The Human Connectome Project (HCP) is a five-year project sponsored by sixteen components of the National Institutes of Health, split between two consortia of research institutions. The project was launched in July 2009 as the first of three Grand Challenges of the NIH's Blueprint for Neuroscience Research. On September 15, 2010, the NIH announced that it would award two grants: $30 million over five years to a consortium led by Washington University in Saint Louis and the University of Minnesota, with strong contributions from Oxford University (FMRIB) and $8.5 million over three years to a consortium led by Harvard University, Massachusetts General Hospital and the University of California Los Angeles.
The goal of the Human Connectome Project is to build a "network map" (connectome) that will shed light on the anatomical and functional connectivity within the healthy human brain, as well as to produce a body of data that will facilitate research into brain disorders such as dyslexia, autism, Alzheimer's disease, and schizophrenia.
WU-Minn-Oxford consortium
The
WU-Minn-Oxford consortium developed improved MRI instrumentation, image
acquisition and image analysis methods for mapping the connectivity in
the human brain at spatial resolutions significantly better than
previously available; using these methods, WU-Minn-Oxford consortium
collected a large amount of MRI and behavioral data on 1,200 healthy
adults — twin pairs and their siblings from 300 families - using a
special 3 Tesla MRI instrument. In addition, it scanned 184 subjects
from this pool at 7 Tesla, with higher spatial resolution. The data are
being analyzed to show the anatomical and functional connections between
parts of the brain for each individual, and will be related to
behavioral test data. Comparing the connectomes and genetic data of genetically identical twins
with fraternal twins will reveal the relative contributions of genes
and environment in shaping brain circuitry and pinpoint relevant genetic variation. The maps will also shed light on how brain networks are organized.
The data that results from this research is being made publicly
available in an open-source web-accessible neuroinformatics platform.
MGH/Harvard-UCLA consortium
The MGH/Harvard-UCLA consortium will focus on optimizing MRI technology for imaging the brain’s structural connections using diffusion MRI, with a goal of increasing spatial resolution,
quality, and speed. Diffusion MRI, employed in both projects, maps the
brain's fibrous long distance connections by tracking the motion of
water. Water diffusion
patterns in different types of cells allow the detection of different
types of tissues. Using this imaging method, the long extensions of
neurons, called white matter, can be seen in sharp relief.
The new scanner built at the MGH Martinos Center for this project is "4 to 8 times as powerful as conventional systems, enabling imaging of human neuroanatomy with greater sensitivity than was previously possible." The scanner has a maximum gradient strength of 300 mT/m and a slew rate of 200 T/m/s, with b-values tested up to 20,000. For comparison, a standard gradient is 45 mT/m, with a b-value of 700.
Behavioral testing and measurement
To
understand the relationship between brain connectivity and behavior
better, the Human Connectome Project will use a reliable and
well-validated battery of measures that assess a wide range of human
functions. The core of its battery is the tools and methods developed by
the NIH Toolbox for Assessment of Neurological and Behavioral function.
Research
The
Human Connectome Project has grown into a large group of research teams.
These teams make use of the style of brain scanning developed by the
Project.
The studies usually include using large groups of participants,
scanning many angles of participants' brains, and carefully documenting
the location of the structures in each participant's brain.
Studies affiliated with the Human Connectome Project are currently
cataloged by the Connectome Coordination Facility. The studies fall into
three categories: Healthy Adult Connectomes, Lifespan Connectome Data,
and Connectomes Related to Human Disease. Under each of these categories
are research groups working on specific questions.
Healthy Adult Connectomes
The Human Connectome Project Young Adult study made data on the brain
connections of 1100 healthy young adults available to the scientific
community. Scientists have used data from the study to support theories about which areas of the brain communicate with one another. For example, one study used data from the project to show that the amygdala,
a part of the brain essential for emotional processing, is connected to
the parts of the brain that receive information from the senses and
plan movement.
Another study showed that healthy individuals who had a high tendency
to experience anxious or depressed mood had fewer connections between
the amygdala and a number of brain areas related to attention.
Lifespan Connectome Data
There
are currently four research groups collecting data on connections in
the brains of populations other than young adults. The purpose of these
groups is to determine ordinary brain connectivity during infancy,
childhood, adolescence, and aging. Scientists will use the data from
these research groups in the same manner in which they have used data
from the Human Connectome Project Young Adult study.
Connectomes Related to Human Disease
Fourteen
research groups investigate how connections in the brain change during
the course of a particular disease. Four of the groups focus on Alzheimer's disease or dementia.
Alzheimer's disease and dementia are diseases that begin during aging.
Memory loss and cognitive impairment mark the progression of these
diseases. While scientists consider Alzheimer's disease to be a disease
with a specific cause, dementia actually describes symptoms which could
be attributed to a number of causes. Two other research groups
investigate how diseases that disrupt vision change connectivity in the
brain. Another four of the research groups focus on anxiety disorders and major depressive disorder, psychological disorders that result in abnormal emotional regulation. Two more of the research groups focus on the effects of psychosis,
a symptom of some psychological disorders in which an individual
perceives reality differently than others do. One of the teams
researches epilepsy, a disease characterized by seizures. Finally, one research team is documenting the brain connections of the Amish people, a religious and ethnic group that has high rates of some psychological disorders.
Although theories have been put forth about the way brain
connections change in the diseases under investigation, many of these
theories have been supported by data from healthy populations.
For example, an analysis of the brains of healthy individuals supported
the theory that individuals with anxiety disorders and depression have
less connectivity between their emotional centers and the areas that
govern attention. By collecting data specifically from individuals with
these diseases, researchers hope to have a more certain idea of how
brain connections in these individuals change over time.
Status
The project has yet to be officially declared complete.
Rendering of a group connectome based on 20 subjects. Anatomical fibers that constitute the white matter architecture of the human brain are visualized color-coded by traversing direction (xyz-directions mapping to RGB colors respectively). Visualization of fibers was done using TrackVis software.
The production and study of connectomes, known as connectomics, may range in scale from a detailed map of the full set of neurons and synapses
within part or all of the nervous system of an organism to a macro
scale description of the functional and structural connectivity between
all cortical areas and subcortical
structures. The term "connectome" is used primarily in scientific
efforts to capture, map, and understand the organization of neural
interactions within the brain.
Research has successfully constructed the full connectome of one animal: the roundwormCaenorhabditis elegans, beginning with the first electron micrographs published by White, Brenner et al., 1986. Based on this seminal work, the first ever connectome (then called "neural circuitry database" by the authors) for C. elegans was published in book form with accompanying floppy disks by Achacoso and Yamamoto in 1992,
with the very first paper on the computer representation of its
connectome presented and published three years earlier in 1989 by
Achacoso at the Symposium on Computer Application in Medical Care
(SCAMC). The C. elegans connectome was later revised and expanded across development. Partial connectomes of a mouse retina and mouse primary visual cortex have also been successfully constructed. Other reconstructions, such as a 12-terabyte dataset by Bock et al. from 2011, are publicly available through NeuroData and other services.
The ultimate goal of connectomics is to map the human brain. This effort is pursued by the Human Connectome Project, sponsored by the National Institutes of Health
(NIH), whose focus is to build a network map of the human brain in
healthy, living adults. Whereas the already mapped roundworm has a total
of 302 neurons in its brain, a human has 86 billion.
Origin and usage of the term
In 2005, Dr. Olaf Sporns at Indiana University and Dr. Patric Hagmann at Lausanne University Hospital
independently and simultaneously suggested the term "connectome" to
refer to a map of the neural connections within the brain. This term was
directly inspired by the ongoing effort to sequence the human genetic code—to build a genome.
"Connectomics" (Hagmann, 2005) has been defined as the science concerned with assembling and analyzing connectome data sets.
In their 2005 paper, "The Human Connectome, a structural description of the human brain", Sporns et al. wrote:
To understand the functioning of a network, one must know
its elements and their interconnections. The purpose of this article is
to discuss research strategies aimed at a comprehensive structural
description of the network of elements and connections forming the human
brain. We propose to call this dataset the human "connectome," and we
argue that it is fundamentally important in cognitive neuroscience and neuropsychology.
The connectome will significantly increase our understanding of how
functional brain states emerge from their underlying structural
substrate, and will provide new mechanistic insights into how brain
function is affected if this structural substrate is disrupted.
In his 2005 Ph.D. thesis, From diffusion MRI to brain connectomics, Hagmann wrote:
It is clear that, like the genome, which is much more than just a juxtaposition of genes,
the set of all neuronal connections in the brain is much more than the
sum of their individual components. The genome is an entity it-self, as
it is from the subtle gene interaction that [life] emerges. In a similar
manner, one could consider the brain connectome, set of all neuronal
connections, as one single entity, thus emphasizing the fact that the
huge brain neuronal communication capacity and computational power
critically relies on this subtle and incredibly complex connectivity
architecture.
Pathways through cerebral white matter can be charted by histologicaldissection and staining, by degeneration methods, and by axonal tracing. Axonal tracing methods form the primary basis for the systematic charting of long-distance pathways into extensive, species-specific anatomical connection matrices between gray matter regions. Landmark studies have included the areas and connections of the visual cortex of the macaque (Felleman and Van Essen, 1991) and the thalamocortical system in the feline brain (Scannell et al., 1999). The development of neuroinformatics
databases for anatomical connectivity allow for continual updating and
refinement of such anatomical connection maps. The online macaque cortex
connectivity tool CoCoMac (Kötter, 2004) and the temporal lobe connectome of the rat are prominent examples of such a database.
In the human brain, the significance of the connectome stems from
the realization that the structure and function of the human brain are
intricately linked, through multiple levels and modes of brain
connectivity. There are strong natural constraints on which neurons or
neural populations can interact, or how strong or direct their
interactions are. Indeed, the foundation of human cognition lies in the pattern of dynamic interactions shaped by the connectome.
However, structure-function relationships in the brain are
unlikely to reduce to simple one-to-one mappings. In fact, the
connectome can evidently support a great number of variable dynamic
states, depending on current sensory inputs, global brain state,
learning and development. Some changes in functional state may involve
rapid changes of structural connectivity at the synaptic level, as has
been elucidated by two-photon imaging experiments showing the rapid appearance and disappearance of dendritic spines (Bonhoeffer and Yuste, 2002).
Despite such complex and variable structure-function mappings,
the connectome is an indispensable basis for the mechanistic
interpretation of dynamic brain data, from single-cell recordings to functional neuroimaging.
The term "connectome" was more recently popularized by Sebastian Seung's I am my Connectome speech given at the 2010 TED conference,
which discusses the high-level goals of mapping the human connectome,
as well as ongoing efforts to build a three-dimensional neural map of
brain tissue at the microscale. In 2012, Seung published the book Connectome: How the Brain's Wiring Makes Us Who We Are.
At multiple scales
Brain networks can be defined at different levels of scale, corresponding to levels of spatial resolution in brain imaging (Kötter, 2007, Sporns, 2010).
These scales can be roughly categorized as microscale, mesoscale and
macroscale. Ultimately, it may be possible to join connectomic maps
obtained at different scales into a single hierarchical map of the
neural organization of a given species that ranges from single neurons
to populations of neurons to larger systems like cortical areas. Given
the methodological uncertainties involved in inferring connectivity from
the primary experimental data, and given that there are likely to be
large differences in the connectomes of different individuals, any
unified map will likely rely on probabilistic representations of connectivity data (Sporns et al., 2005).
Mapping the connectome at the "microscale" (micrometer
resolution) means building a complete map of the neural systems,
neuron-by-neuron. The challenge of doing this becomes obvious: the
number of neurons comprising the brain easily ranges into the billions
in more complex organisms. The human cerebral cortex alone contains on the order of 1010neurons linked by 1014synaptic connections. By comparison, the number of base-pairs in a human genome is 3×109.
A few of the main challenges of building a human connectome at the
microscale today include: data collection would take years given current
technology, machine vision tools to annotate the data remain in their
infancy, and are inadequate, and neither theory nor algorithms are
readily available for the analysis of the resulting brain-graphs. To address the data collection issues, several groups are building high-throughput serial electron microscopes (Kasthuri et al., 2009; Bock et al. 2011). To address the machine-vision and image-processing issues, the Open Connectome Project is alg-sourcing (algorithm outsourcing) this hurdle. Finally, statistical graph theory is an emerging discipline which is developing sophisticated pattern recognition and inference tools to parse these brain-graphs (Goldenberg et al., 2009).
A "mesoscale" connectome corresponds to a spatial resolution of
hundreds of micrometers. Rather than attempt to map each individual
neuron, a connectome at the mesoscale would attempt to capture
anatomically and/or functionally distinct neuronal populations, formed
by local circuits (e.g. cortical columns)
that link hundreds or thousands of individual neurons. This scale still
presents a very ambitious technical challenge at this time and can only
be probed on a small scale with invasive techniques or very high field magnetic resonance imaging (MRI) on a local scale.
A connectome at the macroscale (millimeter
resolution) attempts to capture large brain systems that can be
parcellated into anatomically distinct modules (areas, parcels or
nodes), each having a distinct pattern of connectivity. Connectomic
databases at the mesoscale and macroscale may be significantly more
compact than those at cellular resolution, but they require effective
strategies for accurate anatomical or functional parcellation of the
neural volume into network nodes (for complexities see, e.g., Wallace et
al., 2004).
Mapping at the cellular level
Current
non-invasive imaging techniques cannot capture the brain's activity on a
neuron-by-neuron level. Mapping the connectome at the cellular level in
vertebrates
currently requires post-mortem (after death) microscopic analysis of
limited portions of brain tissue. Non-optical techniques that rely on
high-throughput DNA sequencing have been proposed recently by Anthony Zador (CSHL).
Traditional histological circuit-mapping approaches rely on imaging and include light-microscopic techniques for cell staining, injection of labeling agents for tract tracing, or chemical brain preservation, staining
and reconstruction of serially sectioned tissue blocks via electron
microscopy (EM). Each of these classical approaches has specific
drawbacks when it comes to deployment for connectomics. The staining of
single cells, e.g. with the Golgi stain,
to trace cellular processes and connectivity suffers from the limited
resolution of light-microscopy as well as difficulties in capturing
long-range projections. Tract tracing, often described as the "gold standard" of neuroanatomy
for detecting long-range pathways across the brain, generally only
allows the tracing of fairly large cell populations and single axonal
pathways. EM reconstruction was successfully used for the compilation of
the C. elegans connectome (White et al., 1986).
However, applications to larger tissue blocks of entire nervous systems
have traditionally had difficulty with projections that span longer
distances.
Recent advances in mapping neural connectivity at the cellular
level offer significant new hope for overcoming the limitations of
classical techniques and for compiling cellular connectome data sets
(Livet et al., 2007; Lichtman et al., 2008). Using Brainbow, a combinatorial color labeling method based on the stochastic expression of several fluorescent proteins, Jeff W. Lichtman
and colleagues were able to mark individual neurons with one of over
100 distinct colors. The labeling of individual neurons with a
distinguishable hue then allows the tracing and reconstruction of their
cellular structure including long processes within a block of tissue.
In March 2011, the journal Nature published a pair of articles on micro-connectomes: Bock et al. and Briggman et al.
In both articles, the authors first characterized the functional
properties of a small subset of cells, and then manually traced a subset
of the processes emanating from those cells to obtain a partial
subgraph. In alignment with the principles of open science,
the authors of Bock et al. (2011) have released their data for public
access. The full resolution 12 terabyte dataset from Bock et al. is
available at NeuroData. In 2012, a citizen science project called EyeWire began attempting to crowdsource the mapping of the connectome through an interactive game.
Independently, important topologies of functional interactions among
several hundred cells are also gradually going to be declared (Shimono
and Beggs, 2014). Scaling up ultrastructural circuit mapping to the whole mouse brain is currently underway (Mikula, 2012). An alternative approach to mapping connectivity was recently proposed by Zador and colleagues (Zador et al., 2012).
Zador's technique, called BOINC (barcoding of individual neuronal
connections) uses high-throughput DNA sequencing to map neural circuits.
Briefly, the approach consists of labelling each neuron with a unique
DNA barcode, transferring barcodes between synaptically coupled neurons
(for example using Suid herpesvirus 1,
SuHV1), and fusion of barcodes to represent a synaptic pair. This
approach has the potential to be cheap, fast, and extremely
high-throughput.
In 2016, the Intelligence Advanced Research Projects Activity of the United States government launched MICrONS, a five-year, multi-institute project to map one cubic millimeter of rodent visual cortex, as part of the BRAIN Initiative.
Though only a small volume of biological tissue, this project will
yield one of the largest micro-scale connectomics datasets currently in
existence.
Mapping at the macro scale
Established
methods of brain research, such as axonal tracing, provided early
avenues for building connectome data sets. However, more recent advances
in living subjects has been made by the use of non-invasive imaging
technologies such as diffusion-weighted magnetic resonance imaging (DW-MRI) and functional magnetic resonance imaging
(fMRI). The first, when combined with tractography allows
reconstruction of the major fiber bundles in the brain. The second
allows the researcher to capture the brain's network activity (either at
rest or while performing directed tasks), enabling the identification
of structurally and anatomically distinct areas of the brain that are
functionally connected.
Notably, the goal of the Human Connectome Project, led by the WU-Minn consortium, is to build a structural and functional map of the healthy human brain at the macro scale, using a combination of multiple imaging technologies and resolutions.
Recent advances in connectivity mapping
Tractographic reconstruction of neural connections via DTI
Throughout the 2000s, several investigators have attempted to map the
large-scale structural architecture of the human cerebral cortex. One
attempt exploited cross-correlations in cortical thickness or volume
across individuals (He et al., 2007).
Such gray-matter thickness correlations have been postulated as
indicators for the presence of structural connections. A drawback of the
approach is that it provides highly indirect information about cortical
connection patterns and requires data from large numbers of individuals
to derive a single connection data set across a subject group. Other
investigators have attempted to build whole-brain connection matrices
from DW-MRI imaging data.
The Blue Brain Project is attempting to reconstruct the entire mouse connectome using a diamond knife sharpened to an atomic edge, and electron microscopy for imaging tissue slices.
Primary challenge for macroscale connectomics: determining parcellations of the brain
The
initial explorations in macroscale human connectomics were done using
either equally sized regions or anatomical regions with unclear
relationship to the underlying functional organization of the brain
(e.g. gyral and sulcal-based
regions). While much can be learned from these approaches, it is
highly desirable to parcellate the brain into functionally distinct
parcels: brain regions with distinct architectonics, connectivity,
function, and/or topography (Felleman and Van Essen, 1991).
Accurate parcellation allows each node in the macroscale connectome to
be more informative by associating it with a distinct connectivity
pattern and functional profile. Parcellation of localized areas of
cortex have been accomplished using diffusion tractography (Beckmann et al. 2009) and functional connectivity (Nelson et al. 2010)
to non-invasively measure connectivity patterns and define cortical
areas based on distinct connectivity patterns. Such analyses may best
be done on a whole brain scale and by integrating non-invasive
modalities. Accurate whole brain parcellation may lead to more accurate
macroscale connectomes for the normal brain, which can then be compared
to disease states.
Plasticity of the connectome
At
the beginning of the connectome project, it was thought that the
connections between neurons were unchangeable once established and that
only individual synapses could be altered. However, recent evidence suggests that connectivity is also subject to change, termed neuroplasticity.
There are two ways that the brain can rewire: formation and removal of
synapses in an established connection or formation or removal of entire
connections between neurons.
Both mechanisms of rewiring are useful for learning completely novel
tasks that may require entirely new connections between regions of the
brain.
However, the ability of the brain to gain or lose entire connections
poses an issue for mapping a universal species connectome. Although
rewiring happens on different scales, from microscale to macroscale,
each scale does not occur in isolation. For example, in the C. elegans
connectome, the total number of synapses increases 5-fold from birth to
adulthood, changing both local and global network properties.
Microscale rewiring
Microscale
rewiring is the formation or removal of synaptic connections between
two neurons and can be studied with longitudinal two-photon imaging.
Dendritic spines on pyramidal neurons can be shown forming within days following sensory experience and learning. Changes can even be seen within five hours on apical tufts of layer five pyramidal neurons in the primary motor cortex after a seed reaching task in primates.
Mesoscale rewiring
Rewiring at the mesoscale involves studying the presence or absence of entire connections between neurons. Evidence for this level of rewiring comes from observations that local circuits form new connections as a result of experience-dependent plasticity in the visual cortex. Additionally, the number of local connections between pyramidal neurons in the primary somatosensory cortex increases following altered whisker sensory experience in rodents.
Macroscale rewiring
Evidence
for macroscale rewiring mostly comes from research on grey and white
matter density, which could indicate new connections or changes in axon
density. Direct evidence for this level of rewiring comes from primate
studies, using viral tracing to map the formation of connections.
Primates that were taught to use novel tools developed new connections
between the interparietal cortex and higher visual areas of the brain. Further viral tracing studies have provided evidence that macroscale rewiring occurs in adult animals during associative learning.
However, it is not likely that long-distance neural connections undergo
extensive rewiring in adults. Small changes in an already established nerve tract are likely what is observed in macroscale rewiring.
Mapping functional connectivity to complement anatomical connectivity
Using fMRI in the resting state and during tasks, functions of the connectome circuits are being studied.
Just as detailed road maps of the Earth's surface do not tell us much
about the kind of vehicles that travel those roads or what cargo they
are hauling, to understand how neural structures result in specific
functional behavior such as consciousness, it is necessary to build theories that relate functions to anatomical connectivity.
However, the bond between structural and functional connectivity is not
straightforward. Computational models of whole-brain network dynamics
are valuable tools to investigate the role of the anatomical network in
shaping functional connectivity. In particular, computational models can be used to predict the dynamic effect of lesions in the connectome.
As a network or graph
The connectome can be studied as a network by means of network science and graph theory. In case of a micro-scale connectome, the nodes of this network (or graph) are the neurons, and the edges correspond to the synapses between those neurons. For the macro-scale connectome, the nodes correspond to the ROIs (regions of interest),
while the edges of the graph are derived from the axons interconnecting
those areas. Thus connectomes are sometimes referred to as brain graphs,
as they are indeed graphs in a mathematical sense which describe the
connections in the brain (or, in a broader sense, the whole nervous
system).
One group of researchers (Iturria-Medina et al., 2008) has constructed connectome data sets using diffusion tensor imaging (DTI) followed by the derivation of average connection probabilities between 70–90 cortical and basal
brain gray matter areas. All networks were found to have small-world
attributes and "broad-scale" degree distributions. An analysis of betweenness centrality in these networks demonstrated high centrality for the precuneus, the insula, the superior parietal and the superior frontal cortex. Another group (Gong et al. 2008)
has applied DTI to map a network of anatomical connections between 78
cortical regions. This study also identified several hub regions in the
human brain, including the precuneus and the superior frontal gyrus.
Hagmann et al. (2007)
constructed a connection matrix from fiber densities measured between
homogeneously distributed and equal-sized ROIs numbering between 500 and
4000. A quantitative analysis of connection matrices obtained for
approximately 1,000 ROIs and approximately 50,000 fiber pathways from
two subjects demonstrated an exponential (one-scale) degree distribution
as well as robust small-world attributes for the network. The data sets
were derived from diffusion spectrum imaging (DSI) (Wedeen, 2005), a variant of diffusion-weighted imaging
that is sensitive to intra-voxel heterogeneities in diffusion
directions caused by crossing fiber tracts and thus allows more accurate
mapping of axonal trajectories than other diffusion imaging approaches
(Wedeen, 2008).
The combination of whole-head DSI datasets acquired and processed according to the approach developed by Hagmann et al. (2007) with the graph analysis tools conceived initially for animal tracing studies (Sporns, 2006; Sporns, 2007) allow a detailed study of the network structure of human cortical connectivity (Hagmann et al., 2008).
The human brain network was characterized using a broad array of
network analysis methods including core decomposition, modularity
analysis, hub classification and centrality. Hagmann et al.
presented evidence for the existence of a structural core of highly and
mutually interconnected brain regions, located primarily in posterior
medial and parietal cortex. The core comprises portions of the posterior cingulate cortex, the precuneus, the cuneus, the paracentral lobule, the isthmus of the cingulate, the banks of the superior temporal sulcus, and the inferior and superior parietal cortex, all located in both cerebral hemispheres.
A subfield of connectomics deals with the comparison of the brain
graphs of multiple subjects. It is possible to build a consensus graph
such the Budapest Reference Connectome by allowing only edges that are present in at least connectomes, for a selectable
parameter. The Budapest Reference Connectome has led the researchers to
the discovery of the Consensus Connectome Dynamics of the human brain
graphs. The edges appeared in all of the brain graphs form a connected
subgraph around the brainstem. By allowing gradually less frequent edges, this core subgraph grows continuously, as a shrub. The growth dynamics may reflect the individual brain development and provide an opportunity to direct some edges of the human consensus brain graph.
Alternatively, local difference which are statistically
significantly different among groups have attracted more attention as
they highlight specific connections and therefore shed more light on
specific brain traits or pathology. Hence, algorithms to find local
difference between graph populations have also been introduced (e.g. to
compare case versus control groups). Those can be found by using either an adjusted t-test, or a sparsity model, with the aim of finding statistically significant connections which are different among those groups.
The possible causes of the difference between individual
connectomes were also investigated. Indeed, it has been found that the
macro-scale connectomes of women contain significantly more edges than
those of men, and a larger portion of the edges in the connectomes of
women run between the two hemispheres. In addition, connectomes generally exhibit a small-world character, with overall cortical connectivity decreasing with age. The aim of the as of 2015 ongoing HCP Lifespan Pilot Project is to identify connectome differences between 6 age groups (4–6, 8–9, 14–15, 25–35, 45–55, 65–75).
More recently, connectograms have been used to visualize full-brain data by placing cortical areas around a circle, organized by lobe.
Inner circles then depict cortical metrics on a color scale. White
matter fiber connections in DTI data are then drawn between these
cortical regions and weighted by fractional anisotropy
and strength of the connection. Such graphs have even been used to
analyze the damage done to the famous traumatic brain injury patient Phineas Gage.
Statistical graph theory is an emerging discipline which is
developing sophisticated pattern recognition and inference tools to
parse these brain graphs (Goldenberg et al., 2009).
Recent research studied the brain as a signed network and
indicated that hubness in positive and negative subnetworks increases
the stability of the brain network. It highlighted the role of negative
functional connections that are paid less attention to.
Lorenz studied instinctive behavior in animals, especially in greylag geese and jackdaws. Working with geese, he investigated the principle of imprinting, the process by which some nidifugous
birds (i.e. birds that leave their nest early) bond instinctively with
the first moving object that they see within the first hours of
hatching. Although Lorenz did not discover the topic, he became widely
known for his descriptions of imprinting as an instinctive bond. In
1936 he met Tinbergen, and the two collaborated in developing ethology
as a separate sub-discipline of biology. A Review of General Psychology survey, published in 2002, ranked Lorenz the 65th most cited scholar of the 20th century in the technical psychology journals, introductory psychology textbooks, and survey responses.
Lorenz wrote numerous books, some of which, such as King Solomon's Ring, On Aggression, and Man Meets Dog,
became popular reading. His last work "Here I Am – Where Are You?" is a
summary of his life's work and focuses on his famous studies of greylag
geese.
Biography
Lorenz in 1904 with his elder brother
Lorenz was the son of Adolf Lorenz, a wealthy and distinguished surgeon, and his wife Emma (née Lecher), a physician who had been her husband's assistant. The family lived on a large estate at Altenburg, and had a city apartment in Vienna.
In his autobiographical essay, published in 1973 in Les Prix Nobel
(winners of the prizes are requested to provide such essays), Lorenz
credits his career to his parents, who "were supremely tolerant of my
inordinate love for animals", and to his childhood encounter with Selma Lagerlöf's The Wonderful Adventures of Nils, which filled him with a great enthusiasm about wild geese."
At the request of his father, Adolf Lorenz, he began a premedical curriculum in 1922 at Columbia University, but he returned to Vienna in 1923 to continue his studies at the University of Vienna.
He graduated as Doctor of Medicine (MD) in 1928 and became an assistant
professor at the Institute of Anatomy until 1935. He finished his
zoological studies in 1933 and received his second doctorate (PhD).
While still a student, Lorenz began developing what would become a large menagerie, ranging from domestic to exotic animals. In his popular book King Solomon's Ring, Lorenz recounts that while studying at the University of Vienna he kept a variety of animals at his parents' apartment, ranging from fish to a capuchin monkey named Gloria.
In 1936, at an international scientific symposium on instinct, Lorenz met his great friend and colleague Nikolaas Tinbergen. Together they studied geese—wild, domestic, and hybrid.
One result of these studies was that Lorenz "realized that an
overpowering increase in the drives of feeding as well as of copulation
and a waning of more differentiated social instincts is characteristic
of very many domestic animals". Lorenz began to suspect and fear "that
analogous processes of deterioration may be at work with civilized
humanity." This observation of bird hybrids caused Lorenz to believe
that domestication resulting from urbanisation in humans might also
cause dysgenic effects, and to argue in two papers that the Nazi eugenics policies against this were therefore scientifically justified.
In 1940 he became a professor of psychology at the University of Königsberg. He was drafted into the Wehrmacht
in 1941. He sought to be a motorcycle mechanic, but instead he was
assigned as a military psychologist, conducting racial studies on humans
in occupied Poznań under Rudolf Hippius.
The objective was to study the biological characteristics of
"German-Polish half-breeds" to determine whether they 'benefitted' from
the same work ethics as 'pure' Germans.
The degree to which Lorenz participated in the project is unknown, but
the project director Hippius referred a couple of times to Lorenz as an
"examining psychologist".
Lorenz later described that he once saw transports of concentration camp inmates at Fort VII near Poznań, which made him "fully realize the complete inhumanity of the Nazis".
He was sent to the Russian front in 1944 where he quickly became a prisoner of war in the Soviet Union from 1944 to 1948. In captivity in Soviet Armenia,
he continued to work as a medic and "became tolerably fluent in Russian
and got quite friendly with some Russians, mostly doctors." When he was repatriated, he was allowed to keep the manuscript of a book he had been writing, and his pet starling.
He arrived back in Altenberg (his family home, near Vienna) both "with
manuscript and bird intact." The manuscript became his 1973 book Behind the Mirror.
The Max Planck Society established the Lorenz Institute for Behavioral Physiology in Buldern, Germany,
in 1950. In his memoirs Lorenz described the chronology of his war
years differently from what historians have been able to document after
his death. He himself claimed that he was captured in 1942, where in
reality he was only sent to the front and captured in 1944, leaving out
entirely his involvement with the Poznań project.
He retired from the Max Planck Institute in 1973 but continued to research and publish from Altenberg and Grünau im Almtal in Austria. He died on 27 February 1989 in Altenberg.
Personal life
Lorenz
married his childhood friend, Margarethe Gebhardt, a gynaecologist,
daughter of a market gardener who lived near the Lorenz family;
they had a son and two daughters. He lived at the Lorenz family estate,
which included a "fantastical neo-baroque mansion", previously owned by
his father.
Ethology
Lorenz is recognized as one of the founding fathers of the field of ethology, the study of animal behavior. He is best known for his discovery of the principle of attachment, or imprinting,
through which in some species a bond is formed between a newborn animal
and its caregiver. This principle had been discovered by Douglas Spalding in the 19th century, and Lorenz's mentor Oskar Heinroth had also worked on the topic, but Lorenz's description of Prägung, imprinting, in nidifugous birds such as greylag geese in his 1935 book Der Kumpan in der Umwelt des Vogels ("The Companion in the Environment of Birds") became the foundational description of the phenomenon.
Here, Lorenz used Jakob von Uexküll's concept of Umwelt
to understand how the limited perception of animals filtered out
certain phenomena with which they interacted instinctively. For example,
a young goose instinctively bonds with the first moving stimulus it
perceives, whether it be its mother, or a person. Lorenz showed that
this behavior of imprinting
is what allows the goose to learn to recognize members of its own
species, enabling them to be the object of subsequent behavior patterns
such as mating.
He developed a theory of instinctive behavior that saw behavior
patterns as largely innate but triggered through environmental stimuli,
for example the hawk/goose effect.
He argued that animals have an inner drive to carry out instinctive
behaviors, and that if they do not encounter the right stimulus they
will eventually engage in the behavior with an inappropriate stimulus.
Lorenz's approach to ethology derived from a skepticism towards
the studies of animal behavior done in laboratory settings. He
considered that in order to understand the mechanisms of animal
behavior, it was necessary to observe their full range of behaviors in
their natural context. Lorenz did not carry out much traditional
fieldwork but observed animals near his home. His method involved
empathizing with animals, often using anthropomorphization to imagine
their mental states. He believed that animals were capable of
experiencing many of the same emotions as humans.
Tinbergen, Lorenz's friend with whom he conjointly received the
Nobel prize, summarized Lorenz's major contribution to ethology as
making behavior a topic of biological inquiry, considering behavior a
part of an animal's evolutionary equipment.
Tinbergen and Lorenz contributed to making Ethology a recognized
sub-discipline within Biology and founded the first specialized journal
of the field "Ethology" (originally "Zeitschift für Tierpsychologie")
Politics
Lorenz joined the Nazi Party in 1938 and accepted a university chair under the Nazi regime.
In his application for party membership he wrote, "I'm able to say that
my whole scientific work is devoted to the ideas of the National Socialists."
His publications during that time led in later years to allegations
that his scientific work had been contaminated by Nazi sympathies. His
published writing during the Nazi period included support for Nazi ideas
of "racial hygiene" couched in pseudoscientific metaphors.
In his autobiography, Lorenz wrote:
I was frightened—as I still am—by the thought that
analogous genetical processes of deterioration may be at work with
civilized humanity. Moved by this fear, I did a very ill-advised thing
soon after the Germans had invaded Austria: I wrote about the dangers of
domestication and, in order to be understood, I couched my writing in the worst of Nazi terminology. I do not want to extenuate this action. I did, indeed, believe that some good might come of the new rulers. The precedent narrow-minded catholic regime
in Austria induced better and more intelligent men than I was to
cherish this naive hope. Practically all my friends and teachers did so,
including my own father who certainly was a kindly and humane man. None
of us as much as suspected that the word "selection", when used by
these rulers, meant murder. I regret those writings not so much for the
undeniable discredit they reflect on my person as for their effect of
hampering the future recognition of the dangers of domestication.
After the war, Lorenz denied having been a party member,
until his membership application was made public; and he denied having
known the extent of the genocide, despite his position as a psychologist
in the Office of Racial Policy. He was also shown to have made anti-Semitic jokes on 'Jewish characteristics' in letters to his mentor Heinroth. In 2015, the University of Salzburg
posthumously rescinded an honorary doctorate awarded to Lorenz in 1983,
citing his party membership and his assertions in his application that
he was "always a National Socialist", and that his work "stands to serve
National Socialist thought". The university also accused him of using
his work to spread "basic elements of the racist ideology of National
Socialism".
During the final years of his life, Lorenz supported the fledgling Austrian Green Party and in 1984 became the figurehead of the Konrad Lorenz Volksbegehren, a grass-roots movement that was formed to prevent the building of a power plant at the Danube near Hainburg an der Donau and thus the destruction of the surrounding woodland.
Lorenz has been called 'The father of ethology', by Niko Tinbergen.
Perhaps Lorenz's most important contribution to ethology was his idea
that behavior patterns can be studied as anatomical organs. This concept forms the foundation of ethological research. However, Richard Dawkins called Lorenz a "'good of the species' man", stating that the idea of group selection was "so deeply ingrained" in Lorenz's thinking that he "evidently did not realize that his statements contravened orthodox Darwinian theory."
Together with Nikolaas Tinbergen, Lorenz developed the idea of an innate releasing mechanism to explain instinctive behaviors (fixed action patterns). They experimented with "supernormal stimuli"
such as giant eggs or dummy bird beaks which they found could release
the fixed action patterns more powerfully than the natural objects for
which the behaviors were adapted. Influenced by the ideas of William McDougall, Lorenz developed this into a "psychohydraulic" model of the motivation of behavior, which tended towards group selectionist ideas, which were influential in the 1960s. Another of his contributions to ethology is his work on imprinting. His influence on a younger generation of ethologists; and his popular works, were important in bringing ethology to the attention of the general public.
Lorenz claimed that there was widespread contempt for the
descriptive sciences. He attributed this to the denial of perception as
the source of all scientific knowledge: "a denial that has been elevated
to the status of religion."
He wrote that in comparative behavioral research, "it is necessary to
describe various patterns of movement, record them, and above all,
render them unmistakably recognizable."
Lorenz predicted the relationship between market economics and the threat of ecological catastrophe. In his 1973 book, Civilized Man's Eight Deadly Sins, Lorenz addresses the following paradox:
All the advantages that man has gained from his
ever-deepening understanding of the natural world that surrounds him,
his technological, chemical and medical progress, all of which should
seem to alleviate human suffering... tends instead to favor humanity's
destruction
Lorenz adopts an ecological model to attempt to grasp the mechanisms
behind this contradiction. Thus "all species... are adapted to their
environment... including not only inorganic components... but all the
other living beings that inhabit the locality." p31.
Fundamental to Lorenz's theory of ecology is the function of negative feedback
mechanisms, which, in hierarchical fashion, dampen impulses that occur
beneath a certain threshold. The thresholds themselves are the product
of the interaction of contrasting mechanisms. Thus pain and pleasure act
as checks on each other:
To gain a desired prey, a dog or wolf will do things
that, in other contexts, they would shy away from: run through thorn
bushes, jump into cold water and expose themselves to risks which would
normally frighten them. All these inhibitory mechanisms... act as a
counterweight to the effects of learning mechanisms... The organism
cannot allow itself to pay a price which is not worth paying. p53.
In nature, these mechanisms tend towards a 'stable state' among the living beings of an ecology:
A closer examination shows that these beings... not only
do not damage each other, but often constitute a community of interests.
It is obvious that the predator is strongly interested in the survival
of that species, animal or vegetable, which constitutes its prey. ... It
is not uncommon that the prey species derives specific benefits from
its interaction with the predator species... pp31–33.
Lorenz states that humanity is the one species not bound by these
mechanisms, being the only one that has defined its own environment:
[The pace of human ecology] is determined by the progress
of man's technology (p35)... human ecology (economy) is governed by
mechanisms of POSITIVE feedback, defined as a mechanism which tends to
encourage behavior rather than to attenuate it (p43). Positive feedback
always involves the danger of an 'avalanche' effect... One particular
kind of positive feedback occurs when individuals OF THE SAME SPECIES
enter into competition among themselves... For many animal species,
environmental factors keep... intraspecies selection from [leading to]
disaster... But there is no force which exercises this type of healthy
regulatory effect on humanity's cultural development; unfortunately for
itself, humanity has learned to overcome all those environmental forces
which are external to itself p44.
Regarding aggression in human beings, Lorenz states:
Let us imagine that an absolutely unbiased investigator
on another planet, perhaps on Mars, is examining human behavior on
earth, with the aid of a telescope whose magnification is too small to
enable him to discern individuals and follow their separate behavior,
but large enough for him to observe occurrences such as migrations of
peoples, wars, and similar great historical events. He would never gain
the impression that human behavior was dictated by intelligence, still
less by responsible morality. If we suppose our extraneous observer to
be a being of pure reason, devoid of instincts himself and unaware of
the way in which all instincts in general and aggression in particular
can miscarry, he would be at a complete loss how to explain history at
all. The ever-recurrent phenomena of history do not have reasonable
causes. It is a mere commonplace to say that they are caused by what
common parlance so aptly terms "human nature." Unreasoning and
unreasonable human nature causes two nations to compete, though no
economic necessity compels them to do so; it induces two political
parties or religions with amazingly similar programs of salvation to
fight each other bitterly, and it impels an Alexander or a Napoleon to
sacrifice millions of lives in his attempt to unite the world under his
scepter. We have been taught to regard some of the persons who have
committed these and similar absurdities with respect, even as "great"
men, we are wont to yield to the political wisdom of those in charge,
and we are all so accustomed to these phenomena that most of us fail to
realize how abjectly stupid and undesirable the historical mass behavior
of humanity actually is.
Lorenz does not see human independence from natural ecological processes as necessarily bad. Indeed, he states that:
A completely new [ecology] which corresponds in every way
to [humanity's] desires... could, theoretically, prove as durable as
that which would have existed without his intervention (36).
However, the principle of competition, typical of Western societies, destroys any chance of this:
The competition between human beings destroys with cold
and diabolic brutality... Under the pressure of this competitive fury we
have not only forgotten what is useful to humanity as a whole, but even
that which is good and advantageous to the individual. [...] One asks,
which is more damaging to modern humanity: the thirst for money or
consuming haste... in either case, fear plays a very important role: the
fear of being overtaken by one's competitors, the fear of becoming
poor, the fear of making wrong decisions or the fear of not being up to
snuff... pp45–47.
In this book, Lorenz proposes that the best hope for mankind lies in
our looking for mates based on the kindness of their hearts rather than
good looks or wealth. He illustrates this with a Jewish story,
explicitly described as such.
In his 1973 book Behind the Mirror: A Search for a Natural History of Human Knowledge,
Lorenz considers the old philosophical question of whether our senses
correctly inform us about the world as it is, or provide us only with an
illusion. His answer comes from evolutionary biology.
Only traits that help us survive and reproduce are transmitted. If our
senses gave us wrong information about our environment, we would soon be
extinct. Therefore, we can be sure that our senses give us correct
information, for otherwise we would not be here to be deceived.
Lorenz's best-known books are King Solomon's Ring and On Aggression, both written for a popular audience. His scientific work appeared mainly in journal articles, written in German; it became widely known to English-speaking scientists through its description in Tinbergen's 1951 bookThe Study of Instinct, though many of his papers were later published in English translation in the two volumes titled Studies in Animal and Human Behavior.
King Solomon's Ring (1949) (Er redete mit dem Vieh, den Vögeln und den Fischen, 1949)
Man Meets Dog (1950) (So kam der Mensch auf den Hund, 1950)
Evolution and Modification of Behaviour (1965)
On Aggression (1966) (Das sogenannte Böse. Zur Naturgeschichte der Aggression, 1963)
Studies in Animal and Human Behavior, Volume I (1970)
Studies in Animal and Human Behavior, Volume II (1971)
Motivation of Human and Animal Behavior: An Ethological View. With Paul Leyhausen (1973). New York: D. Van Nostrand Co. ISBN0-442-24886-5
Civilized Man's Eight Deadly Sins (1974) (Die acht Todsünden der zivilisierten Menschheit, 1973)
The Year of the Greylag Goose (1979) (Das Jahr der Graugans, 1979)
The Foundations of Ethology (1982)
The Waning of Humaneness (1987) (Der Abbau des Menschlichen, 1983)
Here I Am – Where Are You? – A Lifetime's Study of the Uncannily Human Behaviour of the Greylag Goose. (1988). Translated by Robert D. Martin from Hier bin ich – wo bist du?.
The Natural Science of the Human Species: An Introduction to
Comparative Behavioral Research – The Russian Manuscript (1944–1948) (1995)
