The indication of palliative whole-brain radiotherapy for patients with brain metastases: a simple prognostic scoring system in the era of stereotactic radiosurgery.

BACKGROUND: Stereotactic irradiation has become the mainstay treatment for brain metastases (BM), and whole-brain radiotherapy (WBRT) is often used for symptom palliation. However, the survival time of patients with BM undergoing palliative WBRT (pWBRT) is limited, making it difficult to select patients who should receive treatment. METHODS: We collected patient data from 2016 to 2022 at the Shizuoka Cancer Center and retrospectively analyzed the factors related to survival time. Overall survival (OS) was defined as the survival time after WBRT. RESULTS: A total of 301 patients (median age, 66 years) who underwent pWBRT were included. The primary cancers were lung, breast, gastrointestinal tract, and other cancers in 203 (67%), 38 (13%), 33 (11%), and 27 (9%) patients, respectively. Median OS of all patients was 4.1 months. In the multivariate analysis, male sex (hazard ratio [HR]:1.4), Karnofsky Performance Status (KPS) ≤ 60 (HR:1.7), presence of extracranial metastasis (ECM) (HR:1.6), neutrophil-lymphocyte ratio (NLR) ≥ 5 (HR:1.6), and lactate dehydrogenase (LDH) ≥ upper limit of normal (ULN) (HR:1.3) were significantly associated with shorter OS (all P < 0.05). To predict the OS, we created a prognostic scoring system (PSS). We gave one point to each independent prognostic factor. Median OS for patients with scores of 0-2, 3, and 4-5 were 9.0, 3.5 and 1.7 months, respectively (P < 0.001). CONCLUSIONS: Male sex, KPS ≤ 60, presence of ECM, NLR ≥ 5, and LDH ≥ ULN were poor prognostic factors for patients with BM undergoing pWBRT. By PSS combining these factors, it may be possible to select patients who should undergo pWBRT.

Assessment of different head tilt angles in volumetric modulated arc therapy for hippocampus-avoidance whole-brain radiotherapy.

Purpose: In the field of radiation therapy for brain metastases, whole-brain hippocampus-avoidance treatment is commonly employed. this study aims to examine the impact of different head tilt angles on the dose distribution in the whole-brain target area and organs at risk. It also aims to determine the head tilt angle to achieve optimal radiation therapy outcomes. Methods: CT images were collected from 8 brain metastases patients at 5 different groups of head tilt angle. The treatment plans were designed using the volumetric modulated arc therapy (VMAT) technique. The 5 groups of tilt angle were as follows: [0°,10°), [10°,20°), [20°,30°), [30°,40°), and [40°,45°]. The analysis involved assessing parameters such as the uniformity index, conformity index, average dose delivered to the target, dose coverage of the target, hot spots within the target area, maximum dose, and average dose received by organs at risk. Additionally, the study evaluated the correlation between hippocampal dose and other factors, and established linear regression models. Results: Significant differences in dosimetric results were observed between the [40°,45°] and [0°,10°) head tilt angles. The [40°,45°] angle showed significant differences compared to the [0°,10°) angle in the average dose in the target area (31.49 ± 0.29 Gy vs. 31.99 ± 0.29 Gy, p=0.016), dose uniformity (1.20 ± 0.03 vs. 1.24 ± 0.03, p=0.016), hotspots in the target area (33.64 ± 0.35 Gy vs. 34.42 ± 0.49 Gy, p=0.016), maximum hippocampal dose (10.73 ± 0.36 Gy vs. 11.66 ± 0.59 Gy, p=0.008), maximum dose in the lens (2.82 ± 1.10 Gy vs. 4.99 ± 0.16 Gy, p=0.016), and average dose in the lens (1.93 ± 0.29 Gy vs. 4.22 ± 0.26 Gy, p=0.008). There is a moderate correlation between the maximum dose in the hippocampi and the PTV length (r=0.49, p=0.001). Likewise, the mean dose in the hippocampi is significantly correlated with the hippocampi length (r=0.34, p=0.04). Conclusion: The VMAT plan with a head tilt angle of [40°,45°] met all dose constraints and demonstrated improved uniformity of the target area while reducing the dose to organs at risk. Furthermore, the linear regression models suggest that increasing the head tilt angle within the current range of [0°,45°] is likely to lead to a decrease in the average hippocampal dose.

Treatment Options for Brain Metastases.

OPINION STATEMENT: Therapies for brain metastasis continue to evolve as the life expectancies for patients have continued to prolong. Novel advances include the use of improved technology for radiation delivery, surgical guidance, and response assessment, along with systemic therapies that can pass through the blood brain barrier. With increasing complexity of treatments and the increased need for salvage treatments, multi-disciplinary management has become significantly more important.

Efficacy of Whole-Brain Radiotherapy Plus Simultaneous Integrated Boost (SIB-WBRT) for Lung Cancer Brain Metastases.

Objective: To investigate the outcomes of SIB-WBRT in patients with brain metastases and analyze the impact of some factors on prognosis. Materials and Methods: This single-arm retrospective study analyzed patients with brain metastases who were treated with SIB-WBRT at Peking Union Medical College Hospital from September 2015 to December 2021. The primary endpoint was intracranial progression free survival (iPFS). Secondary endpoints included overall survival (OS), intracranial new foci, and tumor control. The Kaplan-Meier method was then used to depict and estimate iPFS, OS, intracranial neoplasia, and tumor control. Finally, the Cox model was used to analyze the association between some relevant factors and outcomes. Results: A total of 107 patients were included and the median iPFS in these patients treated with SIB-WBRT was 13.4 (95% CI: 4.2-22.6) months, with 68.0% (95% CI: 57.4%-78.6%) and 50.8% (95% CI: 38.3%-63.3%) iPFS at 6- and 12-months. The median local control was 37.6 (95% CI: 28.3-46.8) months, with local control rates of 84.3% (95% CI: 80.6%-88.0%) and 73.3% (95% CI: 68.2%-78.4%) at 6- and 12-months. The median time to appearance of new intracranial foci was 17.4 (95% CI: 14.1-20.8) months, and the 6- and 12-month control rates were 74.5% (95% CI: 64.5%-84.5%) and 61.5% (95% CI: 49.0%-74.0%). The number of brain metastases in patients before treatment was significantly associated with iPFS (HR=0.4, 95% CI: 0.2-0.973, P=0.043). Conclusions: The iPFS, local control, and intracranial new foci of patients with brain metastases after treatment with SIB-WBRT were acceptable. In addition, the number of brain metastases in patients before treatment may be associated with iPFS.

A Randomised Phase II Trial of Hippocampal Sparing Versus Conventional Whole Brain Radiotherapy After Surgical Resection or Radiosurgery in Favourable Prognosis Patients With 1-10 Brain Metastases.

AIMS: To assess in patients with 1-10 brain metastases, each of which has been treated by neurosurgery or stereotactic radiosurgery, whether hippocampal sparing whole brain radiotherapy (HS-WBRT) better spares neurocognitive function (NCF) than standard WBRT. Further, to assess whether a phase III randomised trial of HS-WBRT would be feasible in the UK. MATERIALS AND METHODS: A multicentre, randomised, open label phase II trial was undertaken, randomising patients to 30Gy in 10 fractions of WBRT or HS-WBRT. The primary endpoint was decline in Total recall using Hopkins Verbal Learning Test Revised (HVLT-R) at 4 months post treatment. To assess this, we aimed to recruit 84 patients over 3 years. Secondary endpoints included further measures of NCF, quality of life, duration of functional independence, local control of treated metastases, development of new metastases, disease control within the hippocampal regions, overall survival, steroid and antiepileptic medication requirements, and toxicity. RESULTS: The trial closed prematurely due to slower than anticipated recruitment. From April 2016 to January 2018, 23 patients were randomised. Follow up was a median of 25 months. Fifteen patients (6 WBRT, 9 HS-WBRT) were assessed for the primary endpoint; of these, 1 in each arm experienced significant decline in the 4-month HVLT-R Total recall score (p = 0.8). Patients in the HS-WBRT arm experienced less insomnia (p < 0.01) and drowsiness (p < 0.01). There were no differences in other secondary endpoints. CONCLUSION: A phase III randomised trial of HS-WBRT was shown not to be feasible at this time in the UK. As most randomised trials of HS-WBRT reported to date share common endpoints, including NCF, an individual patient data meta-analysis should be undertaken.

Dilated lenticulostriate artery on whole-brain vessel wall imaging differentiates pathogenesis and predicts clinical outcomes in single subcortical infarction.

OBJECTIVES: This study aimed to investigate the dilation of lenticulostriate artery (LSA) identified by whole-brain vessel wall imaging (WB-VWI) in differentiating the etiologic subtypes of single subcortical infarction (SSI) and to determine whether the appearance of dilated LSA was associated with 90-day clinical outcomes in parental atherosclerotic disease (PAD)-related SSI. METHODS: Patients with acute SSI were prospectively enrolled and categorized into PAD-related SSI and cerebral small-vessel disease (CSVD)-related SSI groups. The imaging features of LSA morphology (branches, length, dilation, and tortuosity), plaques (burden, remodeling index, enhancement degree, and hyperintense plaque), and CSVD (white matter hyperintensity, lacunes, cerebral microbleed, and enlarged perivascular space) were evaluated. The logistic regression was performed to determine the association of dilated LSA with PAD-related SSI and 90-day clinical outcomes. RESULTS: In total, 131 patients (mean age, 52.2 ± 13.2 years; 99 men) were included. The multivariate logistic regression analysis revealed that the presence of dilated LSAs (odds ratio (OR), 7.40; 95% confidence interval (CI): 1.88-29.17; p = 0.004)) was significantly associated with PAD-related SSI. Moreover, after adjusting for confounding factors, the association of poor outcomes with the total length of LSAs (OR, 0.94; 95% CI: 0.90-0.99; p = 0.011), dilated LSAs (OR, 0.001; 95% CI: 0.0001-0.08; p = 0.002), and plaque burden (OR, 1.35; 95% CI: 1.11-1.63; p = 0.002) remained statistically significant. CONCLUSION: The dilation of LSA visualized on WB-VWI could differentiate various subtypes of SSI within LSA territory and was a prognostic imaging marker for 90-day clinical outcomes for PAD-related SSI. CLINICAL RELEVANCE STATEMENT: Evaluation of LSA morphology based on WB-VWI can differentiate the pathogenesis and predict clinical outcomes in SSI, providing crucial insights into the etiologic mechanisms, risk stratification, and tailored therapies for these patients. KEY POINTS: The prognosis of SSIs within lenticulostriate territory depend on the etiology of the disease. LSA dilation on WB-VWI was associated with parental atherosclerosis and better 90-day outcomes. Accurately identifying the etiology of SSIs in lenticulostriate territory assists in treatment decision-making.

In-vivo neuronal dysfunction by Aß and tau overlaps with brain-wide inflammatory mechanisms in Alzheimer's disease.

The molecular mechanisms underlying neuronal dysfunction in Alzheimer's disease (AD) remain uncharacterized. Here, we identify genes, molecular pathways and cellular components associated with whole-brain dysregulation caused by amyloid-beta (Aß) and tau deposits in the living human brain. We obtained in-vivo resting-state functional MRI (rs-fMRI), Aß- and tau-PET for 47 cognitively unimpaired and 16 AD participants from the Translational Biomarkers in Aging and Dementia cohort. Adverse neuronal activity impacts by Aß and tau were quantified with personalized dynamical models by fitting pathology-mediated computational signals to the participant's real rs-fMRIs. Then, we detected robust brain-wide associations between the spatial profiles of Aß-tau impacts and gene expression in the neurotypical transcriptome (Allen Human Brain Atlas). Within the obtained distinctive signature of in-vivo neuronal dysfunction, several genes have prominent roles in microglial activation and in interactions with Aß and tau. Moreover, cellular vulnerability estimations revealed strong association of microglial expression patterns with Aß and tau's synergistic impact on neuronal activity (q < 0.001). These results further support the central role of the immune system and neuroinflammatory pathways in AD pathogenesis. Neuronal dysregulation by AD pathologies also associated with neurotypical synaptic and developmental processes. In addition, we identified drug candidates from the vast LINCS library to halt or reduce the observed Aß-tau effects on neuronal activity. Top-ranked pharmacological interventions target inflammatory, cancer and cardiovascular pathways, including specific medications undergoing clinical evaluation in AD. Our findings, based on the examination of molecular-pathological-functional interactions in humans, may accelerate the process of bringing effective therapies into clinical practice.

Individualized epidemic spreading models predict epilepsy surgery outcomes: A pseudo-prospective study.

Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients, but up to 50% of patients continue to have seizures one year after the resection. In order to aid presurgical planning and predict postsurgical outcome on a patient-by-patient basis, we developed a framework of individualized computational models that combines epidemic spreading with patient-specific connectivity and epileptogeneity maps: the Epidemic Spreading Seizure and Epilepsy Surgery framework (ESSES). ESSES parameters were fitted in a retrospective study (N = 15) to reproduce invasive electroencephalography (iEEG)-recorded seizures. ESSES reproduced the iEEG-recorded seizures, and significantly better so for patients with good (seizure-free, SF) than bad (nonseizure-free, NSF) outcome. We illustrate here the clinical applicability of ESSES with a pseudo-prospective study (N = 34) with a blind setting (to the resection strategy and surgical outcome) that emulated presurgical conditions. By setting the model parameters in the retrospective study, ESSES could be applied also to patients without iEEG data. ESSES could predict the chances of good outcome after any resection by finding patient-specific model-based optimal resection strategies, which we found to be smaller for SF than NSF patients, suggesting an intrinsic difference in the network organization or presurgical evaluation results of NSF patients. The actual surgical plan overlapped more with the model-based optimal resection, and had a larger effect in decreasing modeled seizure propagation, for SF patients than for NSF patients. Overall, ESSES could correctly predict 75% of NSF and 80.8% of SF cases pseudo-prospectively. Our results show that individualised computational models may inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection. This is the first time that such a model is validated with a fully independent cohort and without the need for iEEG recordings.

Individualized computational models of epilepsy surgery capture some of the key aspects of seizure propagation and the resective surgery. It is to be established whether this information can be integrated during the presurgical evaluation of the patient to improve surgical planning and the chances of a good surgical outcome. Here we address this question with a pseudo-prospective study that applies a computational framework of seizure propagation and epilepsy surgery­the ESSES framework­in a pseudo-prospective study mimicking the presurgical conditions. We found that within this pseudo-prospective setting, ESSES could correctly predict 75% of NSF and 80.8% of SF cases. This finding suggests the potential of individualised computational models to inform surgical planning by suggesting alternative resections and providing information on the likelihood of a good outcome after a proposed resection.

Inducing a meditative state by artificial perturbations: A mechanistic understanding of brain dynamics underlying meditation.

Contemplative neuroscience has increasingly explored meditation using neuroimaging. However, the brain mechanisms underlying meditation remain elusive. Here, we implemented a mechanistic framework to explore the spatiotemporal dynamics of expert meditators during meditation and rest, and controls during rest. We first applied a model-free approach by defining a probabilistic metastable substate (PMS) space for each condition, consisting of different probabilities of occurrence from a repertoire of dynamic patterns. Moreover, we implemented a model-based approach by adjusting the PMS of each condition to a whole-brain model, which enabled us to explore in silico perturbations to transition from resting-state to meditation and vice versa. Consequently, we assessed the sensitivity of different brain areas regarding their perturbability and their mechanistic local-global effects. Overall, our work reveals distinct whole-brain dynamics in meditation compared to rest, and how transitions can be induced with localized artificial perturbations. It motivates future work regarding meditation as a practice in health and as a potential therapy for brain disorders.

Our work explores brain dynamics in a group of expert meditators and controls. First, we characterized meditation and rest with a repertoire of brain patterns, each with its distinct probability of occurrence. Then, we generated whole-brain models of each condition, which enabled us to artificially perturb the systems to induce transitions between rest and meditation. Our results open new avenues in meditation research as a practice in health and disease.

Whole-brain model replicates sleep-like slow-wave dynamics generated by stroke lesions.

Focal brain injuries, such as stroke, cause local structural damage as well as alteration of neuronal activity in distant brain regions. Experimental evidence suggests that one of these changes is the appearance of sleep-like slow waves in the otherwise awake individual. This pattern is prominent in areas surrounding the damaged region and can extend to connected brain regions in a way consistent with the individual's specific long-range connectivity patterns. In this paper we present a generative whole-brain model based on (f)MRI data that, in combination with the disconnection mask associated with a given patient, explains the effects of the sleep-like slow waves originated in the vicinity of the lesion area on the distant brain activity. Our model reveals new aspects of their interaction, being able to reproduce functional connectivity patterns of stroke patients and offering a detailed, causal understanding of how stroke-related effects, in particular slow waves, spread throughout the brain. The presented findings demonstrate that the model effectively captures the links between stroke occurrences, sleep-like slow waves, and their subsequent spread across the human brain.

An arginine-rich nuclear localization signal (ArgiNLS) strategy for streamlined image segmentation of single cells.

High-throughput volumetric fluorescent microscopy pipelines can spatially integrate whole-brain structure and function at the foundational level of single cells. However, conventional fluorescent protein (FP) modifications used to discriminate single cells possess limited efficacy or are detrimental to cellular health. Here, we introduce a synthetic and nondeleterious nuclear localization signal (NLS) tag strategy, called "Arginine-rich NLS" (ArgiNLS), that optimizes genetic labeling and downstream image segmentation of single cells by restricting FP localization near-exclusively in the nucleus through a poly-arginine mechanism. A single N-terminal ArgiNLS tag provides modular nuclear restriction consistently across spectrally separate FP variants. ArgiNLS performance in vivo displays functional conservation across major cortical cell classes and in response to both local and systemic brain-wide AAV administration. Crucially, the high signal-to-noise ratio afforded by ArgiNLS enhances machine learning-automated segmentation of single cells due to rapid classifier training and enrichment of labeled cell detection within 2D brain sections or 3D volumetric whole-brain image datasets, derived from both staining-amplified and native signal. This genetic strategy provides a simple and flexible basis for precise image segmentation of genetically labeled single cells at scale and paired with behavioral procedures.

Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients.

Computational whole-brain models describe the resting activity of each brain region based on a local model, inter-regional functional interactions, and a structural connectome that specifies the strength of inter-regional connections. Strokes damage the healthy structural connectome that forms the backbone of these models and produce large alterations in inter-regional functional interactions. These interactions are typically measured by correlating the time series of the activity between two brain regions in a process, called resting functional connectivity. We show that adding information about the structural disconnections produced by a patient's lesion to a whole-brain model previously trained on structural and functional data from a large cohort of healthy subjects enables the prediction of the resting functional connectivity of the patient and fits the model directly to the patient's data (Pearson correlation = 0.37; mean square error = 0.005). Furthermore, the model dynamics reproduce functional connectivity-based measures that are typically abnormal in stroke patients and measures that specifically isolate these abnormalities. Therefore, although whole-brain models typically involve a large number of free parameters, the results show that, even after fixing those parameters, the model reproduces results from a population very different than that on which the model was trained. In addition to validating the model, these results show that the model mechanistically captures the relationships between the anatomical structure and the functional activity of the human brain.

Psychedelics and disorders of consciousness: the current landscape and the path forward.

Modern medicine has been shaken by the surge of psychedelic science that proposes a new approach to mitigate mental disorders, such as depression and post-traumatic stress disorder. Clinical trials to investigate whether psychedelic substances can treat psychiatric conditions are now underway, yet less discussion gravitates around their use in neurological disorders due to brain injury. One suggested implementation of brain-complexity enhancing psychedelics is to treat people with post-comatose disorders of consciousness (DoC). In this article, we discuss the rationale of this endeavour, examining possible outcomes of such experiments by postulating the existence of an optimal level of complexity. We consider the possible counterintuitive effects of both psychedelics and DoC on the functional connectivity of the default mode network and its possible impact on selfhood. We also elaborate on the role of computational modelling in providing complementary information to experimental studies, both contributing to our understanding of the treatment mechanisms and providing a path towards personalized medicine. Finally, we update the discourse surrounding the ethical considerations, encompassing clinical and scientific values.

A Phase II Trial of Bevacizumab in Patients with Recurrent/Progressive Solid Tumor Brain Metastases That Have Progressed Following Whole-Brain Radiation Therapy.

Patients with solid tumor brain metastases that progress after whole-brain radiation have limited options. This prospective trial investigated the efficacy, safety, and tolerability of bevacizumab as salvage therapy in this population. Eligible patients received bevacizumab 10 mg/kg intravenously every 2 weeks until progression. The primary endpoint was radiologic response using Response Assessment in Neuro-Oncology (RANO) criteria. The secondary endpoints were progression-free survival (PFS), overall survival (OS), duration of response, and safety. Quality of life (QOL) was studied using the Functional Assessment of Cancer Therapy-Brain (FACT-Br) scale. Twenty-seven patients were enrolled, with twenty-four having evaluable data for response. The majority of histologies (n = 21, 78%) were breast cancer. The remaining histologies were non-small-cell lung cancer (n = 4, 15%), neuroendocrine cancer (n = 1, 3%), and papillary fallopian serous adenocarcinoma (n = 1, 3%). Eighteen patients had radiologic response, with two patients demonstrating partial response (8.33%) and sixteen patients demonstrating stable disease (66.7%). The median duration of response was 203 days. PFS at 6 months was 46%, median PFS was 5.3 m, and median OS was 9.5 m. Treatment was well tolerated, with six patients experiencing grade 3 lymphopenia and hypertension. There was one grade 3 thromboembolism. QOL was not negatively impacted. Bevacizumab is a safe and feasible salvage treatment with durable response and favorable overall survival for patients with progressive brain metastases after whole-brain radiation.

A complementary approach for neocortical cytoarchitecture inspection with cellular resolution imaging at whole brain scale.

Cytoarchitecture, the organization of cells within organs and tissues, serves as a crucial anatomical foundation for the delineation of various regions. It enables the segmentation of the cortex into distinct areas with unique structural and functional characteristics. While traditional 2D atlases have focused on cytoarchitectonic mapping of cortical regions through individual sections, the intricate cortical gyri and sulci demands a 3D perspective for unambiguous interpretation. In this study, we employed fluorescent micro-optical sectioning tomography to acquire architectural datasets of the entire macaque brain at a resolution of 0.65 µm × 0.65 µm × 3 µm. With these volumetric data, the cortical laminar textures were remarkably presented in appropriate view planes. Additionally, we established a stereo coordinate system to represent the cytoarchitectonic information as surface-based tomograms. Utilizing these cytoarchitectonic features, we were able to three-dimensionally parcel the macaque cortex into multiple regions exhibiting contrasting architectural patterns. The whole-brain analysis was also conducted on mice that clearly revealed the presence of barrel cortex and reflected biological reasonability of this method. Leveraging these high-resolution continuous datasets, our method offers a robust tool for exploring the organizational logic and pathological mechanisms of the brain's 3D anatomical structure.

Dynamical changes of interaction across functional brain communities during propofol-induced sedation.

It is crucial to understand how anesthetics disrupt information transmission within the whole-brain network and its hub structure to gain insight into the network-level mechanisms underlying propofol-induced sedation. However, the influence of propofol on functional integration, segregation, and community structure of whole-brain networks were still unclear. We recruited 12 healthy subjects and acquired resting-state functional magnetic resonance imaging data during 5 different propofol-induced effect-site concentrations (CEs): 0, 0.5, 1.0, 1.5, and 2.0 µg/ml. We constructed whole-brain functional networks for each subject under different conditions and identify community structures. Subsequently, we calculated the global and local topological properties of whole-brain network to investigate the alterations in functional integration and segregation with deepening propofol sedation. Additionally, we assessed the alteration of key nodes within the whole-brain community structure at each effect-site concentrations level. We found that global participation was significantly increased at high effect-site concentrations, which was mediated by bilateral postcentral gyrus. Meanwhile, connector hubs appeared and were located in posterior cingulate cortex and precentral gyrus at high effect-site concentrations. Finally, nodal participation coefficients of connector hubs were closely associated to the level of sedation. These findings provide valuable insights into the relationship between increasing propofol dosage and enhanced functional interaction within the whole-brain networks.

Innate Orientating Behavior of a Multi-Legged Robot Driven by the Neural Circuits of C. elegans.

The objective of this research is to achieve biologically autonomous control by utilizing a whole-brain network model, drawing inspiration from biological neural networks to enhance the development of bionic intelligence. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of the cellular synapses. The neural network simulation integrates computational programming and the visualization of the neurons and synapse connections of C. elegans, containing the specific controllable circuits and their dynamic characteristics. To illustrate the biological neural network (BNN)'s particular intelligent control capability, we introduced an innovative methodology for applying the BNN model to a 12-legged robot's movement control. Two methods were designed, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of the BNN. Both the simulation and experimental results indicate that the robot exhibits more autonomy and a more intelligent movement performance under BNN control. The systematic approach of employing the whole-brain BNN for robot control provides biomimetic research with a framework that has been substantiated by innovative methodologies and validated through the observed positive outcomes. This method is established as follows: (1) two integrated dynamic models of the C. elegans' whole-brain network and the robot moving dynamics are built, and all of the controllable circuits are discovered and verified; (2) real-time communication is achieved between the BNN model and the robot's dynamical model, both in the simulation and the experiments, including applicable encoding and decoding algorithms, facilitating their collaborative operation; (3) the designed mechanisms using the BNN model to control the robot are shown to be effective through numerical and experimental tests, focusing on 'foraging' behavior control and locomotion control.

NEATmap: a high-efficiency deep learning approach for whole mouse brain neuronal activity trace mapping.

Quantitative analysis of activated neurons in mouse brains by a specific stimulation is usually a primary step to locate the responsive neurons throughout the brain. However, it is challenging to comprehensively and consistently analyze the neuronal activity trace in whole brains of a large cohort of mice from many terabytes of volumetric imaging data. Here, we introduce NEATmap, a deep learning-based high-efficiency, high-precision and user-friendly software for whole-brain neuronal activity trace mapping by automated segmentation and quantitative analysis of immunofluorescence labeled c-Fos+ neurons. We applied NEATmap to study the brain-wide differentiated neuronal activation in response to physical and psychological stressors in cohorts of mice.

Altered Structural Connectivity and Functional Brain Dynamics in Individuals With Heavy Alcohol Use Elucidated via Network Control Theory.

BACKGROUND: Heavy alcohol use and its associated conditions, such as alcohol use disorder, impact millions of individuals worldwide. While our understanding of the neurobiological correlates of alcohol use has evolved substantially, we still lack models that incorporate whole-brain neuroanatomical, functional, and pharmacological information under one framework. METHODS: Here, we utilized diffusion and functional magnetic resonance imaging to investigate alterations to brain dynamics in 130 individuals with a high amount of current alcohol use. We compared these alcohol-using individuals to 308 individuals with minimal use of any substances. RESULTS: We found that individuals with heavy alcohol use had less dynamic and complex brain activity, and through leveraging network control theory, had increased control energy to complete transitions between activation states. Furthermore, using separately acquired positron emission tomography data, we deployed an in silico evaluation demonstrating that decreased D2 receptor levels, as found previously in individuals with alcohol use disorder, may relate to our observed findings. CONCLUSIONS: This work demonstrates that whole-brain, multimodal imaging information can be combined under a network control framework to identify and evaluate neurobiological correlates and mechanisms of heavy alcohol use.

Acetylcholine Neurons Become Cholinergic during Three Time Windows in the Developing Mouse Brain.

Acetylcholine (ACh) neurons in the central nervous system are required for the coordination of neural network activity during higher brain functions, such as attention, learning, and memory, as well as locomotion. Disturbed cholinergic signaling has been described in many neurodevelopmental and neurodegenerative disorders. Furthermore, cotransmission of other signaling molecules, such as glutamate and GABA, with ACh has been associated with essential roles in brain function or disease. However, it is unknown when ACh neurons become cholinergic during development. Thus, understanding the timeline of how the cholinergic system develops and becomes active in the healthy brain is a crucial part of understanding brain development. To study this, we used transgenic mice to selectively label ACh neurons with tdTomato. We imaged serial sectioned brains and generated whole-brain reconstructions at different time points during pre- and postnatal development. We found three crucial time windows-two in the prenatal and one in the postnatal brain-during which most ACh neuron populations become cholinergic in the brain. We also found that cholinergic gene expression is initiated in cortical ACh interneurons, while the cerebral cortex is innervated by cholinergic projection neurons from the basal forebrain. Taken together, we show that ACh neuron populations are present and become cholinergic before postnatal day 12, which is the onset of major sensory processes, such as hearing and vision. We conclude that the birth of ACh neurons and initiation of cholinergic gene expression are temporally separated during development but highly coordinated by brain anatomical structure.