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

Cells of the rodent medial entorhinal cortex (EC) possess cellular properties hypothesized to underlie the spatially periodic firing behaviors of 'grid cells' (GC) observed in vivo. Computational models have simulated experimental GC data, but a consensus as to what mechanism(s) generate GC properties has not been reached. Using whole cell patch-clamp and computational modeling techniques this thesis investigates resonance, rebound spiking and persistent spiking properties of medial EC cells to test potential mechanisms generating GC firing. The first experiment tested the voltage dependence of resonance frequency in layer II medial EC stellate cells. Some GC models use interference between velocity-controlled oscillators to generate GCs. These interference mechanisms work best with a linear relationship between voltage and resonance frequency. Experimental results showed resonance frequency decreased linearly with membrane potential depolarization, suggesting resonance properties could support the generation of GCs. Resonance appeared in medial EC but not lateral EC consistent with location of GCs. The second experiment tested predictions of a recent network model that generates GCs using medial EC stellate cell resonance and rebound spiking properties. Sinusoidal oscillations superimposed with hyperpolarizing currents were delivered to layer II stellate cells. Results showed that relative to the sinusoid, a limited phase range of hyperpolarizing inputs elicited rebound spikes, and the phase range of rebound spikes was even narrower. Tuning model parameters of the stellate cell population to match experimental rebound spiking properties resulted in GC spatial periodicity, suggesting resonance and rebound spiking are viable mechanisms for GC generation. The third experiment tested whether short duration current inputs can induce persistent firing and afterdepolarization in layer V pyramidal cells. During muscarinic acetylcholine receptor activation 1-2 second long current injections have been shown to induce persistent firing in EC principal cells. Persistent firing may underlie working memory performance and has been used to model GCs. However, input stimuli during working memory and navigation may be much shorter than 1-2 seconds. Data showed that input durations of 10, 50 and 100 ms could elicit persistent firing, and revealed time courses and amplitude of afterdepolarization that could contribute to GC firing or maintenance of working memory.

As both the major input and output of the hippocampal formation, the entorhinal cortex (EC) occupies a pivotal position in the medial temporal lobe. The discovery of grid cells in the medial entorhinal cortex (mEC) has led to this region being widely implicated in spatial information processing. Importantly, the EC is also the first area affected by dementia pathology, with neurons appearing particularly susceptible to degeneration. Despite this, little is known about how pathology affects the functional output of mEC neurons, either in their ability to coordinate firing to produce network oscillations, or to represent information regarding the external environment. This thesis will use electrophysiological techniques to examine how dementia pathology contributes to the breakdown of mEC neuronal networks using the rTg4510 mouse model of tauopathy. The first 2 results chapters will show how the anatomical organisation along the dorso-ventral axis of the mEC has profound influence on the network activity that can be observed both in brain slices and awake-behaving mice. It will further show how deficits in network activity in rTg4510 mice occur differentially across this axis, with dorsal mEC appearing more vulnerable to changes in oscillatory function than ventral. The third results chapter will begin to explore the relationship between global network activity and the external environment, showing that rTg4510 mice display clear deficits in the relationship between oscillation properties and locomotor activity. Finally, the underlying basis for these changes will be examined, through the recording of single-unit activity in these mice. It will show a decreased tendency for mEC neurons to display firing rates modulated by running speed, as well as an almost complete breakdown of grid cell periodicity after periods of tau overexpression. Understanding how dementia pathology produces changes to neuronal function and ultimately cognition is key for understanding and treating the disease. This thesis will therefore provide novel insights into the dysfunction of the EC during dementia pathology.

Despite increasing computer power, the requirement to upscale 3D geological models for dynamic reservoir simulation purposes is likely to remain in many commercial environments. This study established that there is a relationship between sandbody size, cell size and changes to predictions of reservoir production as grids are upscaled. The concept of a cell width to sandbody width ratio (CSWR) was developed to allow the comparison of changes in reservoir performance as grids are upscaled. A case study of the Flounder Field in the Gippsland Basin resulted in the interpretation of three depositional environments in the intra-Latrobe reservoir interval. The sandbody dimensions associated with these depositional environments were used to build a series of 3D geological models. These were upscaled vertically and horizontally to numerous grid cell sizes. Results from over 1400 dynamic models indicate that if the CSWR is kept below 0.3 there will be a strong correlation between the average production from the upscaled grids compared to those of a much finer grid, and there will be less than 10% variation in average total field production. If the CSWR is between 0.3 and 1, there could be up to 30% difference, and once the CSWR exceeds 1.0 there is only a weak relationship between the results from upscaled grids and those of finer grids. As grids are upscaled the morphology of bodies in facies models changes, the distribution of petrophysical properties is attenuated and the structure is smoothed. All these factors result in a simplification of the fluid flow pathways through a model. Significant loss of morphology occurs when cells are upscaled to more than a half the width of the reservoir body being modelled. A simple rule of thumb is established — if the geological features of a model cannot be recognised when looking at a layer in the upscaled grid, the properties of the upscaled grid are unlikely to be similar to those of the original grid and the predictions of dynamic models may vary significantly from those of a finer grid. This understanding of the influence of sandbody size on the behaviour of upscaled dynamic models can be used in the planning stages of a reservoir modelling project. Two simple charts have been created. The first chart is for calculating the approximate number of cells in a model before it is built. The second chart is for comparing the proposed cell size against the CWSR, so that the predicted discrepancy between the ultimate production from the upscaled grid and one with much smaller cells can be assessed. These two charts enhance discussion between all interested disciplines regarding the potential dimensions of both static and upscaled dynamic models during the planning stage of a modelling project, and how that may influence the results of dynamic modelling. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1375309 / Thesis (Ph.D.) - University of Adelaide, Australian School of Petroleum, 2009

Despite increasing computer power, the requirement to upscale 3D geological models for dynamic reservoir simulation purposes is likely to remain in many commercial environments. This study established that there is a relationship between sandbody size, cell size and changes to predictions of reservoir production as grids are upscaled. The concept of a cell width to sandbody width ratio (CSWR) was developed to allow the comparison of changes in reservoir performance as grids are upscaled. A case study of the Flounder Field in the Gippsland Basin resulted in the interpretation of three depositional environments in the intra-Latrobe reservoir interval. The sandbody dimensions associated with these depositional environments were used to build a series of 3D geological models. These were upscaled vertically and horizontally to numerous grid cell sizes. Results from over 1400 dynamic models indicate that if the CSWR is kept below 0.3 there will be a strong correlation between the average production from the upscaled grids compared to those of a much finer grid, and there will be less than 10% variation in average total field production. If the CSWR is between 0.3 and 1, there could be up to 30% difference, and once the CSWR exceeds 1.0 there is only a weak relationship between the results from upscaled grids and those of finer grids. As grids are upscaled the morphology of bodies in facies models changes, the distribution of petrophysical properties is attenuated and the structure is smoothed. All these factors result in a simplification of the fluid flow pathways through a model. Significant loss of morphology occurs when cells are upscaled to more than a half the width of the reservoir body being modelled. A simple rule of thumb is established — if the geological features of a model cannot be recognised when looking at a layer in the upscaled grid, the properties of the upscaled grid are unlikely to be similar to those of the original grid and the predictions of dynamic models may vary significantly from those of a finer grid. This understanding of the influence of sandbody size on the behaviour of upscaled dynamic models can be used in the planning stages of a reservoir modelling project. Two simple charts have been created. The first chart is for calculating the approximate number of cells in a model before it is built. The second chart is for comparing the proposed cell size against the CWSR, so that the predicted discrepancy between the ultimate production from the upscaled grid and one with much smaller cells can be assessed. These two charts enhance discussion between all interested disciplines regarding the potential dimensions of both static and upscaled dynamic models during the planning stage of a modelling project, and how that may influence the results of dynamic modelling. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1375309 / Thesis (Ph.D.) - University of Adelaide, Australian School of Petroleum, 2009

It has been proposed that as animals explore their environment they build and maintain a cognitive map, an internal representation of their surroundings (Tolman, 1948). We tested this hypothesis using a task designed to assess the ability of rats to make a spatial inference (take a novel shortcut)(Roberts et al., 2007). Our findings suggest that rats are unable to make a spontaneous spatial inference. Furthermore, they bear similarities to experiments which have been similarly unable to replicate or support Tolman’s (1948) findings. An inability to take novel shortcuts suggests that rats do not possess a cognitive map (Bennett, 1996). However, we found evidence of alternative learning strategies, such as latent learning (Tolman & Honzik, 1930b) , which suggest that rats may still be building such a representation, although it does not appear they are able to utilise this information to make complex spatial computations. Neurons found in the hippocampus show remarkable spatial modulation of their firing rate and have been suggested as a possible neural substrate for a cognitive map (O'Keefe & Nadel, 1978). However, the firing of these place cells often appears to be modulated by features of an animal’s behaviour (Ainge, Tamosiunaite, et al., 2007; Wood, Dudchenko, Robitsek, & Eichenbaum, 2000). For instance, previous experiments have demonstrated that the firing rate of place fields in the start box of some mazes are predictive of the animal’s final destination (Ainge, Tamosiunaite, et al., 2007; Ferbinteanu & Shapiro, 2003). We sought to understand whether this prospective firing is in fact related to the goal the rat is planning to navigate to or the route the rat is planning to take. Our results provide strong evidence for the latter, suggesting that rats may not be aware of the location of specific goals and may not be aware of their environment in the form of a contiguous map. However, we also found behavioural evidence that rats are aware of specific goal locations, suggesting that place cells in the hippocampus may not be responsible for this representation and that it may reside elsewhere (Hok, Chah, Save, & Poucet, 2013). Unlike their typical activity in an open field, place cells often have multiple place fields in geometrically similar areas of a multicompartment environment (Derdikman et al., 2009; Spiers et al., 2013). For example, Spiers et al. (2013) found that in an environment composed of four parallel compartments, place cells often fired similarly in multiple compartments, despite the active movement of the rat between them. We were able to replicate this phenomenon, furthermore, we were also able to show that if the compartments are arranged in a radial configuration this repetitive firing does not occur as frequently. We suggest that this place field repetition is driven by inputs from Boundary Vector Cells (BVCs) in neighbouring brain regions which are in turn greatly modulated by inputs from the head direction system. This is supported by a novel BVC model of place cell firing which predicts our observed results accurately. If place cells form the neural basis of a cognitive map one would predict spatial learning to be difficult in an environment where repetitive firing is observed frequently (Spiers et al., 2013). We tested this hypothesis by training animals on an odour discrimination task in the maze environments described above. We found that rats trained in the parallel version of the task were significantly impaired when compared to the radial version. These results support the hypothesis that place cells form the neural basis of a cognitive map; in environments where it is difficult to discriminate compartments based on the firing of place cells, rats find it similarly difficult to discriminate these compartments as shown by their behaviour. The experiments reported here are discussed in terms of a cognitive map, the likelihood that such a construct exists and the possibility that place cells form the neural basis of such a representation. Although the results of our experiments could be interpreted as evidence that animals do not possess a cognitive map, ultimately they suggest that animals do have a cognitive map and that place cells form a more than adequate substrate for this representation.

The entorhinal cortex (EC) in the medial temporal lobe plays a critical role in memory formation and is implicated in several neurological diseases including temporal lobe epilepsy and Alzheimer’s disease. Despite the known importance of this brain region, little is known about the normal bioelectrical activity patterns of the EC in awake, behaving primates. In order to develop effective therapies for diseases affecting the EC, we must first understand its normal properties. To contribute to our understanding of the EC, I monitored the activity of individual neurons and populations of neurons in the EC of rhesus macaque monkeys during free-viewing of photographs using electrophysiological techniques. The results of these experiments help to explain how primates can form memories of, and navigate through, the visual world. These experiments revealed neurons in the EC that represent visual space with triangular grid receptive fields and other neurons that prefer to fire near image borders. These properties are similar to those previously described in the rodent EC, but here the neuronal responses relate to viewing of remote space as opposed to representing the physical location of the animal. The representation of visual space may be aided by another EC neuron type that was discovered, free-viewing saccade direction cells, neurons that signaled the direction of upcoming saccades. Such a signal could be used by other cells to prepare to fire according to the future gaze location. Many of these spatially-responsive neurons also represented memory for images, suggesting that they may be useful for associating items with their locations. I also examined the neuronal circuitry of recognition memory for visual stimuli in the EC, and I found that population synchronization within the gamma-band (30-140 Hz) in superficial layers of the EC was modulated by stimulus novelty, while the strength of memory formation modulated gamma-band synchronization in the deep layers and in layer III. Furthermore, the strength of connectivity in the gamma-band between different layers was correlated with the strength of memory formation, with deep to superficial power transfer being correlated with stronger memory formation and superficial to deep transfer correlated with weaker memory formation. These findings support several previous investigations of hippocampal-entorhinal connectivity in the rodent and advance our understanding of the functional circuitry of the medial temporal lobe memory system. Finally, I explored the design of a device that could be used to investigate properties of brain tissue in vitro, potentially aiding in the development of treatments for disorders of the EC and other brain structures. We designed, fabricated, and validated a novel device for long-term maintenance of thick brain slices and 3-dimensional dissociated cell cultures on a perforated multi-electrode array. To date, most electrical recordings of thick tissue preparations have been performed by manually inserting electrode arrays. This work demonstrates a simple and effective solution to this problem by building a culture perfusion chamber around a planar perforated multi-electrode array. By making use of interstitial perfusion, the device maintained the thickness of tissue constructs and improved cellular survival as demonstrated by increased firing rates of perfused slices and 3-D cultures, compared to unperfused controls. To the best of our knowledge, this is the first thick tissue culture device to combine forced interstitial perfusion for long-term tissue maintenance and an integrated multi-electrode array for electrical recording and stimulation.