Neural Networks, Год журнала: 2025, Номер unknown, С. 107209 - 107209
Опубликована: Янв. 1, 2025
Язык: Английский
medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2025, Номер unknown
Опубликована: Янв. 10, 2025
Abstract Brain structure plays a pivotal role in shaping neural dynamics. Current models lack the anatomical and functional resolution needed to accurately capture both structural dynamical features of human brain. Here, we introduce FEDE (high FidElity Digital brain modEl) pipeline, generating anatomically accurate digital twins from imaging data. Using advanced techniques tissue segmentation finite-element analysis, reconstructs with high spatial resolution, while also replicating whole-brain activity. We demonstrated its application by creating first twin toddler autism spectrum disorder (ASD). Through parameter optimization, replicated time-frequency recorded Notably, predicted patient-specific aberrant values excitation inhibition ratio, coherently ASD pathophysiology. represents significant leap forward modeling, paving way for more effective applications experimental clinical settings.
Язык: Английский
Процитировано
1
Physics of Life Reviews, Год журнала: 2023, Номер 45, С. 74 - 111
Опубликована: Апрель 25, 2023
Язык: Английский
Процитировано
19
NeuroImage, Год журнала: 2023, Номер 275, С. 120162 - 120162
Опубликована: Май 15, 2023
Disorders of consciousness are complex conditions characterised by persistent loss responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, highlight the urgent need a more thorough understanding how human arises from coordinated neural activity. The increasing availability multimodal neuroimaging data has given rise wide range clinically- scientifically-motivated modelling efforts, seeking improve data-driven stratification patients, identify causal mechanisms patient pathophysiology broadly, develop simulations as means testing in silico potential treatment avenues restore consciousness. As dedicated Working Group clinicians neuroscientists international Curing Coma Campaign, here we provide our framework vision understand diverse statistical generative computational approaches that being employed this fast-growing field. We gaps exist between current state-of-the-art biophysical neuroscience, aspirational goal mature field disorders consciousness; which might drive improved treatments outcomes clinic. Finally, make several recommendations whole can work together address these challenges.
Язык: Английский
Процитировано
18
Brain Informatics, Год журнала: 2023, Номер 10(1)
Опубликована: Фев. 24, 2023
Abstract Progress in dementia research has been limited, with substantial gaps our knowledge of targets for prevention, mechanisms disease progression, and disease-modifying treatments. The growing availability multimodal data sets opens possibilities the application machine learning artificial intelligence (AI) to help answer key questions field. We provide an overview state science, highlighting current challenges opportunities utilisation AI approaches move field forward areas genetics, experimental medicine, drug discovery trials optimisation, imaging, prevention. Machine methods can enhance results genetic studies, determine biological effects facilitate identification based on transcriptomic information. use unsupervised understanding is promising, while analysis characterise quantify severity subtype are also beginning contribute optimisation clinical trial recruitment. Data-driven medicine needed analyse across modalities develop novel algorithms translate insights from animal models human biology. neuroimaging outperform traditional diagnostic classification, although around validation translation remain, there optimism their meaningful integration practice near future. AI-based clarify causality commonality risk factors, informing improving prediction along development preventative interventions. complexity heterogeneity requires alternative approach beyond design analytical approaches. Although not yet widely used research, have potential unlock advance precision medicine.
Язык: Английский
Процитировано
16
eLife, Год журнала: 2023, Номер 12
Опубликована: Дек. 22, 2023
Elucidating the intricate neural mechanisms underlying brain functions requires integrative dynamics modeling. To facilitate this process, it is crucial to develop a general-purpose programming framework that allows users freely define models across multiple scales, efficiently simulate, train, and analyze model dynamics, conveniently incorporate new modeling approaches. In response need, we present BrainPy. BrainPy leverages advanced just-in-time (JIT) compilation capabilities of JAX XLA provide powerful infrastructure tailored for programming. It offers an integrated platform building, simulating, training, analyzing models. Models defined in can be JIT compiled into binary instructions various devices, including Central Processing Unit, Graphics Tensor which ensures high-running performance comparable native C or CUDA. Additionally, features extensible architecture easy expansion infrastructure, utilities, machine-learning This flexibility enables researchers cutting-edge techniques adapt their specific needs.
Язык: Английский
Процитировано
16
iScience, Год журнала: 2024, Номер 27(7), С. 110101 - 110101
Опубликована: Май 24, 2024
Язык: Английский
Процитировано
6
Frontiers in Systems Neuroscience, Год журнала: 2023, Номер 17
Опубликована: Май 10, 2023
The cerebellum operates exploiting a complex modular organization and unified computational algorithm adapted to different behavioral contexts. Recent observations suggest that the is involved not just in motor but also emotional cognitive processing. It therefore critical identify specific regional connectivity microcircuit properties of cerebellum. studies are highlighting differential localization genes, molecules, synaptic mechanisms wiring. However, impact these differences fully understood will require experimental investigation modeling. This review focuses on cellular circuit underpinnings cerebellar role emotion. And since emotion involves an integration cognitive, somatomotor, autonomic activity, we elaborate tradeoff between segregation distribution three main functions
Язык: Английский
Процитировано
15
Frontiers in Human Neuroscience, Год журнала: 2024, Номер 18
Опубликована: Март 18, 2024
Non-invasive brain stimulation (NIBS) is a complex and multifaceted approach to modulating activity holds the potential for broad accessibility. This work discusses mechanisms of four distinct approaches non-invasively: electrical currents, magnetic fields, light, ultrasound. We examine dual stochastic deterministic nature its implications NIBS, highlighting challenges posed by inter-individual variability, nebulous dose-response relationships, biases neuroanatomical heterogeneity. Looking forward, we propose five areas opportunity future research: closed-loop stimulation, consistent intended target region, reducing bias, multimodal approaches, strategies address low sample sizes.
Язык: Английский
Процитировано
5
Mammalian Genome, Год журнала: 2023, Номер 34(3), С. 389 - 407
Опубликована: Июль 8, 2023
Abstract The laboratory mouse is the foremost mammalian model used for studying human diseases and closely anatomically related to humans. Whilst knowledge about anatomy has been collected throughout history of mankind, first comprehensive study was published less than 60 years ago. This followed by more recent publication several books resources on anatomy. Nevertheless, date, our understanding far from being at same level as that In addition, alignment between current nomenclatures developed those existing other species, such domestic animals To close this gap, in depth anatomical research needed it will be necessary extent refine vocabulary terms.
Язык: Английский
Процитировано
11
Scientific Reports, Год журнала: 2024, Номер 14(1)
Опубликована: Фев. 7, 2024
Abstract Exploring how the emergent functional connectivity (FC) relates to underlying anatomy (structural connectivity, SC) is one of major goals modern neuroscience. At macroscale level, no one-to-one correspondence between structural and links seems exist. And we posit that better understand their coupling, two key aspects should be considered: directionality connectome limitations in explaining networks functions through an undirected measure such as FC. Here, employed accurate directed SC mouse brain acquired viral tracers compared it with single-subject effective (EC) matrices derived from a dynamic causal model (DCM) applied whole-brain resting-state fMRI data. We analyzed deviates EC quantified respective couplings by conditioning on strongest links. found when links, obtained coupling follows unimodal-transmodal hierarchy. Whereas reverse not true, there are strong within high-order cortical areas corresponding This mismatch even more clear across networks; only sensory motor did observe connections align terms both strength.
Язык: Английский
Процитировано
4