A5102957609- Neural dynamics and brain function
- Advanced Fluorescence Microscopy Techniques
- Neuroscience and Neuropharmacology Research
- Visual perception and processing mechanisms
- Cell Image Analysis Techniques
- Scientific Computing and Data Management
- Neuroscience and Neural Engineering
- Neurobiology and Insect Physiology Research
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Photoreceptor and optogenetics research
- Neuroinflammation and Neurodegeneration Mechanisms
- Advanced Memory and Neural Computing
- Muscle activation and electromyography studies
- Advanced Sensor and Energy Harvesting Materials
- Data Mining Algorithms and Applications
- Stress Responses and Cortisol
- Research Data Management Practices
- Computational Physics and Python Applications
- Photoacoustic and Ultrasonic Imaging
- Color perception and design
- Scientific Research and Philosophical Inquiry
- Neuroendocrine regulation and behavior
- Advanced X-ray and CT Imaging
- Data Management and Algorithms
Baylor College of Medicine
2014-2025
DataJoint NEURO (United States)
2021-2025
Baylor University
2008-2009
University of Utah
2008
Ripple (United States)
2007
Abstract Understanding the brain requires understanding neurons’ functional responses to circuit architecture shaping them. Here we introduce MICrONS connectomics dataset with dense calcium imaging of around 75,000 neurons in primary visual cortex (VISp) and higher areas (VISrl, VISal VISlm) an awake mouse that is viewing natural synthetic stimuli. These data are co-registered electron microscopy reconstruction containing more than 200,000 cells 0.5 billion synapses. Proofreading a subset...
Abstract Understanding the relationship between circuit connectivity and function is crucial for uncovering how brain computes. In mouse primary visual cortex, excitatory neurons with similar response properties are more likely to be synaptically connected 1–8 ; however, broader rules remain unknown. Here we leverage millimetre-scale MICrONS dataset analyse synaptic functional of across cortical layers areas. Our results reveal that preferentially within areas—including feedback...
Ambitious projects aim to record the activity of ever larger and denser neuronal populations in vivo. Correlations neural measured such recordings can reveal important aspects circuit organization. However, estimating interpreting large correlation matrices is statistically challenging. Estimation be improved by regularization, i.e. imposing a structure on estimate. The amount improvement depends how closely assumed represents dependencies data. Therefore, selection most efficient matrix...
Abstract The rise of big data in modern research poses serious challenges for management: Large and intricate datasets from diverse instrumentation must be precisely aligned, annotated, processed a variety ways to extract new insights. While high levels integrity are expected, teams have backgrounds, geographically dispersed, rarely possess primary interest science. Here we describe DataJoint, an open-source toolbox designed manipulating processing scientific under the relational model....
Understanding the relationship between circuit connectivity and function is crucial for uncovering how brain implements computation. In mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited within V1, leaving much unknown about broader rules. this study, we leverage millimeter-scale MICrONS dataset analyze synaptic functional of individual across cortical layers areas. Our...
Abstract To understand the brain we must relate neurons’ functional responses to circuit architecture that shapes them. Here, present a large connectomics dataset with dense calcium imaging of millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher areas (VISrl, VISal VISlm) an awake mouse viewing natural movies synthetic stimuli. The data were co-registered volumetric electron microscopy (EM) reconstruction containing...
Most upper limb prosthesis controllers only allow the individual selection and control of single joints limb. The main limiting factor for simultaneous multi-joint is usually availability reliable independent signals that can intuitively be used. In this paper, a novel method presented extraction muscle source from surface EMG array recordings, based on energy orthonormalization along principle movement vectors. cases where independently-controllable muscles are present in residual limbs,...
In primates and most carnivores, neurons in primary visual cortex are spatially organized by their functional properties. For example, with similar orientation preferences grouped together iso-orientation domains that smoothly vary over the cortical sheet. rodents, on other hand, different thought to be intermingled, a feature which has been termed “salt-and-pepper” organization. The apparent absence of any systematic structure tuning considered defining rodent system for more than decade,...
Abstract To better understand the representations in visual cortex, we need to generate predictions of neural activity awake animals presented with their ecological input: natural video. Despite recent advances models for static images, predicting responses video are scarce and standard linear-nonlinear perform poorly. We developed a new deep recurrent network architecture that predicts inferred spiking thousands mouse V1 neurons simulta-neously recorded two-photon microscopy, while...
Scientists are adopting new approaches to scale up their activities and goals. Progress in neurotechnologies, artificial intelligence, automation, tools for collaboration promises bursts of discoveries. However, compared other disciplines the industry, neuroscience laboratories have been slow adopt key technologies support collaboration, reproducibility, automation. Drawing on progress fields, we define a roadmap implementing automated research workflows diverse teams. We propose...
Abstract Scientific progress depends on reliable and reproducible results. Progress can also be accelerated when data are shared re-analyzed to address new questions. Current approaches storing analyzing neural typically involve bespoke formats software that make replication, as well the subsequent reuse of data, difficult if not impossible. To these challenges, we created Spyglass , an open-source framework enables analyses sharing both intermediate final results within across labs. uses...
Abstract The goal of this protocol is to enable better characterisation multiphoton microscopy hardware across a large user base. scope purposefully limited focus on hardware, touching software and data analysis routines only where relevant. intended audiences are scientists using building microscopes in their laboratories. that any scientist, not those with optical expertise, can test whether microscope performing well producing consistent over the lifetime system.
Abstract Combining two-photon calcium imaging (2PCI) and electron microscopy (EM) provides arguably the most powerful current approach for connecting function to structure in neural circuits. Recent years have seen dramatic advances obtaining processing CI EM data separately. In addition, several joint CI-EM datasets (with performed vivo, followed by reconstruction of same volume) been collected. However, no automated analysis tools yet exist that can match each signal extracted from a cell...
The relational data model offers unrivaled rigor and precision in defining structure querying complex data. Yet the use of databases scientific pipelines is limited due to their perceived unwieldiness. We propose a simplified conceptually refined named DataJoint. includes language for schema definition, queries, diagramming notation visualizing entities relationships among them. adheres principle entity normalization, which requires that all -- both stored derived must be represented by...
We trained a rhesus monkey to perform randomly cued, individuated finger flexions of the thumb, index, and middle finger. Nine Implantable MyoElectric Sensors (IMES) were then surgically implanted into muscles monkey's forearm, without any observable adverse chronic effects. Using an inductive link, we wirelessly recorded EMG from IMES as performed flexion task. A principal components analysis (PCA) based algorithm was used decode which switch pressed on EMG. This correctly decoded moved 89%...
Tomosynthesis, i.e. reconstruction of 3D volumes using projections from a limited perspective is classical inverse, ill-posed or under constrained problem. Data insufficiency leads to artifacts that vary in severity depending on the particular problem, method and also object being imaged. Machine learning has been used successfully tomographic problems where data insufficient, but challenge with machine it introduces bias dataset. A novel framework improve quality tomosynthesis limits...
Abstract A new resource— DataJoint Elements —provides modular designs for assembling complete workflow solutions to organize data and computations common neurophysiology experiments. The are derived from working developed in leading research groups using the open-source framework integrate collection analysis collaborative workflows.
Early recognition and aggressive management of seizure activity is important in the treatment patients with nerve agent exposure. However, these can experience non-convulsive seizures that are difficult to identify without EEG monitoring. In this paper, we discuss development testing a low-cost, field-deployable device records displays patient trends over time. The optimized for early levels care military mass casualty until they be relocated medical facilities more comprehensive also pulse...