Spatial gradients and multidimensional dynamics in a neural integrator circuit

Abstract

In a neural integrator, the variability and topographical organization of neuronal firing rate persistence can provide information about the circuit’s functional architecture. Here we use optical recording to measure the time constant of decay of persistent firing (“persistence time”) across a population of neurons comprising the larval zebrafish oculomotor velocity-to-position neural integrator. We find extensive persistence time variation (10-fold; coefficients of variation 0.58–1.20) across cells within individual larvae. We also find that the similarity in firing between two neurons decreased as the distance between them increased and that a gradient in persistence time was mapped along the rostrocaudal and dorsoventral axes. This topography is consistent with the emergence of persistence time heterogeneity from a circuit architecture in which nearby neurons are more strongly interconnected than distant ones. Collectively, our results can be accounted for by integrator circuit models characterized by multiple dimensions of slow firing rate dynamics.

A tale of two species: Neural integration in zebrafish and monkeys

“…It now is possible to go beyond the traditional approaches used in monkey research, and to answer questions that were intractable in the past. For example, imaging of calcium signals makes it possible to record from many nearby neurons simultaneously with a temporal resolution that is good enough to capture the relationships between neural and behavioral or stimulus dynamics (Stosiek et al, 2003, Rothschild et al, 2010, Miri et al, 2011). Activation of specific subpopulations of neurons through optogenetics provides a carefully controlled tool for dissection of neural circuits in behaving animals (Han and Boyden, 2007).…”

“…In principle, integration can be implemented in a simple recurrent network that operates as a line attractor (Seung, 1996), or even in a single neuron with appropriate recurrent connections to itself (Seung et al, 2000). In practice, biological facts such as neuron physiology, actual anatomical connections, and the dynamics of the firing rate during eye movements needed to constrain the recurrent networks that might mimic the oculomotor integrator (Cannon et al, 1983, Galiana and Outerbridge, 1984, Cannon and Robinson, 1985, Seung, 1996, Miri et al, 2011, Joshua et al, 2013). …”

“…Focal lesions and simultaneous recordings from multiple neurons revealed the functional relation between bilateral integrator circuits (Aksay et al, 2007). Most recently, calcium imaging in behaving zebrafish demonstrated the relationship between the spatial location of individual neurons and their temporal response profiles (Miri et al, 2011), and suggested principles of a circuit architecture for neural integration. Thus, the new challenge became to bridge across two disparate species.…”

Neurons that Remember How We Got There

“…During fixation, the eyes still showed a small drift, and hence the VPNI is not a perfect integrator. The average activity decay was in both paradigms on a scale of roughly 7 s, and previous work revealed a spatial gradient of decay times of the individual neurons across the VPNI population (Miri et al, 2011). The striking new finding is that this spatial gradient is just opposite in the two movementinducing paradigms.…”

Functional investigation of neural circuits in larval zebrafish

“…Cells in the zebrafish hindbrain that integrate oculomotor information and stabilize eye positions have been analysed optogenetically using both NpHR (Miri et al, 2011) and ChR2 (Gonçalves et al, 2014). Circuits in the hindbrain responsible for the generation of saccades during optokinetic responses have also been identified by targeted loss-of-function and gain-of-function using NpHR and ChR2, respectively (Schoonheim et al, 2010).…”