In vivo one-photon confocal calcium imaging of neuronal activity from the mouse neocortex

2018 ◽  
Vol 17 (3-4) ◽  
pp. 671-678
Author(s):  
Satoshi Iwasaki ◽  
Yuji Ikegaya
2021 ◽  
Author(s):  
Alex A. Legaria ◽  
Julia A. Licholai ◽  
Alexxai V. Kravitz

AbstractFiber photometry recordings are commonly used as a proxy for neuronal activity, based on the assumption that increases in bulk calcium fluorescence reflect increases in spiking of the underlying neural population. However, this assumption has not been adequately tested. Here, using endoscopic calcium imaging in the striatum we report that the bulk fluorescence signal correlates weakly with somatic calcium signals, suggesting that this signal does not reflect spiking activity, but may instead reflect subthreshold changes in neuropil calcium. Consistent with this suggestion, the bulk fluorescence photometry signal correlated strongly with neuropil calcium signals extracted from these same endoscopic recordings. We further confirmed that photometry did not reflect striatal spiking activity with simultaneous in vivo extracellular electrophysiology and fiber photometry recordings in awake behaving mice. We conclude that the fiber photometry signal should not be considered a proxy for spiking activity in neural populations in the striatum.Significance statementFiber photometry is a technique for recording brain activity that has gained popularity in recent years due to it being an efficient and robust way to record the activity of genetically defined populations of neurons. However, it remains unclear what cellular events are reflected in the photometry signal. While it is often assumed that the photometry signal reflects changes in spiking of the underlying cell population, this has not been adequately tested. Here, we processed calcium imaging recordings to extract both somatic and non-somatic components of the imaging field, as well as a photometry signal from the whole field. Surprisingly, we found that the photometry signal correlated much more strongly with the non-somatic than the somatic signals. This suggests that the photometry signal most strongly reflects subthreshold changes in calcium, and not spiking. We confirmed this point with simultaneous fiber photometry and extracellular spiking recordings, again finding that photometry signals relate poorly to spiking in the striatum. Our results may change interpretations of studies that use fiber photometry as an index of spiking output of neural populations.


2020 ◽  
Vol 4 (s1) ◽  
pp. 11-11
Author(s):  
Tyler Nguyen ◽  
Zoe Vriesman ◽  
Peter Andrews ◽  
Sehban Masood ◽  
M Stewart ◽  
...  

OBJECTIVES/GOALS: Our goal is to develop a non-invasive stimulation technique using magneto-electric nanoparticles (MENs) for inducing and enhancing neuronal activity with high spatial and temporal resolutions and minimal toxicity, which can potentially be used as a more effective approach to brain stimulation. METHODS/STUDY POPULATION: MENs compose of core-shell structures that are attracted to strong external magnetic field (~5000 Gauss) but produces electric currents with weaker magnetic field (~450 Gauss). MENs were IV treated into mice and drawn to the brain cortex with a strong magnetic field. We then stimulate MENs with a weaker magnetic field via electro magnet. With two photon calcium imaging, we investigated both the temporal and spatial effects of MENs on neuronal activity both in vivo and in vitro. We performed mesoscopic whole brain calcium imaging on awake animal to assess the MENs effects. Furthermore, we investigated the temporal profile of MENs in the vasculatures post-treatment and its toxicities to CNS. RESULTS/ANTICIPATED RESULTS: MENs were successfully localized to target cortical regions within 30 minutes of magnetic application. After wirelessly applying ~450 G magnetic field between 10-20 Hz, we observed a dramatic increase of calcium signals (i.e. neuronal excitability) both in vitro cultured neurons and in vivo treated animals. Whole brain imaging of awake mice showed a focal increase in calcium signals at the area where MENs localized and the signals spread to regions further away. We also found MENs stimulatory effects lasted up to 24 hours post treatment. MEN stimulation increases c-Fos expression but resulted in no inflammatory changes, up to one week, by assessing microglial or astrocytes activations. DISCUSSION/SIGNIFICANCE OF IMPACT: Our study shows, through controlling the applied magnetic field, MENs can be focally delivered to specific cortical regions with high efficacy and wirelessly activated neurons with high spatial and temporal resolution. This method shows promising potential to be a new non-invasive brain modulation approach disease studies and treatments.


2021 ◽  
Vol 17 (1) ◽  
pp. e1008565
Author(s):  
Johannes Friedrich ◽  
Andrea Giovannucci ◽  
Eftychios A. Pnevmatikakis

In vivo calcium imaging through microendoscopic lenses enables imaging of neuronal populations deep within the brains of freely moving animals. Previously, a constrained matrix factorization approach (CNMF-E) has been suggested to extract single-neuronal activity from microendoscopic data. However, this approach relies on offline batch processing of the entire video data and is demanding both in terms of computing and memory requirements. These drawbacks prevent its applicability to the analysis of large datasets and closed-loop experimental settings. Here we address both issues by introducing two different online algorithms for extracting neuronal activity from streaming microendoscopic data. Our first algorithm, OnACID-E, presents an online adaptation of the CNMF-E algorithm, which dramatically reduces its memory and computation requirements. Our second algorithm proposes a convolution-based background model for microendoscopic data that enables even faster (real time) processing. Our approach is modular and can be combined with existing online motion artifact correction and activity deconvolution methods to provide a highly scalable pipeline for microendoscopic data analysis. We apply our algorithms on four previously published typical experimental datasets and show that they yield similar high-quality results as the popular offline approach, but outperform it with regard to computing time and memory requirements. They can be used instead of CNMF-E to process pre-recorded data with boosted speeds and dramatically reduced memory requirements. Further, they newly enable online analysis of live-streaming data even on a laptop.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Víctor Plata ◽  
Mariana Duhne ◽  
Jesús E. Pérez-Ortega ◽  
Janet Barroso-Flores ◽  
Elvira Galarraga ◽  
...  

Physiological and biochemical experimentsin vivoandin vitrohave explored striatal receptor signaling and neuronal excitability to posit pathophysiological models of Parkinson's disease. However, when therapeutic approaches, such as dopamine agonists, need to be evaluated, behavioral tests using animal models of Parkinson's disease are employed. To our knowledge, recordings of population neuronal activityin vitroto assess anti-Parkinsonian drugs and the correlation of circuit dynamics with disease state have only recently been attempted. We have shown that Parkinsonian pathological activity of neuronal striatal circuits can be characterized inin vitrocerebral tissue. Here, we show that calcium imaging techniques, capable of recording dozens of neurons simultaneously with single-cell resolution, can be extended to assess the action of therapeutic drugs. We used L-DOPA as a prototypical anti-Parkinsonian drug to show the efficiency of this proposed bioassay. In a rodent model of early Parkinson's disease, Parkinsonian neuronal activity can be returned to control levels by the bath addition of L-DOPA in a reversible way. This result raises the possibility to use calcium imaging techniques to measure, quantitatively, the actions of anti-Parkinsonian drugs over time and to obtain correlations with disease evolution and behavior.


2019 ◽  
Author(s):  
V. Korzhova ◽  
P. Marinković ◽  
P. M. Goltstein ◽  
J. Herms ◽  
S. Liebscher

SummaryAlzheimer’s disease (AD) is associated with aberrant neuronal activity levels. How those activity alterations emerge and how stable they are over time in vivo, however, remains elusive to date. To address these questions we chronically recorded the activity from identified neurons in cortex of awake APPPS1 transgenic mice and their non-transgenic littermates over the course of 4 weeks by means of calcium imaging. Surprisingly, aberrant neuronal activity was very stable over time. Moreover, we identified a slow progressive gain of activity of former intermediately active neurons as the main source of new highly active neurons. Interestingly, fluctuations in neuronal activity were independent from amyloid plaque proximity, but aberrant activity levels were more likely to persist close to plaques. These results support the notion that neuronal network pathology observed in AD patients is the consequence of stable single cell aberrant neuronal activity, a finding of potential therapeutic relevance.


2019 ◽  
Author(s):  
Guillaume Etter ◽  
Frederic Manseau ◽  
Sylvain Williams

AbstractUnderstanding the role of neuronal activity in cognition and behavior is a key question in neuroscience. Previously, in vivo studies have typically inferred behavior from electrophysiological data using probabilistic approaches including Bayesian decoding. While providing useful information on the role of neuronal subcircuits, electrophysiological approaches are often limited in the maximum number of recorded neurons as well as their ability to reliably identify neurons over time. This can be particularly problematic when trying to decode behaviors that rely on large neuronal assemblies or rely on temporal mechanisms, such as a learning task over the course of several days. Calcium imaging of genetically encoded calcium indicators has overcome these two issues. Unfortunately, because calcium transients only indirectly reflect spiking activity and calcium imaging is often performed at lower sampling frequencies, this approach suffers from uncertainty in exact spike timing and thus activity frequency, making rate-based decoding approaches used in electrophysiological recordings difficult to apply to calcium imaging data. Here we describe a probabilistic framework that can be used to robustly infer behavior from calcium imaging recordings and relies on a simplified implementation of a naive Baysian classifier. Our method discriminates between periods of activity and periods of inactivity to compute probability density functions (likelihood and posterior), significance and confidence interval, as well as mutual information. We next devise a simple method to decode behavior using these probability density functions and propose metrics to quantify decoding accuracy. Finally, we show that neuronal activity can be predicted from behavior, and that the accuracy of such reconstructions can guide the understanding of relationships that may exist between behavioral states and neuronal activity.


2020 ◽  
Vol 14 ◽  
Author(s):  
Guillaume Etter ◽  
Frederic Manseau ◽  
Sylvain Williams

Understanding the role of neuronal activity in cognition and behavior is a key question in neuroscience. Previously, in vivo studies have typically inferred behavior from electrophysiological data using probabilistic approaches including Bayesian decoding. While providing useful information on the role of neuronal subcircuits, electrophysiological approaches are often limited in the maximum number of recorded neurons as well as their ability to reliably identify neurons over time. This can be particularly problematic when trying to decode behaviors that rely on large neuronal assemblies or rely on temporal mechanisms, such as a learning task over the course of several days. Calcium imaging of genetically encoded calcium indicators has overcome these two issues. Unfortunately, because calcium transients only indirectly reflect spiking activity and calcium imaging is often performed at lower sampling frequencies, this approach suffers from uncertainty in exact spike timing and thus activity frequency, making rate-based decoding approaches used in electrophysiological recordings difficult to apply to calcium imaging data. Here we describe a probabilistic framework that can be used to robustly infer behavior from calcium imaging recordings and relies on a simplified implementation of a naive Baysian classifier. Our method discriminates between periods of activity and periods of inactivity to compute probability density functions (likelihood and posterior), significance and confidence interval, as well as mutual information. We next devise a simple method to decode behavior using these probability density functions and propose metrics to quantify decoding accuracy. Finally, we show that neuronal activity can be predicted from behavior, and that the accuracy of such reconstructions can guide the understanding of relationships that may exist between behavioral states and neuronal activity.


2022 ◽  
Vol 23 (2) ◽  
pp. 638
Author(s):  
Vladimir P. Sotskov ◽  
Nikita A. Pospelov ◽  
Viktor V. Plusnin ◽  
Konstantin V. Anokhin

Hippocampal place cells are a well-known object in neuroscience, but their place field formation in the first moments of navigating in a novel environment remains an ill-defined process. To address these dynamics, we performed in vivo imaging of neuronal activity in the CA1 field of the mouse hippocampus using genetically encoded green calcium indicators, including the novel NCaMP7 and FGCaMP7, designed specifically for in vivo calcium imaging. Mice were injected with a viral vector encoding calcium sensor, head-mounted with an NVista HD miniscope, and allowed to explore a completely novel environment (circular track surrounded by visual cues) without any reinforcement stimuli, in order to avoid potential interference from reward-related behavior. First, we calculated the average time required for each CA1 cell to acquire its place field. We found that 25% of CA1 place fields were formed at the first arrival in the corresponding place, while the average tuning latency for all place fields in a novel environment equaled 247 s. After 24 h, when the environment was familiar to the animals, place fields formed faster, independent of retention of cognitive maps during this session. No cumulation of selectivity score was observed between these two sessions. Using dimensionality reduction, we demonstrated that the population activity of rapidly tuned CA1 place cells allowed the reconstruction of the geometry of the navigated circular maze; the distribution of reconstruction error between the mice was consistent with the distribution of the average place field selectivity score in them. Our data thus show that neuronal activity recorded with genetically encoded calcium sensors revealed fast behavior-dependent plasticity in the mouse hippocampus, resulting in the rapid formation of place fields and population activity that allowed the reconstruction of the geometry of the navigated maze.


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