as DNA methylation, histones modifications, and non-coding RNAs, help decide wh...
Stress can have powerful and lasting effects on our bodies and behavior, partly because it changes how our genes work. These processes, such as DNA methylation, histones modifications, and non-coding RNAs, help decide when genes are active or inactive in cells experiencing stress. This can lead to lasting changes in how the cells function. It's important to understand how these changes in our genes affect our response to stress, as they can lead to problems like anxiety, depression, and heart disease. This chapter explores the link between stress and epigenetics. It talks about how our surroundings and lifestyle can impact these processes. It also shows that epigenetic treatments might help with issues created by stress. By looking at how stress affects our genes, we can discover new ways to treat stress and make medicine better for individuals, helping to lessen the bad impact of stress on our health.
Stress and the gut microbiota-brain axis.
Hyder N, Raza ML
Prog Brain Res · 2025 · PMID 40222779 · Publisher ↗
The gut microbiota-brain axis is a complex system that links the bacteria in our gut with our brain, it plays a part in what way we respond to stress. This chapter explores how stress affects the types of bacteria in the...
The gut microbiota-brain axis is a complex system that links the bacteria in our gut with our brain, it plays a part in what way we respond to stress. This chapter explores how stress affects the types of bacteria in the gut and shows the two-way connection between them. Stress can change the bacteria in our gut, which can cause various problems related to stress, like depression, anxiety, and irritable bowel syndrome (IBS). Figuring out how these interactions may help us develop new treatments that focus on the connection between gut bacteria and the brain. This chapter looks at how gut bacteria could help identify stress-related problems. It also discusses the difficulties and possibilities of using this research in medical practice. In the end, the chapter talks about what comes next in this quickly changing area. It highlights how important it is to include research about the gut-brain connection in overall public health plans.
Stress-related psychiatric disorders.
Al Bazzal A, Mtairek MA, Awde MH … +6 more , Kanso H, Hajj F, Al Amin F, Kazan Z, Mohammed NA, Hamdar H
Prog Brain Res · 2025 · PMID 40222778 · Publisher ↗
Stress is a natural human emotion that motivates us to face difficulties and risks. Everyone experiences stress to some extent, but when it becomes chronic or reaches a level that cannot be managed, its effects begin to...
Stress is a natural human emotion that motivates us to face difficulties and risks. Everyone experiences stress to some extent, but when it becomes chronic or reaches a level that cannot be managed, its effects begin to manifest. It is a common condition that most individuals confront, and its effects on the body and brain have become more obvious in recent years. Social and environmental interactions activate systemic reactions primarily controlled by the brain via immunological, neuroendocrine, and metabolic pathways. Long-term stress disrupts homeostasis, activating stress mediators that attempt to restore balance but frequently cause cumulative damage, particularly to the hippocampus, amygdala, and hypothalamus. Furthermore, persistent stress can have a direct and indirect effect on initiating psychiatric illnesses such as depression, anxiety, ADHD, and schizophrenia. Studies on neuroimaging show anatomical and functional alterations in stress-affected regions such as the prefrontal cortex and the hippocampus, which are linked to emotional dysregulation and cognitive decline. To better understand how stress affects psychiatric disorders and exacerbates their symptoms, this chapter will first discuss the molecular mechanism and neurobiological changes it can cause. It will then demonstrate various neuroimaging techniques for studying the effects of stress and offer potential treatments to mitigate these negative effects.
Understanding the connection between stress and sleep: From underlying mechanisms to therapeutic solutions.
Broderick ML, Khan Q, Moradikor N
Prog Brain Res · 2025 · PMID 40222777 · Publisher ↗
The objective of this chapter is to navigate through the nexus between stress and sleep, highlighting the neurobiological systems that connect them. Starting with an overview of neuroanatomy and physiology of stress and...
The objective of this chapter is to navigate through the nexus between stress and sleep, highlighting the neurobiological systems that connect them. Starting with an overview of neuroanatomy and physiology of stress and sleep, with a further detailed breakdown of sleep stages and key neuroanatomical centers that are responsible for sleep and wakefulness. Starting with suprachiasmatic nuclei (SCN) in circadian rhythm and sleep regulation overview, with a center point on the molecular systems including the CLOCK/CRY and BMAL1/2/PER1/2 feedback loops. Following this is the neurobiological of stress, specifically the hypothalamic-pituitary-adrenal (HPA) axis and sympathetic-adrenal (SPA) axis and influence on sleep. Vital neural circuits connecting stress and sleep are examined with the attention of the ventral tegmental area (VTA) GABA-somatostatin neurons and the locus coerules in sleep regulation in response to stress. In addition, neuroinflammation's role occurs through the cytokines IL-1β and TNF-α are investigated as a mediator of sleep disturbances caused by stress. It concludes by summarizing the implications of neuroinflammatory modulation in stress-related psychopathologies, emphasizing the opening this provides for interventions that target this inflammation helping to lighten sleep disorder.
Effects of stress on cognitive performance.
Nwikwe DC
Prog Brain Res · 2025 · PMID 40222776 · Publisher ↗
Stress remains a pervasive challenge in modern life, exerting significant impacts on cognitive performance and overall well-being by triggering release of stress hormones like adrenaline and cortisol. It has profound imp...
Stress remains a pervasive challenge in modern life, exerting significant impacts on cognitive performance and overall well-being by triggering release of stress hormones like adrenaline and cortisol. It has profound implications for education, work performance, and everyday life, impacting cognitive performance, health outcomes, and social relationships. It does this by impacting memory, attention and focus, informed decision-making, developmental and cognitive performance, work and educational performance, genetic and epigenetic influence, and public health. When a stressor is perceived, the hypothalamus in the brain signals the pituitary gland to release adrenocorticotropic hormone, hence adrenaline is quickly released into the bloodstream, causing immediate physiological changes and thus releasing cortisol gradually to help maintain the body's response to stress over a longer period through the hypothalamic-pituitary-adrenal and sympathetic-adrenomedullar axis. The impacts can be short-term or long-term focusing on the working memory, pre-frontal cortex, amygdala, and hippocampus. By recognizing these implications and implementing targeted interventions, we can foster environments that support resilience, optimize performance, and enhance overall well-being across diverse contexts. This chapter also highlighted some mitigation strategies to reduce stress-related activities and improve cognitive performance, such as cognitive-behavioral therapy, mindfulness-based stress reduction, healthy lifestyle adoption, pet therapy, time management and prioritization, and workplace interventions.
Introduction to neurobiology and pharmacology of stress.
Abbasi-Maleki S, Nakhaei B, Mehr SR … +1 more , Moradikor N
Prog Brain Res · 2025 · PMID 40222775 · Publisher ↗
In order to improve individual and community health outcomes, stress research is crucial for developing our understanding of human biology, psychology, and social dynamics. It also informs therapeutic practices, public h...
In order to improve individual and community health outcomes, stress research is crucial for developing our understanding of human biology, psychology, and social dynamics. It also informs therapeutic practices, public health campaigns, and educational activities. The chapter explores how neurotransmitters, including glutamate, GABA, adrenaline, norepinephrine, serotonin, dopamine, and adrenaline, mediate stress responses, impact mood and behavior, and play a part in a number of stress-related disorders. The relevance of focused research and therapy approaches aimed at reestablishing equilibrium within these systems is highlighted by the fact that dysregulation of these neurotransmitters can exacerbate health problems. Additionally, it is investigated how the amygdala, hippocampus, and prefrontal cortex interact to process emotions, build resilience, and determine an individual's susceptibility to stress. These interactions are regulated by both neuroplasticity and hereditary and epigenetic factors. The chapter discusses the pharmaceutical approach to stress management, which includes a variety of drugs such as beta-blockers, anxiolytics, and antidepressants that work by targeting different neurotransmitter systems to reduce anxiety and mood disorders. Even while these therapies work, they may have negative consequences and side effects that should be carefully considered in clinical settings. The chapter promotes a comprehensive approach to stress management that combines medication, lifestyle changes, psychotherapy, and stress-reduction methods. Healthcare workers can improve patient care and ultimately the health and quality of life for people with stress-related disorders by knowing the complexity of pharmaceutical therapies and how they affect the stress response.
Enhancing classification accuracy of HRF signals in fNIRS using semi-supervised learning and filtering.
Chen CH, Shyu KK, Wu YC … +3 more , Hung CH, Lee PL, Jao CW
Prog Brain Res · 2024 · PMID 39448115 · Publisher ↗
This paper introduces a novel approach to enhance the classification accuracy of hemodynamic response function (HRF) signals acquired through functional near-infrared spectroscopy (fNIRS). Leveraging a semi-supervised le...
This paper introduces a novel approach to enhance the classification accuracy of hemodynamic response function (HRF) signals acquired through functional near-infrared spectroscopy (fNIRS). Leveraging a semi-supervised learning (SSL) framework alongside a filtering technique, the study preprocesses HRF data effectively before applying the SSL algorithm. Collected from the prefrontal cortex, HRF signals capture variations in oxyhemoglobin (oxyHb) and deoxyhemoglobin (deoxyHb) levels in response to odor stimuli and air state. Training the classification model on a dataset containing filtered and feature-extracted HRF signals led to significant improvements in classification accuracy. By comparing the algorithm's performance before and after employing the proposed filtering technique, the study provides compelling evidence of its effectiveness. These findings hold promise for advancing functional brain imaging research and cognitive studies, facilitating a deeper understanding of brain responses across various experimental contexts.
Brain functional networks and structures that categorize type 2 bipolar disorder and major depression.
Chen YL, Jhou JE, Bai YM … +3 more , Chen MH, Tu PC, Wu YT
Prog Brain Res · 2024 · PMID 39448114 · Publisher ↗
BACKGROUND: Distinguishing between type 2 bipolar disorder (BD II) and major depressive disorder (MDD) poses a significant clinical challenge due to their overlapping symptomatology. This study aimed to investigate neuro...
BACKGROUND: Distinguishing between type 2 bipolar disorder (BD II) and major depressive disorder (MDD) poses a significant clinical challenge due to their overlapping symptomatology. This study aimed to investigate neurobiological markers that differentiate BD II from MDD using multimodal neuroimaging techniques. METHODS: Fifty-nine individuals with BD II, 114 with MDD, and 117 healthy controls participated in the study, undergoing structural and functional magnetic resonance imaging. Functional connectivity (FC) analysis used regions from Shen's whole-brain FC-based atlas. Feature selection was carried out using independent t-tests and ReliefF algorithms, followed by classification using Support Vector Machine and wide neural network. RESULTS: Significant differences in brain structure and function were observed among patients with BD II, MDD, and healthy controls. Both structural and functional alterations were more pronounced in BD II compared to MDD, particularly in regions associated with sensory processing, motor function, and the cerebellum. Classification based on neurobiological markers achieved a mean testing accuracy of 88.24%, with the t-test selected features outperforming those selected by ReliefF. Dysconnectivity patterns correlated with symptom severity and functioning in BD II but not MDD. CONCLUSION: Our findings suggest that neurobiological markers derived from multimodal imaging techniques can effectively differentiate patients with BD II from those with MDD. The identified alterations in brain structure and function, particularly in sensory-motor processing networks, may serve as potential biomarkers for distinguishing between these mood disorders. However, the influence of psychotropic medications and daily functioning severity on these neurobiological markers warrants further investigation.
Brain structural network modular and connectivity alterations in subtypes of patients with migraine and medication overuse headache.
Jao CW, Wu YT, Chen WH … +5 more , Yeh JH, Tsai YF, Hsiao CY, Walsh V, Lau CI
Prog Brain Res · 2024 · PMID 39448113 · Publisher ↗
Migraine, one of the most prevalent and debilitating neurological disorders, can be classified based on attack frequency into episodic migraine (EM) and chronic migraine (CM). Medication overuse headache (MOH), a type of...
Migraine, one of the most prevalent and debilitating neurological disorders, can be classified based on attack frequency into episodic migraine (EM) and chronic migraine (CM). Medication overuse headache (MOH), a type of chronic headache, arises when painkillers are overused by individuals with untreated or inadequately treated headaches. This study compares regional cortical morphological alterations and brain structural network changes among these headache subgroups. Sixty participants, including 20 in each of the following patient groups (EM, CM, MOH), and healthy controls (HC) completed the study. Our results show that the EM group exhibited cortical thickness (CTs) thinning predominantly in the left limbic, whereas CM patients exhibited CTs thinning across both left and right hemispheres. The MOH group demonstrated the most widespread CTs thinning. Both CM and MOH exhibited comparable patterns of CTs thinning within lobes, leading to reduced intra-lobe connectivity. While there were no significant differences in total inter-lobe connectivity between migraine groups and HC, both CM and MOH groups exhibited significantly decreased inter-limbic connectivity compared to HC and EM groups. In addition, they showed increased inter-frontal and inter-parietal connectivity, suggesting possible compensatory mechanisms to offset the loss of inter-lobe connectivity between the limbic and other lobes. Both CM and MOH groups exhibited a significant loss of global efficiency and a decrease in betweenness centrality in their brain networks, with MOH showing the most pronounced decrease and CM showing the second largest decrease. Our results suggest that aberrant structural brain networks in CM and MOH are less efficient, less centralization, and abnormally segregated.
Analysis of the difference between Alzheimer's disease, mild cognitive impairment and normal people by using fractal dimensions and small-world network.
Lee WK, Hinrichs C, Chen YL … +3 more , Wang PS, Guo WY, Wu YT
Prog Brain Res · 2024 · PMID 39448112 · Publisher ↗
This research examined the distinctions in brain network characteristics among individuals with Alzheimer's disease (AD), mild cognitive impairment (MCI), and a control group. Magnetic resonance imaging (MRI) and mini-me...
This research examined the distinctions in brain network characteristics among individuals with Alzheimer's disease (AD), mild cognitive impairment (MCI), and a control group. Magnetic resonance imaging (MRI) and mini-mental state examination (MMSE) data were retrieved from the Alzheimer's Disease Neuroimaging Initiative (ANDI) database, comprising 40 subjects in each group. Correlation maps for evaluating brain network connectivity were generated using fractal dimension (FD) analysis, a method capable of quantifying morphological changes in cortical and cerebral regions. Employing graph theory, each parcellated brain region was represented as a node, and edges between nodes were utilized to compute small-world network properties for each group. In the comparison between control and AD demonstrated the significantly lower FD values (P<0.05) in temporal lobe, motor cortex, part of occipital and parietal, hippocampus, amygdala, and entorhinal cortex, which present the atrophy. Similarly, comparing control group to MCIs, regions closely associated with memory, such as the hippocampus, showed significantly lower FD values. Furthermore, both AD and MCI groups displayed diminished connectivity and decreased network efficiency. In conclusion, fractal dimension (FD) analysis illustrate the progression of structural declination from mild cognitive impairment (MCI) to Alzheimer's disease (AD). Additionally, structural small-world network analysis presents itself as a potential method for assessing network efficiency and the progression of AD. Moving forward, further clinical assessments are warranted to validate the findings observed in this study.
Comparative analysis of rs-fMRI markers in heat and mechanical pain sensitivity.
Chen YL, Pan LH, Niddam DM … +3 more , Hinrichs C, Wang SJ, Wu YT
Prog Brain Res · 2024 · PMID 39448111 · Publisher ↗
This study investigates the comparative analysis of resting-state functional magnetic imaging (rs-fMRI) markers in heat and mechanical pain sensitivity among healthy adults. Using quantitative sensory testing (QST) in th...
This study investigates the comparative analysis of resting-state functional magnetic imaging (rs-fMRI) markers in heat and mechanical pain sensitivity among healthy adults. Using quantitative sensory testing (QST) in the orofacial area and rs-fMRI, we explored the relationship between pain sensitivities and resting-state functional connectivity (rsFC) across whole brain areas. Brain regions were spatially divided using group independent component analysis (gICA), and additional masked gICA was performed for brainstem regions. Our findings revealed that a significant number of rsFCs were correlated with either heat or mechanical pain sensitivity, with a substantial portion originating from the Sensorimotor Network (SMN). Furthermore, multivariable regression models incorporating rsFC features demonstrated predictive capabilities for pain sensitivities, with the inclusion of brainstem gICA components significantly enhancing model accuracy. Finally, a composite critical rsFC value was introduced to simplify and describe overall abnormal communication in the brain network, which could also be used in univariable regression models to predict heat and mechanical pain sensitivity.
Enhancing facial feature de-identification in multiframe brain images: A generative adversarial network approach.
Lien CY, Deng RJ, Fuh JL … +2 more , Ting YN, Yang AC
Prog Brain Res · 2024 · PMID 39448110 · Publisher ↗
The collection of head images for public datasets in the field of brain science has grown remarkably in recent years, underscoring the need for robust de-identification methods to adhere with privacy regulations. This pa...
The collection of head images for public datasets in the field of brain science has grown remarkably in recent years, underscoring the need for robust de-identification methods to adhere with privacy regulations. This paper elucidates a novel deep learning-based approach to deidentifying facial features in brain images using a generative adversarial network to synthesize new facial features and contours. We employed the precision of the three-dimensional U-Net model to detect specific features such as the ears, nose, mouth, and eyes. Results: Our method diverges from prior studies by highlighting partial regions of the head image rather than comprehensive full-head images. We trained and tested our model on a dataset comprising 490 cases from a publicly available head computed tomography image dataset and an additional 70 cases with head MR images. Integrated data proved advantageous, with promising results. The nose, mouth, and eye detection achieved 100% accuracy, while ear detection reached 85.03% in the training dataset. In the testing dataset, ear detection accuracy was 65.98%, and the validation dataset ear detection attained 100%. Analysis of pixel value histograms demonstrated varying degrees of similarity, as measured by the Structural Similarity Index (SSIM), between raw and generated features across different facial features. The proposed methodology, tailored for partial head image processing, is well suited for real-world imaging examination scenarios and holds potential for future clinical applications contributing to the advancement of research in de-identification technologies, thus fortifying privacy safeguards.
Relationship of SSVEP response between flash frequency conditions.
Chang CT, Pai KJ, Huang CH … +3 more , Chou CY, Liu KW, Lin HB
Prog Brain Res · 2024 · PMID 39448109 · Publisher ↗
This study delves into the application of Brain-Computer Interfaces (BCIs), focusing on exploiting Steady-State Visual Evoked Potentials (SSVEPs) as communication tools for individuals facing mobility impairments. SSVEP-...
This study delves into the application of Brain-Computer Interfaces (BCIs), focusing on exploiting Steady-State Visual Evoked Potentials (SSVEPs) as communication tools for individuals facing mobility impairments. SSVEP-BCI systems can swiftly transmit substantial volumes of information, rendering them suitable for diverse applications. However, the efficacy of SSVEP responses can be influenced by variables such as the frequency and color of visual stimuli. Through experiments involving participants equipped with electrodes on the brain's visual cortex, visual stimuli were administered at 4, 17, 25, and 40Hz, using white, red, yellow, green, and blue light sources. The results reveal that white and green stimuli evoke higher SSVEP responses at lower frequencies, with color's impact diminishing at higher frequencies. At low light intensity (1W), white and green stimuli elicit significantly higher SSVEP responses, while at high intensity (3W), responses across colors tend to equalize. Notably, due to seizure risks, red and blue lights should be used cautiously, with white and green lights preferred for SSVEP-BCI systems. This underscores the critical consideration of color and frequency in the design of effective and safe SSVEP-BCI systems, necessitating further research to optimize designs for clinical applications.
Optimizing user experience in SSVEP-BCI systems.
Chang CT, Pai KJ, Huang CH … +3 more , Chou CY, Liu KW, Lin HB
Prog Brain Res · 2024 · PMID 39448108 · Publisher ↗
The emergence of brain-computer interface (BCI) technology provides enormous potential for human medical and daily applications. Therefore, allowing users to tolerate the visual response of SSVEP for a long time has alwa...
The emergence of brain-computer interface (BCI) technology provides enormous potential for human medical and daily applications. Therefore, allowing users to tolerate the visual response of SSVEP for a long time has always been an important issue in the SSVEP-BCI system. We recruited three subjects and conducted visual experiments in groups using different frequencies (17 and 25Hz) and 60Hz light. After recording the physiological signal, use FFT to perform a time-frequency analysis on the physiological signal to check whether there is any difference in the signal-to-noise ratio and amplitude of the 60Hz light source compared with a single low-frequency signal source. The results show that combining a 60Hz light source with low-frequency LEDs can reduce participants' eye discomfort while achieving effective light stimulation control. At the same time, there was no significant difference in signal-to-noise ratio and amplitude between the groups. This also means that 60Hz can make vision more continuous and improve the subject's experience and comfort. At the same time, it does not affect the performance of the original SSVEP-induced response. This study highlights the importance of considering technical aspects and user comfort when designing SSVEP-BCI systems to increase the usability of SSVEP systems for long-term flash viewing.
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