High-density, long-lasting, and multi-region electrophysiological recordings using polymer electrode arrays

Chung, Jason; Joo, Hannah R.; Fan, Jiang Lan; Liu, Daniel F.; Barnett, Alex H.; Chen, Supin; Geaghan-Breiner, Charlotte; Karlsson, Matts; Karlsson, Magnus; Lee, Kye Y; Liang, Hexin; Magland, Jeremy F.; Mehaffey, W. Hamish; Tooker, Angela; Brainard, Michael S.; Greengard, Leslie; Tolosa, Vanessa; Frank, Loren M.

doi:10.1101/242693

Cited by 38 publications

(40 citation statements)

References 60 publications

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“…Finally, we examined the temporal autocorrelation functions, shown for two representative examples in control and APP/PS1 animals (Figs. 1g,h,p,q, S3), and used this to identify single units, as has been done previously in dorsal CA1 36,37 . While we found up to 128 well isolated units in a single animal, on average we identified 56 ± 48 units in the control animals and 41 ± 17 units in the APP/PS1 animals.…”

Section: Resultsmentioning

confidence: 99%

Altered dorsal CA1 neuronal population coding in the APP/PS1 mouse model of Alzheimer’s disease

Chockanathan

Warner

Turpin

et al. 2020

Sci Rep

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While the link between amyloid β (Aβ) accumulation and synaptic degradation in Alzheimer's disease (AD) is known, the consequences of this pathology on population coding remain unknown. We found that the entropy, a measure of the diversity of network firing patterns, was lower in the dorsal CA1 region in the APP/PS1 mouse model of Aβ pathology, relative to controls, thereby reducing the population's coding capacity. Our results reveal a network level signature of the deficits Aβ accumulation causes to the computations performed by neural circuits. Alzheimer's disease (AD) is a progressive neurodegenerative disorder associated with cognitive decline that is thought to arise in part from the pathological accumulation of amyloid β (Aβ) plaques 1 throughout the neocortex and hippocampus. Plaques cause a constellation of changes in neural circuits including, but not limited to, degradation of dendritic spines 2 , reductions in synapse density 2,3 , and increases in the intrinsic excitability of neurons 3. Aβ pathology has been linked to various behavioral and cognitive changes 4,5 ; for example in mouse models, plaque burden correlates with degradation of place fields in the dorsal CA1 (dCA1) subfield of the hippocampus, and is associated with poor performance on spatial memory tasks 4. Such behaviors require the orchestration of activity across large groups of neurons, or ensembles, whose dynamics are governed by the structure of neural circuits 6. However, although Aβ pathology disrupts multiple features of these circuits 2,7,8 , the net effect of these changes on the structure of population activity and the resulting disruptions in neural computation remains unknown. To address this question, we performed electrophysiological recordings in the hippocampus of awake APP/ PS1 mice (model of Aβ pathology 9), where amyloid plaques can be seen at 12 months of age 10 and plaque burden corresponds to poor performance on spatial cognition and memory tasks, such as the T-maze alternation task 4,5. We found a reduction in the pair-wise correlations between neurons in APP/PS1 animals as compared to controls. Additionally, we identified a reduction in the entropy of population activity across a large array of ensemble sizes, suggesting that the coding vocabulary of populations of neurons in the dCA1 region of hippocampus is compromised in this mouse model of amyloid pathology. Materials and Methods Animals. All protocols and procedures were approved by the University Committee on Animal Resources (UCAR) at the University of Rochester and were performed in accordance with the guidelines of the Institutional Animal Care and Use Committee (IACUC) at the University of Rochester. 4 APP/PS1 double transgenic mice and 4 littermate control mice were used in this study. The APP/PS1 mice expressed chimeric mouse/human amyloid precursor protein (Mo/HuApp695swe) 11 and mutant human presenilin-1 (PS1-dE9) 12 under the control of the neuron-specific prion protein promotor element 9. All mice were males aged 11 to 13 months. By this age, amyl...

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Section: Resultsmentioning

confidence: 99%

Altered dorsal CA1 neuronal population coding in the APP/PS1 mouse model of Alzheimer’s disease

Chockanathan

Warner

Turpin

et al. 2020

Sci Rep

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“…First, at millisecond timescale resolution, they yield high-quality single units recorded continuously over many months. Recording continuously for 10 -11 d in three animals (Chung et al, 2019a), the team tracked the activity of 2232 units from rat medial prefrontal cortex (mPFC), each for at least 24 h. Of the 1150 units first detected in the initial few days of the 10 -11 d period, 21% (247 of 1150) could be followed for Ͼ1 week. Second, these probes and the associated hardware and software (Chung et al, 2017) permit high-density sampling from multiple brain regions.…”

Section: New Tools For Understanding Distributed Patterns Of Brain Acmentioning

confidence: 99%

BRAIN Initiative: Cutting-Edge Tools and Resources for the Community

et al. 2019

Self Cite

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The overarching goal of the NIH BRAIN (Brain Research through Advancing Innovative Neurotechnologies) Initiative is to advance the understanding of healthy and diseased brain circuit function through technological innovation. Core principles for this goal include the validation and dissemination of the myriad innovative technologies, tools, methods, and resources emerging from BRAIN-funded research. Innovators, BRAIN funding agencies, and non-Federal partners are working together to develop strategies for making these products usable, available, and accessible to the scientific community. Here, we describe several early strategies for supporting the dissemination of BRAIN technologies. We aim to invigorate a dialogue with the neuroscience research and funding community, interdisciplinary collaborators, and trainees about the existing and future opportunities for cultivating groundbreaking research products into mature, integrated, and adaptable research systems. Along with the accompanying Society for Neuroscience 2019 Mini-Symposium, "BRAIN Initiative: Cutting-Edge Tools and Resources for the Community," we spotlight the work of several BRAIN investigator teams who are making progress toward providing tools, technologies, and services for the neuroscience community. These tools access neural circuits at multiple levels of analysis, from subcellular composition to brain-wide network connectivity, including the following: integrated systems for EM-and florescence-based connectomics, advances in immunolabeling capabilities, and resources for recording and analyzing functional connectivity. Investigators describe how the resources they provide to the community will contribute to achieving the goals of the NIH BRAIN Initiative. Finally, in addition to celebrating the contributions of these BRAIN-funded investigators, the Mini-Symposium will illustrate the broader diversity of BRAIN Initiative investments in cutting-edge technologies and resources.

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“…Thus, new two‐photon imaging methodologies born from an astrocytic perspective, particularly those that allow imaging multiple laminae simultaneously, are necessary to advance our understanding of these cells within larger, mesoscale circuits. Another area of improvement for large‐scale Ca 2+ recording in astrocytes and spike‐recording in neurons is the development of new electrophysiological approaches, including flexible polymer probes (Chung et al, ) and clear electrode arrays (Thunemann et al, ), to solve the current problem posed by the large equipment necessary to carry out single‐neuron recordings, which precludes astrocyte imaging. Despite the advances in Ca 2+ imaging, single‐neuron electrophysiological measurements are preferable, for Ca 2+ transients lack temporal resolution to reveal single‐action potentials.…”

Section: A Roadmap To Advance the Integration Of Astrocytes Into Systmentioning

confidence: 99%

A roadmap to integrate astrocytes into Systems Neuroscience

Kastanenka

Moreno-Bote

Pittà

et al. 2019

Glia

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Systems neuroscience is still mainly a neuronal field, despite the plethora of evidence supporting the fact that astrocytes modulate local neural circuits, networks, and complex behaviors. In this article, we sought to identify which types of studies are necessary to establish whether astrocytes, beyond their well‐documented homeostatic and metabolic functions, perform computations implementing mathematical algorithms that sub‐serve coding and higher‐brain functions. First, we reviewed Systems‐like studies that include astrocytes in order to identify computational operations that these cells may perform, using Ca2+ transients as their encoding language. The analysis suggests that astrocytes may carry out canonical computations in a time scale of subseconds to seconds in sensory processing, neuromodulation, brain state, memory formation, fear, and complex homeostatic reflexes. Next, we propose a list of actions to gain insight into the outstanding question of which variables are encoded by such computations. The application of statistical analyses based on machine learning, such as dimensionality reduction and decoding in the context of complex behaviors, combined with connectomics of astrocyte–neuronal circuits, is, in our view, fundamental undertakings. We also discuss technical and analytical approaches to study neuronal and astrocytic populations simultaneously, and the inclusion of astrocytes in advanced modeling of neural circuits, as well as in theories currently under exploration such as predictive coding and energy‐efficient coding. Clarifying the relationship between astrocytic Ca2+ and brain coding may represent a leap forward toward novel approaches in the study of astrocytes in health and disease.

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High-density, long-lasting, and multi-region electrophysiological recordings using polymer electrode arrays

Cited by 38 publications

References 60 publications

Altered dorsal CA1 neuronal population coding in the APP/PS1 mouse model of Alzheimer’s disease

Altered dorsal CA1 neuronal population coding in the APP/PS1 mouse model of Alzheimer’s disease

BRAIN Initiative: Cutting-Edge Tools and Resources for the Community

A roadmap to integrate astrocytes into Systems Neuroscience

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