February 22, 2019
Focus Program on "Towards Mathematical Modeling of Neurological Disease from Cellular Perspectives"
Alzheimer's Disease/Pharmaceuticals Workshop
May 31-June 1, 2012


Vassilis Cutsuridis, King's College, London
Encoding and retrieval of episodic memories in the animal hippocampus

The hippocampus, one of the most studied brain regions, has been implicated in the encoding and retrieval of episodic memories (declarative and spatial memories). Recent hippocampus research has yielded a wealth of data on network architecture, cell types, the anatomy and membrane properties of pyramidal cells and interneurons, and synaptic plasticity. Understanding the functional roles of the different families of hippocampal neurons in encoding and retrieval of memory patterns, synaptic plasticity and network oscillations poses a great challenge, but also promises deep insights into how the brain stores and recalls memories. Computational models play an instrumental role in providing clues on how these processes may take place. In my talk, I will present two computational models of hippocampal dynamics addressing the issues of memory capacity, recall performance and rate code and phase code in the hippocampus.
Cutsuridis V, Hasselmo M. (2012). GABAergic modulation of gating, timing and theta phase precession of hippocampal neuronal activity during theta oscillations. Hippocampus, DOI: 10.1002/hipo.21002
Cutsuridis V, Graham BP, Cobb S. (2010). Encoding and retrieval in the hippocampal CA1 microcircuit model. Hippocampus, 20(3): 423-446

Barry Greenberg, Toronto Western Research Institute
Hurdles in preclinical in vivo studies for Alzheimer's disease

Abstract: Manifold challenges exist in developing drugs to treat neurological disorders. Issues such as pharmacokinetics of the potential therapeutic compounds, target access, and pharmacodynamic outcomes are frequently overlooked in preclinical development efforts, as are systems biology effects and toxicokinetics. Moreover, it is crucial to understand what the preclinical animal models are actually informing in terms of alignment with the clinical population on which the potential therapeutics will be tested. Mis-alignment animal models with these clinical cohorts likely explain at least some, if not most of the failed clinical trials in Alzheimer’s disease. An iterative discourse between basic and clinical scientists is required to overcome these issues.

Michael E. Hasselmo, Boston University
Physiological properties of entorhinal cortex and a model of Alzheimer's disease supporting treatment with NMDA receptor blockers and muscarinic M4 agonists

The neurofibrillary tangles associated with Alzheimer's disease first appear and attain their highest density in the entorhinal cortex. The identification of molecular pathways involved in Alzheimer's disease does not yet explain this selective sensitivity of the entorhinal cortex. My work focuses on the physiological properties of entorhinal cortex, some of which may be relevant to Alzheimer's disease. I will review modeling on two different levels of function: 1. Models of dynamical mechanisms for generation of single neuron physiological properties, and 2. Models of network dynamics that show a potential mechanism for the initiation and spread of Alzheimer's disease pathology and suggest pharmacological approaches to treatment using NMDA antagonists and muscarinic M4 agonists.

Single neuron recordings reveal grid cells in medial entorhinal cortex, that fire when a rat visits an array of locations in the environment (Moser and Moser, 2008). The spacing and size of firing fields is larger in grid cells recorded in more ventral anatomical locations (Sargolini et al., 2006). Models of grid cells using interference of oscillations predicted that this difference in spacing could arise from differences in the intrinsic oscillation frequency of entorhinal neurons (Burgess, Barry and O'Keefe, 2007). Whole cell patch data from my laboratory shows that neurons have higher frequencies of resonance and membrane potential oscillations in dorsal compared to ventral entorhinal cortex (Giocomo et al., 2007; Giocomo and Hasselmo, 2008), supporting the model. We further tested the role of oscillations by combining the recording of grid cells with inactivation of the medial septum by infusions of muscimol (Brandon et al. 2011). These infusions block theta rhythm oscillations in the entorhinal cortex and are accompanied by a loss of spatial periodicity of grid cell firing, while sparing head direction selectivity of entorhinal neurons. This supports an important role of theta rhythm oscillations in generating the spatially periodic firing of gird cells. Cholinergic modulation reduces resonance frequency of single neurons (Heys et al., 2010), providing a potential mechanism for changes of grid cell firing fields in novel environments. Another variant of the model (Hasselmo, 2008) uses the rhythmic persistent spiking induced in entorhinal cortex by muscarinic acetylcholine receptors (Fransen et al., 2006; Tahvildari et al., 2007). Newer versions of the model utilize network interactions between spiking neurons (Zilli and Hasselmo, 2010) or combine network attractor dynamics with oscillations (Hasselmo and Brandon, 2012).

In older research, I addressed network level models that show an interesting breakdown of function relevant to Alzheimer's disease (Hasselmo, 1994; 1997). In these models, interference between overlapping memories causes runaway synaptic modification of excitatory synapses in the entorhinal cortex and the hippocampus. This model of malignant synaptic growth provides a potential mechanism for the selective distribution of molecular pathology in terms of excessive demands placed on the remodeling of synaptic connections and on axonal transport for redistribution of synaptic resources. This network-level functional breakdown can spread between regions without requiring the transfer of molecular pathology. I will review this phenomenon in models and its potential contribution to molecular, anatomical and behavioral properties of Alzheimer's disease. This model shows how the blockade of NMDA receptors by the drug memantine could slow the spread of the pathology, and suggests that selective M4 receptor agonists could slow progression of pathology via selective presynaptic inhibition of glutamatergic transmission.

Hinke Osinga, University of Auckland
Spike-adding mechanisms in transient bursts

Joint work with: Jakub Nowacki and Krasimira Tsaneva-Atanasova, University of Bristol, UK
We show how tools from dynamical systems can be used to analyse transient bursting behaviour in a simplified five-dimensional excitable neuron model subject to a short current injection. We use one-parameter continuation of the perturbed orbit segments, formulated as a well-posed boundary value problem, to investigate the phenomenon that additional spikes are added to the transient response as a parameter is varied. By exploiting a natural time-scale separation, we obtain insight into the spike-adding mechanism via geometric singular perturbation theory. More specifically, spike adding occurs through a canard-like transition, where the transient response involves unstable sheets of the critical manifold.

Patrick Roberts, Oregon Health and Sciences University
Simulations of Symptomatic Treatments for Alzheimer's Disease

A substantial number of therapeutic drugs for Alzheimer's disease (AD) have failed in late-stage trials, highlighting the translational disconnect with pathology-based animal models. To bridge the gap between preclinical animal models and clinical outcomes, we implemented a conductance-based computational model of cortical circuitry to simulate working memory as a measure for cognitive function. The model was initially calibrated using preclinical data on receptor pharmacology of catecholamine and cholinergic neurotransmitters. The pathology of AD was subsequently implemented as synaptic and neuronal loss and a decrease in cholinergic tone. The model was then calibrated with clinical ADAS-Cog results on acetylcholinesterase inhibitors and 5-HT6 antagonists to improve the model's prediction of clinical outcomes. As an independent validation, we reproduced clinical data for APOE genotypes showing that the ApoE4 genotype reduces the network performance much more in mild cognitive impairment conditions than at later stages of Alzheimer's disease pathology. We use the model to demonstrate differential effect of memantine, an NMDA subunit selective weak inhibitor, in early and late Alzheimer's disease pathology, and show that inhibition of the NMDA receptor NR2C/NR2D subunits located on inhibitory interneurons compensates for the greater excitatory decline observed with pathology. This quantitative systems pharmacology approach is shown to be complementary to traditional animal models, with the potential to assess potential off-target effects, the consequences of pharmacologically active human metabolites, the effect of comedications, and the impact of a small number of well described genotypes.

Horacio Rotstein, New Jersey Institute of Technology
Mechanisms of frequency preference response to oscillatory inputs in reduced neural models

This work is motivated by experimental and theoretical results on medial entorhinal cortex layer II stellate cells (SCs) in which persistent sodium and h-currents have been shown to be responsible for the generation of subthreshold oscillations in the theta frequency band. We use modeling, dynamical systems tools and numerical simulations to investigate the mechanisms underlying the subthreshold frequency response of SCs to oscillatory inputs and their consequences for the selection of preferred frequency responses to oscillatory inputs in both the sub- and supra-threshold voltage regimes. Previous theoretical work has used linear models. We incorporate the role of nonlinearities and time-scale separation between the participating ionic currents present in the model in determining the cell's voltage response to oscillatory inputs. We explain the dynamic mechanisms of attenuation of the voltage response to oscillatory inputs at both low and high-frequencies that give rise to the intermediate, resonant frequency band. These two mechanisms result from qualitatively different constraints on the speed and direction of the trajectory in phase-space imposed by the displacement of the voltage nullcline due to the oscillatory forcing. The nonlinearities present in the model are able to produce an additional amplification of the voltage response and a decrease in the resonant frequency as compared to the corresponding linearized model. Importantly, these nonlinear effects are observable when the time-scales of the voltage and h-current gating variables are well separated and, for constant input amplitudes, decrease as the level of time-scale separation decreases. In the latter cases, the nonlinearites are "ignored" and the voltage response approaches that of the linearized model. For low enough supra-threshold input amplitudes, the sub-threshold resonant frequency is communicated to the spiking regime. However, for higher input amplitudes, the firing frequency has additional peaks at higher frequencies. These patterns are qualitatively different from the analogous ones observed in the corresponding linearized systems. The principles extracted from our results are valid for a more general class of models including other types of ionic currents such as M-currents, and have implications for the response of cells to conductance-based oscillatory inputs.

Gerold Schmitt-Ulms, University of Toronto
Untangling molecular complexity of AD in search for diagnostic markers and disease intervention strategies

The pre-mortem diagnosis of Alzheimer's disease (AD) relies on a combination of cognitive assessment scores, and increasingly draws from advances in brain scanning. At the molecular level, a reduction in soluble Aß combined with an increase in tau protein levels may to this day represent the most reliable biomarkers. While a number of palliative treatments are on the market, to date all attempts to delay progression of the disease have failed. It can be argued that sensitive biomarkers and disease intervention strategies are most likely to emerge from a detailed understanding of the molecular etiology underlying AD. The talk will present vignettes into current AD research activities at the Tanz Centre for Research in Neurodegenerative Diseases which build on this premise. It will provide an overview of recent advances in the understanding of genetic AD risk factors. Using the biology surrounding Aß release and its presumed receptor-mediated toxicity as an example, it will provide insights into the clinical and molecular complexity underlying AD and its emerging relationship to prion diseases. Finally, it will discuss challenges and promising trends for uncovering molecular mechanisms of the disease which may lead to differential diagnostics and disease intervention strategies.

Kaori Takehara-Nishiuchi, University of Toronto
Communication between the entorhinal and medial prefrontal cortices underlying the expression of associative memory

The entorhinal cortex is thought to be the first region affected i n Alzheimer's disease. The region is a part of the medial temporal lobe memo ry system, relaying information between the hippocampus and association area s throughout the neocortex. Damage to the circuits of entorhinal cortex duri ng early stages of Alzheimer's disease is therefore likely to be responsible for the initial development of memory impairments. This talk will present s everal studies that examined how the entorhinal cortex dynamically interacts with the medial prefrontal cortex and hippocampus to support the expression of long-term memories. First, using trace eyeblink conditioning in rats as a model of associative memory, I will show that lateral portions of the ento rhinal cortex play a long-lasting role in memory retrieval, and that this ro le depends on the region's connection with the medial prefrontal cortex. Sec ond, I will present recordings of local field potentials collected from late ral entorhinal and medial prefrontal cortices, as well as from the hippocamp us, suggesting that communication between these regions changes over the cou rse of learning. The results emphasize that the role of the entorhinal corte x in memory depends on its interactions with the hippocampus and other regio ns of neocortex, providing a locus for future attempts to model the neural b asis of memory impairments accompanying Alzheimer’s disease.

Sylvain Williams, McGill University
Very early changes in hippocampal network rhythms before Aß appearance in an Alzheimer mouse model

One of the most important symptoms of Alzheimer's disease is a dramatic reduction in episodic memory, a task dependent on the hippocampus. These symptoms occur usually later in life but the underlying neuronal changes probably developed over decades. There is now more emphasis in the Alzheimer's disease field to find very early biomarkers of the disease so that an effective pharmacological approach may be used to prevent the occurrence of disease or slow down the disease process. There has been suggestion that early alterations of hippocampal networks might lead to perturbations of hippocampal oscillatory activity which are essential for episodic memory. Brain oscillations in the theta (3-12Hz) and gamma frequency bands (30-250Hz) are crucial for supporting normal cognitive and executive functioning. Moreover, it was recently found that the magnitude of the coupling between these two oscillations (or coupling strength) was positively associated with memory in humans and in rats. Therefore, hippocampal oscillations might be altered in the early stage of AD. In this presentation, I will show evidence in a mouse model of AD (CRND8 mice), that high-gamma frequency band (200Hz) becomes uncoupled to theta frequency oscillations in the subiculum, the main output region of the hippocampus. I will show some of the physiological consequences of this uncoupling and suggest how alterations of GABAergic interneurons may be responsible in this process. The results provide indications that theta-gamma uncoupling may be an early biomarker in AD.



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