Tag Archives: electrophysiology

Accurately computing noise levels for calcium imaging data

It is fascinating how much data quality can vary between different calcium imaging data sets. In this blog post, I will discuss a metric to quantify and compare data quality and in particular shot noise between calcium imaging datasets. This … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology, Imaging, machine learning, Neuronal activity, neuroscience | Tagged , , , , | Leave a comment

Online spike inference with GCaMP8

Calcium imaging is used to record the activity of neurons in living animals. Often, these activity patterns are analyzed after the experiments to investigate how the brain works. Alternatively, it is also possible to extract the activity patterns in real … Continue reading

Posted in Brain machine interface, Calcium Imaging, closed-loop, Data analysis, electrophysiology, Imaging, machine learning, neuroscience | Tagged , , , , , | Leave a comment

Detecting single spikes from calcium imaging

There are two mutually exclusive holy grails of calcium imaging: First, recording from the highest number of neurons simultaneously. Second, detecting spike patterns with single-spike precision. This blog post focuses on the latter. Many studies have claimed to demonstrate single-spike … Continue reading

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Spike inference with GCaMP8: new pretrained models available

Calcium imaging is only an indirect readout of neuronal activity via fluorescence signals. To estimate the true underlying firing rates of these neurons, methods for “spike inference” have been developed. They are useful to denoise calcium imaging data and make … Continue reading

Posted in Calcium Imaging, Data analysis, Imaging, machine learning, Network analysis, Neuronal activity | Tagged , , , , | 4 Comments

Useful pieces from Twitter

Twitter used to be (and still is to some extent) a source of useful information for neuroscientists about technical details, clarifications of research findings and open discussions that cannot be obtained so easily otherwise. Here is a list of some … Continue reading

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Two random but interesting papers on neurophysiology with behavior

Bagur, Bourg et al. (2022) from the Bathellier Lab in Paris make the interesting finding that the auditory code is represented as temporal sequences of neuronal activity in early auditory processing stages and as spatial patterns in auditory cortex. I … Continue reading

Posted in Brain machine interface, closed-loop, Data analysis, electrophysiology, hippocampus, machine learning, Network analysis, Neuronal activity, neuroscience, Reviews | Tagged , , , , | Leave a comment

Interesting papers on behavioral timescale synaptic plasticity (experiments)

Behavioral timescale synaptic plasticity (BTSP) is a form of single-shot learning observed in hippocampal place cells in mice (Bittner et al., 2015, 2017). The idea is that post-synaptic activations (“eligibility traces”) are potentiated by a dendritic plateau potential/burst (“instructive signal”) … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology, Network analysis, Neuronal activity, Reviews | Tagged , , , | 4 Comments

Annual report of my intuition about the brain (2022)

How does the brain work and how can we understand it? To view this big question from a broad perspective at the end of each year, I’m reporting some of the thoughts about the brain that marked me most during … Continue reading

Posted in electrophysiology, Network analysis, Neuronal activity, Review, Reviews | Tagged , , | 8 Comments

Ambizione fellowship and an open PhD position

I’m glad to share that I am going to start my own junior research group at the University of Zurich in March 2023! As an Ambizione fellow, I will receive funding for my own salary, some equipment, consumables and a … Continue reading

Posted in Calcium Imaging, Data analysis, electrophysiology, machine learning, Microscopy, Neuronal activity | Tagged , , , , , , , | Leave a comment

Temporal dispersion of spike rates from deconvolved calcium imaging data

On Twitter, Richie Hakim asked whether the toolbox Cascade for spike inference (preprint, Github) induces temporal dispersion of the predicted spiking activity compared to ground truth. This kind of temporal dispersion had been observed in a study from last year … Continue reading

Posted in Calcium Imaging, Data analysis, machine learning, Microscopy, Neuronal activity | Tagged , , | 1 Comment