Intra-ripple frequency accommodation in an inhibitory network model for hippocampal ripple oscillations.

Hippocampal ripple oscillations have been implicated in important cognitive functions such as memory consolidation and planning. Multiple computational models have been proposed to explain the emergence of ripple oscillations, relying either on excitation or inhibition as the main pacemaker. Nevertheless, the generating mechanism of ripples remains unclear. An interesting dynamical feature of experimentally measured ripples, which may advance model selection, is intra-ripple frequency accommodation (IFA): a decay of the instantaneous ripple frequency over the course of a ripple event. So far, only a feedback-based inhibition-first model, which relies on delayed inhibitory synaptic coupling, has been shown to reproduce IFA. Here we use an analytical mean-field approach and numerical simulations of a leaky integrate-and-fire spiking network to explain the mechanism of IFA. We develop a drift-based approximation for the oscillation dynamics of the population rate and the mean membrane potential of interneurons under strong excitatory drive and strong inhibitory coupling. For IFA, the speed at which the excitatory drive changes is critical. We demonstrate that IFA arises due to a speed-dependent hysteresis effect in the dynamics of the mean membrane potential, when the interneurons receive transient, sharp wave-associated excitation. We thus predict that the IFA asymmetry vanishes in the limit of slowly changing drive, but is otherwise a robust feature of the feedback-based inhibition-first ripple model.

The transformation from grid cells to place cells is robust to noise in the grid pattern.

Spatial navigation in rodents has been attributed to place-selective cells in the hippocampus and entorhinal cortex. However, there is currently no consensus on the neural mechanisms that generate the place-selective activity in hippocampal place cells or entorhinal grid cells. Given the massive input connections from the superficial layers of the entorhinal cortex to place cells in the hippocampal cornu ammonis (CA) regions, it was initially postulated that grid cells drive the spatial responses of place cells. However, recent experiments have found that place cell responses are stable even when grid cell responses are severely distorted, thus suggesting that place cells cannot receive their spatial information chiefly from grid cells. Here, we offer an alternative explanation. In a model with linear grid-to-place-cell transformation, the transformation can be very robust against noise in the grid patterns depending on the nature of the noise. In the two more realistic noise scenarios, the transformation was very robust, while it was not in the other two scenarios. Although current experimental data suggest that other types of place-selective cells modulate place cell responses, our results show that the simple grid-to-place-cell transformation alone can account for the origin of place selectivity in the place cells.

Transformation of the head-direction signal into a spatial code.

Animals integrate multiple sensory inputs to successfully navigate in their environments. Head direction (HD), boundary vector, grid and place cells in the entorhinal-hippocampal network form the brain's navigational system that allows to identify the animal's current location, but how the functions of these specialized neuron types are acquired remain to be understood. Here we report that activity of HD neurons is influenced by the ambulatory constraints imposed upon the animal by the boundaries of the explored environment, leading to spurious spatial information. However, in the post-subiculum, the main cortical stage of HD signal processing, HD neurons convey true spatial information in the form of border modulated activity through the integration of additional sensory modalities relative to egocentric position, unlike their driving thalamic inputs. These findings demonstrate how the combination of HD and egocentric information can be transduced into a spatial code.