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% This file was created with JabRef 2.8.1.
% Encoding: UTF-8
@ARTICLE{Aburn_2012,
author = {Matthew J Aburn and C. A. Holmes and James A Roberts and Tjeerd W
Boonstra and Michael Breakspear},
title = {Critical fluctuations in cortical models near instability.},
journal = {Front. Physiol.},
year = {2012},
volume = {3},
pages = {331},
abstract = {Computational studies often proceed from the premise that cortical
dynamics operate in a linearly stable domain, where fluctuations
dissipate quickly and show only short memory. Studies of human electroencephalography
(EEG), however, have shown significant autocorrelation at time lags
on the scale of minutes, indicating the need to consider regimes
where non-linearities influence the dynamics. Statistical properties
such as increased autocorrelation length, increased variance, power
law scaling, and bistable switching have been suggested as generic
indicators of the approach to bifurcation in non-linear dynamical
systems. We study temporal fluctuations in a widely-employed computational
model (the Jansen-Rit model) of cortical activity, examining the
statistical signatures that accompany bifurcations. Approaching supercritical
Hopf bifurcations through tuning of the background excitatory input,
we find a dramatic increase in the autocorrelation length that depends
sensitively on the direction in phase space of the input fluctuations
and hence on which neuronal subpopulation is stochastically perturbed.
Similar dependence on the input direction is found in the distribution
of fluctuation size and duration, which show power law scaling that
extends over four orders of magnitude at the Hopf bifurcation. We
conjecture that the alignment in phase space between the input noise
vector and the center manifold of the Hopf bifurcation is directly
linked to these changes. These results are consistent with the possibility
of statistical indicators of linear instability being detectable
in real EEG time series. However, even in a simple cortical model,
we find that these indicators may not necessarily be visible even
when bifurcations are present because their expression can depend
sensitively on the neuronal pathway of incoming fluctuations.},
doi = {10.3389/fphys.2012.00331},
institution = {School of Mathematics and Physics, The University of Queensland Brisbane,
QLD, Australia.},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pmid = {22952464},
timestamp = {2012.12.18},
url = {http://dx.doi.org/10.3389/fphys.2012.00331}
}
@ARTICLE{Akberdin_2007,
author = {Ilya R Akberdin and Evgeniy A Ozonov and Victoria V Mironova and
Nadezda A Omelyanchuk and Vitaly A Likhoshvai and Dmytry N Gorpinchenko
and Nikolai A Kolchanov},
title = {A cellular automaton to model the development of primary shoot meristems
of Arabidopsis thaliana.},
journal = {J Bioinform Comput Biol},
year = {2007},
volume = {5},
pages = {641--650},
number = {2B},
month = {Apr},
abstract = {Development of organisms is a very complex process in which a lot
of gene networks of different cell types are integrated. Development
of a cellular automaton (Ermentrout and Edelshtein-Keshet, J Theor
Biol 160:97-133, 1993) that models the morphodynamics of different
cell types is the first step in understanding and analysis of the
regulatory mechanisms underlying the functioning of developmental
gene networks. A model of a cellular automaton has been developed,
which simulates the embryonic development of shoot meristem in Arabidopsis
thaliana. The model adequately describes the basic stages in development
of this organ in wild and mutant types.},
institution = {Institute of Cytology and Genetics SB RAS, Lavrentieva ave. 10 Novosibirsk,
630090, Russia. [email protected]},
keywords = {Arabidopsis Proteins, metabolism; Arabidopsis, physiology; Computer
Simulation; Gene Expression Regulation, Developmental, physiology;
Gene Expression Regulation, Plant, physiology; Meristem, physiology;
Models, Biological; Morphogenesis, physiology; Plant Shoots, physiology;
Signal Transduction, physiology},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {S0219720007002862},
pmid = {17636867},
timestamp = {2013.09.04}
}
@ARTICLE{Akil_2011,
author = {Huda Akil and Maryann E Martone and David C Van Essen},
title = {Challenges and opportunities in mining neuroscience data.},
journal = {Science},
year = {2011},
volume = {331},
pages = {708--712},
number = {6018},
month = {Feb},
abstract = {Understanding the brain requires a broad range of approaches and methods
from the domains of biology, psychology, chemistry, physics, and
mathematics. The fundamental challenge is to decipher the "neural
choreography" associated with complex behaviors and functions, including
thoughts, memories, actions, and emotions. This demands the acquisition
and integration of vast amounts of data of many types, at multiple
scales in time and in space. Here we discuss the need for neuroinformatics
approaches to accelerate progress, using several illustrative examples.
The nascent field of "connectomics" aims to comprehensively describe
neuronal connectivity at either a macroscopic level (in long-distance
pathways for the entire brain) or a microscopic level (among axons,
dendrites, and synapses in a small brain region). The Neuroscience
Information Framework (NIF) encompasses all of neuroscience and facilitates
the integration of existing knowledge and databases of many types.
These examples illustrate the opportunities and challenges of data
mining across multiple tiers of neuroscience information and underscore
the need for cultural and infrastructure changes if neuroinformatics
is to fulfill its potential to advance our understanding of the brain.},
doi = {10.1126/science.1199305},
institution = {The Molecular and Behavioral Neuroscience Institute, University of
Michigan, Ann Arbor, MI, USA. [email protected]},
keywords = {Access to Information; Animals; Brain, anatomy /&/ histology/physiology;
Computational Biology; Data Mining; Databases, Factual; Humans; Internet;
Neural Pathways; Neurons, physiology; Neurosciences; Online Systems;
Terminology as Topic},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {331/6018/708},
pmid = {21311009},
timestamp = {2012.12.27},
url = {http://dx.doi.org/10.1126/science.1199305}
}
@ARTICLE{Albada_2010,
author = {S. J. van Albada and C. C. Kerr and A. K I Chiang and C. J. Rennie
and P. A. Robinson},
title = {Neurophysiological changes with age probed by inverse modeling of
EEG spectra.},
journal = {Clin Neurophysiol},
year = {2010},
volume = {121},
pages = {21--38},
number = {1},
month = {Jan},
abstract = {To investigate age-associated changes in physiologically-based EEG
spectral parameters in the healthy population.Eyes-closed EEG spectra
of 1498 healthy subjects aged 6-86 years were fitted to a mean-field
model of thalamocortical dynamics in a cross-sectional study. Parameters
were synaptodendritic rates, cortical wave decay rates, connection
strengths (gains), axonal delays for thalamocortical loops, and power
normalizations. Age trends were approximated using smooth asymptotically
linear functions with a single turning point. We also considered
sex differences and relationships between model parameters and traditional
quantitative EEG measures.The cross-sectional data suggest that changes
tend to be most rapid in childhood, generally leveling off at age
15-20 years. Most gains decrease in magnitude with age, as does power
normalization. Axonal and dendritic delays decrease in childhood
and then increase. Axonal delays and gains show small but significant
sex differences.Mean-field brain modeling allows interpretation of
age-associated EEG trends in terms of physiological processes, including
the growth and regression of white matter, influencing axonal delays,
and the establishment and pruning of synaptic connections, influencing
gains.This study demonstrates the feasibility of inverse modeling
of EEG spectra as a noninvasive method for investigating large-scale
corticothalamic dynamics, and provides a basis for future comparisons.},
doi = {10.1016/j.clinph.2009.09.021},
institution = {School of Physics, The University of Sydney, NSW 2006, Australia.
keywords = {Adolescent; Adult; Aged; Aged, 80 and over; Aging, physiology; Axons;
Cerebral Cortex, physiology; Child; Cross-Sectional Studies; Dendrites;
Electroencephalography; Female; Humans; Male; Middle Aged; Models,
Neurological; Sex Factors; Thalamus, physiology; Time Factors; Young
Adult},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {S1388-2457(09)00571-9},
pmid = {19854102},
timestamp = {2013.08.19},
url = {http://dx.doi.org/10.1016/j.clinph.2009.09.021}
}
@ARTICLE{Albada_2013,
author = {S. J. van Albada and P. A. Robinson},
title = {Relationships between Electroencephalographic Spectral Peaks Across
Frequency Bands.},
journal = {Front Hum Neurosci},
year = {2013},
volume = {7},
pages = {56},
abstract = {The degree to which electroencephalographic spectral peaks are independent,
and the relationships between their frequencies have been debated.
A novel fitting method was used to determine peak parameters in the
range 2-35 Hz from a large sample of eyes-closed spectra, and their
interrelationships were investigated. Findings were compared with
a mean-field model of thalamocortical activity, which predicts near-harmonic
relationships between peaks. The subject set consisted of 1424 healthy
subjects from the Brain Resource International Database. Peaks in
the theta range occurred on average near half the alpha peak frequency,
while peaks in the beta range tended to occur near twice and three
times the alpha peak frequency on an individual-subject basis. Moreover,
for the majority of subjects, alpha peak frequencies were significantly
positively correlated with frequencies of peaks in the theta and
low and high beta ranges. Such a harmonic progression agrees semiquantitatively
with theoretical predictions from the mean-field model. These findings
indicate a common or analogous source for different rhythms, and
help to define appropriate individual frequency bands for peak identification.},
doi = {10.3389/fnhum.2013.00056},
institution = {Institute of Neuroscience and Medicine (INM-6) and Institute for
Advanced Simulation (IAS-6), Jülich Research Centre and Jülich-Aachen
Research Alliance Jülich, Germany ; School of Physics, The University
of Sydney Sydney, NSW, Australia ; Brain Dynamics Center, Sydney
Medical School - Western, University of Sydney Sydney, NSW, Australia.},
language = {eng},
medline-pst = {epublish},
owner = {paula},
pmid = {23483663},
timestamp = {2013.08.19},
url = {http://dx.doi.org/10.3389/fnhum.2013.00056}
}
@ARTICLE{Albada_2009,
author = {S. J. van Albada and P. A. Robinson},
title = {Mean-field modeling of the basal ganglia-thalamocortical system.
I Firing rates in healthy and parkinsonian states.},
journal = {J Theor Biol},
year = {2009},
volume = {257},
pages = {642--663},
number = {4},
month = {Apr},
abstract = {Parkinsonism leads to various electrophysiological changes in the
basal ganglia-thalamocortical system (BGTCS), often including elevated
discharge rates of the subthalamic nucleus (STN) and the output nuclei,
and reduced activity of the globus pallidus external (GPe) segment.
These rate changes have been explained qualitatively in terms of
the direct/indirect pathway model, involving projections of distinct
striatal populations to the output nuclei and GPe. Although these
populations partly overlap, evidence suggests dopamine depletion
differentially affects cortico-striato-pallidal connection strengths
to the two pallidal segments. Dopamine loss may also decrease the
striatal signal-to-noise ratio, reducing both corticostriatal coupling
and striatal firing thresholds. Additionally, nigrostriatal degeneration
may cause secondary changes including weakened lateral inhibition
in the GPe, and mesocortical dopamine loss may decrease intracortical
excitation and especially inhibition. Here a mean-field model of
the BGTCS is presented with structure and parameter estimates closely
based on physiology and anatomy. Changes in model rates due to the
possible effects of dopamine loss listed above are compared with
experiment. Our results suggest that a stronger indirect pathway,
possibly combined with a weakened direct pathway, is compatible with
empirical evidence. However, altered corticostriatal connection strengths
are probably not solely responsible for substantially increased STN
activity often found. A lower STN firing threshold, weaker intracortical
inhibition, and stronger striato-GPe inhibition help explain the
relatively large increase in STN rate. Reduced GPe-GPe inhibition
and a lower GPe firing threshold can account for the comparatively
small decrease in GPe rate frequently observed. Changes in cortex,
GPe, and STN help normalize the cortical rate, also in accord with
experiments. The model integrates the basal ganglia into a unified
framework along with an existing thalamocortical model that already
accounts for a wide range of electrophysiological phenomena. A companion
paper discusses the dynamics and oscillations of this combined system.},
doi = {10.1016/j.jtbi.2008.12.018},
institution = {School of Physics, The University of Sydney, New South Wales 2006,
Australia. [email protected]},
keywords = {Adult; Animals; Basal Ganglia, physiology/physiopathology; Cerebral
Cortex, physiology/physiopathology; Humans; Models, Neurological;
Neural Inhibition, physiology; Neural Pathways, physiology; Parkinsonian
Disorders, physiopathology; Subthalamic Nucleus, physiology/physiopathology;
Thalamus, physiology/physiopathology},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {S0022-5193(08)00648-6},
pmid = {19168074},
timestamp = {2013.08.19},
url = {http://dx.doi.org/10.1016/j.jtbi.2008.12.018}
}
@ARTICLE{Amari_1977,
author = {Amari, SI},
title = {Dynamics of pattern formation in lateral-inhibition type neural fields.},
journal = {Biol. Cybern.},
year = {1977},
volume = {22},
pages = {77-87},
keywords = {dynamics},
owner = {paula},
timestamp = {2012.10.18}
}
@ARTICLE{Amari_1975,
author = {Amari, SI},
title = {Homogeneous nets of neuron-like elements.},
journal = {Biol. Cybern.},
year = {1975},
volume = {17},
pages = {211--220},
number = {4},
month = mar,
abstract = {{Abstract\ \ Propagation and reverberation of excitation
patterns are investigated for 1-dimensional and 2-dimensional homogeneous
nets of neuron-like elements. A 1-dimensional net has a proper set
of excitation patterns which only can be conducted in the net. Such
a net has an ability of discriminating and shaping stimulus signals.
Two types of self-reproducing reverberatory excitation patterns are
shown for 2-dimensional homogeneous nets. An algebraic theory of
general homogeneous nets is also developed.}},
citeulike-article-id = {5813013},
citeulike-linkout-0 = {http://dx.doi.org/10.1007/bf00339367},
citeulike-linkout-1 = {http://www.springerlink.com/content/e0v5x54827165122},
day = {27},
doi = {10.1007/bf00339367},
keywords = {bump, neural\_field},
posted-at = {2009-09-21 13:15:42},
priority = {2},
url = {http://dx.doi.org/10.1007/bf00339367}
}
@ARTICLE{Amunts_2013,
author = {Katrin Amunts and Claude Lepage and Louis Borgeat and Hartmut Mohlberg
and Timo Dickscheid and Marc-Étienne Rousseau and Sebastian Bludau
and Pierre-Louis Bazin and Lindsay B Lewis and Ana-Maria Oros-Peusquens
and Nadim J Shah and Thomas Lippert and Karl Zilles and Alan C Evans},
title = {BigBrain: an ultrahigh-resolution 3D human brain model.},
journal = {Science},
year = {2013},
volume = {340},
pages = {1472--1475},
number = {6139},
month = {Jun},
abstract = {Reference brains are indispensable tools in human brain mapping, enabling
integration of multimodal data into an anatomically realistic standard
space. Available reference brains, however, are restricted to the
macroscopic scale and do not provide information on the functionally
important microscopic dimension. We created an ultrahigh-resolution
three-dimensional (3D) model of a human brain at nearly cellular
resolution of 20 micrometers, based on the reconstruction of 7404
histological sections. "BigBrain" is a free, publicly available tool
that provides considerable neuroanatomical insight into the human
brain, thereby allowing the extraction of microscopic data for modeling
and simulation. BigBrain enables testing of hypotheses on optimal
path lengths between interconnected cortical regions or on spatial
organization of genetic patterning, redefining the traditional neuroanatomy
maps such as those of Brodmann and von Economo.},
doi = {10.1126/science.1235381},
institution = {Institute of Neuroscience and Medicine (INM-1, INM-4), Research Centre
Jülich, Jülich, Germany. [email protected]},
keywords = {Aged; Brain Mapping; Brain, anatomy /&/ histology/cytology; Cerebral
Cortex, anatomy /&/ histology/cytology; Female; Humans; Image Processing,
Computer-Assisted; Imaging, Three-Dimensional; Magnetic Resonance
Imaging; Microtomy},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {340/6139/1472},
pmid = {23788795},
timestamp = {2013.07.04},
url = {http://dx.doi.org/10.1126/science.1235381}
}
@ARTICLE{Aquino_2012,
author = {Kevin M Aquino and Mark M Schira and P. A. Robinson and Peter M Drysdale
and Michael Breakspear},
title = {Hemodynamic traveling waves in human visual cortex.},
journal = {PLoS Comput. Biol.},
year = {2012},
volume = {8},
pages = {e1002435},
number = {3},
abstract = {Functional MRI (fMRI) experiments rely on precise characterization
of the blood oxygen level dependent (BOLD) signal. As the spatial
resolution of fMRI reaches the sub-millimeter range, the need for
quantitative modelling of spatiotemporal properties of this hemodynamic
signal has become pressing. Here, we find that a detailed physiologically-based
model of spatiotemporal BOLD responses predicts traveling waves with
velocities and spatial ranges in empirically observable ranges. Two
measurable parameters, related to physiology, characterize these
waves: wave velocity and damping rate. To test these predictions,
high-resolution fMRI data are acquired from subjects viewing discrete
visual stimuli. Predictions and experiment show strong agreement,
in particular confirming BOLD waves propagating for at least 5-10
mm across the cortical surface at speeds of 2-12 mm s-1. These observations
enable fundamentally new approaches to fMRI analysis, crucial for
fMRI data acquired at high spatial resolution.},
doi = {10.1371/journal.pcbi.1002435},
institution = {School of Physics, University of Sydney, New South Wales, Australia.
keywords = {Biological Clocks, physiology; Blood Flow Velocity, physiology; Cerebrovascular
Circulation, physiology; Computer Simulation; Humans; Magnetic Resonance
Imaging, methods; Models, Cardiovascular; Models, Neurological; Visual
Cortex, physiology; Visual Perception, physiology},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {PCOMPBIOL-D-11-01560},
pmid = {22457612},
timestamp = {2013.02.18},
url = {http://dx.doi.org/10.1371/journal.pcbi.1002435}
}
@ARTICLE{Assisi_2005,
author = {Assisi, CG and Jirsa, VK and Kelso, JAS},
title = {Synchrony and clustering in heterogeneous networks with global coupling
and parameter dispersion},
journal = {Phys. Rev. Lett.},
year = {2005},
volume = {94},
pages = {94},
number = {1},
owner = {paula},
timestamp = {2012.10.18}
}
@ARTICLE{Attay_2006,
author = {Atay, F. and Hutt, A.},
title = {Neural Fields with Distributed Transmission Speeds and Long Range
Feedback Delays},
journal = {SIAD},
year = {2006},
volume = {5},
pages = {670-698},
number = {4},
doi = {10.1137/050629367},
eprint = {http://epubs.siam.org/doi/pdf/10.1137/050629367},
url = {http://epubs.siam.org/doi/abs/10.1137/050629367}
}
@ARTICLE{Attay_2005,
author = {Atay, F. and Hutt, A.},
title = {Stability and Bifurcations in Neural Fields with Finite Propagation
Speed and General Connectivity},
journal = {SIAP},
year = {2005},
volume = {65},
pages = {644-666},
abstract = {Linear bifurcation analysis for IDEs for general connectivities involving
large but finite propagation speeds, comparison of analytical results
to numerical results, graphical criterion for phase transitions by
Fourier components of connectivity function},
comment = {SIAM Journal on Applied Mathematics (SIAP)},
owner = {paupau},
timestamp = {2013.05.01}
}
@ARTICLE{Axer_2011a,
author = {Markus Axer and Katrin Amunts and David Grässel and Christoph Palm
and Jürgen Dammers and Hubertus Axer and Uwe Pietrzyk and Karl Zilles},
title = {A novel approach to the human connectome: ultra-high resolution mapping
of fiber tracts in the brain.},
journal = {Neuroimage},
year = {2011},
volume = {54},
pages = {1091--1101},
number = {2},
month = {Jan},
abstract = {Signal transmission between different brain regions requires connecting
fiber tracts, the structural basis of the human connectome. In contrast
to animal brains, where a multitude of tract tracing methods can
be used, magnetic resonance (MR)-based diffusion imaging is presently
the only promising approach to study fiber tracts between specific
human brain regions. However, this procedure has various inherent
restrictions caused by its relatively low spatial resolution. Here,
we introduce 3D-polarized light imaging (3D-PLI) to map the three-dimensional
course of fiber tracts in the human brain with a resolution at a
submillimeter scale based on a voxel size of 100 μm isotropic or
less. 3D-PLI demonstrates nerve fibers by utilizing their intrinsic
birefringence of myelin sheaths surrounding axons. This optical method
enables the demonstration of 3D fiber orientations in serial microtome
sections of entire human brains. Examples for the feasibility of
this novel approach are given here. 3D-PLI enables the study of brain
regions of intense fiber crossing in unprecedented detail, and provides
an independent evaluation of fiber tracts derived from diffusion
imaging data.},
doi = {10.1016/j.neuroimage.2010.08.075},
institution = {Institute of Neuroscience and Medicine (INM-1, INM-2, INM-4), Research
Centre Jülich, Jülich, Germany. [email protected]},
keywords = {Birefringence; Brain Mapping, methods; Brain, ultrastructure; Humans;
Image Processing, Computer-Assisted, methods; Imaging, Three-Dimensional,
methods; Nerve Fibers, ultrastructure; Neural Pathways, anatomy /&/
histology},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {S1053-8119(10)01178-X},
pmid = {20832489},
timestamp = {2013.07.04},
url = {http://dx.doi.org/10.1016/j.neuroimage.2010.08.075}
}
@ARTICLE{Axer_2011,
author = {Markus Axer and David Grässel and Melanie Kleiner and Jürgen Dammers
and Timo Dickscheid and Julia Reckfort and Tim Hütz and Björn Eiben
and Uwe Pietrzyk and Karl Zilles and Katrin Amunts},
title = {High-resolution fiber tract reconstruction in the human brain by
means of three-dimensional polarized light imaging.},
journal = {Front Neuroinform},
year = {2011},
volume = {5},
pages = {34},
abstract = {Functional interactions between different brain regions require connecting
fiber tracts, the structural basis of the human connectome. To assemble
a comprehensive structural understanding of neural network elements
from the microscopic to the macroscopic dimensions, a multimodal
and multiscale approach has to be envisaged. However, the integration
of results from complementary neuroimaging techniques poses a particular
challenge. In this paper, we describe a steadily evolving neuroimaging
technique referred to as three-dimensional polarized light imaging
(3D-PLI). It is based on the birefringence of the myelin sheaths
surrounding axons, and enables the high-resolution analysis of myelinated
axons constituting the fiber tracts. 3D-PLI provides the mapping
of spatial fiber architecture in the postmortem human brain at a
sub-millimeter resolution, i.e., at the mesoscale. The fundamental
data structure gained by 3D-PLI is a comprehensive 3D vector field
description of fibers and fiber tract orientations - the basis for
subsequent tractography. To demonstrate how 3D-PLI can contribute
to unravel and assemble the human connectome, a multiscale approach
with the same technology was pursued. Two complementary state-of-the-art
polarimeters providing different sampling grids (pixel sizes of 100
and 1.6 μm) were used. To exemplarily highlight the potential of
this approach, fiber orientation maps and 3D fiber models were reconstructed
in selected regions of the brain (e.g., Corpus callosum, Internal
capsule, Pons). The results demonstrate that 3D-PLI is an ideal tool
to serve as an interface between the microscopic and macroscopic
levels of organization of the human connectome.},
doi = {10.3389/fninf.2011.00034},
institution = {Institute of Neuroscience and Medicine (INM-1, INM-2, INM-4), Research
Centre Jülich and Jülich Aachen Research Alliance Jülich, Germany.},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pmid = {22232597},
timestamp = {2013.07.04},
url = {http://dx.doi.org/10.3389/fninf.2011.00034}
}
@ARTICLE{Baars_2012,
author = {Bernard J Baars and David B Edelman},
title = {Consciousness, biology and quantum hypotheses.},
journal = {Phys. Life. Rev.},
year = {2012},
volume = {9},
pages = {285--294},
number = {3},
month = {Sep},
abstract = {Natural phenomena are reducible to quantum events in principle, but
quantum mechanics does not always provide the best level of analysis.
The many-body problem, chaotic avalanches, materials properties,
biological organisms, and weather systems are better addressed at
higher levels. Animals are highly organized, goal-directed, adaptive,
selectionist, information-preserving, functionally redundant, multicellular,
quasi-autonomous, highly mobile, reproducing, dissipative systems
that conserve many fundamental features over remarkably long periods
of time at the species level. Animal brains consist of massive, layered
networks of specialized signaling cells with 10,000 communication
points per cell, and interacting up to 1000 Hz. Neurons begin to
divide and differentiate very early in gestation, and continue to
develop until middle age. Waking brains operate far from thermodynamic
equilibrium under delicate homeostatic control, making them extremely
sensitive to a range of physical and chemical stimuli, highly adaptive,
and able to produce a remarkable range of goal-relevant actions.
Consciousness is "a difference that makes a difference" at the level
of massive neuronal interactions in the most parallel-interactive
anatomical structure of the mammalian brain, the cortico-thalamic
(C-T) system. Other brain structures are not established to result
in direct conscious experiences, at least in humans. However, indirect
extra-cortical influences on the C-T system are pervasive. Learning,
brain plasticity and major life adaptations may require conscious
cognition. While brains evolved over hundreds of millions of years,
and individual brains grow over months, years and decades, conscious
events appear to have a duty cycle of ∼100 ms, fading after a few
seconds. They can of course be refreshed by inner rehearsal, re-visualization,
or attending to recurrent stimulus sources. These very distinctive
brain events are needed when animals seek out and cope with new,
unpredictable and highly valued life events, such as evading predators,
gathering critical information, seeking mates and hunting prey. Attentional
selection of conscious events can be observed behaviorally in animals
showing coordinated receptor orienting, flexible responding, alertness,
emotional reactions, seeking, motivation and curiosity, as well as
behavioral surprise and cortical and autonomic arousal. Brain events
corresponding to attentional selection are prominent and widespread.
Attention generally results in conscious experiences, which may be
needed to recruit widespread processing resources in the brain. Many
neuronal processes never become conscious, such as the balance system
of the inner ear. An air traveler may "see" the passenger cabin tilt
downward as the plane tilts to descend for a landing. That visual
experience occurs even at night, when the traveler has no external
frame of spatial reference. The passenger's body tilt with respect
to gravity is detected unconsciously via the hair cells of the vestibular
canals, which act as liquid accelerometers. However, that sensory
activity is not experienced directly. It only becomes conscious via
vision and the body senses. The vestibular sense is therefore quite
different from visual perception, which "reports" accurately to a
conscious field of experience, so that we can point accurately to
a bright star on a dark night. Vestibular input is also precise but
unconscious. Conscious cognition is therefore a distinct kind of
brain event. Many of its features are well established, and must
be accounted for by any adequate theory. No non-biological examples
are known. Penrose and Hameroff have proposed that consciousness
may be viewed as a fundamental problem in quantum physics. Specifically,
their 'orchestrated objective reduction' (Orch-OR) hypothesis posits
that conscious states arise from quantum computations in the microtubules
of neurons. However, a number of microtubule-associated proteins
are found in both plant and animal cells (like neurons) and plants
are not generally considered to be conscious. Current quantum-level
proposals do not explain the prominent empirical features of consciousness.
Notably, they do not distinguish between closely matched conscious
and unconscious brain events, as cognitive-biological theories must.
About half of the human brain does not support conscious contents
directly, yet neurons in these "unconscious" brain regions contain
large numbers of microtubules. QM phenomena are famously observer-dependent,
but to the best of our knowledge it has not been shown that they
require a conscious observer, as opposed to a particle detector.
Conscious humans cannot detect quantum events "as such" without the
aid of special instrumentation. Instead, we categorize the wavelengths
of light into conscious sensory events that neglect their quantum
mechanical properties. In science the burden of proof is on the proposer,
and this burden has not yet been met by quantum-level proposals.
While in the future we may discover quantum effects that bear distinctively
on conscious cognition 'as such,' we do not have such evidence today.},
doi = {10.1016/j.plrev.2012.07.001},
institution = {The Neurosciences Institute, San Diego, CA 92121, United States.
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {S1571-0645(12)00084-X},
pmid = {22925839},
timestamp = {2013.03.05},
url = {http://dx.doi.org/10.1016/j.plrev.2012.07.001}
}
@ARTICLE{Babajani_2005,
author = {Babajani, Abbas and Nekooei, Mohammad-Hossein and Soltanian-Zadeh,
Hamid},
title = {Integrated MEG and fMRI model: synthesis and analysis.},
journal = {Brain Topogr.},
year = {2005},
volume = {18},
pages = {101--113},
number = {2},
abstract = {An integrated model for magnetoencephalography (MEG) and functional
Magnetic Resonance Imaging (fMRI) is proposed. In the model, the
neural activity is related to the Post Synaptic Potentials (PSPs)
which is common link between MEG and fMRI. Each PSP is modeled by
the direction and strength of its current flow which are treated
as random variables. The overall neural activity in each voxel is
used for equivalent current dipole in MEG and as input of extended
Balloon model in fMRI. The proposed model shows the possibility of
detecting activation by fMRI in a voxel while the voxel is silent
for MEG and vice versa. Parameters of the model can illustrate situations
like closed field due to non-pyramidal cells, canceling effect of
inhibitory PSP on excitatory PSP, and effect of synchronicity. In
addition, the model shows that the crosstalk from neural activities
of the adjacent voxels in fMRI may result in the detection of activations
in these voxels that contain no neural activities. The proposed model
is instrumental in evaluating and comparing different analysis methods
of MEG and fMRI. It is also useful in characterizing the upcoming
combined methods for simultaneous analysis of MEG and fMRI.},
doi = {10.1007/s10548-005-0279-5},
institution = {Control and Intelligent Processing Center of Excellence, Electrical
and Computer Engineering Department, University of Tehran, Tehran,
Iran.},
keywords = {Algorithms; Excitatory Postsynaptic Potentials, physiology; Humans;
Image Processing, Computer-Assisted, statistics /&/ numerical data;
Linear Models; Magnetic Resonance Imaging, statistics /&/ numerical
data; Magnetoencephalography, statistics /&/ numerical data; Models,
Statistical; Oxygen, blood},
language = {eng},
medline-pst = {ppublish},
owner = {paupau},
pmid = {16341578},
timestamp = {2013.04.09},
url = {http://dx.doi.org/10.1007/s10548-005-0279-5}
}
@ARTICLE{Babajani_2006,
author = {Babajani, Abbas and Soltanian-Zadeh, Hamid},
title = {Integrated MEG/EEG and fMRI model based on neural masses.},
journal = {IEEE Trans. Biomed. Eng.},
year = {2006},
volume = {53},
pages = {1794--1801},
number = {9},
month = {Sep},
abstract = {We introduce a bottom-up model for integrating electroencephalography
(EEG) or magnetoencephalography (MEG) with functional magnetic resonance
imaging (fMRI). An extended neural mass model is proposed based on
the physiological principles of cortical minicolumns and their connections.
The fMRI signal is extracted from the proposed neural mass model
by introducing a relationship between the stimulus and the neural
activity and using the resultant neural activity as input of the
extended Balloon model. The proposed model, validated using simulations,
is instrumental in evaluating the upcoming combined methods for simultaneous
analysis of MEG/EEG and fMRI.},
doi = {10.1109/TBME.2006.873748},
institution = {Control and Intelligent Processing Center of Excellence, Electrical
and Computer Engineering Department, University of Tehran, Iran.
keywords = {Algorithms; Brain Mapping, methods; Brain, physiology; Computer Simulation;
Diagnosis, Computer-Assisted, methods; Electroencephalography, methods;
Evoked Potentials, physiology; Humans; Magnetic Resonance Imaging,
methods; Magnetoencephalography, methods; Models, Neurological; Nerve
Net, physiology; Systems Integration},
language = {eng},
medline-pst = {ppublish},
owner = {paupau},
pmid = {16941835},
timestamp = {2013.04.09},
url = {http://dx.doi.org/10.1109/TBME.2006.873748}
}
@ARTICLE{Babajani_2012,
author = {Babajani, Gholamreza and Tropak, Michael B. and Mahuran, Don J. and
Kermode, Allison R.},
title = {Pharmacological chaperones facilitate the post-ER transport of recombinant
N370S mutant β-glucocerebrosidase in plant cells: evidence that N370S
is a folding mutant.},
journal = {Mol. Genet. Metab.},
year = {2012},
volume = {106},
pages = {323--329},
number = {3},
month = {Jul},
abstract = {Gaucher disease is a prevalent lysosomal storage disease in which
affected individuals inherit mutations in the gene (GBA1) encoding
lysosomal acid β-glucosidase (glucocerebrosidase, GCase, EC 3.2.1.45).
One of the most prevalent disease-causing mutations in humans is
a N370S missense mutation in the GCase protein. As part of a larger
endeavor to study the fate of mutant human proteins expressed in
plant cells, the N370S mutant protein along with the wild-type- (WT)-GCase,
both equipped with a signal peptide, were synthesized in transgenic
tobacco BY2 cells, which do not possess lysosomes. The enzymatic
activity of plant-recombinant N370S GCase lines was significantly
lower (by 81-95\%) than that of the WT-GCase lines. In contrast to
the WT-GCase protein, which was efficiently secreted from tobacco
BY2 cells, and detected in large amounts in the culture medium, only
a small proportion of the N370S GCase was secreted. Pharmacological
chaperones such as N-(n-nonyl) deoxynojirimycin and ambroxol increased
the steady-state mutant protein levels both inside the plant cells
and in the culture medium. These findings contradict the assertion
that small molecule chaperones increase N370S GCase activity (as
assayed in treated patient cell lysates) by stabilizing the enzyme
in the lysosome, and suggest that the mutant protein is impaired
in its ability to obtain its functional folded conformation, which
is a requirement for exiting the lumen of the ER.},
doi = {10.1016/j.ymgme.2012.04.018},
institution = {Department of Biological Sciences, Simon Fraser University, 8888
University Dr., Burnaby, BC, Canada V5A 1S6.},
keywords = {Biological Transport; Catalytic Domain; Cells, Cultured; Endoplasmic
Reticulum, metabolism; Gaucher Disease, enzymology/genetics; Glucosylceramidase,
genetics/metabolism; Humans; Molecular Chaperones, genetics/metabolism;
Mutation; Plant Cells, metabolism; Plants, Genetically Modified;
Protein Folding; Recombinant Proteins, genetics/metabolism},
language = {eng},
medline-pst = {ppublish},
owner = {paupau},
pii = {S1096-7192(12)00161-8},
pmid = {22592100},
timestamp = {2013.04.09},
url = {http://dx.doi.org/10.1016/j.ymgme.2012.04.018}
}
@ARTICLE{Babajani_2010,
author = {Babajani-Feremi, Abbas and Soltanian-Zadeh, Hamid},
title = {Multi-area neural mass modeling of EEG and MEG signals.},
journal = {Neuroimage},
year = {2010},
volume = {52},
pages = {793--811},
number = {3},
month = {Sep},
abstract = {We previously proposed an integrated electroencephalography (EEG),
magnetoencephalography (MEG), and functional Magnetic Resonance Imaging
(fMRI) model based on an extended neural mass model (ENMM) within
a single cortical area. In the ENMM, a cortical area contains several
minicolumns where strengths of their connections diminish exponentially
with their distances. The ENMM was derived based on the physiological
principles of the cortical minicolumns and their connections within
a single cortical area to generate EEG, MEG, and fMRI signals. The
purpose of this paper is to further extend the ENMM model from a
single-area to a multi-area model to develop a neural mass model
of the entire brain that generates EEG and MEG signals. For multi-area
modeling, two connection types are considered: short-range connections
(SRCs) and long-range connections (LRCs). The intra-area SRCs among
the minicolumns within the areas were previously modeled in the ENMM.
To define inter-area LRCs among the cortical areas, we consider that
the cell populations of all minicolumns in the destination area are
affected by the excitatory afferent of the pyramidal cells of all
minicolumns in the source area. The state-space representation of
the multi-area model is derived considering the intra-minicolumn,
SRCs', and LRCs' parameters. Using simulations, we evaluate effects
of parameters of the model on its dynamics and, based on stability
analysis, find valid ranges for parameters of the model. In addition,
we evaluate reducing redundancy of the model parameters using simulation
results and conclude that the parameters of the model can be limited
to the LRCs and SRCs while the intra-minicolumn parameters stay at
their physiological mean values. The proposed multi-area integrated
E/MEG model provides an efficient neuroimaging technique for effective
connectivity analysis in healthy subjects as well as neurological
and psychiatric patients.},
doi = {10.1016/j.neuroimage.2010.01.034},
institution = {Image Analysis Lab., Radiology Department, Henry Ford Hospital, One
Ford Place, 2F, Detroit, MI 48202, USA. [email protected]},
keywords = {Brain Mapping, methods; Brain, physiology; Electroencephalography;
Humans; Magnetic Resonance Imaging; Magnetoencephalography; Models,
Neurological; Nerve Net},
language = {eng},
medline-pst = {ppublish},
owner = {paupau},
pii = {S1053-8119(10)00054-6},
pmid = {20080193},
timestamp = {2013.04.14},
url = {http://dx.doi.org/10.1016/j.neuroimage.2010.01.034}
}
@ARTICLE{Bakker_2012,
author = {Rembrandt Bakker and Thomas Wachtler and Markus Diesmann},
title = {CoCoMac 2.0 and the future of tract-tracing databases.},
journal = {Front. Neuroinform.},
year = {2012},
volume = {6},
pages = {30},
abstract = {The CoCoMac database contains the results of several hundred published
axonal tract-tracing studies in the macaque monkey brain. The combined
results are used for constructing the macaque macro-connectome. Here
we discuss the redevelopment of CoCoMac and compare it to six connectome-related
projects: two online resources that provide full access to raw tracing
data in rodents, a connectome viewer for advanced 3D graphics, a
partial but highly detailed rat connectome, a brain data management
system that generates custom connectivity matrices, and a software
package that covers the complete pipeline from connectivity data
to large-scale brain simulations. The second edition of CoCoMac features
many enhancements over the original. For example, a search wizard
is provided for full access to all tables and their nested dependencies.
Connectivity matrices can be computed on demand in a user-selected
nomenclature. A new data entry system is available as a preview,
and is to become a generic solution for community-driven data entry
in manually collated databases. We conclude with the question whether
neuronal tracing will remain the gold standard to uncover the wiring
of brains, thereby highlighting developments in human connectome
construction, tracer substances, polarized light imaging, and serial
block-face scanning electron microscopy.},
doi = {10.3389/fninf.2012.00030},
institution = {Donders Institute for Brain, Cognition and Behaviour, Radboud University
Nijmegen Nijmegen, Netherlands ; Institute of Neuroscience and Medicine
6, Research Center Jülich Jülich, Germany ; Department Biology II,
Ludwig-Maximilians-Universität München Munich, Germany.},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pmid = {23293600},
timestamp = {2013.02.18},
url = {http://dx.doi.org/10.3389/fninf.2012.00030}
}
@ARTICLE{Bangera_2010,
author = {Nitin B Bangera and Donald L Schomer and Nima Dehghani and Istvan
Ulbert and Sydney Cash and Steve Papavasiliou and Solomon R Eisenberg
and Anders M Dale and Eric Halgren},
title = {Experimental validation of the influence of white matter anisotropy
on the intracranial EEG forward solution.},
journal = {J. Comput. Neurosci.},
year = {2010},
volume = {29},
pages = {371--387},
number = {3},
month = {Dec},
abstract = {Forward solutions with different levels of complexity are employed
for localization of current generators, which are responsible for
the electric and magnetic fields measured from the human brain. The
influence of brain anisotropy on the forward solution is poorly understood.
The goal of this study is to validate an anisotropic model for the
intracranial electric forward solution by comparing with the directly
measured 'gold standard'. Dipolar sources are created at known locations
in the brain and intracranial electroencephalogram (EEG) is recorded
simultaneously. Isotropic models with increasing level of complexity
are generated along with anisotropic models based on Diffusion tensor
imaging (DTI). A Finite Element Method based forward solution is
calculated and validated using the measured data. Major findings
are (1) An anisotropic model with a linear scaling between the eigenvalues
of the electrical conductivity tensor and water self-diffusion tensor
in brain tissue is validated. The greatest improvement was obtained
when the stimulation site is close to a region of high anisotropy.
The model with a global anisotropic ratio of 10:1 between the eigenvalues
(parallel: tangential to the fiber direction) has the worst performance
of all the anisotropic models. (2) Inclusion of cerebrospinal fluid
as well as brain anisotropy in the forward model is necessary for
an accurate description of the electric field inside the skull. The
results indicate that an anisotropic model based on the DTI can be
constructed non-invasively and shows an improved performance when
compared to the isotropic models for the calculation of the intracranial
EEG forward solution.},
doi = {10.1007/s10827-009-0205-z},
institution = {Department of Biomedical Engineering, Boston University, Boston,
MA, USA. [email protected]},
keywords = {Algorithms; Anisotropy; Brain, physiology; Cerebrospinal Fluid, physiology;
Data Interpretation, Statistical; Diffusion Magnetic Resonance Imaging;
Electric Conductivity; Electrodes; Electroencephalography, statistics
/&/ numerical data; Finite Element Analysis; Head; Humans; Image
Processing, Computer-Assisted; Linear Models; Models, Neurological;
Reproducibility of Results; Skull, anatomy /&/ histology},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pmid = {20063051},
timestamp = {2013.04.17},
url = {http://dx.doi.org/10.1007/s10827-009-0205-z}
}
@ARTICLE{Barnard_1967,
author = {Barnard, ACL and Duck, IM and Lynn, MS and Timlake, WP},
title = {The Application of Electromagnetic Theory to Electrocardiology::
II. Numerical Solution of the Integral Equations},
journal = {Biophys. J.},
year = {1967},
volume = {7},
pages = {463--491},
number = {5},
doi = {10.1016/S0006-3495(67)86599-8},
issn = {0006-3495},
publisher = {Elsevier}
}
@ARTICLE{Bastiani_2012,
author = {Matteo Bastiani and Nadim Jon Shah and Rainer Goebel and Alard Roebroeck},
title = {Human cortical connectome reconstruction from diffusion weighted
MRI: the effect of tractography algorithm.},
journal = {Neuroimage},
year = {2012},
volume = {62},
pages = {1732--1749},
number = {3},
month = {Sep},
abstract = {Reconstructing the macroscopic human cortical connectome by Diffusion
Weighted Imaging (DWI) is a challenging research topic that has recently
gained a lot of attention. In the present work, we investigate the
effects of intra-voxel fiber direction modeling and tractography
algorithm on derived structural network indices (e.g. density, small-worldness
and global efficiency). The investigation is centered on three semi-independent
distinctions within the large set of available diffusion models and
tractography methods: i) single fiber direction versus multiple directions
in the intra-voxel diffusion model, ii) deterministic versus probabilistic
tractography and iii) local versus global measure-of-fit of the reconstructed
fiber trajectories. The effect of algorithm and parameter choice
has two components. First, there is the large effect of tractography
algorithm and parameters on global network density, which is known
to strongly affect graph indices. Second, and more importantly, there
are remaining effects on graph indices which range in the tens of
percent even when global density is controlled for. This is crucial
for the sensitivity of any human structural network study and for
the validity of study comparisons. We then investigate the effect
of the choice of tractography algorithm on sensitivity and specificity
of the resulting connections with a connectome dissection quality
control (QC) approach. In this approach, evaluation of Tract Specific
Density Coefficients (TSDCs) measures sensitivity while careful inspection
of tractography path results assesses specificity. We use this to
discuss interactions in the combined effects of these methods and
implications for future studies.},
doi = {10.1016/j.neuroimage.2012.06.002},
institution = {Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience,
Maastricht University, Maastricht, The Netherlands. [email protected]},
keywords = {Adult; Algorithms; Cerebral Cortex, physiology; Connectome, methods;
Diffusion Tensor Imaging, methods; Humans; Image Interpretation,
Computer-Assisted; Male; Neural Pathways, physiology},
language = {eng},
medline-pst = {ppublish},
owner = {paula},
pii = {S1053-8119(12)00579-4},
pmid = {22699045},
timestamp = {2013.02.14},
url = {http://dx.doi.org/10.1016/j.neuroimage.2012.06.002}
}
@ARTICLE{Bastien_2012,
author = {Fr{\'e}d{\'e}ric Bastien and Pascal Lamblin and Razvan Pascanu and
James Bergstra and Ian J. Goodfellow and Arnaud Bergeron and Nicolas
Bouchard and David Warde-Farley and Yoshua Bengio},
title = {Theano: new features and speed improvements},
journal = {CoRR.},
year = {2012},
volume = {abs/1211.5590},
pages = {--},
bibsource = {DBLP, http://dblp.uni-trier.de},
ee = {http://arxiv.org/abs/1211.5590},
owner = {paupau},
timestamp = {2013.04.18}
}
@ARTICLE{Beggs_2004,
author = {John M Beggs and Dietmar Plenz},
title = {Neuronal avalanches are diverse and precise activity patterns that
are stable for many hours in cortical slice cultures.},
journal = {J. Neurosci.},
year = {2004},
volume = {24},
pages = {5216--5229},
number = {22},
month = {Jun},
abstract = {A major goal of neuroscience is to elucidate mechanisms of cortical
information processing and storage. Previous work from our laboratory
(Beggs and Plenz, 2003) revealed that propagation of local field
potentials (LFPs) in cortical circuits could be described by the