Coffee is a popular drink enjoyed around the world, and scientists are very interested in studying how it affects the human brain. This chapter looks at lots of different studies to understand how drinking coffee might change the brain and help protect it from neurodegenerative disorders especially like schizophrenia. With the help of available literature a link between the coffee mechanism and neurodegenerative disorders is established in this chapter. Researchers have found that drinking coffee can change the size of certain parts of the brain that control things like thinking and mood. Scientists also study how coffee's ingredients, especially caffeine, can change how the brain works. They think these changes could help protect the brain from diseases. This chapter focuses on how coffee might affect people with schizophrenia as hallucination is caused during and after excess consumption of caffeine. There's still a lot we don't know, but researchers are learning more by studying how different people's brains respond to coffee over time. Overall, this chapter shows that studying coffee and the brain could lead to new ways to help people with brain disorders. This study also draws ideas for future research and ways to help people stay healthy.

The chapter "Behavioral and Psychological Aspects of Coffee Consumption" delves into the complex interplay between coffee drinking and cognitive functions, human behavior, and health-related effects. It starts by looking at coffee's physiological impacts, such as how it affects the body's neurotransmitter systems, metabolism, cardiovascular health, liver health, mental health, and bone health. The larger framework of behavioral and psychological variables impacting patterns of coffee drinking provides further context for these effects. The chapter explores a range of behavior change interventions designed to encourage moderate coffee use. It also covers the role that technology, customized methods, and environmental alterations might play in supporting healthier choices. The statement underscores the significance of attending to the requirements of heterogeneous populations, surmounting obstacles to behavior modification, and guaranteeing the enduring viability of intervention results. The chapter also outlines new directions in neuroscience and behavioral science research, including developments in neuroimaging methods and the application of digital health technology to the delivery of interventions. Additionally, it emphasizes how coffee use affects public health and policy, arguing in favor of evidence-based guidelines and treatments that encourage sensible coffee consumption habits and enhance population health outcomes. Ultimately, the chapter offers a thorough summary of the behavioral and psychological effects of coffee drinking, highlighting the significance of multidisciplinary studies and cooperative efforts to deepen our comprehension of this intricate phenomenon.

Coffee, a universally consumed beverage, is known to contain thousands of bioactive constituents that have garnered interest due to their potential neuroprotective effects against various neurodegenerative disorders, including Alzheimer's disease (AD). Extensive research has been conducted on coffee constituents such as Caffeine, Trigonelline, Chlorogenic acid, and Caffeic acid, focusing on their neuroprotective properties. These compounds have potential to impact key mechanisms in AD development, including amyloidopathy, tauopathy, and neuroinflammation. Furthermore, apart from its neuroprotective effects, coffee consumption has been associated with anticancerogenic and anti-inflammatory effects, thereby enhancing its therapeutic potential. Studies suggest that moderate coffee intake, typically around two to three cups daily, could potentially contribute to mitigating AD progression and lowering the risk of related neurological disorders. This literature underscores the potential neuroprotective properties of coffee compounds, which usually perform their neuronal protective effects via modulating nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), nuclear factor erythroid-derived 2-like 2 (Nrf2), interleukins, tumor necrosis factor-alpha (TNF-α), and many other molecules.

The physiological structure and functioning of the brain are determined by activity-dependent processes and affected by "synapse plasticity." Because chemical transmitters target and regulate synapses, exogenous chemical stimulants and transmitters can alter their physiological functions by interacting with synaptic surface receptors or chemical modulators. Caffeine, a commonly used pharmacologic substance, can target and alter synapses. It impact various biological, chemical, and metabolic processes related to synaptic function. This chapter investigates how caffeine affects fluctuations in structure and function in the hippocampus formation and neocortical structure, regions known for their high synaptic plasticity profile. Specifically, caffeine modulates various synaptic receptors and channel activities by mobilizing intracellular calcium, inhibiting phosphodiesterase, and blocking adenosine and GABA cellular receptors. These caffeine-induced pathways and functions allow neurons to generate plastic modulations in synaptic actions such as efficient and morphological transmission. Moreover, at a network level, caffeine can stimulate neural oscillators in the cortex, resulting in repetitive signals that strengthen long-range communication between cortical areas reliant on N-methyl-d-aspartate receptors. This suggests that caffeine could facilitate the reorganization of cortical network functions through its effects on synaptic mobilization.

This chapter explores the complex relationship between coffee drinking and stress management, highlighting the advantages and disadvantages of this widely consumed beverage. The chapter explores the physiological, psychological, and social effects of coffee on stress response and resilience through a thorough analysis of recent studies. It highlights the negative consequences of excessive intake on cardiovascular, gastrointestinal, and mental health while also discussing how moderate coffee consumption may lower stress levels, improve coping skills, and promote relaxation. Considerations for vulnerable populations, interactions with medications and supplements, and sustainability concerns in coffee production and consumption are also addressed. By identifying missing gaps in our understanding of coffee and stress management, the chapter underscores the need for future research to elucidate underlying mechanisms and promote mindful consumption practices. Ultimately, by embracing a holistic approach that considers individual health, environmental sustainability, and social responsibility, we can harness the potential of coffee to support resilience, well-being, and sustainability for individuals and communities worldwide.

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.

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.

Parkinson's disease (PD) is a prevalent neurodegenerative disease marked by dopaminergic neuronal loss and misfolded alpha-synuclein (α-syn) accumulation, which results in both motor and cognitive symptoms. Its occurrence grows with age, with a larger prevalence among males. Despite substantial study, effective medicines to reduce or stop the progression of diseases remain elusive. Interest has grown in examining dietary components, such as caffeine present in coffee, for potential medicinal effects. Epidemiological studies imply a lower incidence of PD with coffee drinking, attributable to caffeine's neuroprotective abilities. Beyond caffeine, coffee constituent like chlorogenic acid and cafestol have anti-Parkinsonian benefits. Moreover, coffee use has been related with variations in gut microbiota composition, which may reduce intestinal inflammation and prevent protein misfolding in enteric nerves, perhaps through the microbiota-gut-brain axis. This review gives a summary of the neuroprotective effects of coffee, investigating both its motor and non-motor advantages in individuals with PD as well as in experimental models of PD. We reviewed some bioactive constituents of coffee, their respective interactions with misfolded α-syn accumulation, and its emerging mechanisms associated to the gut microbiome.

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.

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.

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.

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.

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.

Coffee is the most popular beverage in the world and, aside from tea and water, the most often consumed caffeine-containing beverage. Because of its high caffeine concentration, it is typically classified as a stimulant. There are other bioactive ingredients in coffee besides caffeine. The coffee beverage is a blend of several bioactive substances, including diterpenes (cafestol and kahweol), alkaloids (caffeine and trigonelline), and polyphenols (particularly chlorogenic acids in green beans and caffeic acid in roasted coffee beans). Caffeine has also been linked to additional beneficial benefits such as antioxidant and anti-inflammatory properties, which change cellular redox and inflammatory status in a dose-dependent manner. Pyrocatechol, a constituent of roasted coffee that is created when chlorogenic acid is thermally broken down, has anti-inflammatory properties as well. It is postulated that coffee consumption reduces neuroinflammation, which is intimately linked to the onset of neurodegenerative disorders like Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD). This review provides an overview of the most recent studies regarding coffee's possible benefits in preventing brain inflammation and neurodegenerative disorders.

Spinocerebellar ataxia type 3 (SCA3), or Machado-Joseph disease, presents as a cerebellar cognitive affective syndrome (CCAS) and represents the predominant SCA genotype in Taiwan. Beyond cerebellar involvement, SCA3 patients exhibit cerebral atrophy. While prior neurodegenerative disease studies relied on voxel-based morphometry (VBM) for brain atrophy assessment, its qualitative nature limits individual and region-specific evaluations. To address this, we employed fractal dimension (FD) analysis to quantify cortical complexity changes in SCA3 patients. We examined 50 SCA3 patients and 50 age- and sex-matched healthy controls (HC), dividing MRI cerebral gray matter (GM) into 68 auto-anatomical subregions. Using three-dimensional FD analysis, we identified GM atrophy manifestations in SCA3 patients. Results revealed lateral atrophy symptoms in the left frontal, parietal, and occipital lobes, and fewer symptoms in the right hemisphere's parietal and occipital lobes. Focal areas of atrophy included regions previously identified in SCA3 studies, alongside additional regions with decreased FD values. Bilateral postcentral gyrus and inferior parietal gyrus exhibited pronounced atrophy, correlating with Scale for the Assessment and Rating of Ataxia (SARA) scores and disease duration. Notably, the most notable focal areas were the bilateral postcentral gyrus and the left superior temporal gyrus, serving as imaging biomarkers for SCA3. Our study enhances understanding of regional brain atrophy in SCA3, corroborating known clinical features while offering new insights into disease progression.

This review delves into the intricate interplay between caffeine consumption and schizophrenia, examining evidence from epidemiological and clinical studies. While epidemiological research offers conflicting findings regarding the association between coffee intake and schizophrenia risk, clinical studies reveal diverse impacts of caffeine on symptomatology and cognition in individuals with schizophrenia. Some epidemiological studies suggest a potential protective effect of coffee consumption against schizophrenia, whereas others fail to establish a significant correlation. Clinical investigations highlight the complexity of caffeine's influence, with varied effects on symptom severity and cognitive function observed among schizophrenia patients. Notably, caffeine may exacerbate positive symptoms while alleviating negative symptoms and cognitive deficits in this population. However, limitations such as small sample sizes and reliance on self-reported data hinder the generalizability of these findings. Furthermore, genetic factors, prenatal exposure, and substance abuse contribute to the complexity of the relationship between caffeine and schizophrenia. Studies indicate that individuals with a genetic predisposition to schizophrenia may be more vulnerable to the effects of caffeine, while prenatal exposure to caffeine may elevate the risk of schizophrenia in offspring. Additionally, substance abuse, including high caffeine and nicotine consumption, is prevalent among individuals with schizophrenia, exacerbating symptom severity. Future research directions include addressing methodological limitations, such as small sample sizes and reliance on self-reported data, and exploring the effects of caffeine on schizophrenia using larger, more diverse cohorts and controlled methodologies. A deeper understanding of caffeine's impact on schizophrenia is crucial for informing clinical practice and developing personalized interventions for patients. Ultimately, this review underscores the need for further investigation into the complex relationship between caffeine consumption and schizophrenia to improve patient outcomes and inform evidence-based interventions.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder characterized by progressive loss of motor neurons. The effective treatments for ALS remain elusive, necessitating exploration into novel preventive strategies. ALS pathogenesis is triggered by oxidative stress which results in neuroinflammation, exicitotoxicity and neuronal cell death. Nutritional mechanism for halting progression of neurodegeneration is through dietary compounds with antioxidants, anti-inflammatory or neuromodulating activity. Coffee is a widely consumed beverage made up of polyphenols, caffeine and other compounds with possible antioxidants and neuro-protective roles. It is important to say that various epidemiological studies have documented association between coffee intake and ALS. This chapter is aimed to present a comprehensive review of existing literature on coffee consumption and ALS, involving epidemiological studies, preclinical research, and its mechanism of actions in animal model of ALS. It highlights key findings regarding the potential neuroprotective properties of coffee constituents such as caffeine, polyphenols, and other bioactive compounds. Furthermore, it discusses possible pathways through which coffee may modulate ALS pathogenesis, including suppressing oxidative stress and neuroinflammation while boosting adenosine function via the adenosine receptor two on the motor neuron cells membrane in the spinal cord to enhance motor function via the corticospinal tract. Overall, this chapter underscores the significance of further research to unravel the specific mechanisms by which coffee exerts its neuroprotective effects in ALS, with the ultimate goal of identifying dietary strategies for ALS prevention and management.

Consuming coffee, a widely enjoyed beverage with caffeine, can impact the central nervous system and disturb sleep if taken too close to bedtime. Caffeine impacts sleep by slowing the onset, blocking adenosine receptors, lowering deep sleep levels, disrupting sleep patterns, and lessening rapid eye movement sleep. Although coffee can help with alertness in the morning, it may disturb sleep in the evening, particularly for individuals who are sensitive to caffeine. To enhance the quality of sleep, reduce the consumption of caffeine in the afternoon and evening, refrain from drinking caffeine before going to bed, and choose decaffeinated drinks instead. Variables such as personal reactions, ability to handle caffeine, and engagement with other compounds also influence the impact of coffee on sleep. Keeping track of how much caffeine you consume and your sleeping habits can assist in recognizing any disturbances and making needed changes. Furthermore, taking into account variables such as metabolism, age, and the timing of coffee consumption can assist in lessening the effects of coffee on sleep. In general, paying attention to the amount of caffeine consumed from different sources and consuming it at the right times can assist in preserving healthy sleep patterns even while enjoying coffee.

Multiple Sclerosis (MS) is a long-term autoimmune disorder affecting the central nervous system, marked by inflammation, demyelination, and neurodegeneration. While the exact cause of MS remains unknown, recent research indicates that environmental factors, particularly diet, may influence the disease's risk and progression. As a result, the potential neuroprotective effects of coffee, one of the most popular beverages worldwide, have garnered significant attention due to its rich content of bioactive compounds. This chapter explores the impact of coffee consumption on patients with Multiple Sclerosis, highlighting how coffee compounds like caffeine, polyphenols, and diterpenes can reduce inflammation and oxidative stress while enhancing neural function. It highlights caffeine's effect in regulating adenosine receptors, specifically A1R and A2AR, which play important roles in neuroinflammation and neuroprotection in MS. The dual role of microglial cells, which promote inflammation while also aiding neuroprotection, is also highlighted concerning caffeine's effects. Furthermore, the potential of A2AR as a therapeutic target in MS and the non-A2AR-dependent neuroprotective benefits of coffee. In this chapter we suggest that the consumption of coffee has no harmful effect on an MS patient and to a larger extent on public health, and informs future research directions and clinical practice, ultimately improving outcomes for individuals living with MS.

Caffeine is an alkaloid obtained from plants and is one of the most consumptive drug in the form of chocolate, coffee and beverages. The potential impact of caffeine within CNS can be easily understood by mechanism of action-antagonism of adenosine receptor, calcium influx, inhibits phosphodiesterases. Adenosine a neuromodulator for adenosine receptors, which are abundantly expressed within the central nervous system. Caffeine antagonized the adenosine receptor, hence stimulate expression of dopamine. It plays pivotal role in many metabolic pathways within the brain and nervous system, it reduced the amyloid-β-peptide (Aβ) accumulation, downregulation of tau protein phosphorylation, stimulate cholinergic neurons and inhibits the acetylcholinestrase (AChE). It also possess antioxidant and antiapoptotic activity. Caffeine act as nutraceutical product, improves mental health. It contains antioxidants, vitamins, minerals and dietary supplements, by reducing the risk factor of several neurodegenerations including Alzheimer's disease, migraine, gallstone, cancer, Huntington's disease and sclerosis. This act as a stimulant and have capability to increase the effectiveness of certain pain killer. Beside positive affects, over-consumption of caffeine leads to negative impact: change in sleep pattern, hallucinations, high blood pressure, mineral loss and even heartburn. This chapter highlights pros and cons of caffeine consumption.

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.