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.
References
--------------
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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