An Intracortical Implantable Brain-Computer Interface for Telemetric Real-Time Recording and Manipulation of Neuronal Circuits for Closed-Loop Intervention

Recording and manipulating neuronal ensemble activity is a key requirement in advanced neuromodulatory and behavior studies. Devices capable of both recording and manipulating neuronal activity brain-computer interfaces (BCIs) should ideally operate un-tethered and allow chronic longitudinal manipulations in the freely moving animal. In this study, we designed a new intracortical BCI feasible of telemetric recording and stimulating local gray and white matter of visual neural circuit after irradiation exposure. To increase the translational reliance, we put forward a Göttingen minipig model. The animal was stereotactically irradiated at the level of the visual cortex upon defining the target by a fused cerebral MRI and CT scan. A fully implantable neural telemetry system consisting of a 64 channel intracortical multielectrode array, a telemetry capsule, and an inductive rechargeable battery was then implanted into the visual cortex to record and manipulate local field potentials, and multi-unit activity. We achieved a 3-month stability of the functionality of the un-tethered BCI in terms of telemetric radio-communication, inductive battery charging, and device biocompatibility for 3 months. Finally, we could reliably record the local signature of sub- and suprathreshold neuronal activity in the visual cortex with high bandwidth without complications. The ability to wireless induction charging combined with the entirely implantable design, the rather high recording bandwidth, and the ability to record and stimulate simultaneously put forward a wireless BCI capable of long-term un-tethered real-time communication for causal preclinical circuit-based closed-loop interventions.

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Perceptual detection depends on spike count integration

10.1101/865410 ◽

2019 ◽

Author(s):

Jackson J. Cone ◽

Morgan L. Bade ◽

Nicolas Y. Masse ◽

Elizabeth A. Page ◽

David J. Freedman ◽

...

Keyword(s):

Neural Networks ◽

Cerebral Cortex ◽

Visual Cortex ◽

Recurrent Neural Networks ◽

Neural Circuit ◽

Visual Detection ◽

Spike Count ◽

Neuronal Responses ◽

Neuronal Populations ◽

And Behavior

AbstractWhenever the retinal image changes some neurons in visual cortex increase their rate of firing, while others decrease their rate of firing. Linking specific sets of neuronal responses with perception and behavior is essential for understanding mechanisms of neural circuit computation. We trained mice to perform visual detection tasks and used optogenetic perturbations to increase or decrease neuronal spiking primary visual cortex (V1). Perceptual reports were always enhanced by increments in V1 spike counts and impaired by decrements, even when increments and decrements were delivered to the same neuronal populations. Moreover, detecting changes in cortical activity depended on spike count integration rather than instantaneous changes in spiking. Recurrent neural networks trained in the task similarly relied on increments in neuronal activity when activity was costly. This work clarifies neuronal decoding strategies employed by cerebral cortex to translate cortical spiking into percepts that can be used to guide behavior.

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A novel device for real-time measurement and manipulation of licking behavior in head-fixed mice

Journal of Neurophysiology ◽

10.1152/jn.00500.2018 ◽

2018 ◽

Vol 120 (6) ◽

pp. 2975-2987 ◽

Cited By ~ 1

Author(s):

Brice Williams ◽

Anderson Speed ◽

Bilal Haider

Keyword(s):

Real Time ◽

Neural Activity ◽

Closed Loop ◽

Neural Circuits ◽

Neural Circuit ◽

Visual Behavior ◽

Sensory Stimuli ◽

Neural Recordings ◽

Control Signals ◽

Sensory Motor

The mouse has become an influential model system for investigating the mammalian nervous system. Technologies in mice enable recording and manipulation of neural circuits during tasks where they respond to sensory stimuli by licking for liquid rewards. Precise monitoring of licking during these tasks provides an accessible metric of sensory-motor processing, particularly when combined with simultaneous neural recordings. There are several challenges in designing and implementing lick detectors during head-fixed neurophysiological experiments in mice. First, mice are small, and licking behaviors are easily perturbed or biased by large sensors. Second, neural recordings during licking are highly sensitive to electrical contact artifacts. Third, submillisecond lick detection latencies are required to generate control signals that manipulate neural activity at appropriate time scales. Here we designed, characterized, and implemented a contactless dual-port device that precisely measures directional licking in head-fixed mice performing visual behavior. We first determined the optimal characteristics of our detector through design iteration and then quantified device performance under ideal conditions. We then tested performance during head-fixed mouse behavior with simultaneous neural recordings in vivo. We finally demonstrate our device’s ability to detect directional licks and generate appropriate control signals in real time to rapidly suppress licking behavior via closed-loop inhibition of neural activity. Our dual-port detector is cost effective and easily replicable, and it should enable a wide variety of applications probing the neural circuit basis of sensory perception, motor action, and learning in normal and transgenic mouse models. NEW & NOTEWORTHY Mice readily learn tasks in which they respond to sensory cues by licking for liquid rewards; tasks that involve multiple licking responses allow study of neural circuits underlying decision making and sensory-motor integration. Here we design, characterize, and implement a novel dual-port lick detector that precisely measures directional licking in head-fixed mice performing visual behavior, enabling simultaneous neural recording and closed-loop manipulation of licking.

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Track-Control, an automatic video-based real-time closed-loop behavioral control toolbox

10.1101/2019.12.11.873372 ◽

2019 ◽

Author(s):

Guang-Wei Zhang ◽

Li Shen ◽

Zhong Li ◽

Huizhong W. Tao ◽

Li I. Zhang

Keyword(s):

Real Time ◽

Neuronal Activity ◽

Closed Loop ◽

Behavioral Control ◽

Rapid Development ◽

Automated System ◽

Processing Unit ◽

Plus Maze ◽

Functional Extension ◽

Tight Correlation

AbstractApproaches of optogenetic manipulation of neuronal activity have boosted our understanding of the functional architecture of brain circuits underlying various behaviors. In the meantime, rapid development in computer vision greatly accelerates the automation of behavioral analysis. Real-time and event-triggered interference is often necessary for establishing a tight correlation between neuronal activity and behavioral outcome. However, it is time consuming and easily causes variations when performed manually by experimenters. Here, we describe our Track-Control toolbox, a fully automated system with real-time object detection and low latency closed-loop hardware feedback. We demonstrate that the toolbox can be applied in a broad spectrum of behavioral assays commonly used in the neuroscience field, including open field, plus maze, Morris water maze, real-time place preference, social interaction, and sensory-induced defensive behavior tests. The Track-Control toolbox has proved an efficient and easy-to-use method with excellent flexibility for functional extension. Moreover, the toolbox is free, open source, graphic processing unit (GPU)-independent, and compatible across operating system (OS) platforms. Each lab can easily integrate Track-Control into their existing systems to achieve automation.

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Open source modules for tracking animal behavior and closed-loop stimulation based on Open Ephys and Bonsai

10.1101/340141 ◽

2018 ◽

Cited By ~ 1

Author(s):

Alessio Paolo Buccino ◽

Mikkel Elle Lepperød ◽

Svenn-Arne Dragly ◽

Philipp Häfliger ◽

Marianne Fyhn ◽

...

Keyword(s):

Open Source ◽

Real Time ◽

Closed Loop ◽

Low Cost ◽

Data Formats ◽

Behavioral Tracking ◽

Real Time Tracking ◽

Set Up ◽

And Behavior ◽

Closed Loop Stimulation

AbstractObjectiveA major goal in systems neuroscience is to determine the causal relationship between neural activity and behavior. To this end, methods that combine monitoring neural activity, behavioral tracking, and targeted manipulation of neurons in closed-loop are powerful tools. However, commercial systems that allow these types of experiments are usually expensive and rely on non-standardized data formats and proprietary software which may hinder user-modifications for specific needs. In order to promote reproducibility and data-sharing in science, transparent software and standardized data formats are an advantage. Here, we present an open source, low-cost, adaptable, and easy to set-up system for combined behavioral tracking, electrophysiology and closed-loop stimulation.ApproachBased on the Open Ephys system (www.open-ephys.org) we developed multiple modules to include real-time tracking and behavior-based closed-loop stimulation. We describe the equipment and provide a step-by-step guide to set up the system. Combining the open source software Bonsai (bonsai-rx.org) for analyzing camera images in real time with the newly developed modules in Open Ephys, we acquire position information, visualize tracking, and perform tracking-based closed-loop stimulation experiments. To analyze the acquired data we provide an open source file reading package in Python.Main resultsThe system robustly visualizes real-time tracking and reliably recovers tracking information recorded from a range of sampling frequencies (30-1000Hz). We combined electrophysiology with the newly-developed tracking modules in Open Ephys to record place cell and grid cell activity in the hippocampus and in the medial entorhinal cortex, respectively. Moreover, we present a case in which we used the system for closed-loop optogenetic stimulation of entorhinal grid cells.SignificanceExpanding the Open Ephys system to include animal tracking and behavior-based closed-loop stimulation extends the availability of high-quality, low-cost experimental setup within standardized data formats serving the neuroscience community.

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Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE)

10.1101/2021.06.21.449019 ◽

2021 ◽

Author(s):

Mark Schatza ◽

Ethan Blackwood ◽

Sumedh Nagrale ◽

Alik S Widge

Keyword(s):

Open Source ◽

Real Time ◽

Closed Loop ◽

Brain Activity ◽

Loop Control ◽

Oscillatory Phase ◽

Wide Range ◽

Real Time Tracking ◽

Therapeutic Tools ◽

And Behavior

Closing the loop between brain activity and behavior is one of the most active areas of development in neuroscience. There is particular interest in developing closed-loop control of neural oscillations. Many studies report correlations between oscillations and functional processes. Oscillation-informed closed-loop experiments might determine whether these relationships are causal and would provide important mechanistic insights which may lead to new therapeutic tools. These closed-loop perturbations require accurate estimates of oscillatory phase and amplitude, which are challenging to compute in real time. We developed an easy to implement, fast and accurate Toolkit for Oscillatory Real-time Tracking and Estimation (TORTE). TORTE operates with the open-source Open Ephys GUI (OEGUI) system, making it immediately compatible with a wide range of acquisition systems and experimental preparations. TORTE efficiently extracts oscillatory phase and amplitude from a target signal and includes a variety of options to trigger closed-loop perturbations. Implementing these tools into existing experiments is easy and adds minimal latency to existing protocols. Most labs use in-house lab-specific approaches, limiting replication and extension of their experiments by other groups. Accuracy of the extracted analytic signal and accuracy of oscillation-informed perturbations with TORTE match presented results by these groups. However, TORTE provides access to these tools in a flexible, easy to use toolkit without requiring proprietary software. We hope that the availability of a high-quality, open-source, and broadly applicable toolkit will increase the number of labs able to perform oscillatory closed-loop experiments, and will improve the replicability of protocols and data across labs.

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4 Brain computer interface for paralysis

Journal of Neurology Neurosurgery & Psychiatry ◽

10.1136/jnnp-2021-bnpa.4 ◽

2021 ◽

Vol 92 (8) ◽

pp. A1.4-A2

Author(s):

Leigh R Hochberg

Keyword(s):

Real Time ◽

Closed Loop ◽

Assistive Technologies ◽

Computer Interfaces ◽

Cord Injury ◽

Challenges And Opportunities ◽

Communication Devices ◽

Intention To Move ◽

The Brain ◽

Made In

Intracortically-based Brain-Computer Interfaces (iBCIs) are poised to revolutionize our ability to restore lost neurologic functions. By recording high resolution neural activity from the brain, the intention to move ones hand can be detected and decoded in real- time, potentially providing people with motor neuron disease (ALS), stroke, or spinal cord injury with restored or maintained ability to control communication devices, assistive technologies, and their own limbs. iBCIs also are central to the development of closed-loop neuromodulation systems, with great potential to serve people with neuropsychiatric disorders. A multi-site pilot clinical trial of the investigational BrainGate system is assessing the feasibility of people with tetraplegia controlling a computer cursor and other devices simply by imagining the movement of their own arm or hand. This presentation will review some of the recent progress made in iBCIs, the information that can be decoded from ensembles of cortical or subcortical neurons in real-time, and the challenges and opportunities for restorative neurotechnologies in research and clinical practice.

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Marked point process filter for clusterless and adaptive encoding-decoding of multiunit activity

10.1101/438440 ◽

2018 ◽

Author(s):

Kensuke Arai ◽

Daniel F. Liu ◽

Loren M. Frank ◽

Uri T. Eden

Keyword(s):

Real Time ◽

Point Process ◽

Neural Activity ◽

Closed Loop ◽

Marked Point ◽

Marked Point Process ◽

Important Advance ◽

New Information ◽

Adaptive Encoding ◽

And Behavior

AbstractReal-time, closed-loop experiments can uncover causal relationships between specific neural activity and behavior. An important advance in realizing this is the marked point process filtering framework which utilizes the “mark” or the waveform features of unsorted spikes, to construct a relationship between these features and behavior, which we call the encoding model. This relationship is not fixed, because learning changes coding properties of individual neurons, and electrodes can physically move during the experiment, changing waveform characteristics. We introduce a sequential, Bayesian encoding model which allows incorporation of new information on the fly to adapt the model in real time. A possible application of this framework is to the decoding of the contents of hippocampal ripples in rats exploring a maze. During physical exploration, we observe the marks and positions at which they occur, to update the encoding model, which is employed to decode contents of ripples when rats stop moving, and switch back to updating the model once the rat starts moving again.

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Astrocyte subdomains respond independently in vivo

10.1101/675769 ◽

2019 ◽

Cited By ~ 1

Author(s):

Mónica López-Hidalgo ◽

Vered Kellner ◽

James Schummers

Keyword(s):

Visual Cortex ◽

Neuronal Activity ◽

Visual Stimulus ◽

Calcium Concentration ◽

Neural Circuit ◽

Functional Unit ◽

Spatial Interaction ◽

Topographic Organization ◽

Orientation Maps

AbstractAstrocytes contact thousands of synapses throughout the territory covered by its fine bushy processes. Astrocytes respond to neuronal activity with an increase in calcium concentration that is in turn linked to their capacity to modulate neuronal activity. It remains unclear whether astrocytes behave as a single functional unit that integrates all of these inputs, or if multiple functional subdomains reside within an individual astrocyte. We utilized the topographic organization of ferret visual cortex to test whether local neuronal activity can elicit spatially restricted events within an individual astrocyte. We monitored calcium activity throughout the extent of astrocytes in ferret visual cortex while presenting visual stimuli that elicit coordinated neuronal activity spatially restricted to functional columns. We found visually-driven calcium responses throughout the entire astrocyte that was largely independent in individual subdomains, often responding to different visual stimulus orientations. A model of the spatial interaction of astrocytes and neuronal orientation maps recapitulated these measurements, consistent with the hypothesis that astrocyte subdomains integrate local neuronal activity. Together, these results suggest that astrocyte responses to neural circuit activity are dominated by functional subdomains that respond locally and independently to neuronal activity.

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