A – Sensory Gating Deficits and Neuroinflammation in ME/CFS – A Testable Hypothesis

  • Part I – Sensory Gating – Set out a hypothesis that, if tested, ME/CFS patients (in particular those patients that would describe themselves as the ‘Wired and Tired’ type) might be found to have a sensory gating deficit which might explain various symptoms not often discussed in ME/CFS literature.  These include various sensitivities to light, sound, touch, smell, etc., that might be considered to be a kind of sensory defensiveness and which can lead to sensory overload.  Part I also identified a range of conditions (including those involving pain, mood disorders, neuropsychiatric and neurodegenerative disorders) that are already known to result in sensory gating deficits and, while usually considered to be discrete and separate disorders, they all appeared to share common underlying pathophysiologies including immune perturbations, oxidative stress and mitochondrial dysfunction (all of which have been identified in ME/CFS).  One small study (described in a dissertation) had examined sensory gating in adolescent ME/CFS patients and significant results were found after controlling for other variables.
  • cycle symbol

    Is a self-perpetuating neuroinflammatory cycle causing chronic fatigue syndrome?

    Part II – Glutamate – Identified a neuroinflammatory ‘vicious cycle’ that could underlie most if not all of the conditions associated with a sensory gating deficit (with diabetes/metabolic syndrome also showing an association).  Glutamate (or more precisely an imbalance between glutamate and GABA) is increasingly implicated in these conditions and in ‘mental fatigue’ and various encephalopathies, which may result in a self-perpetuating cycle of glutamate excitoxicity, oxidative stress, and mitochondrial dysfunction.  It was suggested that such a vicious cycle might be the underpinning pathology in ME/CFS. CORT – IS excitoxicity REALLY A WORD?

  • Part III- Stiff Person Syndrome– Described stiff person syndrome, a rare and disabling condition in which a glutamate/GABA imbalance results in both mood/neuropsychiatric symptoms and significant physical disability including painful muscle spasms that can be triggered by various sensory or other stressors.  Part III also discussed how stiff person syndrome is believed to be of autoimmune origin but may also have a viral trigger – a mechanism which may also underlie some alleged psychiatric disorders and may play a role in ME/CFS.
  • Part IV- Neuroinflammation – Attempted to show how such a neuroinflammatory process could explain not only the cardinal and minor symptoms of ME/CFS (and those ‘atypical’ symptoms that started this inquiry) but also those consistent biological findings that point to a multi-systemic illness but for which, at present, no unifying process has been confirmed.  It also suggested that the neuroinflammatory state underlying ME/CFS is not benign – resulting only in ‘dysperception’ of sensory inputs – but that over time it may lead to progressive nerve damage resulting in various peripheral and autonomic neuropathies, and may also hasten the development of a range of inflammatory/degenerative conditions usually associated with aging.

I believe what I have set out is plausible, but I accept that the whole model depends initially on confirmation that ME/CFS patients do indeed share a sensory gating deficit with those other conditions, and that this may be a measurable artifact of a shared neuroinflammatory state.  I also accept that one study described in a student dissertation is flimsy evidence on which to build a case, and consequently stated that a sensory gating deficit in ME/CFS remains a ‘testable hypothesis’.

Sensory Gating in ME/CFS – ‘Made in Japan’

“The findings in the present study were consonant with the hypothesis that patients with CCFS have brain dysfunction”

When I first started to look into what might be causing the various ‘sensory processing’ abnormalities in ME/CFS (well over a year ago) I was happy that I had practiced ‘due diligence’ – using terms commonly used in sensory gating paradigms including ‘sensory gating’, PPI, ERP, P50, Startle, CFS, ME, etc., to search the (mostly Anglophone) published literature – in attempting to identify any existing research that might support or refute the notion of a sensory gating deficit in ME/CFS

What I hadn’t counted on was that (a) a key publication might not include any of these exact terms in its title and (b) would originate from outside the western hemisphere.  It was only by luck that I came across the published research that will be the subject of most of the following discussion.

Event-related potentials in Japanese childhood chronic fatigue syndrome. Akemi Tomoda, Kei Miyuno, Nobuki Murayama, Takaka Joudoi, Tomohiko Igasaki. Journal of Pediatric Neurology,  January 2007. http://iospress.metapress.com/content/w14pg23t125337q8/

Not just any ME/CFS Study

filling in the pieces of a wall

This large and comprehensive study included tests for sensory gating, autonomic functioning and cognition.

This is an unusual study for several key reasons:

  • First, and most important, it is a large study (by ME/CFS standards) with 414 patients and 190 age-matched healthy control subjects;
  • The study focused on childhood chronic fatigue syndrome (CCFS). Patients were 9 to 18 years of age, and all met the CDC Fukuda criteria with the numbers of males and females roughly equal;
  • Rather than focusing on one single measure and testing one hypothesis, the researchers simultaneously measured cognitive function/information processing; autonomic function, and frontal lobe function, all of which have been reported to be impaired in ME/CFS;
  • Rather than simply carry out ‘group comparisons’ between all CCFS patients and all controls, they were able to measure individual responses. On the basis of these, as will be discussed further below, they were able to objectively identify two distinct subgroups within this CCFS cohort.

The same researchers (Tomoda, et al., 1995, 2000) have previously noted decreased regional cerebral blood flow and a “remarkable elevation of the choline/creatine ratio” in CCFS patients.  The latter finding has also been associated with brain tumours, with autism (Sokol et al., 2008) and in inflammatory processes such as ischemia (Hesselink, undated) – a condition involving glutamate toxicity (Ischemic cascade – Wikipedia).

Tomoda, et al., however concluded that these findings did not necessarily indicate a high level cognitive processing deficit.  The current study was intended to investigate such a deficit.


P300 ERP – Oddball paradigm

This does sound a little ‘oddball.  P300 ERP  is a measure of cognitive function, specifically attention ‘allocation’ (the orienting of attention), and information processing (efficiency/reactivity) to stimuli.

In this test a small number of ‘target’ stimuli are presented at random among a larger number of ‘non-target’ stimuli. The subjects are asked to respond (usually via a button press) when a target is detected.  In this case visual stimuli were used with a circle as the target and a cross as the non-target.

Each individual’s responses to these stimuli were measured as ERPs (event related potentials, which are brain electrical signals detected by electrodes) which you may recall from Part I is one of the measures used to investigate sensory gating. P300 refers to the time in milliseconds from the stimulus onset to the peak brain response.

The task requires both maintaining attention to the task of detecting target stimuli and discriminating between target and non-target.  Both amplitude (the peak signal) and latency (time taken for peak response) were measured following each target or non target stimulus.

Compared to the gating measures discussed in Part I which involved the early ‘gating out’ of irrelevant stimuli, this is a later, higher level measure of ‘gating in’ where attention is oriented towards novel (comparatively rare) target stimuli.

Autonomic Function – ECG ‘RR’ Intervals

Electrocardiograph (ECG) measurement of heart RR (beat to beat) intervals (Wikipedia – Heart Rate Variability) is intended to measure the ratio between the sympathetic and parasympathetic sides of the nervous system, with the  low frequency component (LFC) reflecting the sympathetic and the high frequency component (HFC) the parasympathetic system.

ying yang symbol

This study examined whether the ‘ying/yang’ of the autonomic nervous system was in balance

While often considered to be complementary excitatory (sympathetic) and inhibitory (parasympathetic) facets of the autonomic nervous system, with a few exceptions it is now considered that these two systems work interactively:

“the sympathetic nervous system is a ‘quick response mobilizing system’ and the parasympathetic is a ‘more slowly activated dampening system’.

“For an analogy to an automobile, one may think of the sympathetic division as the accelerator and the parasympathetic division as the brake. The sympathetic division typically functions in actions requiring quick responses. The parasympathetic division functions with actions that do not require immediate reaction. The sympathetic system is often considered the ‘fight or flight’ system, while the parasympathetic system is often considered the ‘rest and digest’ or ‘feed and breed’ system.”  (Wikipedia – Autonomic Nervous System)

The ratio between the LFC and HFC components therefore represents the balance between the sympathetic and parasympathetic nervous system.

KANA Pick Out Test

This test is widely used in Japan to test frontal lobe function in conditions such as Parkinson’s Disease and dementia to assess both short term working memory and executive function/multi-tasking (impairments in both of which have frequently been reported in ME/CFS).

Kana are Japanese written symbols which equate to vowels.  The test requires subjects to read a short passage (in this case a fairy tale) for comprehension while simultaneously being required to indicate which vowel symbols (Kana) appear in the text.  Subjects are scored on both vowels identified and overall story comprehension.

The test can also be interpreted as simultaneously measuring a continuous task (ongoing comprehension of the story) and a discrete task (identifying vowels).

Compared to a single task, the simultaneous dual task requires far greater mental resources, and some have proposed that poor performance on this dual task may reflect a cognitive processing ‘bottleneck’ (Tachibana et al., 2012).

“Diminished performance during dual tasks, compared to performance of separate single tasks, is attributed to the allocation of limited resources to attend to and perform competing task requirements.”

You may also recall Rönnbäck and Hansson’s description of mental fatigue resulting from continuous mental effort without a break, which was discussed in Part II : .

“a decreased ability to intake and process information over time. Mental exhaustion becomes pronounced when cognitive tasks have to be performed for longer time periods with no breaks (cognitive loading).”


Cognitive Function – P300 ERP

As mentioned above, in measuring cognitive function, these researchers did not just test group differences for significance, but tested each individual patient against the mean values for healthy controls on the two measures of P300 – amplitude (peak response) and latency (time taken to respond).  An abnormal response (i.e., a significant difference between a patient’s score and controls) was defined as being two standard deviations outside the mean value of  the corresponding data from the controls.

The investigators approach made it easier for subsets, if they were present, to show up....and they did.

The investigators approach made it easier for subsets, if they were present, to show up….and they did.

To put this in perspective, if they had been measuring intelligence (IQ), to be considered ‘abnormal’ a patient’s score would have to be either below 70 (borderline deficient) or above 130 (very superior intelligence) compared to the mean of 100 and a standard deviation of 15.

This approach turned out to be key to identifying three patient subgroups which may not have been recognized if they had just compared the CCFS group as a whole against normal controls. Particularly, as will be seen, on some measures the subgroups trended in opposite directions.

The results for all the measures have been tabulated below.

Patient subgroups compared to healthy controls

Type I (n=40) Type II (n=49) Type III (n=325) All Patient Groups
ERP Amplitude (Target) Lower than controls Higher than controls Below threshold of significance No difference
ERP Amplitude (Non-Target) Lower than controls Abnormally increased Below threshold of significance Increased amplitude
ERP Latency to target Abnormally prolonged Reduced Reduced Reduced latency
Low/High Autonomic ratio Very low parasympathetic Low parasympathetic Very low parasympathetic Low parasympathetic
Kana pick out test 25% 75% 50% Lower than controls

All CCFS Patients

As can be seen, for the CCFS patients as a whole, on the ERP measure there was no difference between them and healthy controls on the response amplitude (strength of response) to the target stimulus, while the overall CCFS response to the non-target stimulus was higher than that of healthy controls.

In terms of latency (time taken for peak response to stimuli), CCFS patients responded quicker as a group than healthy controls.

However, these group results largely mask some very significant findings.

Poles Apart? The Hyper/Hypo-active Subsets….

One group (termed Type I and comprising 40 patients) had an abnormally prolonged latency (a slower time to respond) compared to controls, and the strength of response (amplitude) to both target and non-target stimuli was lower than controls.

In contrast another sub-group (termed Type II and comprising 49 patients) had an abnormally increased response (amplitude) to the non-target stimulus compared to controls, while their response to the target stimulus was also increased and the latency (time to respond) to the target stimulus was reduced.

In summary, Type II showed pretty much the opposite picture to Type I.

The remaining 325 patients whose responses were not found to be statistically abnormal compared to controls were termed Type III; however, as discussed below, their status on other measures was far from ‘normal’.

Part III of the Neuroinflammatory Series made the observation that ME/CFS may comprise subgroups in a similar fashion to attention deficit/hyperactivity disorder, which includes the  inattentive, hyperactive and mixed or combined subgroups.

It’s interesting to note that (without having a theoretical rationale outside of hypothesized maladaptive patterns of thinking and behaviour) some biopsychosocial researchers have suggested two broad types of behaviour in ME/CFS – an avoidance/inactivity pattern and a hyperactive pattern leading to ‘boom and bust’ (PACE Manual for Therapists V2, 2004).

Autonomic Function.  Sympathetic/Parasympathetic Ratio

As with other findings CCFS patients, as a group, showed evidence of autonomic dysfunction. (Freeman and Komaroff, 1997; Newton et al., 2007;  Beaumont et al., 2012).  CCFS patients had low parasympathetic function, or in other words, sympathetic dominance which reflected a sustained response from the ‘fight and flight’ side of the autonomic nervous system.

It’s interesting that both Type I and Type III subgroups had ‘very low’ parasympathetic function while type II was just ‘low’.

Frontal Lobe Function

From our own experience and numerous anecdotal reports (not to mention the cognitive deficits stated in the various case definitions), cognitive deficits are common in ME/CFS, yet the results of studies have been mixed with some researchers concluding that patients’ reports of the severity of cognitive deficits are not matched by objective findings outside of slowed processing speed (Scheffers et al., 1992; Wearden, Appleby, 1996) while others have suggested that any cognitive problems may be due to co-morbid depression.  Recent studies, however, have successfully shown that cognitive deficits in ME/CFS may appear by some measures to be subtle, but are ‘real’ whether or not ‘co-morbid’ mood disorders are present (Constant et al., 2011;  Cockshell, Mathias, 2013).

Again, the finding of three subgroups in this cohort with, in some cases, results which trended in opposite directions may have contributed to previous negative or apparently inconsequential findings.

When scores were summed for mistakes made in either story comprehension or vowel identification, healthy controls made no errors and consequently scored 100%.

Startling Cognitive Deficits Found

brain with life preserver

The cognitive tests used in this study revealed a severe level of cognitive dysfunction

The performance deficits found in the CCFS patients were startling with the best performing patients scoring only 75% and the worst 25%.  Even a 25% reduction in important cognitive abilities such as short-term memory and executive function should be a major cause for concern, but a loss of 75% of these functions must be devastating, particularly in children (whose cognitive abilities are still developing).

Executive Functioning – higher level processes that control and manage “planning, working memory, attention, problem solving, verbal reasoning, inhibition, mental flexibility, task switching and initiation and monitoring of actions” (Executive Functions, Wikipedia)

To put these findings into perspective, the Kana Pick Out Test was originally used to test for cognitive impairments in dementia, and while frontal lobe dysfunction in isolation is considered to represent ‘mild’ dementia or ‘mild cognitive impairment’, it affects many everyday activities and is defined by the Mayo Clinic as follows :

“Mild cognitive impairment (MCI) is an intermediate stage between the expected cognitive decline of normal aging and the more serious decline of dementia. It can involve problems with memory, language, thinking and judgement that are greater than normal age-related changes.”

Bear in mind that these were children between 9 and 18 years of age whose cognitive abilities should be developing and not showing deficits in excess of those usually found in the elderly!


“their higher nervous system has deteriorated as demented subjects were previously reported to have longer P300 latencies”

I don’t intend here to go much beyond what the researchers have concluded.

Type I –Slower and Less Efficient Cognitive Functioning

Reduced ERP amplitude and prolonged latency (as seen in the Type I subgroup) has been reported in fibromyalgia patients (Alanoğlu et al., 2005), in schizophrenia and bipolar disorder (O’Donnell et al., 2004), major depression (Işıntaş et al., 2012), adult ADHD (Szuromi et al., 2011) and multiple sclerosis (Honig et al., 1992) and these findings are also associated with aging and Alzheimer’s Disease. This suggests conditions such as schizophrenia and bipolar disorder may also involve neurodegeneration (Mathalon et al., 1999) as appears to be the case with ADHD (Szuromi et al.).

Similar deficits in cognitive function as measured by P300 ERP have also been found in the (currently unaffected) children of Alzheimer’s patients suggesting a familial predisposition to neurodegeneration (Ally et al., 2006).

Generally a reduction in amplitude and prolonged latency suggests slower and less efficient cognitive function as would be expected in aging and dementia.

Type II –  The ‘Wired and Tired’ Group

“their nervous system has an abnormal, hypersensitive reaction: a nervous state”.

nervous image

The sensory gating tests suggested the nervous system of the ‘wired and tired’ group was in a ‘nervous state’

Increased amplitude of P300 ERP (as found with the Type II patients) has been previously associated with phobia, panic disorder, generalized anxiety disorder (GAD) and ‘introversion’ while reduced latency ( also seen with type II) may suggest higher cognitive function (compared to prolonged latencies) but is also associated with obsessive compulsive disorder (Sur, Sinha, 2009). (P300 ERP findings for visual stimuli in autism spectrum disorder (ASD) are mixed, perhaps reflecting the ‘spectrum’ nature of the disorder, but early ERP responses (signals with latency less than 300 ms) are also exaggerated for ‘non-target’ stimuli (Baruth et al., 2010).

It’s notable that P300 ERP amplitude normally increases with novelty and salience (or meaningfulness) of the stimuli, and that in PTSD increased amplitude is only found when the stimulus is relevant to the original trauma.  In these Type II patients, the fact that the ERP amplitude was abnormally increased for non-target stimuli suggests a general state of ‘hyper-arousal’ where even irrelevant and common stimuli evoke a strong (and rapid) response.  Clearly (in terms of this measure) these patients appear to fit the ‘Wired and Tired’ ME/CFS type.

TYPE III – Trending ‘Wired and Tired’

Type III patients represent by far the largest group.  While findings for this group were not statistically abnormal and the paper provides few details, it is possible to make some inferences:

If their responses were essentially neutral (not long or short latency or not high or low amplitude) then the overall mean response would be skewed in the direction one of the ‘extreme’ groups (Type I or II where one of the responses was significantly abnormal where in numerical terms both groups are almost identical).  This may be the case with ERP amplitude in response to non-target stimulus, as group II had a statistically abnormally increased amplitude and the amplitude for all patients was also increased but not significantly.

However, as regards latency, all patients showed reduced latency but group I was the only significantly abnormal group and demonstrated prolonged latency.

This strongly suggests that, on the ERP measures, the Type III group trended in the direction of the Type II ‘Wired and Tired’ type.

Autonomic dysfunction – Sympathetic Dominance…. (again)

A reduction in the ratio of the parasympathetic (rest and digest) to sympathetic (fight and flight) autonomic components (along with reduced heart rate variability and vagal tone) has been associated with ASD (Ming et al., 2005), schizophrenia (Fujibayashi et al., 2009), bipolar disorder (Latalova et al., 2010), major depression (Carney et al., 2005), PTSD (Sherin, Nemeroff, 2011), fibromyalgia, IBS (Manabe et al., 2009) and Huntington’s Disease (Ahmad, Roos, 2010).

Intriguingly, (as with the P300 ERP findings in Alzheimer’s) unaffected first degree relatives of those with schizophrenia also had similar autonomic dysfunction, perhaps reflecting a shared genetic predisposition for both conditions (Bär et al., 2010).

Of note also is that autonomic symptoms may precede cognitive deficits in Huntington’s Disease, and autonomic dysfunction in major depression may be worsened by some antidepressants (Koschke et al., 2009).

SNS model

As in other ME/CFS studies the sympathetic nervous system (fight/flight) system was dominant

Sympathetic dominance is also associated with metabolic syndrome (which as seen in Part II has been linked with ME/CFS) and indeed may predict the onset of metabolic disorders (Lict et al., 2013) :

“Increased sympathetic activity predicts an increase in metabolic abnormalities over time. These findings suggest that a dysregulation of the autonomic nervous system is an important predictor of cardiovascular diseases and diabetes through dysregulating lipid metabolism and blood pressure over time.”

As previously discussed on Health Rising, this pattern of autonomic dysfunction (as well as being associated with the above conditions) may predict increased mortality in a range of conditions and is a risk factor for cardiovascular disease.

Frontal Lobe Function

The results of the KANA Pick Out Test speak for themselves.  Even the best performing group (Type II) had a 25% deficit compared to healthy controls while the Type I group with a 75% deficit might well merit a description in terms of  IQ of at least ‘borderline deficient’.

Needless to say, deficits in functions associated with the frontal lobe such as executive function are found in most, if not all, of the ‘behavioural’ (ASD, ADHD, OCD, PTSD), ‘mood’ (Schizophrenia, MDD, Bipolar disorder, anxiety disorders) and neurodegenerative diseases (Alzheimer’s, Huntington’s, etc.) but also in ‘pain’ disorders such as fibromyalgia and IBS.  Unfortunately direct comparisons are not available as the Kana Pick Out Test appears to be used in few of these conditions outside of the neurodegenerative ones.

What did the researchers conclude?

These researchers certainly didn’t mince words in their interpretation of their findings.  They suggest that these results may reflect a high order brain function abnormality:

“…abnormal P300 patterns and frontal dysfunctions might be associated with a high-order brain function abnormality in patients with CCFS”


“The findings in the present study were consonant with the hypothesis that patients with CCFS have brain dysfunction”

Type I – They infer that in these patients:

“their higher nervous system has deteriorated as demented subjects were previously reported to have longer P300 latencies”

While these findings are correlational (that is, they can’t prove that CCFS is responsible) they do suggest that these young patients may have a learning dysfunction and also highlight the potential that these children may subsequently  be (or may have been) diagnosed with inattentive type ADHD.

Type II – With a shortened P300 latency and abnormally high response to non-target stimuli, they suggest that these patients:

“… might be a hypersensitive type with phobia” and that “their nervous system has an abnormal, hypersensitive reaction: a nervous state”.

They further suggest that these patients may be at risk of later developing ‘psychiatric’ conditions such as anxiety disorders.

Subgroups – Will the ‘Real ME’ Please Stand Up?

As previously discussed, the issue of ‘heterogeneity’ has dogged ME/CFS research for decades.

What then to make of objective findings that two subgroups (Types I and II) might exist within a single Fukuda defined cohort that shows abnormal cognitive function but in opposite directions? Remarkably, both groups also show similar deficits in autonomic and frontal lobe function with Type I having more severe deficits, Type III intermediate, and Type II the least affected.

Are these subgroups all part of the same illness but representing different variants e.g., does ME/CFS consist of subgroups analogous to the inattentive, hyperactive or mixed types in ADHD?

Which if any of these subgroups (if any) represents the ‘true ME’ (if such a thing exists)?

Previously I proposed that the ‘Wired and Tired’ ME/CFS type  (i.e., the “abnormal, hypersensitive reaction” found in Type II) might be due to a hyperglutamatergic neuroinflammatory state.  What, then, to make of the Type I patients with their turned on ‘fight or flight’ response but their hypoactive nervous system functioning?

Do different pathophysiologies underlie these two types or can a single mechanism explain both as well as the apparently intermediate Type III?


Some suggest that rather than being discrete subgroups, the various types of ADHD (inattentive, combined and hyperactive) may represent a progressive deterioration  with a hyperactive state giving way over time to an inattentive one. This may explain progressively reduced ERP amplitudes found as ADHD patients age (Szuromi, 2011), which reflect lower cognitive efficiency, and may result from a similar neurodegenerative process as found in Alzheimer’s Disease, schizophrenia, and to a lesser extent in normal aging.  This might be expected with a (largely untreated) neuroinflammatory vicious cycle.

cascade shot

Is ME/CFS a progressive disorder that sometimes flips from a hyper-active to a hypo-active state?

Similarly, the findings of the comparatively unresponsive nervous system in Type I patients (very low parasympathetic activity, very poor frontal lobe functioning) could reflect not subtypes with a different pathophysiology, but progressive deterioration in brain function which causes the group to pass from the ‘Wired and Tired’ Type II stage to Type I, with Type III being an intermediate stage. This scenario is consistent with a chronic neurotoxic neuroinflammatory state that may lead to progressive disability, and/or a condition that may initially present with variable levels of severity.

A number of studies have identified autonomic dysfunction in ME/CFS and some have associated this with cognitive deficits. This study, however, associates both of these problems with the type of sensory gating/information processing deficits discussed previously which parsimony would suggest are likely to arise from the same underlying pathology.

The relationship between the three measures (or deficits) of course remains to be determined. For example, does autonomic dysfunction lead to a frontal lobe and information processing deficit or vice versa?  How do these findings relate to other consistent findings such as systemic inflammation and immune dysfunction?


Event-related potentials in Japanese childhood chronic fatigue syndrome

Akemi Tomoda, Kei Miyuno, Nobuki Murayama, Takaka Joudoi, Tomohiko Igasaki.



Chronic fatigue syndrome in childhood.

Tomoda A, Miike T, Yamada E, Honda H, Moroi T, Ogawa M, Ohtani Y, Morishita S.Single-



Photon emission computed tomography for cerebral blood flow in school phobia

Akemi Tomoda, Teruhisa Miike, Takako Honda, Keiko Fukuda, Yumiko Kai, Mitsuko Nabeshima, Mutsumasa Takahashi



Hydrogen Proton Magnetic Resonance Spectroscopy in Autism: Preliminary Evidence of Elevated Choline/Creatine Ratio

Deborah K. Sokol, PhD, MD,  David W. Dunn, MD,  Mary Edwards-Brown, MD,  Judy Feinberg, PhD, OT




John R. Hesselink, MD, FACR



Ischemic Cascade




Autonomic Nervous System




Activation of dorsolateral prefrontal cortex in a dual neuropsychological screening test: An fMRI approach

Atsumichi Tachibana, J A Noah, Shaw Bronner, Yumie Ono, Yoshiyuki Hirano, Masami Niwa, Kazuko Watanabe and Minoru Onozuka



PACE Manual for Therapists, MREC Version 2



Does the Chronic Fatigue Syndrome Involve the Autonomic Nervous System?

Roy Freeman, MD, , Anthony L. Komaroff, MD



Symptoms of autonomic dysfunction in chronic fatigue




Reduced Cardiac Vagal Modulation Impacts on Cognitive Performance in Chronic Fatigue Syndrome

Alison Beaumont,  Alexander R. Burton,  Jim Lemon,  Barbara K. Bennett, Andrew Lloyd,  Uté Vollmer-Conna



Attention and short-term memory in chronic fatigue syndrome patients

An event‐related potential analysis

M. K. Scheffers, Drs, R. Johnson Jr., PhD, J. Grafman, PhD, J. K. Dale, RN and S. E. Straus, MD



Research on cognitive complaints and cognitive functioning in patients with chronic fatigue syndrome (CFS): What conclusions can we draw?

Wearden AJ, Appleby L.



Cognitive deficits in patients with chronic fatigue syndrome compared to those with major depressive disorder and healthy controls

Constant EL, Adam S, Gillain B, Lambert M, Masquelier E, Seron X.



Cognitive deficits in chronic fatigue syndrome and their relationship to psychological status, symptomatology, and everyday functioning

Cockshell, Susan J.; Mathias, Jane L.



Executive Functions




Mild cognitive impairment (MCI)

The Mayo Clinic



Auditory event-related brain potentials in fibromyalgia syndrome

Alanoğlu E, Ulaş UH, Ozdağ F, Odabaşi Z, Cakçi A, Vural O.



Auditory event-related potential abnormalities in bipolar disorder and schizophrenia

by B F O’Donnell, J L Vohs, W P Hetrick, C A Carroll, A Shekhar



Event-related potentials in major depressive disorder: the relationship between P300 and treatment response

Işıntaş M, Ak M, Erdem M, Oz O, Ozgen F.



P300 deficits in adults with attention deficit hyperactivity disorder: a meta-analysis

Szuromi B, Czobor P, Komlósi S, Bitter I.



Event-related potential P300 in multiple sclerosis. Relation to magnetic resonance imaging and cognitive impairment

Honig LS, Ramsay RE, Sheremata WA.



P300 reduction and prolongation with illness duration in schizophrenia

Daniel H Mathalon, Judith M Ford, Margaret Rosenbloom, Adolf Pfefferbaum



The P300 component in patients with Alzheimer’s Disease and

their biological children

Brandon A. Ally, Gary E. Jones, Jack A. Cole, Andrew E. Budson



Event-related potential: An overview

Shravani Sur and V. K. Sinha



Early-stage visual processing abnormalities in high-functioning autism spectrum disorder (ASD)

Joshua M. Baruth,  Manuel F. Casanova, Lonnie Sears, and Estate Sokhadze



Reduced cardiac parasympathetic activity in children with autism

Ming X, Julu PO, Brimacombe M, et al.



Autonomic nervous system activity and psychiatric severity in schizophrenia

Fujibayashi M, Matsumoto T, Kishida I, Kimura T, Ishii C, Ishii N, Moritani T.



Autonomic nervous system in euthymic patients with bipolar affective disorder

Latalova K, Prasko J, Diveky T, Grambal A, Kamaradova D, Velartova H, Salinger J, Opavsky J.



Depression, the autonomic nervous system, and coronary heart disease

Carney RM, Freedland KE, Veith RC.



Post-traumatic stress disorder: the neurobiological impact of psychological trauma

Jonathan E. Sherin, MD, PhD,  Charles B. Nemeroff, MD, PhD



Pathophysiology underlying irritable bowel syndrome–from the viewpoint of dysfunction of autonomic nervous system activity

Manabe N, Tanaka T, Hata J, Kusunoki H, Haruma K.



Autonomic Symptoms in Huntington’s Disease – Current Understanding and Perspectives for the Future

N Ahmad Aziz, Raymund AC Roos



Autonomy of autonomic dysfunction in major depression

Koschke M, Boettger MK, Schulz S, Berger S, Terhaar J, Voss A, Yeragani VK, Bär KJ.



Autonomic dysfunction in unaffected first-degree relatives of patients suffering from schizophrenia

Bär KJ, Berger S, Metzner M, Boettger MK, Schulz S, Ramachandraiah CT, Terhaar J, Voss A, Yeragani VK, Sauer H.



Dysregulation of the autonomic nervous system predicts the development of the metabolic syndrome

Licht CM, de Geus EJ, Penninx BW.





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