Choice-specific sequences in parietal cortex during a virtual-navigation decision task

By Christopher D. Harvey, P. Coen, David W. Tank. Nature, 2012

926 citations recorded by the source corpus.

The posterior parietal cortex (PPC) has an important role in many cognitive behaviours; however, the neural circuit dynamics underlying PPC function are not well understood. Here we optically imaged the spatial and temporal activity patterns of neuronal populations in mice performing a PPC-dependent task that combined a perceptual decision and memory-guided navigation in a virtual environment. Individual neurons had transient activation staggered relative to one another in time, forming a sequence of neuronal activation spanning the entire length of a task trial. Distinct sequences of neurons were triggered on trials with opposite behavioural choices and defined divergent, choice-specific trajectories through a state space of neuronal population activity. Cells participating in the different sequences and at distinct time points in the task were anatomically intermixed over microcircuit length scales (<100 micrometres). During working memory decision tasks, the PPC may therefore perform computations through sequence-based circuit dynamics, rather than long-lived stable states, implemented using anatomically intermingled microcircuits.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/5b9b18443270dc4f24faf18aabfe290d7ee4a052

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Citations in the corpus

Causes and consequences of representational drift (2019, methodology): “Using chronic two-photon calcium imaging, the authors monitored the activity of large groups of individual neurons in the PPC, which is known to be required for solving the task [4 ,12].”
Using goal-driven deep learning models to understand sensory cortex (2016, background): “Mapping these to ideas in the neuroscience of the interface between ventral visual cortex and, for example, parietal cortex or the hippocampus will be of great interest 61,62 .”
If deep learning is the answer, what is the question? (2020, background): “The curious phenomenon of ‘representational drift’ (in which neural codes meander unpre dictably over time) 134 might reflect the allocation of information to different neural circuits in distinct contexts, enabling task knowledge to be partitioned in a way that minimizes interference 135 .”
Closed-loop and activity-guided optogenetic control. (2015, positive): “…Pfau et al., 2013) are desirable for their consistency with current models of low-rank state evolution and common-input properties in observed brain dynamics (Shenoy et al., 2013; Mante et al., 2013; Kaufman et al., 2014; Churchland et al., 2012; Harvey et al., 2012; Yu et al., 2006; Sahani, 1999).”
Navigating the Neural Space in Search of the Neural Code. (2017, neutral): “…of neurons and neural circuits (Buschman and Miller, 2007; Churchland et al., 2012; DiCarlo and Cox, 2007; Georgopoulos, 1994; Hanks et al., 2015; Harvey et al., 2012; Jazayeri and Movshon, 2006; Laurent et al., 2001; Lo and Wang, 2006; Mante et al., 2013; Ma et al., 2006; Moore and Armstrong,…”
Nanotools for Neuroscience and Brain Activity Mapping (2013, background): “In this acute recording situation, the interface longevity issue is less critical than the need to sample as many neurons as possible.(126,127) This creates an intriguing opportunity to pursue in parallel a different set of BAM tools for acute, ultra-largescale electrophysiology and tools for chroni”
A large field of view two-photon mesoscope with subcellular resolution for in vivo imaging (2016, methodology): “Together with calcium imaging, 2-photon microscopy is now routinely used to examine behavior-related activity in populations of neurons (Harvey et al. 2012, Huber et al. 2012, Peron et al. 2015b).”
Spatiotemporal Dynamics of Functional Clusters of Neurons in the Mouse Motor Cortex during a Voluntary Movement (2013, result): “This amount was similar to that used in other studies (70 l used by Komiyama et al., 2010; 50 l used by Harvey et al., 2012).”
From the neuron doctrine to neural networks (2015, background): “Recent evidence for the existence of emergent circuit states in the mammalian cortex comes from experiments on mice navigating a virtual maze 144 (FIG.”
The neuroscience of learning: beyond the Hebbian synapse. (2013, result): “For similar results from neurons in posterior parietal cortex in mice, see Harvey et al. (2012).”