Human Brain Research Articles

Of artificial intelligence, machine learning, and the human brain. Celebrating Miklos Palkovits' 90th birthday.

Of artificial intelligence, machine learning, and the human brain. Celebrating Miklos Palkovits' 90th birthday.

Discovery of novel cholinesterase inhibitors easily crossing the blood-brain barrier via structure-property relationship investigation: Methylenedioxy-cinnamicamides containing tertiary amine side chain.

In the present investigation, a series of dimethoxy or methylenedioxy substituted-cinnamamide derivatives containing tertiary amine moiety (N. N-Dimethyl, N, N-diethyl, Pyrrolidine, Piperidine, Morpholine) were synthesized and evaluated for cholinesterase inhibition and blood-brain barrier (BBB) permeability. Although their chemical structures are similar, their biological activities exhibit diversity. The results showed that all compounds except for those containing morpholine group exhibited moderate to potent acetylcholinesterase inhibition. Preliminary screening of BBB permeability shows that methylenedioxy substituted compounds have better brain permeability than the others. Compound 10c, containing methylenedioxy and pyrrolidine side chain, showed a better acetylcholinesterase inhibition (IC50: 1.52±0.19 μmol/L) and good blood-brain barrier permeability. Further pharmacokinetic investigation of compound 10c using ultra high performance liquid chromatography-mass/mass spectrometry (UPLC-MS/MS) in mice showed that compound 10c in brain tissue reached its peak concentration (857.72 ± 93.56 ng/g) after dosing 30 min. Its half-life in the serum is 331 min (5.52 h), and the CBrain/CSerum at various sampling points is ranged from 1.65 to 4.71(Mean: 2.76) within 24 hours. This investigation provides valuable information on the chemistry and pharmacological diversity of cinnamic acid derivatives and may be beneficial for the discovery of central nervous system drugs.

Efficient Machine Learning and Deep Learning Techniques for Detection of Breast Cancer Tumor

The detection of cancer tumors is an essential component that has important consequences for the speedy involvement of medical professionals and the enhancement of patient outcomes. This review paper presents a complete study of the current body of research and methodology, as well as an in-depth assessment of the use of machine learning (ML) and deep learning (DL) in the detection of cancer tumors. In addition, the article gives a full analysis of the approaches involved. Machine learning and deep learning, which effectively handle ambiguity in the identification of malignant tumors, provide an alternative method for dealing with the complexity of brain tissue. This method is offered by a combination of machine learning and deep learning. The first part of the review draws attention to the significance of making an accurate diagnosis of breast cancer, highlights the limits of traditional diagnostic methods, and investigates the cutting-edge area of medical imaging technology. After that, it investigates the fundamentals of ML and DL and how they might be used to deal with the challenges that are inherent in the interpretation of complicated imaging data. In addition, the paper explores the ways in which models enhance the processes of feature extraction, picture segmentation, and classification in breast tumor detection systems.

Chronic toxicity of sediment-bound triclosan on freshwater walking catfish Clarias magur: Organ level accumulation and selected enzyme biomarker responses

Triclosan (TCS) is a biocide widely used in personal care and medicinal products. TCS persists in sediments and has been detected worldwide, making sediments a vital route of TCS exposure to aquatic organisms. This experiment explored the bioaccumulation and toxicological effects of TCS-contaminated sediment. The study revealed that the half-life of TCS in the sediment-water system was 21.52 days. Exposure of Clarias magur juveniles to 0.4 and 0.8 mg kg−1 TCS-spiked sediment resulted in high Biota-Sediment Accumulation Factor (BSAF) with the highest bioaccumulation in the liver (29.62–73.61 mg kg−1), followed by gill (9.22–17.57 mg kg−1), kidney (5.04–9.76 mg kg−1), muscle (2.63–4.87 mg kg−1) and brain (1.53–3.20 mg kg−1). Furthermore, a concentration-dependent increase in oxidative stress biomarkers such as superoxide dismutase (SOD), catalase (CAT) and glutathione-S-transferase (GST) was documented during 45 days of exposure in gill, liver, kidney, muscle, and brain tissues of exposed fish. A similar increasing trend was also recorded for liver transaminase enzymes such as glutamic oxaloacetic transaminase (GOT) and glutamic pyruvic transaminase (GPT) during the experimental period compared to control. Serum biochemical analysis revealed a significant time and concentration-dependent increase in serum glucose, serum GOT, and serum GPT, while serum total protein and albumin decreased significantly during exposure. These findings demonstrate high bioaccumulative and toxic nature of TCS in fish, promoting multiple physiological and biochemical dysfunctions through sediment exposure. The study underscores the urgent need for strengthened regulations and robust monitoring of triclosan across various environmental matrices, including sediment, to mitigate the detrimental impacts of TCS effectively.

Speckle-enabled in vivo demixing of neural activity in the mouse brain

Functional imaging of neuronal activity in awake animals, using a combination of fluorescent reporters of neuronal activity and various types of microscopy modalities, has become an indispensable tool in neuroscience. While various imaging modalities based on one-photon (1P) excitation and parallel (camera-based) acquisition have been successfully used for imaging more transparent samples, when imaging mammalian brain tissue, due to their scattering properties, two-photon (2P) microscopy systems are necessary. In 2P microscopy, the longer excitation wavelengths reduce the amount of scattering while the diffraction-limited 3D localization of excitation largely eliminates out-of-focus fluorescence. However, this comes at the cost of time-consuming serial scanning of the excitation spot and more complex and expensive instrumentation. Thus, functional 1P imaging modalities that can be used beyond the most transparent specimen are highly desirable. Here, we transform light scattering from an obstacle into a tool. We use speckles with their unique patterns and contrast, formed when fluorescence from individual neurons propagates through rodent cortical tissue, to encode neuronal activity. Spatiotemporal demixing of these patterns then enables functional recording of neuronal activity from a group of discriminable sources. For the first time, we provide an experimental, in vivo characterization of speckle generation, speckle imaging and speckle-assisted demixing of neuronal activity signals in the scattering mammalian brain tissue. We found that despite an initial fast speckle decorrelation, substantial correlation was maintained over minute-long timescales that contributed to our ability to demix temporal activity traces in the mouse brain in vivo. Informed by in vivo quantifications of speckle patterns from single and multiple neurons excited using 2P scanning excitation, we recorded and demixed activity from several sources excited using 1P oblique illumination. In our proof-of-principle experiments, we demonstrate in vivo speckle-assisted demixing of functional signals from groups of sources in a depth range of 220–320 µm in mouse cortex, limited by available speckle contrast. Our results serve as a basis for designing an in vivo functional speckle imaging modality and for maximizing the key resource in any such modality, the speckle contrast. We anticipate that our results will provide critical quantitative guidance to the community for designing techniques that overcome light scattering as a fundamental limitation in bioimaging.

Simultaneous whole-head electrophysiological recordings using EEG and OPM-MEG

Abstract Electroencephalography (EEG) and magnetoencephalography (MEG) non-invasively measure human brain electrophysiology. They differ in nature; MEG offers better performance whilst EEG (a wearable platform) is more practical. They are also complementary, with studies showing that concurrent MEG/EEG provides advantages over either modality alone, and consequently clinical guidelines for MEG in epilepsy recommend simultaneous acquisition of MEG and EEG. In recent years, new instrumentation— the optically pumped magnetometer (OPM)— has had a significant impact on MEG, offering improved performance, lifespan compliance, and wearable MEG systems. Nevertheless, the ability to carry out simultaneous EEG/OPM-MEG remains critical. Here, we investigated whether simultaneous, wearable, whole-head EEG and OPM-MEG measurably degrades signal quality in either modality. We employed two tasks: a motor task known to modulate beta oscillations, and an eyes-open/closed task known to modulate alpha oscillations. In both, we characterised the performance of EEG alone, OPM-MEG alone, and concurrent EEG/OPM-MEG. Results show that the SNR of the beta response was similar, regardless of whether modalities were used individually or concurrently. Likewise, our alpha band recordings demonstrated that signal contrast was stable, regardless of the concurrent recording. We also demonstrate significant advantages of OPM-MEG; specifically, the OPM-MEG signal is less correlated across channels and less susceptible to interference from non-brain sources. Our results suggest that there are no barriers to simultaneous wearable EEG/OPM-MEG, and consequently this technique is ripe for neuroscientific and clinical adoption. This will be important in the clinic where simultaneous EEG and OPM-MEG recordings will facilitate better interpretation of OPM-MEG data in patients.

Connectome reorganization associated with temporal lobe pathology and its surgical resection.

Network neuroscience offers a unique framework to understand the organizational principles of the human brain. Despite recent progress, our understanding of how the brain is modulated by focal lesions remains incomplete. Resection of the temporal lobe is the most effective treatment to control seizures in pharmaco-resistant temporal lobe epilepsy (TLE), making this syndrome a powerful model to study lesional effects on network organization in young and middle-aged adults. Here, we assessed the downstream consequences of a focal lesion and its surgical resection on the brain's structural connectome, and explored how this reorganization relates to clinical variables at the individual patient level. We included adults with pharmaco-resistant TLE (n = 37) who underwent anterior temporal lobectomy between two imaging time points, as well as age- and sex-matched healthy controls who underwent comparable imaging (n = 31). Core to our analysis was the projection of high-dimensional structural connectome data-derived from diffusion MRI tractography from each subject-into lower-dimensional gradients. We then compared connectome gradients in patients relative to controls before surgery, tracked surgically-induced connectome reconfiguration from pre- to postoperative time points, and examined associations to patient-specific clinical and imaging phenotypes. Before surgery, individuals with TLE presented with marked connectome changes in bilateral temporo-parietal regions, reflecting an increased segregation of the ipsilateral anterior temporal lobe from the rest of the brain. Surgery-induced connectome reorganization was localized to this temporo-parietal subnetwork, but primarily involved postoperative integration of contralateral regions with the rest of the brain. Using a partial least-squares analysis, we uncovered a latent clinical-imaging signature underlying this pre- to postoperative connectome reorganization, showing that patients who displayed postoperative integration in bilateral fronto-occipital cortices also had greater preoperative ipsilateral hippocampal atrophy, lower seizure frequency, and secondarily generalized seizures. Our results bridge the effects of focal brain lesions and their surgical resections with large-scale network reorganization and inter-individual clinical variability, thus offering new avenues to examine the fundamental malleability of the human brain.

Modeling distracted driving behavior considering cognitive processes

The modeling of distracted driving behavior has been studied for many years, however, there remain many distraction phenomena that can not be fully modeled. This study proposes a new method that establishes the model using the queuing network model human processor (QN-MHP) framework. Unlike previous models that only consider distracted-driving-related human factors from a mathematical perspective, the proposed method reflects the information processing in the human brain, and simulates the distracted driver’s cognitive processes based on a model structure supported by physiological and cognitive research evidence. Firstly, a cumulative activation effect model for external stimuli is adopted to mimic the phenomenon that a driver responds only to stimuli above a certain threshold. Then, dual-task queuing and switching mechanisms are modeled to reflect the cognitive resource allocation under distraction. Finally, the driver's action is modeled by the Intelligent Driver Model (IDM). The model is developed for visual distraction auditory distraction separately. 773 distracted car-following events from the Shanghai Naturalistic Driving Study data were used to calibrate and verify the model. Results show that the model parameters are more uniform and reasonable. Meanwhile, the model accuracy has improved by 57% and 66% compared to the two baseline models respectively. Moreover, the model demonstrates its ability to generate critical pre-crash scenarios and estimate the crash rate of distracted driving. The proposed model is expected to contribute to safety research regarding new vehicle technologies and traffic safety analysis.

Exosomes derived from HUVECs alleviate ischemia-reperfusion induced inflammation in neural cells by upregulating KLF14 expression.

Neuroinflammation plays a key role in the progression of secondary brain injury after ischemic stroke, and exosomes have been increasingly recognized to eliminate inflammatory responses through various mechanisms. This study aimed to explore the effect and possible mechanism of human umbilical vein endothelial cells derived exosomes (H-EXOs) on neuroinflammation. We established a transient middle cerebral artery occlusion/reperfusion (tMCAO/R) in male rats and oxygen-glucose-deprivation/reoxygenation (OGD/R) model in cultured neurons to mimic secondary brain injury after ischemic stroke in vivo. H-EXOs were administered at the same time of reperfusion. Results showed that the production of pro-inflammatory cytokines TNF-α, IL-1β, and IL-6, and the transcription factor Krüppel-like factor 14 (KLF14) were significantly increased both in rat brain tissue and cultured neural cells after ischemic-reperfusion (I/R) injury. H-EXOs treatment significantly improved the cultured cell viability, reduced infarct sizes, mitigated neurobehavioral defects, and alleviated the expression of pro-inflammatory cytokines compared with the control group, indicating that H-EXOs exerted anti-inflammatory effect against I/R injury. Further studies revealed that the anti-inflammatory effect of H-EXOs could be weakened by small-interfering RNA (siKLF4) transfection. KLF14 was a protective factor produced during cerebral ischemia-reperfusion injury. In conclusion, H-EXOs protect neurons from inflammation after I/R injury by enhancing KLF14 expression.

Electro-Immobilisation and Fish Welfare: An Investigation into Stress, Consciousness, and Physiological Aspects During Slaughter

ABSTRACT The aquaculture industry frequently employs various slaughter methods that subject fish to inhumane conditions, resulting in significant suffering. This study examined the effects of electrical method on the welfare of farmed fish (Mesopotamichthys sharpeyi) compared to air asphyxiation. Fish captured with electricity exhibited calm behavior until death, in contrast to fish treated with air asphyxiation, which exhibited violent responses within 4 minutes of capture. The electrical method achieved a complete state of unconsciousness 7 minutes faster than air asphyxiation. Our results show that air asphyxiation raised cortisol levels more than the electrical method, with no significant difference in glucose and lactate concentrations. Electrically treated fish had higher superoxide dismutase and liver-reduced glutathione levels, while suffocated fish showed elevated GSH and liver catalase levels. Radiographs revealed no fractures or skeletal changes. Electrical stunning had no effect on gill tissue, but caused brain tissue hemorrhage, whereas air asphyxiation caused less damage. Air asphyxiation caused gill tissue issues but less brain damage. Consciousness loss is crucial for humane practices. Specific electrical currents (110V for 30s) could improve aquaculture and fish welfare.

Delta opioid peptide [D-ala2, D-leu5]-Enkephalin’s ability to enhance mitophagy via TRPV4 to relieve ischemia/reperfusion injury in brain microvascular endothelial cells

BackgroundLocal brain tissue can suffer from ischaemia/reperfusion (I/R) injury, which lead to vascular endothelial damage. The peptide δ opioid receptor (δOR) agonist [D-ala2, D-leu5]-Enkephalin (DADLE) can reduce apoptosis caused by...

Hippocampal volume mediates the association of arterial stiffness with cognitive impairment in adult population.

To investigate the association of arterial stiffness with brain perfusion, brain tissue volume and cognitive impairment in the general adult population. This prospective study included 1488 adult participants (age range: 22.8-83.9 years) from the Kailuan study. All participants underwent brachial-ankle pulse wave velocity (PWV) measurement, brain MRI, and Montreal Cognitive Assessment (MoCA). The association of PWV with cerebral blood flow (CBF), brain tissue volume and MoCA score was investigated. Mediation analysis was used to determine whether CBF and brain tissue volume changes mediated the associations between PWV and MoCA score. A 1 standard deviation (SD) increase in PWV was associated with lower total brain CBF [β (95% CI) -0.67 (-1.2 to -0.14)], total gray matter CBF [β (95% CI) -0.7 [-1.27 to -0.13)], frontal lobe CBF [β (95% CI) -0.59 (-1.17 to -0.01)], parietal lobe CBF [β (95% CI) -0.8 (-1.43 to -0.18)], and temporal lobe CBF [β (95% CI) -0.68 (-1.24 to -0.12)]. Negative associations were found for PWV and total brain volume [β (95% CI) -4.8 (-7.61 to -1.99)] and hippocampus volume [β (95% CI) -0.08 (-0.13 to -0.04)]. A 1 SD increase PWV was significantly associated with elevated odds of developing cognitive impairment [odds ratio (95% CI) 1.21 (1.01-1.45)]. Mediation analysis showed that hippocampal volume partially mediated the negative association between PWV and MoCA scores (proportion: 14.173%). High arterial stiffness was associated with decreased total and regional CBF, brain tissue volume, and cognitive impairment. Hippocampal volume partially mediated the effects of arterial stiffness on cognitive impairment.

In Search for Low-Molecular-Weight Ligands of Human Serum Albumin That Affect Its Affinity for Monomeric Amyloid β Peptide.

An imbalance between production and excretion of amyloid β peptide (Aβ) in the brain tissues of Alzheimer's disease (AD) patients leads to Aβ accumulation and the formation of noxious Aβ oligomers/plaques. A promising approach to AD prevention is the reduction of free Aβ levels by directed enhancement of Aβ binding to its natural depot, human serum albumin (HSA). We previously demonstrated the ability of specific low-molecular-weight ligands (LMWLs) in HSA to improve its affinity for Aβ. Here we develop this approach through a bioinformatic search for the clinically approved AD-related LMWLs in HSA, followed by classification of the candidates according to the predicted location of their binding sites on the HSA surface, ranking of the candidates, and selective experimental validation of their impact on HSA affinity for Aβ. The top 100 candidate LMWLs were classified into five clusters. The specific representatives of the different clusters exhibit dramatically different behavior, with 3- to 13-fold changes in equilibrium dissociation constants for the HSA-Aβ40 interaction: prednisone favors HSA-Aβ interaction, mefenamic acid shows the opposite effect, and levothyroxine exhibits bidirectional effects. Overall, the LMWLs in HSA chosen here provide a basis for drug repurposing for AD prevention, and for the search of medications promoting AD progression.

Optical Methods for Brain Tumor Detection: A Systematic Review.

Background: In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. Methods: This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. Results: In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. Conclusions: This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.

Test-retest reliability and time-of-day variations of perfusion imaging at rest and during a vigilance task.

Arterial spin-labeled perfusion and blood oxygenation level-dependent functional MRI are indispensable tools for noninvasive human brain imaging in clinical and cognitive neuroscience, yet concerns persist regarding the reliability and reproducibility of functional MRI findings. The circadian rhythm is known to play a significant role in physiological and psychological responses, leading to variability in brain function at different times of the day. Despite this, test-retest reliability of brain function across different times of the day remains poorly understood. This study examined the test-retest reliability of six repeated cerebral blood flow measurements using arterial spin-labeled perfusion imaging both at resting-state and during the psychomotor vigilance test, as well as task-induced cerebral blood flow changes in a cohort of 38 healthy participants over a full day. The results demonstrated excellent test-retest reliability for absolute cerebral blood flow measurements at rest and during the psychomotor vigilance test throughout the day. However, task-induced cerebral blood flow changes exhibited poor reliability across various brain regions and networks. Furthermore, reliability declined over longer time intervals within the day, particularly during nighttime scans compared to daytime scans. These findings highlight the superior reliability of absolute cerebral blood flow compared to task-induced cerebral blood flow changes and emphasize the importance of controlling time-of-day effects to enhance the reliability and reproducibility of future brain imaging studies.

Tumors Affect the Metabolic Connectivity of the Human Brain Measured by 18F-FDG PET.

18F-FDG PET captures the relationship between glucose metabolism and synaptic activity, allowing for modeling brain function through metabolic connectivity. We investigated tumor-induced modifications of brain metabolic connectivity. Forty-three patients with left hemispheric tumors and 18F-FDG PET/MRI were retrospectively recruited. We included 37 healthy controls (HCs) from the database CERMEP-IDB-MRXFDG. We analyzed the whole brain and right versus left hemispheres connectivity in patients and HC, frontal versus temporal tumors, active tumors versus radiation necrosis, and patients with high Karnofsky performance score (KPS = 100) versus low KPS (KPS < 70). Results were compared with 2-sided t test (P < 0.05). Twenty high-grade glioma, 4 low-grade glioma, and 19 metastases were included. The patients' whole-brain network displayed lower connectivity metrics compared with HC (P < 0.001), except assortativity and betweenness centrality (P = 0.001). The patients' left hemispheres showed decreased similarity, and lower connectivity metrics compared with the right (P < 0.01), with the exception of betweenness centrality (P = 0.002). HC did not show significant hemispheric differences. Frontal tumors showed higher connectivity metrics (P < 0.001) than temporal tumors, but lower betweenness centrality (P = 4.5-7). Patients with high KPS showed higher distance local efficiency (P = 0.01), rich club coefficient (P = 0.0048), clustering coefficient (P = 0.00032), betweenness centrality (P = 0.008), and similarity (P = 0.0027) compared with low KPS. Patients with active tumor(s) (14/43) demonstrated significantly lower connectivity metrics compared with necroses. Tumors cause reorganization of metabolic brain networks, characterized by formation of new connections and decreased centrality. Patients with frontal tumors retained a more efficient, centralized, and segregated network than patients with temporal tumors. Stronger metabolic connectivity was associated with higher KPS.

Emulation of optical and electrical synaptic functions in MoS2/SnSe2 van der Waals heterojunction memtransistors

Abstract The simulation of advanced synaptic functions of the human brain by electrical devices could be an effective strategy towards constructing high-efficiency neuromorphic systems. Two-dimensional (2D) materials are promising candidates in fabrication of optoelectronic devices due to their excellent photoelectric performances. Herein, opto-electronic synapses based on layered MoS2/SnSe2 van der Waals heterojunction (vdWH) memtransistors have been investigated. It can be observed that the typical synaptic functions, such as excitatory/inhibitory postsynaptic current (EPSC/IPSC), long-term potentiation/depression (LTP/LTD), paired-pulse facilitation/depression (PPF/PPD), as well as the transition from short-term memory (STM) to long-term memory (LTM) are realized using both electrical and optical pulses as input signals. In addition, the time constant for PPF under optical pulses was 3.91 s, which was comparable with the response times of biological neural synapses. So the MoS2/SnSe2 memtransistor could work as an electronic synapse in future artificial neural networks, inspiring the implementation of 2D materials for neuromorphic computation.

Nymphaea Alba for Resistive Switching Devices: Exploring the Non‐Volatile Memory and Neuromorphic Computing Applications of the Plant Leaves

AbstractBiomaterial‐based resistive switching memory is one promising technology that could significantly impact the current direction of non‐volatile memory and neuromorphic computing. Given this, we report the fabrication of a resistive switching (RS) device based on Nymphaea Alba as an active switching layer and investigate its RS properties for memory and neuromorphic computing applications. The Nymphaea Alba switching layer was deposited by the conventional doctor blade method. Further, this is characterized by various analytical techniques. The fabricated device showed bipolar RS behavior and demonstrated good non‐volatile memory properties. Additionally, the device mimics various synaptic properties of the human brain, such as potentiation‐depression, Excitatory post‐synaptic current (EPSC), and Paired‐pulse facilitation (PPF). The charge‐flux relation reveals the non‐ideal memristor‐type behavior of the device. The Ohmic and Child's square law dominates the conduction of the device and the filamentary process responsible for the RS process of the device. These results show that the Nymphaea Alba is a promising biomaterial for non‐volatile memory applications.

Wishful Thinking about Consciousness

We contrast three very distinct mathematical approaches to the hard problem of consciousness: quantum consciousness, integrated information theory, and the very large-scale dynamical systems simulation of a network of networks. We highlight their features and their associated hypotheses, and we discuss how they are aligned or in conflict. We suggest some challenges to these theories, in considering how they might apply to the human brain as it develops both cognitive and conscious sophistication, from infancy to adulthood. We indicate how an evolutionary perspective challenges the distinct approaches to aver performance advantages and physiological surrogates for consciousness.

Optimal treatment conditions for low-intensity pulsed ultrasound therapy for Alzheimer's disease: applications from mice to humans.

We previously developed a novel therapy with low-intensity pulsed ultrasound (LIPUS) that ameliorates cognitive decline through upregulation of endothelial nitric oxide synthase (eNOS) in mouse models of Alzheimer's disease (AD). In a randomized, double-blind, placebo-controlled pilot trial, we demonstrated that whole-brain LIPUS therapy is safe and tends to suppress the cognitive decline in early AD patients. We herein report the findings of our basic experiments that we performed for the pilot trial in order to apply whole-brain LIPUS therapy to humans, as well. First, we examined the relationship between bone density/thickness and ultrasound transmittance using human temporal bone. Next, based on the results of ultrasound transmittance, we further examined mRNA expression of VEGF, FGF2, and eNOS in response to variable ultrasound frequencies, duty cycles, and sound pressures. There was a significant correlation between bone thickness and transmittance (1.0MHz, P < 0.001), while there was no significant correlation between bone density and transmittance (1.0MHz, P = 0.421). At a frequency of 0.5MHz, the optimum duty cycle was considered to be up to 20%. When the tissue amplitude was in the range of 0.05-0.5MPa, VEGF, FGF2, and eNOS were significantly upregulated by LIPUS. Thus, the conditions necessary for LIPUS therapy for the human brain were identified as sound pressure just below the probe 1.3MPa (tissue amplitude 0.15MPa), duty cycle 5%, and frequency 0.5MHz. We successfully identified the optimal treatment conditions for LIPUS therapy for patients with AD.