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March 11, 2021
  

[Brain Image]    

PSY 340 Brain and Behavior

Class 13: Brodmann Areas & Large-Scale Brain Networks

   


The Problem Solved by Korbinian Brodmann (1868-1918)

Korbinian BrodmannThe rapid development of neurology and psychiatry in the second half of the 19th and early part of the 20th century presented researchers with a significant problem in communication. There were agreed-upon terms for the major lobes and gyri of the human cerebral cortex. However, there remained a difficulty in identifying subregions of the cortex in a way which would be understood by scientists in different nations who spoke different languages. The work of Korbinian Brodmann helped to settle that problem.

Brodmann examined the cellular and laminar structure of the human cortex and the cortical tissue of other animals. Eventually he published his important monograph on the cytoarchitectonic structure of the human cortex in 1909. "Cytoarchitectonic" means the architecture of the cells (cyto = cell in Greek) Dr. Laurence Garey (1994) notes:

The basis of Brodmann's cortical localisation is its subdivision into 'areas' with similar cellular and laminar structure. He compared localisation in the human cortex with that in a number of other mammals, including primates, rodents and marsupials. In humans, he distinguished 47 areas, each carrying an individual number, and some being further subdivided.

Brodmann's numbering of these cortical locations has become one of the standard ways in which clinician identify brain areas. These are generally known as "Brodmann Areas" (BA) and will often be cited in texts, for example, as "in BA 45 and 46...". It is presumed that the informed reader will know already or have access to a map of these areas (see below):

Brodmann's Original Map
Brodmann Areas of the Lobes of the Left Hemisphere




Large-Scale Networks of the Brain
Research Methods to Identify Networks
1. fMRI (Functional Magnetic Resonance Imaging): see notes from last class

2. DTI
(Diffusion Tensor Imaging) aka Diffusion MRI
Rather than concentrating on oxygen and the BOLD signal (as in fMRI), Diffusion Tensor Imaging (DTI) focuses upon molecules of water (H2O) and how water flows through various forms of brain tissue (note that DTI is also used to study other organs of the body). Indeed, Le Bihan & Iima (2015) describe this form of imaging as "What Water Tells Us about Biological Tissue".

Isotropic
                  vs. anisotropic movementDepending on whether they are constrained by barriers or not, water molecules can flow or diffuse either equally in all directions (= isotropy [iso = equal; tropy = turning]) or in an unequal set of directions (= anisotropy [an = not]). See diagram at left


DTI looks at the specific direction for the movement (or their "fractional anisotropy") for water molecules. Since water molecules are most frequently found in the white matter of the brain, DTI can map what the predominant direction (on the X, Y, & Z axis) as H2O diffuses.

 

When a DTI study is done, each of the major directions can be color-coded so that fibers of tissue that form tracts going in a particular direction (e.g., from the bottom to the top at a 45º angle) can be visualized easily compared to tracts going in other directions. See the examples below (Figs. B, C, & D). The study of the differing tracks of white matter fibers in the brain is known as tractography.


Images of DTI Studies
In another example the image below shows two different patterns of the superior longitudinal fasciculus (SLF) which connects the anterior and posterior of the cerebral cortex. On the right are examples of traditional atlas maps of the SLF and on the left are the results of a DTI study using two techniques of imaging the tracts.

SLF in multiple views 
The Connectome

The human connectome initiative had a predecessor: “The Human Genome Project is an international scientific research project with a primary goal of determining the sequence of chemical base pairs which make up human DNA, and of identifying and mapping the total genes of the human genome from both a physical and functional standpoint. It remains the largest collaborative biological project.” {W} The Human Genome Project began in 1990 and was completed by the NIH in 2003 with a final publication of the composition of the last chromosome in 2006.

connectomeIn 2005 Olaf Sporns (Indiana University) and Patrick Hagmann (Lausanne University Hospital, Switzerland) independently proposed searching for and building what they termed the “connectome,” that is, a comprehensive map of the neural connections in the brain. They coined the term “connectome” to parallel the use of the term “genome” for the full complement of human genes.

Nature Mouse Connectome
                2014Note that the definition of the connectome as a “comprehensive map of the neural connections in the brain” does not specify how finely detailed that map needs to be. Hence, there are a variety of possible scales that could be applied to the connectome. The possible scales include
  • Microscale: This would include maps of the interconnection among individual neurons. Since this would involve looking at extremely tiny spatial regions (1 cubic mm = ~80,000 neurons & 4.5 million synapses; Insel et al., 2013), such maps would necessarily be quite limited and focused. At this point, technologies are not well developed to map at this scale.
  • Mesoscale:  A map at such a scale would look at groupings of neurons rather than individual cells, e.g., how columns are interconnected. In such a map, which is still technologically very challenging, each group would contain neurons on the order of 100s to 1000s (rather than single cells).
  • Macroscale: Current connectome efforts are directed at producing maps showing how larger regions of interest (nodes, nuclei, ganglia, etc.) are structurally (and functionally linked) by projection, commissural and association tracks or fibers (mostly myelinated bundles of axons)

The Human Connectome Project at the University of Southern California and funded by the National Institute of Health was a 5-year endeavor (2011-2016) both to build better brain scanning and imaging tools and to map the connections across healthy adult brains. "In five years, this highly coordinated effort mapped the connections of 1,200 healthy adults paired with behavioral assessments and GWAS (genome-wide association study) results, resulting in the publication of over 100 papers" -- NIH Feb. 2018. Information on various human connectome projects sponsored by NIH can be found at this link.

Large Scale Brain Networks

A large scale brain network is a set of connections among various locations (neural bodies) inside the cerebrum. There are two basic kinds of connections in the brain: structural connections and functional connections. How do they differ?

Structural Connections

"Structural connectivity describes anatomical connections linking a set of neural elements. At the scale of the human brain, these connections generally refer to white matter projections linking cortical and subcortical regions. Structural connectivity of this kind is thought to be relatively stable on shorter time scales (seconds to minutes) but may be subject to plastic experience dependent changes at longer time scales (hours to days)." (Sporns, 2013, p. 248) Research with DTI (combined with fMRI) has allowed us to identify many very large structural connections across the brain and, increasingly, even smaller connections that had not previously been noticed. In addition to what Sporns (2013) has to say, many of these connections actually remain in place structurally for long periods of time.

Functional-Dynamic Connections

Compared to "built-in" anatomical connectivity, functional connectivity reflects actual interactions between neural elements in the brain over periods of times of various lengths. These connections are "highly time-dependent, often changing in a matter of tens or hundreds of milliseconds as functional connections are continually modulated [influenced] by sensory stimuli and task context." (Sporns, 2013, p. 248) Note that some of these time-dependent functional connections may actually show a more or less continuous state of activity. The networks described below reflect long-term rather than short-term functional activity. 


Yeo Brain
                NetworksThe Functional Networks

There is disagreement over how many major networks function in the brain. The list below indicates 8 networks that many researchers have come to regard as quite important. Not all of these networks are shown in the image on the right from Yeo et al (2011).


Anatomy of DMNDefault Mode Network (DMN) ["Task-Negative Network"]

In 2001, Marcus Raichle and his colleagues at Washington University in St. Louis first identified what they called “a default mode of brain function.” This new understanding of the brain came when Raichle (and other researchers) began to notice the difference in the patterns of blood oxygen use via fMRI images between brains that were (1) actively doing something versus (2) quietly “resting” (i.e., during the periods in-between activities). Certain areas during these resting periods steadily used a certain amount of oxygen (indicating, therefore, that the neurons were doing something) and, when individuals were given a particular task, these resting areas became deactivated (they decreased their oxygen use). Thus, there seemed to be a default mode of activity in the brain when it was not actively working on a task. Another name given to this network is the "task-negative network" since it seems to be engaged in the absence of clear external stimuli.

What does the DMN do? While there is no clear agreement by scientists, here are some of the more important roles suggested for the DMN:

  • Daydreaming & other forms of "spontaneous thinking"
  • Considering one's own present mental state; self-referential or "introspective" thinking; one's own internal narrative (internal talk); internally-directed thought
  • Reflecting on "the autobiographical self"
  • Episodic memory and future thinking;  decision making about the future, i.e., recalling the past and thinking ahead about what to to do in the future
  • Mentalizing, that is, thinking about others: Reflecting on what others may be thinking about (figuring out their "theory of mind") and trying to "understand, infer, and share the thoughts, feelings, and intentions of other individuals (Crepsi et al., 2016, p. 185).

Development of the DMNResearch finds that the DMN actually develops across childhood into early adulthood (Fair et al, 2008; see figure).

Damage to or dysfunction of the DMN. So, what might happen if the DMN is either damaged or has not developed properly? Various problems have been associated with DMN dysfunction. These include possible involvement in autism spectrum disorders, behavioral impulsivity, and other psychiatric disorders. In both schizophrenia and major depressive disorder there are signs that the DMN is hyperactive. This may lead to "overly intensive self-reference and impairments in attention and working memory" for those with schizophrenia and "negative rumination" (constantly thinking about negative matters) in depression (Whitfield-Gabrieli & Ford, 2012, abstract).



SALN
                  AnatomySalience Network (SALN)

The SALN gives a person the ability to sift through the various external and internal stimuli and identify what is most important at that moment (= what is most salient). This network integrates the various stimuli which come from the senses monitoring the outside world (visual, auditory, somatosensory, etc.) with the data that report what is happening within the individual's body (e.g., autonomic nervous system arousal, feelings of pleasure or pain, hunger, etc.). In doing so, the SALN signals when the person's behavior has to change, e.g., it's time to eat...to study...to run away from danger...to turn on a different television channel, etc. This network has been called the "Task-Positive Network" since it is "commonly activated in tasks that demand attention & mental control" (Chai et al.,, 2012, p. 1420)

The SALN is associated with the anterior cingulate cortex (ACC), presupplementary motor areas (preSMA), and the anterior insula (AI).

Executive Control Network (ECN) or Fronto-Parietal Network [FPN]

As its name implies, the ECN coordinates a person's behavior. How? It directs a person's attention to the most important stimuli in the surrounding environment and weighs the choices which need to be made in response to the shifting demands of that environment and the individual's own internal state. The ECN deploys sustained attention and working memory to process the sensory-motor data it is receiving and both chooses to respond in a selective and particular way while suppressing responses which it finds irrelevant or erroneous. The ECN is goal directed and involved in intensive or demanding cognitive tasks.

The ECN has been identified as involving the multiple areas of the prefrontal cortex (dorsolateral, dorsomedial, ventrolateral) as well as the lateral parietal cortex.

Damage to or dysfunction of the ECN results in the widely-recognized problems of what is called "dysexecutive syndome." These problems involve cognitive, emotional, and behavioral symptoms. Cognitively an individual may have difficulties with both short and long-term memory, in understanding how to deal with the problems of daily life, short attention span, cognitive flexibility (changing how to do something from past ways), etc. Emotionally, an individual may behave or speak in inappropriate ways (e.g., about sexual or financial issues) or express anger, aggression or high levels of frustration. In different behavioral symptoms, ECN-impaired individuals have trouble interacting with others socially, following social norms, and dealing with emergencies or other pressing demands, etc.

Dorsal Attention Network (DAN): when we choose to pay attention to something

The DAN is a "top-down" network of the brain which selects or attends to important visual and spatial information, particularly in detecting novel features of the environment which are important or most salient for the individual. The DAN is active when we are deliberately searching for or exploring what is around us. Whenever we are carrying out a deliberately-chosen task, the DAN is active. Note, though, that it functions in a flexible and complementary fashion with the VAN discussed below.

Ventral Attention Network (VAN): when something around us suddenly grabs our attention

The VAN is a "bottom-up" network of the brain which responds when stimuli in the environment unexpectedly or suddenly appear and require that an individual pay attention. For example, if a pipe in the basement ruptures and the floor begins to flood, a person putting clothes in a washing machine will immediately stop loading the clothing and try to deal with the ruptured pipe. This represents a shift from the DAN to the VAN.


All three of the networks below are recognized as "sensorimotor networks" since they are associated with processing various classes of external stimuli and responding with physical movement.


Auditory Network (AUDN)

Auditory
              Network
  • Discrimination of tone & pitch as well as response to speech & music

Visual Network (VISN)

Visual
              Network
  • Multiple tasks involving the visual recognition of both simple visual stimuli as well as many different higher level tasks, e.g., handwriting, silent reading, reading Braille, emotional stimuli including faces & films, naming objects, tracking visual objects, mental object rotation.

Motor-Tactile Network (MTN; aka Sensory-Motor Network [SMN])

Motor-Tactile Network



RESOURCES

Chai, X. J., Castañón, A. N., Öngür, D., & Whitfield-Gabrieli, S. (2012). Anticorrelations in resting state networks without global signal regression. NeuroImage, 59, 1420-1428. doi:10.1016/j.neuroimage.2011.08.048

Crespi, B., Leach, E., Dinsdale, N., Makkonen, M., & Hurd, P. (2016). Imagination in human social cognition, autism, and psychotic-affective conditions. Cognition, 150, 181-199. http://dx.doi.org/10.1016/j.cognition.2016.02.001

Fair, D. A., Cohen, A. L., Dosenbach, N. U. F., Church, J. A., et al. (2008). The maturing architecture of the brain's default brain. PNAS, 105(10), 4028-4032. doi: 10.1073.pnas.0800376105

Insel, T. R., Landis, S. C., & Collins, F. S. (2013). The NIH BRAIN initiative. Science, 340, 687-688.

Le Bihan, D. & Iima, M. (2015). Diffusion magnetic resonance imaging: What water tells us about biological tissue. PLOS Biology, 13(7): e1002203. doi:10.1371/journal.pbio.1002203

Reijmer et al. (2012): Segmentation of the superior longitudinal fasciculus (SLF) with DTI and CSD based fiber tractography. PLOS One, 7(8): e44074.  https://dx.doi.org/10.1371/journal.pone.0044074.g006

Sporns, O. (2013). Structure and function of complex brain networks. Dialogues in Clinical Neuroscience, 15(3), 247-262.

Whitfield-Gabrieli, S., & Ford, J. M. (2012). Default mode network activity and connectivity in psychopathology. Annual Review of Clinical Psychology, 8, 49-76. DOI: 10.1146/annurev-clinpsy-032511-143049

Yeo, B. T. T., Krienen, F. M., .... Buckner, R. L. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity Journal of Neurophysiology, 106, 1125-1165. doi: 10.1152jn.00338.2011

This page was first posted February 25, 2016