7 results on '"Miroslav Román, Rosón"'
Search Results
2. Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.
- Author
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Philipp Berens, Jeremy Freeman, Thomas Deneux, Nikolay Chenkov, Thomas McColgan, Artur Speiser, Jakob H Macke, Srinivas C Turaga, Patrick Mineault, Peter Rupprecht, Stephan Gerhard, Rainer W Friedrich, Johannes Friedrich, Liam Paninski, Marius Pachitariu, Kenneth D Harris, Ben Bolte, Timothy A Machado, Dario Ringach, Jasmine Stone, Luke E Rogerson, Nicolas J Sofroniew, Jacob Reimer, Emmanouil Froudarakis, Thomas Euler, Miroslav Román Rosón, Lucas Theis, Andreas S Tolias, and Matthias Bethge
- Subjects
Biology (General) ,QH301-705.5 - Abstract
In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.
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- 2018
- Full Text
- View/download PDF
3. Mouse dLGN Receives Input from a Diverse Population of Retinal Ganglion Cells with Limited Functional Convergence
- Author
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Yannik Bauer, Thomas Euler, Laura Busse, Philipp Berens, and Miroslav Román Rosón
- Subjects
Retina ,Visual perception ,genetic structures ,Thalamus ,Biology ,Retinal ganglion ,eye diseases ,Visual processing ,medicine.anatomical_structure ,Cortex (anatomy) ,Geniculate ,medicine ,sense organs ,Neuroscience ,Nucleus - Abstract
In the mouse, the parallel output of more than 30 functional types of retinal ganglion cells (RGCs) serves as the basis for all further visual processing. Little is known about how the representation of visual information changes between the retina and the dorsolateral geniculate nucleus (dLGN) of the thalamus, the main relay station between the retina and cortex. Here, we functionally characterized responses of retrogradely labeled dLGN-projecting RGCs and dLGN neurons to the same set of visual stimuli. We found that many of the previously identified functional RGC types innervate the dLGN, which maintained a high degree of functional diversity. Using a linear model to assess functional connectivity between RGC types and dLGN neurons, we found that the responses of dLGN neurons could be predicted as a linear combination of inputs from on average five RGC types, but only two of those had the strongest functional impact. Thus, mouse dLGN receives input from a diverse population of RGCs with limited functional convergence.
- Published
- 2018
- Full Text
- View/download PDF
4. Mouse dLGN Receives Functional Input from a Diverse Population of Retinal Ganglion Cells with Limited Convergence
- Author
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Thomas Euler, Miroslav Román Rosón, Laura Busse, Ann H. Kotkat, Philipp Berens, and Yannik Bauer
- Subjects
Retinal Ganglion Cells ,0301 basic medicine ,Cell type ,genetic structures ,Thalamus ,Biology ,Retinal ganglion ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Cortex (anatomy) ,Geniculate ,medicine ,Animals ,Visual Pathways ,Vision, Ocular ,Neurons ,Retina ,General Neuroscience ,Geniculate Bodies ,Electroencephalography ,eye diseases ,030104 developmental biology ,medicine.anatomical_structure ,Retinal ganglion cell ,Linear Models ,sense organs ,Neuroscience ,Nucleus ,Photic Stimulation ,030217 neurology & neurosurgery - Abstract
Mouse vision is based on the parallel output of more than 30 functional types of retinal ganglion cells (RGCs). Little is known about how representations of visual information change between retina and dorsolateral geniculate nucleus (dLGN) of the thalamus, the main relay between retina and cortex. Here, we functionally characterized responses of retrogradely labeled dLGN-projecting RGCs and dLGN neurons to the same set of visual stimuli. We found that many of the previously identified functional RGC types innervate dLGN, which maintained a high degree of functional diversity. Using a linear model to assess functional connectivity between RGC types and dLGN neurons, we found that responses of dLGN neurons could be predicted as linear combination of inputs from on average five RGC types, but only two of those had the strongest functional impact. Thus, mouse dLGN receives functional input from a diverse population of RGC types with limited convergence.
- Published
- 2019
- Full Text
- View/download PDF
5. Benchmarking Spike Rate Inference in Population Calcium Imaging
- Author
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Philipp Berens, Jacob Reimer, Emmanouil Froudarakis, Lucas Theis, Miroslav Román Rosón, Andreas S. Tolias, Matthias Bethge, Thomas Euler, and Tom Baden
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Male ,0301 basic medicine ,Computer science ,Models, Neurological ,Population ,Action Potentials ,Inference ,Retina ,Article ,Mice ,03 medical and health sciences ,0302 clinical medicine ,Animals ,education ,Neurons ,Signal processing ,education.field_of_study ,business.industry ,General Neuroscience ,Supervised learning ,Probabilistic logic ,Signal Processing, Computer-Assisted ,Pattern recognition ,Benchmarking ,030104 developmental biology ,Benchmark (computing) ,Calcium ,Spike (software development) ,Artificial intelligence ,business ,Algorithms ,030217 neurology & neurosurgery - Abstract
A fundamental challenge in calcium imaging has been to infer spike rates of neurons from the measured noisy fluorescence traces. We systematically evaluate different spike inference algorithms on a large benchmark dataset (>100.000 spikes) recorded from varying neural tissue (V1 and retina) using different calcium indicators (OGB-1 and GCaMP6). In addition, we introduce a new algorithm based on supervised learning in flexible probabilistic models and find that it performs better than other published techniques. Importantly, it outperforms other algorithms even when applied to entirely new datasets for which no simultaneously recorded data is available. Future data acquired in new experimental conditions can be used to further improve the spike prediction accuracy and generalization performance of the model. Finally, we show that comparing algorithms on artificial data is not informative about performance on real data, suggesting that benchmarking different methods with real-world datasets may greatly facilitate future algorithmic developments in neuroscience.
- Published
- 2016
6. Subcortical source and modulation of the narrowband gamma oscillation in mouse visual cortex
- Author
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Bilal Haider, Matteo Carandini, Aman B. Saleem, Laura Busse, Anthony D Lien, Michael Krumin, Aslı Ayaz, Kenneth D. Harris, Miroslav Román Rosón, and Kimberley Reinhold
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Physics ,0303 health sciences ,genetic structures ,business.industry ,Oscillation ,Neuroscience(all) ,Thalamus ,Lateral geniculate nucleus ,03 medical and health sciences ,Light intensity ,0302 clinical medicine ,Optics ,medicine.anatomical_structure ,Visual cortex ,Narrowband ,Cortex (anatomy) ,Gamma Rhythm ,medicine ,sense organs ,business ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
SummaryPrimary visual cortex (V1) exhibits two types of gamma rhythm: broadband activity in the 30–90 Hz range, and a narrowband oscillation seen in mice at frequencies close to 60 Hz. We investigated the sources of the narrowband gamma oscillation, the factors modulating its strength, and its relationship to broadband gamma activity. Narrowband and broadband gamma power were uncorrelated. Increasing visual contrast had opposite effects on the two rhythms: it increased broadband activity, but suppressed the narrowband oscillation. The narrowband oscillation was strongest in layer 4, and was mediated primarily by excitatory currents entrained by the synchronous, rhythmic firing of neurons in the lateral geniculate nucleus (LGN). The power and peak frequency of the narrowband gamma oscillation increased with light intensity. Silencing the cortex optogenetically did not affect narrowband oscillation in either LGN firing or cortical excitatory currents, suggesting that this oscillation reflects unidirectional flow of signals from thalamus to cortex.Highlights•Local field potential in mouse primary visual cortex exhibits a pronounced narrowband gamma oscillation close to 60 Hz.•Narrowband gamma is highest in the thalamorecipient layer 4•Narrowband gamma increases with light intensity and arousal state, and is suppressed by visual contrast.•Lateral geniculate nucleus neurons fire synchronously at the narrowband gamma frequency, independent of V1 activity.
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- 2016
- Full Text
- View/download PDF
7. Subcortical Source and Modulation of the Narrowband Gamma Oscillation in Mouse Visual Cortex
- Author
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Aman B, Saleem, Anthony D, Lien, Michael, Krumin, Bilal, Haider, Miroslav Román, Rosón, Asli, Ayaz, Kimberly, Reinhold, Laura, Busse, Matteo, Carandini, and Kenneth D, Harris
- Subjects
Neurons ,genetic structures ,Excitatory Postsynaptic Potentials ,Geniculate Bodies ,mouse vision ,Mice ,lateral geniculate nucleus ,Inhibitory Postsynaptic Potentials ,Report ,thalamus ,Synapses ,Animals ,Gamma Rhythm ,Visual Pathways ,gamma ,sense organs ,primary visual cortex ,Photic Stimulation ,neural circuits ,Visual Cortex - Abstract
Summary Primary visual cortex exhibits two types of gamma rhythm: broadband activity in the 30–90 Hz range and a narrowband oscillation seen in mice at frequencies close to 60 Hz. We investigated the sources of the narrowband gamma oscillation, the factors modulating its strength, and its relationship to broadband gamma activity. Narrowband and broadband gamma power were uncorrelated. Increasing visual contrast had opposite effects on the two rhythms: it increased broadband activity, but suppressed the narrowband oscillation. The narrowband oscillation was strongest in layer 4 and was mediated primarily by excitatory currents entrained by the synchronous, rhythmic firing of neurons in the lateral geniculate nucleus (LGN). The power and peak frequency of the narrowband gamma oscillation increased with light intensity. Silencing the cortex optogenetically did not abolish the narrowband oscillation in either LGN firing or cortical excitatory currents, suggesting that this oscillation reflects unidirectional flow of signals from thalamus to cortex., Highlights • Mouse V1 exhibits a pronounced narrowband gamma oscillation close to 60 Hz • This oscillation is strongest in layer 4 and specific to excitatory currents • It increases with arousal and light intensity and decreases with visual contrast • It is seen in lateral geniculate neurons, regardless of V1 activity, Saleem et al. discover that the narrowband gamma oscillation close to 60 Hz prevalent in the mouse visual cortex is inherited from the visual thalamus. The oscillation is enhanced by arousal and light intensity, and suppressed by visual contrast.
- Published
- 2016
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