Encoding and decoding of overlapping odor sequences.

By B. M. Broome, V. Jayaraman, Gilles Laurent. 2006

185 citations recorded by the source corpus.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Sensory Systems

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Citations in the corpus

Re-evaluating circuit mechanisms underlying pattern separation (2019, neutral): “In this view, neural circuits must learn to encode distinct stimuli with separated trajectories with minimal overlap due to noise or variability (Friedrich and Laurent, 2001; Stopfer et al., 2003; Broome et al., 2006; Shen et al., 2013; Zylberberg et al., 2016; Remington et al., 2018).”
Olfactory representations by Drosophila mushroom body neurons. (2008, background): “We propose that sparsening is an intrinsic requirement of such memory systems (Broome et al. 2006; Laurent 2002; Perez-Orive et al. 2002).”
Cellular-resolution population imaging reveals robust sparse coding in the Drosophila Mushroom Body (2011, background): “Electrophysiological recordings show that, unlike PNs, individual KCs have highly odor-specific responses and odors are represented by sparse population activity in the MB (Perez-Orive et al., 2002; Broome et al., 2006; Murthy et al., 2008; Turner et al., 2008).”
Computation Through Neural Population Dynamics (2020, background): “…to sensory input dynamics (Seely et al. 2016), and has been explored over the past 15 years in a variety of contexts (Briggman et al. 2005, 2006; Broome et al. 2006; Churchland et al. 2006c; Mazor & Laurent 2005; Rabinovich et al. 2008; Stopfer et al. 2003; Sussillo & Abbott 2009; Yu et al.…”
Cortical control of arm movements: a dynamical systems perspective. (2013, background): “Indeed, the dynamical systems perspective may be experiencing a renaissance in neuroscience as a whole (e.g., Briggman et al. 2005, 2006; Broome et al. 2006; Mazor & Laurent 2005; Rabinovich et al. 2008; Stopfer et al. 2003; Yu et al. 2006), largely as the result of the widening adoption of…”
Dimensionality reduction for large-scale neural recordings (2014, methodology): “…reduction has also been fruitfully applied to population recordings in other studies of decision-making 7–9 , the motor system 10–12 and the olfactory system 13,14 , as well as in working memory 15,16 , visual attention 17 , the auditory system 18 , rule learning 19 , speech 20 and more.”
Encoding of mixtures in a simple olfactory system. (2013, unknown): “…et al., 2004; Perez-Orive et al., 2002), it is useful to examine PN responses as time-series of instantaneous population vectors, or trajectories, and visualize them in an appropriately reduced state space (Broome et al., 2006; Brown et al., 2005; Mazor and Laurent, 2005; Stopfer et al., 2003).”
Imaging a Population Code for Odor Identity in the Drosophila Mushroom Body (2013, methodology): “…was chosen because it is well established (Fisher, 1936), has been commonly used both within (MacLeod et al., 1998; Friedrich and Laurent, 2001; Broome et al., 2006; Bhandawat et al., 2007; Silbering et al., 2008; Cury and Uchida, 2010) and outside olfaction (Briggman et al., 2005; Walker et…”
SORN: A Self-Organizing Recurrent Neural Network (2009, unknown): “Interestingly, neuronal responses are highly dynamic in time (even when the stimulus is static) (Broome et al., 2006) and contain a rich amount of information about past events (Brosch and Schreiner, 2000; Bartlett and Wang, 2005; Broome et al., 2006; Nikolic et al., 2006).”
Extracting spatial-temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition. (2014, background): “Fortunately, the activity of complex networks of neurons can often be described by relatively few distinct patterns (for instance, [1, 2, 3, 4, 5]).”