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Feb 13, 2025
  

[Brain Image]    

PSY 340 Brain and Behavior

Class 14: Large-Scale Brain Networks

   



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 

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. 


The Functional Networks

There is disagreement over how many major networks function in the brain. The list below indicates 7 networks that many researchers have come to regard as quite important (Sughrue, 2022).

(1) Daydreaming & other forms of "spontaneous thinking"

(2)
Considering one's own present mental state; self-referential or "introspective" thinking; one's own internal narrative (internal talk); internally-directed thought

(3)
Reflecting on "the autobiographical self" and dealing with autobiographical memories

(4)
Episodic memory and future thinkingdecision making about the future, i.e., recalling the past and thinking ahead about what to to do in the future, and

(5)
Mentalizing or social cognition, that is, thinking about other people: 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)

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 is not actively working on tasks that demand significant levels of attention. Another name given to this network is the "task-negative network" since it seems to be engaged in the absence of clear external stimuli.


Other networks that have been proposed include




References

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. https://dx.doi.org/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. https://dx.doi.org/10.1073.pnas.0800376105

Fan, F., Liao, X., Lei, T. … He, Y. (2021). Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study. Neuroimage, 226, 117581. https://dx.doi.org/10.1016/j.neuroimage.2020.117581

Insel, T. R., Landis, S. C., & Collins, F. S. (2013). The NIH BRAIN initiative. Science, 340, 687-688. https://dx.doi.org/10.1126/science.1239276

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

Rosazza, C., & Minati, L. (2011). Resting-state brain networks: literature review and clinical application Neurological Science, 32, 773-785. https://dx.doi.org/10.1007/s10072-011-0636-y

Sughrue, M. (2022, July 5) What are brain networks? [Online]. https://www.o8t.com/blog/brain-networks

Sporns, O. (2013). Structure and function of complex brain networks. Dialogues in Clinical Neuroscience, 15(3), 247-262. https://dx.doi.org/10.31887/DCNS.2013.15.3/osporns

Whitfield-Gabrieli, S., & Ford, J. M. (2012). Default mode network activity and connectivity in psychopathology. Annual Review of Clinical Psychology, 8, 49-76. https://dx.doi.org/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. https://dx.doi.org/10.1152jn.00338.2011

Yeshurun, U., Nguyen, M., & Hasson, U. (2021). The default mode network: where the idiosyncratic self meets the shared social world. Nature Reviews Neuroscience, 22, 181-192. https://dx.doi.org/10.1038/s41583-020-00420-w

The first version of this page was posted on February 25, 2016