RESUMO

Mammalian hippocampal circuits undergo extensive remodeling through adult neurogenesis. While this process has been widely studied, the specific contribution of adult-born granule cells (aGCs) to spatial operations in the hippocampus remains unknown. Here, we show that optogenetic activation of 4-week-old (young) aGCs in free-foraging mice produces a non-reversible reconfiguration of spatial maps in proximal CA3 while rarely evoking neural activity. Stimulation of the same neuronal cohort on subsequent days recruits CA3 neurons with increased efficacy but fails to induce further remapping. In contrast, stimulation of 8-week-old (mature) aGCs can reliably activate CA3 cells but produces no alterations in spatial maps. Our results reveal a unique role of young aGCs in remodeling CA3 representations, a potential that can be depleted and is lost with maturation. This ability could contribute to generate orthogonalized downstream codes supporting pattern separation.

Assuntos

RESUMO

Autoassociative neural networks provide a simple model of how memories can be stored through Hebbian synaptic plasticity as retrievable patterns of neural activity. Although progress has been made along the last decades in understanding the biological implementation of autoassociative networks, their modest theoretical storage capacity has remained a major constraint. While most previous approaches utilize randomly connected networks, here we explore the possibility of optimizing network performance by selective connectivity between neurons, that could be implemented in the brain through creation and pruning of synaptic connections. We show through numerical simulations that a reconfiguration of the connectivity matrix can improve the storage capacity of autoassociative networks up to one order of magnitude compared to randomly connected networks, either by reducing the noise or by making it reinforce the signal. Our results indicate that the signal-reinforcement scenario is not only the best performing but also the most adequate for brain-like highly diluted connectivity. In this scenario, the optimized network tends to select synapses characterized by a high consensus across stored patterns. We also introduced an online algorithm in which the network modifies its connectivity while learning new patterns. We observed that, similarly to what happens in the human brain, creation of connections dominated in an initial stage, followed by a stage characterized by pruning, leading to an equilibrium state that was independent of the initial connectivity of the network. Our results suggest that selective connectivity could be a key component to make attractor networks in the brain viable in terms of storage capacity.

RESUMO

The Octodon degus is a South American rodent that is receiving increased attention as a potential model of aging and sporadic late-onset Alzheimer's disease (AD). Impairments in spatial memory tasks in Octodon degus have been reported in relation to either advanced AD-like disease or hippocampal lesion, opening the way to investigate how the function of hippocampal networks affects behavior across AD stages. However, no characterization of hippocampal electrophysiology exists in this species. Here we describe in young, healthy specimens the activity of neurons and local field potential rhythms during spatial navigation tasks with and without objects. Our findings show similarities between the Octodon degus and laboratory rodents. First, place cells with characteristics similar to those found in rats and mice exist in the CA1 subfield of the Octodon degus. Second, the introduction of objects elicits novelty-related exploration and an increase in activity of CA1 cells, with location specific and unspecific components. Third, oscillations of the local field potential are organized according to their spectral content into bands similar to those found in laboratory rodents. These results suggest a common framework of underlying mechanisms, opening the way to future studies of hippocampal dysfunction in this species associated to aging and disease.

Assuntos

RESUMO

Possible links between the transmission of COVID-19 and meteorology have been investigated by comparing positive cases across geographical regions or seasons. Little is known, however, about the degree to which environmental conditions modulate the daily dynamics of COVID-19 spread at a given location. One reason for this is that individual waves of the disease typically rise and decay too sharply, making it hard to isolate the contribution of meteorological cycles. To overcome this shortage, we here present a case study of the first wave of the outbreak in the city of Buenos Aires, which had a slow evolution of the caseload extending along most of 2020. We found that humidity plays a prominent role in modulating the variation of COVID-19 positive cases through a negative-slope linear relationship, with an optimal lag of 9 days between the meteorological observation and the positive case report. This relationship is specific to winter months, when relative humidity predicts up to half of the variance in positive case count. Our results provide a tool to anticipate possible local surges in COVID-19 cases after events of low humidity. More generally, they add to accumulating evidence pointing to dry air as a facilitator of COVID-19 transmission.

Assuntos

RESUMO

In the study of the neural code, information-theoretical methods have the advantage of making no assumptions about the probabilistic mapping between stimuli and responses. In the sensory domain, several methods have been developed to quantify the amount of information encoded in neural activity, without necessarily identifying the specific stimulus or response features that instantiate the code. As a proof of concept, here we extend those methods to the encoding of kinematic information in a navigating rodent. We estimate the information encoded in two well-characterized codes, mediated by the firing rate of neurons, and by the phase-of-firing with respect to the theta-filtered local field potential. In addition, we also consider a novel code, mediated by the delta-filtered local field potential. We find that all three codes transmit significant amounts of kinematic information, and informative neurons tend to employ a combination of codes. Cells tend to encode conjunctions of kinematic features, so that most of the informative neurons fall outside the traditional cell types employed to classify spatially-selective units. We conclude that a broad perspective on the candidate stimulus and response features expands the repertoire of strategies with which kinematic information is encoded.

RESUMO

Grid cells in the medial entorhinal cortex have spatial firing fields that repeat periodically in a hexagonal pattern. When animals move, activity is translated between grid cells in accordance with the animal's displacement in the environment. For this translation to occur, grid cells must have continuous access to information about instantaneous running speed. However, a powerful entorhinal speed signal has not been identified. Here we show that running speed is represented in the firing rate of a ubiquitous but functionally dedicated population of entorhinal neurons distinct from other cell populations of the local circuit, such as grid, head-direction and border cells. These 'speed cells' are characterized by a context-invariant positive, linear response to running speed, and share with grid cells a prospective bias of ∼50-80 ms. Our observations point to speed cells as a key component of the dynamic representation of self-location in the medial entorhinal cortex.

Assuntos

RESUMO

Throughout the adult life of all mammals including humans, new neurons are incorporated to the dentate gyrus of the hippocampus. During a critical window that lasts about two weeks, adult-born immature neurons are more excitable and plastic than mature ones, and they respond to a wider range of inputs. In apparent contradiction, new neurons have been shown to be crucial to solve behavioral tasks that involve the discrimination of very similar situations, which would instead require high input specificity. We propose that immature neurons are initially unspecific because their task is to identify novel elements inside a high dimensional input space. With maturation, they would specialize to represent details of these novel inputs, favoring discrimination.

Assuntos

RESUMO

Developing granule cells (GCs) of the adult dentate gyrus undergo a critical period of enhanced activity and synaptic plasticity before becoming mature. The impact of developing GCs on the activity of preexisting dentate circuits remains unknown. Here we combine optogenetics, acute slice electrophysiology, and in vivo chemogenetics to activate GCs at different stages of maturation to study the recruitment of local target networks. We show that immature (4-week-old) GCs can efficiently drive distal CA3 targets but poorly activate proximal interneurons responsible for feedback inhibition (FBI). As new GCs transition toward maturity, they reliably recruit GABAergic feedback loops that restrict spiking of neighbor GCs, a mechanism that would promote sparse coding. Such inhibitory loop impinges only weakly in new cohorts of young GCs. A computational model reveals that the delayed coupling of new GCs to FBI could be crucial to achieve a fine-grain representation of novel inputs in the dentate gyrus.

Assuntos