No description available.

Anatomical connectivity and single neuron coding suggest a dissociation of information representation within the lateral and medial entorhinal cortex, a brain region with widespread connections to cortical areas. We aimed to expand this idea by examining differential contribution of these two sub-regions to the retrieval of non-spatial and spatial memory. Inactivation of lateral, but not medial regions severely impaired the retrieval of recently and remotely acquired non-spatial memory while spatial memory remained intact. To link functioning of the lateral entorhinal cortex with the known roles of the hippocampus and medial prefrontal cortex for memory retrieval, communication with these two regions was detected as synchronized oscillations in local field potentials. We found that stronger communication between the lateral entorhinal and prefrontal cortex during stimulus-free periods correlated with better memory performance. The lateral entorhinal cortex therefore may serve as a gateway of memory-related information between the medial prefrontal and other cortical regions.

Anatomical connectivity and single neuron coding suggest a dissociation of information representation within the lateral and medial entorhinal cortex, a brain region with widespread connections to cortical areas. We aimed to expand this idea by examining differential contribution of these two sub-regions to the retrieval of non-spatial and spatial memory. Inactivation of lateral, but not medial regions severely impaired the retrieval of recently and remotely acquired non-spatial memory while spatial memory remained intact. To link functioning of the lateral entorhinal cortex with the known roles of the hippocampus and medial prefrontal cortex for memory retrieval, communication with these two regions was detected as synchronized oscillations in local field potentials. We found that stronger communication between the lateral entorhinal and prefrontal cortex during stimulus-free periods correlated with better memory performance. The lateral entorhinal cortex therefore may serve as a gateway of memory-related information between the medial prefrontal and other cortical regions.

The entorhinal cortex (EC) is a vital structure in the mammalian brain, implicated in the processes of learning and memory, and a possible site for the generation of seizures in temporal lobe epilepsy. Neurones in the EC are constantly bombarded with inhibitory and excitatory neurotransmitter. This background activity is thought to exert significant control on the excitability and function of neurones in cortical networks, with changes in the levels and proportion of background inhibition (IBg) and excitation (EBg) driving rhythmic oscillations in membrane potential, and even underlying the generation of epileptic seizures.

acase@tulane.edu / 1 / Jeremiah Hartner

The entorhinal cortex is reciprocally connected with both neocortical sensory areas and the hippocampal formation, and is thought to play a pivotal role in learning and memory. Changes in synaptic strength are thought to provide the major neurophysiological basis for memory formation, but little is known about synaptic plasticity in the entorhinal cortex. The objectives of this research were to provide a basis for the interpretation of evoked potentials recorded from the entorhinal cortex following pyriform (primary olfactory) cortex stimulation 𝘪𝘯 𝘷𝘪𝘷𝘰, and to determine the conditions under which synaptic enhancements in this pathway may occur and contribute to lasting changes in the processing of olfactory information. The synaptic currents which generate field potentials in the entorhinal cortex following pyriform cortex and medial septal stimulation were first localized to the superficial layers of the entorhinal cortex using current source density analysis techniques in the anesthetized rat. This allowed changes in the strength of these synaptic inputs to be monitored in the awake rat by measuring evoked field potential amplitudes at a single cortical depth. Long-term synaptic potentiation (LTP) in this pathway was reliably induced following stimulation of the pyriform cortex with either epileptogenic stimuli, or with prolonged subconvulsive high-frequency trains. Further, stimulation which results in short-term frequency potentiation effects, was found to increase the amount of LTP induced. Concurrent stimulation of the medial septum at a frequency similar to that of the endogenous theta rhythm also resulted in a cooperative enhancement of the LTP produced. Computational modelling techniques were then used to formalize the heterosynaptic contribution of frequency potentiating medial septal inputs to Hebbian synaptic modification in entorhinal cortex. These results indicate that the frequency of rhythmic activity in sensory afferents and the activity of the medial septum may play critical roles in the regulation of synaptic plasticity in the entorhinal cortex. / Thesis / Doctor of Philosophy (PhD)

The relationship between structure, dynamics, and function of neural networks in nervous systems is still an open question in the neuroscience community. Nevertheless, for certain areas of the mammalian nervous system we do have sufficient data to impose constraints on the organisation of the network structure. One of these areas is the medial entorhinal cortex which contains cells with hexagonally repeating spatial receptive fields, called grid cells. Another intriguing property of entorhinal cortex and other cortical regions is a population oscillatory activity, with frequency in the theta (4-10 Hz) and gamma (30-100 Hz) range. This leads to a question, whether these oscillations are a common circuit mechanism that is functionally relevant and how the oscillatory activity interacts with the computation performed by grid cells. This thesis deals with applying the continuous attractor network theory to modelling of the microcircuit of layer II in the medial entorhinal cortex. Based on recent experimental evidence on connectivity between stellate cells, and fast spiking interneurons, I first develop a two-population spiking attractor network model that is capable of reproducing the activity of a population of grid cells in layer II. The network was implemented with exponential integrate and fire neurons that allowed me to address both the attractor states and the oscillatory activity in this region. Subsequently, I show that the network can produce theta-nested gamma oscillations with properties that are similar to the cross-frequency coupling observed in vivo and in vitro in entorhinal cortex, and that these theta-nested gamma oscillations can co-exist with grid-like receptive fields generated by the network. I also show that the connectivity inspired by anatomical evidence produces a number of directly testable predictions about the firing fields of interneurons in layer II of the medial entorhinal cortex. The excitatory-inhibitory attractor network, together with the theta-nested gamma oscillations, allowed me to explore potential relationships between nested gamma oscillations and grid field computations. I show, by varying the overall level of excitatory and inhibitory synaptic strengths, and levels of noise, in the network, that this relationship is complex, and not easily predictable. Specifically, I show that noise promotes generation of grid firing fields and theta-nested gamma oscillations by the model. I subsequently demonstrate that theta-nested gamma oscillations are dissociable from the grid field computations performed by the network. By changing the relative strengths of interactions between excitatory and inhibitory neurons in the network, the power and frequency of the gamma oscillations changes without disrupting the rate-coded grid field computations. Since grid cells have been suggested to be a part of the spatial cognitive circuit in the brain, these results have potential implications for several cognitive disorders, including autism and schizophrenia, as well as theories that propose a cognitive role for gamma oscillations.

We analyze the spike trains of multiple simultaneously recorded grid cells obtained in di erent conditions, to help determine the role of recurrent network feedback in generating grid responses. An important class of models of grid cell activity is based on low dimensional continuous attractor dynamics arising from recurrent connections within the grid system. A necessary prediction of these models is that the strong recurrent connections force the grid responses of di erent cells to maintain fi xed relative spatial phases over long periods of time, even if the response patterns of each neuron change. The observation that grid cells maintain their relative spatial phase relationships across di erent familiar environments supports the presence of recurrent connections, but does not rule out the possibility that these relationships persist due to feed-forward input. We analyze the stability of pairwise neural correlations for experiments in which the spatial responses of single neurons change over time. The first such experiment involves resizing of a familiar enclosure, with the result that spatial grid responses rescale along the resized dimension. We show that the relative spatial phase of ring between pairs of cells remains stable over time even as the absolute spatial phase of ring in these same cells changes greatly through rescaling. This result is again consistent with recurrent connectivity, but it remains possible that common external sensory cues (e.g. border information arriving from boundary cells) somehow register the rescaled grids of all cells to display the same relative phases as before rescaling. In an attempt to address this, we analyze responses from animals first exposure to novel environments. Grid ring becomes more noisy and the spatial ring pattern expands, then relaxes back to the periodicity seen in familiar enclosures. During the relaxation, external sensory cues are static and thus likely not responsible for the changing grid responses. We show that the constant phase relationships seen across familiar environments are present from first exposure as well. Finally, we illustrate a generative model to predict grid cell spikes. The aim is to obtain the key determinants of grid cell ring, including animal location, velocity modulation, neural adaptation, and recurrent feedback in a Bayesian framework, and thus assess network contributions to grid cell activity. / text

Through the use of chronic experimental animal models, the majority of in vitro investigations of temporal lobe epilepsy have demonstrated enhanced network activity within the subdivisions of the hippocampal formation. However, clinical evidence in combination with in vivo and in vitro studies indicates that structures external to the hippocampus contribute to the genesis of seizure activity. To address the effects of limbic network excitation, I have utilized combined hippocampal---entorhinal cortex brain slices from pilocarpine-treated rats that display chronic seizures. / My investigations have focused upon three structures, the subiculum, entorhinal cortex and the insular cortex. The experiments in the pilocarpine-treated subiculum demonstrated increased network excitability that was attributed to a more positive GABAA receptor mediated inhibitory post-synaptic potential (IPSP) reversal point coupled with a reduced IPSP peak conductance. Utilizing RT-PCR analysis and immunohistochemical staining we observed a decline in K+-Cl- cotransporter mRNA expression and a reduced number of parvalbumin-positive, presumptive inhibitory interneurons. My second project assessed the network hyperexcitability in layer V of the lateral entorhinal cortex. This is the first study to report spontaneous bursting, in the absence of epileptogenic agents, in the epileptic entorhinal cortex. We attributed this level of network excitation to reduced GABAA receptor mediated inhibition and increased synaptic sprouting. In the final project, we extended our slice preparation to include the insular cortex, a structure external to the temporal lobe. Our investigations identified a mechanism of NMDA receptor dependent synaptic bursting that masked GABA A receptor mediated conductances.

In mammals, spatial learning and memory depend on neural processing carried out in the hippocampal formation. Interestingly, extracellular recordings from behaving animals have shown that cells in this region exhibit spatially modulated activity patterns, thus providing insights into the neural activity underlying spatial behaviour. One area within the hippocampal formation, layer II of the medial entorhinal cortex, houses cells that encode a grid-like map of space using a firing rate code. At the same time, oscillatory signals at distinct theta (4–12 Hz) and gamma (30–120 Hz) frequencies are also present in layer II, providing a substrate for a timing code. To understand how layer II of the medial entorhinal cortex produces these outputs I sought to characterise the electrical properties and functional computational architecture of its microcircuitry. The functionality of any neural circuit depends on the electrical properties of its constituent cells. Because the grid cells in layer II are likely to be stellate cells, I used the perforated patch-clamp technique to accurately assess the intrinsic excitable properties of this cell type. Compared to whole-cell recordings, these recordings indicate that some intrinsic properties of stellate cells, such as spike clustering, which is revealed to be robust, are more likely to play a functional role in circuit computation. Conversely, other intrinsic properties, such as spontaneous membrane potential fluctuations, which are confirmed to be insufficiently stable to support reliable interference patterns, are revealed to be less likely than other, more robust electrical properties to play a direct role in circuit function. The characteristic connectivity profiles of different cell types are also critical for circuit function. To investigate cell type-specific connectivity in layer II I used optogenetic stimulation in combination with in vitro electrophysiology to record synaptic activity in different cell types while selectively activating distinct subpopulations of cells with light. Using this method I found that connections between stellate cells are absent or very rare and that communication between stellate cells is instead mediated by strong feedback inhibition from fast-spiking interneurons. Dissecting oscillatory activity in neural circuits may be important for establishing functionally relevant circuit architecture and dynamics but is difficult in vivo. I accomplished this in vitro by recapitulating the interacting theta and gamma rhythms that are observed in vivo with an optogenetic method. I found that locally driving a subset of neurons in the layer II microcircuit at theta frequency with a light stimiulus produced a nested field rhythm at gamma frequency that was also evident as rhythmic inhibition onto stellate cells. Critically, these interacting rhythms closely resembled those recorded from behaving animals. In addition, I found that this thetanested gamma is sufficiently regular to act as a clock-like reference signal, indicating its potential role in implementing a timing code. To functionally dissect the circuit I performed multiple simultaneous whole-cell patch-clamp recordings during circuit activation. These recordings revealed how feedback interactions between stellate cells and fast-spiking interneurons underpin the theta-nested gamma rhythm. Together, these results suggest that feedback inhibition in layer II acts as a common substrate for theta-nested gamma oscillations and possibly also grid firing fields, thereby providing a framework for understanding how computations are carried out in layer II of the medial entorhinal cortex.