Assisi, C. | bioRxiv Science

bioRxiv2019

Theta oscillations gate the transmission of reliable sequences in the medial entorhinal cortex

Reliable sequential activity of neurons in the entorhinal cortex is necessary to encode spatially guided behavior and memory. In a realistic computational model of a medial entorhinal cortex (MEC) microcircuit, with stellate cells coupled via a network of inhibitory interneurons, we show how intrinsic and network mechanisms interact with theta oscillations to generate reliable outputs. Sensory inputs activate interneurons near their most excitable phase during each theta cycle. As the inputs change, different groups of interneurons are recruited and postsynaptic stellate cells are released from inhibition causing a sequence of rebound spikes. Since the rebound time scale of stellate cells matches theta oscillations, its spikes get relegated to the least excitable phase of theta ensuring that the network encodes only the external drive and ignores recurrent excitation by rebound spikes. In the absence of theta, rebound spikes compete with external inputs and disrupt the sequence that follows. Our simulations concur with experimental data that show, subduing theta oscillations disrupts the spatial periodicity of grid cell receptive fields. Further, the same mechanism where theta modulates the gain of incoming inputs may be used to select between competing sources of input and create transient functionally connected networks.

neuroscience↗

bioRxiv2019

Optimal sparse olfactory representations persist in a plastic network

The neural representation of a stimulus is repeatedly transformed as it moves from the sensory periphery to deeper layers of the nervous system. Sparsening transformations are thought to increase the separation between similar representations, encode stimuli with great specificity, maximize storage capacity as associative memories, and provide an energy efficient instantiation of information in neural circuits. In the insect olfactory system, odors are initially represented in the periphery as a combinatorial code with simple temporal dynamics. Subsequently, in the antennal lobe this representation is transformed into a dense spatiotemporal activity pattern. Next, in the mushroom body Kenyon cells (KCs), the representation is dramatically sparsened. Then in mushroom body output neurons (MBONs), the representation takes on a new dense spatiotemporal format. Here, we develop a computational model to simulate this chain of olfactory processing from the receptor neurons to MBONs. We demonstrate that representations of similar odorants are maximally separated, measured by the distance between the corresponding MBON activity vectors, when KC responses are sparse and that the sparseness is maintained across variations in odor concentration by adjusting the feedback inhibition KCs receive. Different odor concentrations require different strength and timing of feedback inhibition for optimal processing. Further, in vivo, the KC-MBON synapse is highly plastic, and changes in synaptic strength after learning can change the balance of excitation and inhibition and may lead to a change in the distance between MBON activity vectors of two odorants for the same level of KC population sparseness. Thus, what is an optimal degree of sparseness before odor learning, could be rendered sub-optimal post learning. Here, we show, however, that synaptic weight changes caused by spike timing dependent plasticity increase the distance between the odor representations from the perspective of MBONs and do not lead to a concomitant change in the optimal sparseness. Author SummaryKenyon cells (KCs) of the mushroom body represent odors as a sparse code. When viewed from the perspective of follower neurons, mushroom body output neurons (MBONs), an optimal level of KC sparseness maximally separates the representations of odors. However, the KC-MBON synapse is highly plastic and may be potentiated or depressed by odor-driven experience that could, in turn, perturb the optimality formed by pre-synaptic circuits. Contrary to this expectation, we show that synaptic plasticity based on spike timing of pre- and postsynaptic neurons improves the ability of the system to distinguish between the representations of similar odors while preserving the optimality determined by pre-synaptic circuits.

neuroscience↗