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Adult-born granule cells improve stimulus encoding and discrimination in the dentate gyrus

Citation

Arribas, Diego; Marin-Burgin, Antonia; Morelli, Luis (2022), Adult-born granule cells improve stimulus encoding and discrimination in the dentate gyrus, Dryad, Dataset, https://doi.org/10.5061/dryad.73n5tb309

Abstract

Heterogeneity plays an important role in diversifying neural responses to support brain function. Adult neurogenesis provides the dentate gyrus with a heterogeneous population of granule cells (GCs) that were born and developed their properties at different times. Immature GCs have distinct intrinsic and synaptic properties than mature GCs and are needed for correct encoding and discrimination in spatial tasks. How immature GCs enhance the encoding of information to support these functions is not well understood. Here, we record the responses to fluctuating current injections of GCs of different ages to study how they encode stimuli. Immature GCs produce unreliable responses compared to mature GCs, exhibiting imprecise spike timings across repeated stimulation. We use a statistical model to describe the stimulus-response transformation performed by GCs of different ages. We fit this model to the data and obtain parameters that capture GCs encoding properties. Parameter values from this fit reflect the maturational differences of the population and indicate that immature GCs perform a differential encoding of stimuli. To study how this age heterogeneity influences encoding by a population, we perform stimulus decoding using populations that contain GCs of different ages. We find that, despite their individual unreliability, immature GCs enhance the fidelity of the signal encoded by the population and improve the discrimination of similar time dependent stimuli. Thus, the observed heterogeneity confers the population with enhanced encoding capabilities.

Methods

Electrophysiological Recordings

The dataset contains electrophysiological recordings from neurons of the mouse dentate gyrus.

Recorded immature neurons were visually identified by fluorescence. GCs used between 28 and 30 days post injection were labeled as 4w and GCs used between 34 and 36 days post injection were labeled as 5w. The mature population encompassed unlabeled neurons localized in the outer third of the granule cell layer. Whole-cell current-clamp recordings were performed using microelectrodes (4–6 MΩ) filled with a potassium gluconate internal solution (in mM): 120 potassium gluconate, 4 MgCl2, 10 HEPES buffer, 0.1 EGTA, 5NaCl, 20KCl, 4ATP-tris, 0.3 GTP-tris, and 10 phosphocreatine (pH = 7.3; 290 mOsm). Excitatory and inhibitory synaptic transmission were blocked pharmacologically with kynurenic acid (Sigma-Aldrich Cat K3375) and picrotoxin (Sigma-Aldrich Cat P1675). Recordings were obtained using Multiclamp 700B amplifiers (Molecular Devices), digitized using Digidata 1550 (Axon instruments), and acquired at 10 kHz onto a personal computer using the pClamp10 software (Molecular Devices). Before starting every protocol of stimulation, the resting membrane potential was kept at around -70 mV by passing a holding current. Passive properties were measured by injecting a small hyperpolarizing current step. Current step amplitude was adapted to each neuron and resulted in a negative membrane potential deviation of 1-4 mV.

Usage Notes

File type and access

Raw data files are in the Axon Binary File format (ABF) which allows the storage of binary experimental data. It is the format type used by the pCLAMP suite of data acquisition and analysis programs, but is also supported by AxoTape and AxoScope software. Any software that opens ABF files can be used to access the data, for example the open source Python package pyABF available at https://swharden.com/pyabf/.

Funding

Agencia Nacional de Promoción Científica y Tecnológica, Award: PICT 2015 0634

Agencia Nacional de Promoción Científica y Tecnológica, Award: PICT 2017 3753

Agencia Nacional de Promoción Científica y Tecnológica, Award: PICT 2018 0880

Agencia Nacional de Promoción Científica y Tecnológica, Award: PICT 2019 0445