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Tag Archives: machine learning
Astrocytes hiding in a hippocampal CA3 EM dataset
Few things in neuroscience are more beautiful than the ultrastructure of individual neurons. Zhihao Zheng and his colleagues from the Tank/Seung labs have now published a 3D electron microscopy dataset from hippocampal CA3. All neurons in this volume were automatically … Continue reading
Posted in Astrocytes, Electron microscopy, hippocampus, Imaging, Microscopy, neuroscience, Reviews
Tagged CA3, Data analysis, hippocampus, machine learning, Microscopy, Neuroglancer, neuroscience, science
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CascadeTorch: a PyTorch version of Cascade for spike inference
I’m glad to share a PyTorch-based implementation of spike inference from calcium imaging data: CascadeTorch, now available on GitHub. The original Cascade repository remains fully supported. This post explains why I re-implemented Cascade in Torch, and what this means for … Continue reading
Annual report of my intuition about the brain (2025, part I)
How does the brain work, and how can we understand it? To approach this big question from a broad perspective, I want to report on some ideas about the brain that marked me most over the past twelve months and that, on the … Continue reading
Open PhD position in my research group
Are you a finishing Master’s student with a quantitative background and are interested in neuroscience? This is your opportunity. Project: You will be supervised by Dr. Peter Rupprecht and Prof. Fritjof Helmchen at the Brain Research Institute, University of Zurich. … Continue reading
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
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
Non-linearity of calcium indicators: history-dependence of spike reporting
Calcium indicators are used to report the calcium concentration inside single cells. In neurons, calcium imaging can be used as a readout of neuronal activity (action potentials). However, some calcium indicators like GCaMP transform the calcium concentration of a cell … Continue reading
A collaborative review on error signals in predictive processing
Predictive processing is one of the most influential ideas from computational neuroscience for the experimental neurosciences. However, definitions of predictive processing vary broadly, to the extent that “predictive coding” is used sometimes in a very narrow sense (there are specific … Continue reading
Three recent interesting papers on computational neuroscience
Three papers:
1. The Neuron as a Direct Data-Driven Controller
2. A learning algorithm beyond backpropagation
3. Continuous vs. discrete representations in a recurrent network Continue reading
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
A blog about neurophysiology 