The functional diversity of retinal ganglion cells in the mouse

Baden, Tom; Berens, Philipp; Franke, Katrin; Rosón, Miroslav Román; Bethge, Matthias; Euler, Thomas

doi:10.1038/nature16468

Cited by 879 publications

(1,378 citation statements)

References 56 publications

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“…While matching of fixed labeled tissue with live imaged tissue has been conducted in small sections of neocortex and retina using manual alignment to identify small numbers of cells (Kerlin et al, 2010; O’Connor et al, 2010; Langer and Helmchen, 2012; Baden et al, 2016; Wilson et al, 2017), here, we develop an approach for the entire zebrafish brain through automated registration of tens of thousands of neurons in intact tissue volumes. MultiMAP allowed us to rapidly screen active cell types without constructing transgenic lines for each.…”

Section: Discussionmentioning

confidence: 99%

Ancestral Circuits for the Coordinated Modulation of Brain State

Lovett-Barron¹,

Andalman²,

Allen³

et al. 2017

Cell

152

144

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SUMMARY Internal states of the brain profoundly influence behavior. Fluctuating states such as alertness can be governed by neuromodulation, but the underlying mechanisms and cell types involved are not fully understood. We developed a method to globally screen for cell types involved in behavior by integrating brain-wide activity imaging with high-content molecular phenotyping and volume registration at cellular resolution. We used this method (MultiMAP) to record from 22 neuromodulatory cell types in behaving zebrafish during a reaction-time task that reports alertness. We identified multiple monoaminergic, cholinergic, and peptidergic cell types linked to alertness and found that activity in these cell types was mutually correlated during heightened alertness. We next recorded from and controlled homologous neuromodulatory cells in mice; alertness-related cell-type dynamics exhibited striking evolutionary conservation and modulated behavior similarly. These experiments establish a method for unbiased discovery of cellular elements underlying behavior and reveal an evolutionarily conserved set of diverse neuromodulatory systems that collectively govern internal state.

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Section: Discussionmentioning

confidence: 99%

Ancestral Circuits for the Coordinated Modulation of Brain State

Lovett-Barron¹,

Andalman²,

Allen³

et al. 2017

Cell

152

144

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“…alternatively transformed data. That said, PCA followed by GMM has been successfully employed to cluster the Ca ++ responses of retinal ganglion cells without any time-frequency transformations (Baden et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Systematic exploration of unsupervised methods for mapping behavior

Todd

Kain²,

Bivort

2017

Phys. Biol.

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To fully understand the mechanisms giving rise to behavior, we need to be able to precisely measure it. When coupled with large behavioral data sets, unsupervised clustering methods offer the potential of unbiased mapping of behavioral spaces. However, unsupervised techniques to map behavioral spaces are in their infancy, and there have been few systematic considerations of all the methodological options. We compared the performance of seven distinct mapping methods in clustering a wavelettransformed data set consisting of the x-and y-positions of the six legs of individual flies. Legs were automatically tracked by small pieces of fluorescent dye, while the fly was tethered and walking on an air-suspended ball. We find that there is considerable variation in the performance of these mapping methods, and that better performance is attained when clustering is done in higher dimensional spaces (which are otherwise less preferable because they are hard to visualize). High dimensionality means that some algorithms, including the non-parametric watershed cluster assignment algorithm, cannot be used. We developed an alternative watershed algorithm which can be used in high-dimensional spaces when a probability density estimate can be computed directly. With these tools in hand, we examined the behavioral space of fly leg postural dynamics and locomotion. We find a striking division of behavior into modes involving the fore legs and modes involving the hind legs, with few direct transitions between them. By computing behavioral clusters using the data from all flies simultaneously, we show that this division appears to be common to all flies. We also identify individual-to-individual differences in behavior and behavioral transitions. Lastly, we suggest a computational pipeline that can achieve satisfactory levels of performance without the taxing computational demands of a systematic combinatorial approach.

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“…This imaging technique has proven to be quite powerful in characterizing the receptive field properties of retinal ganglion cells [9][10][11][12]. We loaded retinas of WT mice near eye-opening (P13-P14) and in adulthood (>P30) with the calcium dye Oregon green 488 BAPTA-1 hexapotassium salt (OGB-1) via electroporation, thus uniformly labeling the ganglion cell layer ( Figure 1A; see Supplemental Information).…”

Section: Clustering Of Dsgc Preferred Directions Along Cardinal Axesmentioning

confidence: 99%

Role for Visual Experience in the Development of Direction-Selective Circuits

Bos¹,

Gainer²,

Feller³

2017

Current Biology

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SUMMARYVisually-guided behavior can depend critically on detecting the direction of object movement. This computation is first performed in the retina where direction is encoded by direction-selective ganglion cells (DSGCs) that respond strongly to an object moving in the preferred direction and weakly to an object moving in the opposite, or null, direction (reviewed in [1]). These DSGCs come in multiple types that are classified based on their morphologies, response properties and targets in the brain. This study focuses on two types -ON and ON-OFF DSGCs. Though animals can sense motion in all directions, the preferred directions of DSGCs in adult retina cluster along distinct directions that we refer to as the cardinal axes. ON DSGCs have three cardinal axestemporal, ventral and dorsonasal -while ON-OFF DSGCs have four -nasal, temporal, dorsal, and ventral. How these preferred directions emerge during development is still not understood. Several studies have demonstrated that ON [2] and ON-OFF DSGCs are well tuned at eye-opening, and even a few days prior to eye-opening, in rabbits [3], rats [4] and mice [5][6][7][8], suggesting that visual experience is not required to produce direction selective tuning. However, here we show that at eye-opening the preferred directions of both ON and ON-OFF DSGCs are diffusely distributed and that visual deprivation prevents the preferred directions from clustering along the cardinal axes. Our findings indicate a critical role for visual experience in shaping responses in the retina. HHS Public Access RESULTS Clustering of DSGC preferred directions along cardinal axes after eye-opening requires visual experienceWe used two-photon calcium imaging to study the development of DSGC populations in mouse retina. This imaging technique has proven to be quite powerful in characterizing the receptive field properties of retinal ganglion cells [9][10][11][12]. We loaded retinas of WT mice near eye-opening (P13-P14) and in adulthood (>P30) with the calcium dye Oregon green 488 BAPTA-1 hexapotassium salt (OGB-1) via electroporation, thus uniformly labeling the ganglion cell layer ( Figure 1A; see Supplemental Information). Ventral portions of the retina were stimulated with light centered at 385 nm to maximally activate UV-cones [13,14] while minimizing cross talk with the imaging detectors ( Figure S1). This approach allowed us to record from all DSGC subtypes within a single field of view (~40000 μm 2 ).To identify DSGCs, we first used full field UV-light flashes to classify cells as ON, OFF or ON-OFF retinal ganglion cells (RGCs) ( Figure S1; Table S1). We found that around 80% of the cells in the ganglion cell layer of young and adult retinas responded to light flashes with changes in fluorescence (Table S1), similar to the RGC percentages reported in previous studies [9,11,12]. In addition, over development we observed a decrease in the percentage of ON-OFF RGCs (28.03% at P13-14 to 20.84% in adult) (Table S1) [15].Second, we used light bars on a dark background drifting in 8 dir...

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The functional diversity of retinal ganglion cells in the mouse

Cited by 879 publications

References 56 publications

Ancestral Circuits for the Coordinated Modulation of Brain State

Ancestral Circuits for the Coordinated Modulation of Brain State

Systematic exploration of unsupervised methods for mapping behavior

Role for Visual Experience in the Development of Direction-Selective Circuits

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