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Zinn, Zinn, Jason: Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks

mango

Senior Member
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905
Intrinsic Functional Hypoconnectivity in Core Neurocognitive Networks Suggests Central Nervous System Pathology in Patients with Myalgic Encephalomyelitis: A Pilot Study.

Zinn ML1, Zinn MA2, Jason LA2.

Author information
1Department of Community Psychology, Center for Community Research, DePaul University, Chicago, IL, 60614, USA.
2Department of Community Psychology, Center for Community Research, DePaul University, Chicago, IL, 60614, USA.

Appl Psychophysiol Biofeedback.
2016 Feb 11. [Epub ahead of print]

Abstract
Exact low resolution electromagnetic tomography (eLORETA) was recorded from nineteen EEG channels in nine patients with myalgic encephalomyelitis (ME) and 9 healthy controls to assess current source density and functional connectivity, a physiological measure of similarity between pairs of distributed regions of interest, between groups. Current source density and functional connectivity were measured using eLORETA software. We found significantly decreased eLORETA source analysis oscillations in the occipital, parietal, posterior cingulate, and posterior temporal lobes in Alpha and Alpha-2. For connectivity analysis, we assessed functional connectivity within Menon triple network model of neuropathology. We found support for all three networks of the triple network model, namely the central executive network (CEN), salience network (SN), and the default mode network (DMN) indicating hypo-connectivity in the Delta, Alpha, and Alpha-2 frequency bands in patients with ME compared to controls. In addition to the current source density resting state dysfunction in the occipital, parietal, posterior temporal and posterior cingulate, the disrupted connectivity of the CEN, SN, and DMN appears to be involved in cognitive impairment for patients with ME. This research suggests that disruptions in these regions and networks could be a neurobiological feature of the disorder, representing underlying neural dysfunction.

KEYWORDS: Chronic fatigue syndrome; Lagged phase synchronization; Myalgic encephalomyelitis; Triple network model; eLORETA

PMID: 26869373 [PubMed - as supplied by publisher]

http://www.ncbi.nlm.nih.gov/pubmed/26869373
 

Marco

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Umm - pardon?

Very interesting but I do wonder what evidence there is for the objective existence of these networks (central executive network (CEN), salience network (SN), and the default mode network (DMN)) and how accepted is the ' Menon triple network model of neuropathology'?

Maybe it's all perfectly mainstream in neurology?
 

jimells

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Umm - pardon?

Very interesting but I do wonder what evidence there is for the objective existence of these networks (central executive network (CEN), salience network (SN), and the default mode network (DMN)) and how accepted is the ' Menon triple network model of neuropathology'?

Maybe it's all perfectly mainstream in neurology?

It's not the only paper to use those terms, although I would look very carefully at anything that mentions Borderline Personality Disorder - it's another one of those controversial diagnoses (a former girlfriend had this diagnosis).

http://www.ncbi.nlm.nih.gov/pubmed/24198777
Shifted intrinsic connectivity of central executive and salience network in borderline personality disorder.
Doll A1, Sorg C, Manoliu A, Wöller A, Meng C, Förstl H, Zimmer C, Wohlschläger AM, Riedl V.
Abstract
Borderline personality disorder (BPD) is characterized by "stable instability" of emotions and behavior and their regulation. This emotional and behavioral instability corresponds with a neurocognitive triple network model of psychopathology, which suggests that aberrant emotional saliency and cognitive control is associated with aberrant interaction across three intrinsic connectivity networks [i.e., the salience network (SN), default mode network (DMN), and central executive network (CEN)].

The objective of the current study was to investigate whether and how such triple network intrinsic functional connectivity (iFC) is changed in patients with BPD.

We acquired resting-state functional magnetic resonance imaging (rs-fMRI) data from 14 patients with BPD and 16 healthy controls. High-model order independent component analysis was used to extract spatiotemporal patterns of ongoing, coherent blood-oxygen-level-dependent signal fluctuations from rs-fMRI data.

Main outcome measures were iFC within networks (intra-iFC) and between networks (i.e., network time course correlation inter-iFC). Aberrant intra-iFC was found in patients' DMN, SN, and CEN, consistent with previous findings. While patients' inter-iFC of the CEN was decreased, inter-iFC of the SN was increased.

In particular, a balance index reflecting the relationship of CEN- and SN-inter-iFC across networks was strongly shifted from CEN to SN connectivity in patients. Results provide first preliminary evidence for aberrant triple network iFC in BPD.

Our data suggest a shift of inter-network iFC from networks involved in cognitive control to those of emotion-related activity in BPD, potentially reflecting the persistent instability of emotion regulation in patients.

Sounds kinda woo-woo to me, although this is way too dense for me to understand. It's unsettling to compare these two papers. Jason's research makes this triple-network thingy sound like biochemistry and uses the term "neuropathology" while the psychiatric researchers above make the triple-network sound like a psychological construct and uses the term "psychopathology".

It would be interesting to hear what @Jonathan Edwards thinks of these papers.
 

jimells

Senior Member
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northern Maine
Well here is the poop on the triple network from Menon himself:

https://www.ncbi.nlm.nih.gov/pubmed/21908230
Large-scale brain networks and psychopathology: a unifying triple network model.
Menon V1.
  • 1Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanfod, CA 94305, USA. menon@stanford.edu
Abstract
The science of large-scale brain networks offers a powerful paradigm for investigating cognitive and affective dysfunction in psychiatric and neurological disorders. This review examines recent conceptual and methodological developments which are contributing to a paradigm shift in the study of psychopathology.

I summarize methods for characterizing aberrant brain networks and demonstrate how network analysis provides novel insights into dysfunctional brain architecture. Deficits in access, engagement and disengagement of large-scale neurocognitive networks are shown to play a prominent role in several disorders including schizophrenia, depression, anxiety, dementia and autism.

Synthesizing recent research, I propose a triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders.

It must be catching on, as it has been cited by over 100 PubMed Central articles.
 

siggycat

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Menon is talking about neural pathology, which then produces symptoms. Why not just contact him? He is at Stanford and easy to get hold of. You could clear this whole thing up with one email.

Siggy
 
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3,263
Very interesting but I do wonder what evidence there is for the objective existence of these networks (central executive network (CEN), salience network (SN), and the default mode network (DMN)) and how accepted is the ' Menon triple network model of neuropathology'?
CEN, SN, and DMN are pretty mainstream. The idea is is that the DMN (default mode network), is a network of structures that's highly active when people are at rest and thinking their own thoughts.

The SN (salience network), on the other hand, is a system that alerts the person to start taking an interest in things going on outside of them, and therefore to switch from primarily internal, default mode network (DFN) thinking to more active processing of incoming info. The active thinking is believed to be governed by the CEN (central executive network).

So in other words, the three networks kind of work together to control a person's mode of thinking.

What isn't clear is what variations in connectivity within these networks actually means, and what the causal factors are. Researchers are reporting differences in different pathological groups all over the place. Then they try to work backwards, and say "well, this network is not normal because people are too busy thinking of X or can't think of Y" (or whatever). Its all very hand-waving, and can be interpreted in any way you fancy really.

This study use 9 participants, which isn't enough in my view when you're trying to establish a group difference.
 
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Sounds kinda woo-woo to me, although this is way too dense for me to understand. It's unsettling to compare these two papers. Jason's research makes this triple-network thingy sound like biochemistry and uses the term "neuropathology" while the psychiatric researchers above make the triple-network sound like a psychological construct and uses the term "psychopathology".
Yes, exactly, jimells. You can interpret this stuff any way you like. It suffers from the reverse inference problem, because the networks being described govern so many types of mental processes, and you can cherry pick the ones you think might be relevant to your study.

So easy to use this kind of evidence to confirm your preconceptions. In fact, I'd challenge anyone to come up with an instance where a network connectivity measure could actually distinguish between two opposing explanations for an illness/disorder.

Also, its all a huge fishing expedition. You take two groups (even two groups of "normal" people), and you'll get some differences. So many opportunities, you see, to find differences. And one of them is sure to fit your hypothesis, because we only have a very vague notion of what these networks do..

Until we can come up with a way of generating predictions about these measures ahead of time, and then seeing whether our predictions are supported, I think this method is descriptive only, and can only be used to look for non-specific "markers" of different illnesses (it doesn't speak to their causes yet).
 

searcher

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I spoke a lot with the Zinns as the Stanford conference and have kept in touch. I don't think it's fair to call it a fishing expedition, although I agree that there doesn't seem to be a way to determine root causes. They made some observations from looking at individuals, then were able to easily differentiate between 50 patients and 50 controls. I don't think they have compared with other diseases (which they mention in this full paper), so I believe it's an open question if they could differentiate between an ME patient and an MS patient for example. There have been remarkable similarities between patients though, and the differences are not subtle when compared to healthy controls.
(Full disclosure: I am one of the CCC patients in this study.)
 
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I don't think it's fair to call it a fishing expedition
The term "fishing expedition" is often used to describe a study that doesn't test any predictions derived from theory, but instead runs multiple analyses and comparisons to see what comes out significant (or any study that pretends to have a prediction, but they actually only came up with that after they looked at the data). So technically speaking, the term does apply to the Zinn study as well as most other connectivity studies.

This is an okay approach to exploring an area we don't know anything about yet. But the problem with fishing expeditions is that you have to be careful of false positives: if you examine enough variables, something will come out as significant, and this may be by chance alone.

So to be sure you have something real, you have to replicate many, many times. We've found in the past in cognitive neuroscience that many such studies don't replicate, so there is something very real to worry about here.

Not saying the research is a waste of time - you might eventually find a "signature" of the disease this way - but the problems i mentioned are things people might like to know when deciding how much to read into the findings.

I agree with you that appropriate control groups are vital. Especially one with similar physical symptoms/disability severity (so we know what's really the ME and what's more general effects of chronic illness). Or better still, la large ME group that varies in the cognitive complaints, then you look for a relation between cognitive complaint and neural signature.

PS interested in full paper - the one I read only had 9 participants in each group.
 
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searcher

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To clarify I believe that they had a model of what they thought was wrong in patients' brains before they looked at the qEEG. Marcie has ME (which she is open about) which helped her come up with a theory about what could be causing some of the cognitive impairment due to her expertise in qEEG. I totally agree about control groups that would be very important for proving that this is a reliable, meaningful test. One point they have made is that they don't think this can be a stand-alone test because of similarities with other neurological diseases, but I don't think they know that for sure. As is basically always the case, we need much more research and bigger studies to confirm these pilot studies.

I wrote a little about the recently published case study and the 50/50 research at http://www.meaction.net/2016/02/07/case-study-brain-fog-in-cfs-can-be-seen-in-qeegloreta-analysis/. The 50/50 study was at Stanford and is unpublished as is most of the recent Stanford research. I think that led to them doing a smaller study at DePaul to ensure that the findings could be published. The two abstracts that they presented at IACFS/ME and Stanford can be found at the bottom of http://iacfsme.org/PDFS/2014Syllabus25.aspx#page=44.

These findings are consistent with some outside research. I just saw that Cort posted about the research at www.cortjohnson.org/forums/threads/two-studies-capture-the-brain-drain-in-chronic-fatigue-syndrome-me-cfs.3658/
 

Kati

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I wrote a little about the recently published case study and the 50/50 research at http://www.meaction.net/2016/02/07/case-study-brain-fog-in-cfs-can-be-seen-in-qeegloreta-analysis/. The 50/50 study was at Stanford and is unpublished as is most of the recent Stanford research. I think that led to them doing a smaller study at DePaul to ensure that the findings could be published. The two abstracts that they presented at IACFS/ME and Stanford can be found at the bottom of http://iacfsme.org/PDFS/2014Syllabus25.aspx#page=44.

@searcher Help me understand why the big study has not published, and why most of the recent Stanford research is not published? (Feel free to start another thread or PM me if you feel this is too out of topic)
 

searcher

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Honestly, I don't know. Marcie Zinn doesn't know either, at least from what she told me. I believe a few people are reaching out to Dr Montoya and others to try to understand.
 

siggycat

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CEN, SN, and DMN are pretty mainstream. The idea is is that the DMN (default mode network), is a network of structures that's highly active when people are at rest and thinking their own thoughts.

The SN (salience network), on the other hand, is a system that alerts the person to start taking an interest in things going on outside of them, and therefore to switch from primarily internal, default mode network (DFN) thinking to more active processing of incoming info. The active thinking is believed to be governed by the CEN (central executive network).

So in other words, the three networks kind of work together to control a person's mode of thinking.

What isn't clear is what variations in connectivity within these networks actually means, and what the causal factors are. Researchers are reporting differences in different pathological groups all over the place. Then they try to work backwards, and say "well, this network is not normal because people are too busy thinking of X or can't think of Y" (or whatever). Its all very hand-waving, and can be interpreted in any way you fancy really.

This study use 9 participants, which isn't enough in my view when you're trying to establish a group difference.
 

siggycat

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Boise, Idaho
Why not read about brain networks yourself? You may also want to acquaint yourself of the process by which neuroscience operates. Didn't they say "pilot?" I think it was somewhere in the title, if I am not mistaken. Pilot studies are underfunded, and therefore have low numbers of people. Most imaging studies, pilot or not, have only a handful of people in them.
 

siggycat

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Boise, Idaho
After just now reading all of these comments, I cannot help but wonder what the authors of them would do to show the cognitive problems in ME/CFS. I wonder what they would study, how they would study it, and what they predict would be the outcome? I for one am so very relieved that this work is being done. I guess I know something about the process. I have always understood that science works this way--compare people who have a disease (and no other disease) with others who do not have any disease.
 

adreno

PR activist
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4,841
The fMRI studies are somewhat interesting. They do show some problems in brain functionality, however the findings are not specific to ME/CFS, as other disease states also show hypoconnectivity. Perhaps it will become more specific in the future.

The main criticism I have of these kind of studies is that they show no causation. Okay, so we can see hypoconnectivity in some brain networks, but the problem is we don't know why. It simply seems to be a feature of our (and other) diseases.
 
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After just now reading all of these comments, I cannot help but wonder what the authors of them would do to show the cognitive problems in ME/CFS. I wonder what they would study, how they would study it, and what they predict would be the outcome? I for one am so very relieved that this work is being done.
@siggycat, welcome to PR! Please don't feel we don't appreciate the research people are doing. Its just that here is a place we can discuss and critically evaluate the research. We're tough here on research done by the psychological medicine folks (like PACE), aren't we? So it wouldn't be balanced not to give other research a similar careful analysis.

On your point about how to go about designing a tighter study, one suggestion I raised above - and I think the authors mentioned too - was to treat the cognitive problem as the key outcome variable, and then see whether certain connectivity patterns correlate with scores on that variable. So for example, if you're interested in cognitive slowing, you develop a behavioural measure of slowing (perhaps measure how quickly people do a task that involves responding to or monitoring something). Then you see whether those that score badly on this task have a more marked signature on your key connectivity analysis.

I guess I know something about the process. I have always understood that science works this way--compare people who have a disease (and no other disease) with others who do not have any disease.
The problem with this is that then your two groups differ on a lot of other things other than the thing of interest - which in this case is cognitive dysfunction. So people with ME are unlikely to feel as good about the world as those who are normal - its a tough disease to have - and they are more likely to feel unwell during the EEG too (which will also impact on connectivity results).
 
Messages
3,263
To clarify I believe that they had a model of what they thought was wrong in patients' brains before they looked at the qEEG. Marcie has ME (which she is open about) which helped her come up with a theory about what could be causing some of the cognitive impairment due to her expertise in qEEG. I totally agree about control groups that would be very important for proving that this is a reliable, meaningful test. One point they have made is that they don't think this can be a stand-alone test because of similarities with other neurological diseases, but I don't think they know that for sure. As is basically always the case, we need much more research and bigger studies to confirm these pilot studies.

I wrote a little about the recently published case study and the 50/50 research at http://www.meaction.net/2016/02/07/case-study-brain-fog-in-cfs-can-be-seen-in-qeegloreta-analysis/. The 50/50 study was at Stanford and is unpublished as is most of the recent Stanford research. I think that led to them doing a smaller study at DePaul to ensure that the findings could be published. The two abstracts that they presented at IACFS/ME and Stanford can be found at the bottom of http://iacfsme.org/PDFS/2014Syllabus25.aspx#page=44.
Okay, thanks, @searcher. I guess maybe some of that theory stuff of Marcie's ever made it into the paper we've got here. Looks like there must be another, much bigger paper coming out soon.
 

Marco

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Thanks @Woolie

Yes I'd come across the default network mode before and the others are pretty much what they say on the tin. The problem I have is that, while they sound impressively 'sciencey', it reminds me of many psychological concepts where they commit the nominal fallacy of naming something but not really explaining it.

I may be wrong, but, as per @adreno I just wonder what these observations can tell us about the underlying pathophysiology?