Population code in mouse V1 facilitates read-out of natural scenes through increased sparseness
By Emmanouil Froudarakis, Philipp Berens, Alexander S. Ecker, R. Cotton, Fabian H Sinz, Dimitri Yatsenko, P. Saggau, Matthias Bethge, Andreas S. Tolias. 2014
200 citations recorded by the source corpus.
Neural codes are believed to have adapted to the statistical properties of the natural environment. However, the principles that govern the organization of ensemble activity in the visual cortex during natural visual input are unknown. We recorded populations of up to 500 neurons in the mouse primary visual cortex and characterized the structure of their activity, comparing responses to natural movies with those to control stimuli. We found that higher order correlations in natural scenes induced a sparser code, in which information is encoded by reliable activation of a smaller set of neurons and can be read out more easily. This computationally advantageous encoding for natural scenes was state-dependent and apparent only in anesthetized and active awake animals, but not during quiet wakefulness. Our results argue for a functional benefit of sparsification that could be a general principle governing the structure of the population activity throughout cortical microcircuits.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience
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Citations in the corpus
- Re-evaluating circuit mechanisms underlying pattern separation (2019, neutral): “Several promising new imaging technologies that can record intracellular calcium from large numbers of identified cells have also been recently developed (Grewe et al., 2011; Katona et al., 2012; Froudarakis et al., 2014; Nadella et al., 2016; Sofroniew et al., 2016; Yang et al., 2016).”
- Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes (2016, background): “…al., 2016), image compression (Malo et al., 2006), distributed neural representations (Simoncelli & Heeger, 1998), stimulus decoding (Ringach, 2009; Froudarakis et al., 2014), winner-take-all mechanisms (Busse et al., 2009), attention (Reynolds & Heeger, 2009), redundancy reduction (Schwartz &…”
- Navigating the Neural Space in Search of the Neural Code. (2017, unknown): “First, many behaviors depend on converging and redundant signals from large populations of similarly behaving neurons (Cohen and Maunsell, 2009; Froudarakis et al., 2014; Jazayeri and Movshon, 2006; Priebe and Lisberger, 2004; Rust et al., 2006; Shadlen et al., 1996; Zohary et al., 1994).”
- Pupil fluctuations track fast switching of cortical states during quiet wakefulness (2014, unknown): “In mouse primary visual cortex (V1), this desynchronization is coupled with an enhancement of sensory responses (Fu et al., 2014; Froudarakis et al., 2014) and a reduction in detection thresholds (Bennett et al., 2013), and similar effects are seen in primary somatosensory cortex (area S1; Zagha et…”