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Related News: Default Mode Network Acts Up in SchizophreniaComment by: Vince Calhoun
Submitted 27 January 2009
Posted 27 January 2009
In this work the authors test for differences in the default mode network between healthy controls, patients with schizophrenia, and first degree relatives of the patients. They look at both the degree to which the default mode is modulated by a working memory task and also examine the strength of the functional connectivity. The controls are found to show the most default mode signal decrease during a task, with relatives and patients showing much less. The controls, relatives, and patients show increasing amounts of functional connectivity within the default mode regions. In addition, signal in some of the regions correlated with positive symptoms. The findings in the chronic patients and controls are consistent with our previous work in Garrity et al., 2007, which also showed significantly more functional connectivity in the default mode of schizophrenia patients and significant correlations in certain regions of the default mode with positive symptoms, and in both cases the regions we identified are similar to those shown in the Whitfield-Gabrieli paper. Our work in Kim et al., 2009, was a large multisite study showing significantly fewer default mode signal decreases for the auditory oddball task in chronic schizophrenia patients, again consistent with the Whitfield-Gabrieli paper, but in a different task.
The most interesting contribution of the Whitfield-Gabrieli paper is their inclusion of a first-degree relative group. They found that the first-degree relatives are “in between” the healthy controls and the chronic patients in terms of both the degree to which they modulate the default mode, as well as in their degree of functional connectivity. This has interesting implications in terms of the genetic aspects of the illness and suggests that the default mode may be a potential schizophrenia endophenotype. It will be interesting in future studies to examine both the heritability of the default mode patterns and their genetic underpinnings.
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Related News: Default Mode Network Acts Up in Schizophrenia
Comment by: Edith Pomarol-Clotet
Submitted 28 January 2009
Posted 28 January 2009
The Default Mode Network and Schizophrenia
For a long time functional imaging research has focused on brain activations. However, since 2001 it has been appreciated that there is also a network of brain regions—which includes particularly two midline regions, the medial prefrontal cortex and the posterior cingulate cortex/precuneous—which deactivates during performance of a wide range of cognitive tasks. Why some brain regions should be active at rest but deactivate when tasks have to be performed is unclear, but there is intense speculation that this network is involved in functions such as self-reflection, self-monitoring, and the maintenance of one’s sense of self.
Could the default mode network be implicated in neuropsychiatric disease states? There is evidence that this is the case in autism, and a handful of studies have been also carried out in schizophrenia. Now, Whitfield-Gabrieli and colleagues report that 13 schizophrenic patients in the early phase of illness showed a failure to deactivate the anterior medial prefrontal node of the default mode network when they performed a working memory task. They also find that failure to deactivate is seen to a lesser but still significant extent in unaffected first-degree relatives of the schizophrenic patients, and that the degree of failure to deactivate is associated with both the severity of positive and negative symptoms in the patients.
Importantly, the findings of Whitfield-Gabrieli and colleagues are closely similar to those of another recent study by our group (Pomarol-Clotet et al., 2008), which found failure to deactivate in the medial prefrontal cortex node of the default mode network in 32 chronic schizophrenic patients. This is a striking convergence in the field of functional imaging studies of schizophrenia, which has previously been marked by diverse and often conflicting findings. Additionally, in both studies the magnitude of the difference between patients and controls was large and visually striking. These findings suggest that we may be dealing with an important abnormality which could be close to the disease process in schizophrenia.
If so, what does dysfunction in the default mode network mean? On the one hand, failure to deactivate part of a network whose activity normally decreases when attention has to be turned to performance of external tasks might be expected to interfere with normal cognitive operations. Consistent with this, cognitive impairment is nowadays accepted as being an important, or even a “core” feature of schizophrenia. Perhaps more importantly, could it be that default mode network dysfunction can help us understand the symptoms of schizophrenia? As Whitfield-Gabrieli and colleagues note, if the default mode network is involved in self-reflection, self-monitoring, and maintenance of one’s sense of self, then failure of deactivation might lead to an exaggerated focus on one’s own thoughts and feelings, excessive self-reference, and/or a breakdown in the boundary between the inner self and the external world. The default mode network may thus have the potential to account for two major realms of clinical abnormality in schizophrenia—its symptoms and the cognitive impairment that is frequently associated with them.
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Related News: Default Mode Network Acts Up in Schizophrenia
Comment by: Samantha Broyd, Edmund Sonuga-Barke
Submitted 4 February 2009
Posted 4 February 2009
The surge in scientific interest in patterns of connectivity and activation of resting-state brain function and the default-mode network has recently extended to default-mode brain dysfunction in mental disorders (for a review, please see Broyd et al., 2008). Whitfield-Gabrieli et al. examine resting-state and (working-memory) task-related brain activity in 13 patients with early-phase schizophrenia, 13 unaffected first-degree relatives, and 13 healthy control participants. These authors report hyperconnectivity in the default-mode network in patients and relatives during rest, and note that this enhanced connectivity was correlated with psychopathology. Further, patients and relatives exhibited reduced task-related suppression (hyperactivation) of the medial prefrontal region of the default-mode network relative to the control group, even after controlling for task performance.
The findings from the Whitfield-Gabrieli paper are in accordance with those from a number of other research groups investigating possible default-mode network dysfunction in schizophrenia. For example, in a similar working memory task Pomarol-Clotet and colleagues (2008) have also shown reduced task-related suppression of medial frontal nodes of the default-mode network in 32 patients with chronic schizophrenia. However, the findings are at odds with research reporting widespread reductions in functional connectivity in the resting brain of this clinical group (e.g., Bluhm et al., 2007; Liang et al., 2006). As noted by Whitfield-Gabrieli et al., increased connectivity and reduced task-related suppression of default-mode activity may redirect attentional focus from task-related events to introspective and self-referential thought processes. The reduced anti-correlation between the task-positive and default-mode network in patients further supports and helps biologically ground suggestions of the possibility of an overzealous focus on internal thought. Perhaps even more interestingly, the study by Whitfield-Gabrieli and colleagues suggests that aberrant patterns of activation and connectivity in the default-mode network, and in particular the medial frontal region of this network, may be associated with genetic risk for schizophrenia. Although there are some inconsistencies in the literature regarding the role of the default-mode network in schizophrenia, the work of Whitfield-Gabrieli and others suggests that this network may well contribute to the pathophysiology of this disorder and is relevant to contemporary models of schizophrenia. Indeed, the recent flurry in empirical research investigating the clinical relevance of this network to mental disorder has highlighted a number of possible putative mechanisms that might link the default-mode network to disorder. Firstly, effective transitioning from the resting-state to task-related activity appears to be particularly vulnerable to dysfunction in mental disorders and may be characterized by deficits in attentional control. Sonuga-Barke and Castellanos (2007) have suggested that interference arising from a reduction in the task-related deactivation of the default-mode network may underlie the disruption of attentional control. The default-mode interference hypothesis proposes that spontaneous low-frequency activity in the default-mode network, normally attenuated during goal-directed tasks, can intrude on task-specific activity and create cyclical lapses in attention resulting in increased variability and a decline in task performance (Sonuga-Barke and Castellanos, 2007). Sonuga-Barke and Castellanos (2007) suggest that the efficacious transition from rest to task and the maintenance of task-specific activity may be moderated by trait factors such as disorder. Secondly, the degree of functional connectivity in the default-mode network may highlight problems of reduced connectivity, or excess functional connectivity (e.g., schizophrenia), which suggests a zealous focus on self-referential processing and introspective thought. Thirdly, the strength of the anti-correlation between the default-mode and task-positive networks may also indicate a clinical susceptibility to introspective or extrospective orienting. Finally, future research should continue to examine the etiology of the default-mode network in schizophrenia.
Bluhm, R.L., Miller, J., Lanius, R.A., Osuch, E.A., Boksman, K., Neufeld, R.W.J., Théberge, J., Schaefer, B., & Williamson, P. (2007). Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients: Anomalies in the default network. Schizophrenia Bulletin, 33, 1004-1012. Abstract
Broyd, S.J., Demanuele, D., Debener, S., Helps, S.K., James, C.J., & Sonuga-Barke, E.J.S. (in press). Default-mode brain dysfunction in mental disorders: a systematic review. Neurosci Biobehav Rev. 2008 Sep 9. Abstract
Liang, M., Zhou, Y., Jiang, T., Liu, Z., Tian, L., Liu, H., and Hao, Y. (2006). Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging. NeuroReport, 17, 209-213. Abstract
Pomarol-Clotet, E., Salvador, R., Sarro, S., Gomar, J., Vila, F., Martinez, A., Guerrero, A.,Ortiz-Gil, J., Sans-Sansa, B., Capdevila, A., Cebemanos, J.M., McKenna, P.J., 2008. Failure to deactivate in the prefrontal cortex in schizophrenia: dysfunction of the default-mode network? Psychological Medicine, 38, 1185–1193. Abstract
Sonuga-Barke, E.J.S., Castellanos, F.X., 2007. Spontaneous attentional fluctuations in impaired states and pathological conditions: a neurobiological hypothesis. Neuroscience Biobehavioural Reviews, 31, 977–986. Abstract
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Related News: Default Mode Network Acts Up in Schizophrenia
Comment by: Yuan Zhou, Tianzi Jiang, Zhening Liu
Submitted 18 February 2009
Posted 22 February 2009
I recommend the Primary Papers
The consistent findings on default-mode network in human brain have attracted the researcher’s attention to the task-independent activity. The component regions of the default-mode network, especially medial prefrontal cortex and posterior cingulate cortex/precuneus, are related to self-reflective activities and attention. Both of these functions are observed to be impaired in schizophrenia. And thus the default-mode network has also attracted more and more attention in the schizophrenia research community. The study of Whitfield-Gabrieli et al. shows a further step along this research streamline.
The authors found hyperactivity (reduced task suppression) and hyperconnectivity of the default network in schizophrenia, and found that hyperactivity and hyperconnectivity of the default network are associated with poor work memory performance and greater psychopathology in schizophrenia. And they found less anticorrelation between the medial prefrontal cortex and the right dorsolateral prefrontal cortex, a region showing increased task-related activity in schizophrenia, whether during rest or task. Furthermore, the hyperactivity in medial prefrontal cortex is negatively related to the hyperconnectivity of the default network in schizophrenia.
There are two main contributions in this work. First, they found significant correlation between the abnormalities in the default mode network and impaired cognitive performance and psychopathology in schizophrenia. Thus they propose a new explanation for the impaired working memory and attention in schizophrenia, and propose a possibility that schizophrenic symptoms, such as delusions and hallucinations, may be due to the blurred boundary between internal thoughts and external perceptions. Secondly, they recruited the first-degree relatives of these patients in this study, and found that these healthy relatives showed abnormalities in the default network similar to that of patients but to a lesser extent. This is the first study investigating the default mode network of relatives of individuals with schizophrenia. This finding indicates that the dysfunction in the default mode network is associated with genetic risk for schizophrenia.
The findings in schizophrenia are consistent with our previous work (Zhou et al., 2007), in which we also found hyperconnectivity of the default mode network during rest. Considering the differences in ethnicity of participants (Chinese in our study) and methodology, the consistency in the hyperconnectivity of the default mode network in schizophrenia is exciting, which supports the possibility that abnormality in the default-mode network may be a potential imaging biomarker to assist diagnosis of schizophrenia. However, this needs to be validated in future studies with a large sample size, due to other contradictory findings, for example, the reduced resting-state functional connectivities associated with the posterior cingulate cortex in chronic, medicated schizophrenic patients (Bluhm et al., 2007). In addition, further studies should focus on default-mode function in different clinical subtypes, as schizophrenia is a complicated disorder. Finally, it should be noticed that the hyperconnectivity of the default-mode network is not exclusively contradictory with hyperconnectivity in other regions, as we previously found (Liang et al., 2006). It is possible that hyperconnectivity and hyperconnectivity coexist in the brains of individuals with schizophrenia and together lead to the complicated symptoms and cognitive deficits.
Bluhm, R. L., Miller, J., Lanius, R. A., Osuch, E. A., Boksman, K., Neufeld, R. W., et al., 2007. Spontaneous low-frequency fluctuations in the BOLD signal in schizophrenic patients: anomalies in the default network. Schizophr Bull 33, 1004-1012. Abstract
Liang, M., Zhou, Y., Jiang, T., Liu, Z., Tian, L., Liu, H., et al., 2006. Widespread functional disconnectivity in schizophrenia with resting-state functional magnetic resonance imaging. Neuroreport 17, 209-213. Abstract
Whitfield-Gabrieli, S., Thermenos, H. W., Milanovic, S., Tsuang, M. T., Faraone, S. V., McCarley, R. W., et al., 2009. Hyperactivity and hyperconnectivity of the default network in schizophrenia and in first-degree relatives of persons with schizophrenia. Proc Natl Acad Sci U S A 106, 1279-1284. Abstract
Zhou, Y., Liang, M., Tian, L., Wang, K., Hao, Y., Liu, H., et al., 2007. Functional disintegration in paranoid schizophrenia using resting-state fMRI. Schizophr Res 97, 194-205. Abstract
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Related News: Monkey Model of Schizophrenia Debuts
Comment by: Dan Javitt, SRF Advisor
Submitted 30 September 2013
Posted 30 September 2013
This is an important paper that confirms the role of NMDA receptors in the generation of mismatch negativity (MMN) and, by extension, the potential role of NMDA receptors in the pathophysiology of schizophrenia. As in prior studies with MMN in monkeys, the latency of MMN in monkeys appears to obey the 2/3 rule, which allows cross-species scaling of sensory ERP.
Since our initial report of PCP effects on MMN in monkeys in the late 1990s (Javitt et al., 1996) and subsequent reports on ketamine effects on MMN in humans shortly thereafter (Umbricht et al., 2000), the findings have been extensively replicated in humans. This, however, is the first replication in monkeys and the first to use primarily surface electrodes, and so opens the door to more widespread investigation. In particular, studies in humans are limited to acute administration. However, acute administration of NMDA receptor antagonists only captures a portion of the syndrome. In monkeys, chronic administration of NMDA receptor antagonists is possible and is associated with progressive development of negative-like symptoms (Linn et al., 2007).
As in our earlier report, ketamine treatment reduced MMN-related activity but did not affect responses to rapidly presented, repetitive, standard stimuli, reproducing the pattern of deficit observed in schizophrenia. In this initial study, no other classes of compounds were tested. However, establishment of this model permits testing of a wide range of compounds, including pharmacological probes for other classes of glutamate receptors, or from other transmitter systems (e.g., dopaminergic, cholinergic, GABAergic) that have also been implicated in schizophrenia. Especially during subchronic treatment, the ability to reverse MMN deficits may be an important screening model for potentially psychotherapeutic compounds in schizophrenia and other NMDA receptor-related disorders.
Another important issue that can be addressed using monkey models is the nature and identity of the "frontal generator." It is clear from both MEG and intracranial recording studies that primary generators for MMN are in auditory regions of the superior temporal cortex. Additional, frontal generators are also sometimes reported based upon source analysis. However, unless constrained through physiological means, source localizations can easily produce spurious results. This study uses LORETTA, a common source-localization approach, and identifies sources in frontal and anterior cingulate cortices (ACC), as well as in auditory cortex.
Generators in ACC are unlikely in humans, because they should be detectable by MEG. Nevertheless, an obvious follow-up of this study is to implant intracranial electrodes in those regions detected using LORETTA. If local generators are found, it will give renewed understanding about the relationship between auditory and frontal interaction during MMN generation. If local generators are not found, it will permit refinement of the LORETTA approach and reduction in "false positive" localizations that may, of themselves, complicate understanding of disorders such as schizophrenia.
Finally, a goal of biomarker research is the development of measures that can be implemented in relatively simple species, such as rodents. For complex disorders such as schizophrenia, however, it could be that more complex, primate models are required. As opposed to most primate paradigms, MMN can be obtained even in untrained animals, permitting a development path from rodents through primates and into humans.
Javitt DC, Steinschneider M, Schroeder CE, Arezzo JC. Role of cortical N-methyl-D-aspartate receptors in auditory sensory memory and mismatch negativity generation: implications for schizophrenia. Proc Natl Acad Sci U S A. 1996;93(21):11962-7. Abstract
Umbricht D, Schmid L, Koller R, Vollenweider FX, Hell D, Javitt DC. Ketamine-induced deficits in auditory and visual context-dependent processing in healthy volunteers: implications for models of cognitive deficits in schizophrenia. Arch Gen Psychiatry. 2000;57(12):1139-47. Abstract
Linn GS, O'Keeffe RT, Lifshitz K, Schroeder C, Javitt DC. Behavioral effects of orally administered glycine in socially housed monkeys chronically treated with phencyclidine. Psychopharmacology (Berl). 2007;192(1):27-38. Abstract
Javitt DC, Spencer KM, Thaker GK, Winterer G, Hajos M. Neurophysiological biomarkers for drug development in schizophrenia. Nature reviews. 2008;7(1):68-83. Abstract
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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia
Comment by: Hugo Geerts
Submitted 26 August 2014
Posted 26 August 2014
This is a very interesting contribution to improve the understanding of the
progressive nature of schizophrenia pathology. Ketamine-induced effects
have been used for a long time in healthy volunteers or in animal models,
both rodents and non-human primates to "mimic" schizophrenia pathology. The
observation that ketamine mimics more the very early schizophrenia or the
at-risk state but not the more chronic pathology helps to explain the
dissociation between effects of compounds in ketamine-induced deficits and
in chronic schizophrenia, for example, nicotine (D'Souza et al., 2012), glycine
transport inhibitor (D'Souza et al., 2012), haloperidol (Oranje et al., 2009), and lamotrigine (Goff et al., 2007).
The impact of these findings, if reproduced in a longitudinal study, is very
important. This model of ketamine-induced deficit can be used in animals to
test new experimental interventions in very early psychosis or in at-risk
subjects. This is a patient group that is currently underserved in terms of
therapeutic interventions and for which there is great interest. For the
first time, we now have a model that mimics important aspects of the early
schizophrenia pathology, and the hope is that when addressing these changes
with the right medication early on, one could postpone or delay the onset of
overt schizophrenia pathology, which could be the beginning of a preventive
D'Souza DC, Ahn K, Bhakta S, Elander J, Singh N, Nadim H, Jatlow P, Suckow RF, Pittman B, Ranganathan M. Nicotine fails to attenuate ketamine-induced cognitive deficits and negative and positive symptoms in humans: implications for schizophrenia. Biol Psychiatry . 2012 Nov 1 ; 72(9):785-94. Abstract
D'Souza DC, Singh N, Elander J, Carbuto M, Pittman B, Udo De Haes J, Sjogren M, Peeters P, Ranganathan M, Schipper J. Glycine transporter inhibitor attenuates the psychotomimetic effects of ketamine in healthy males: preliminary evidence. Neuropsychopharmacology . 2012 Mar ; 37(4):1036-46. Abstract
Oranje B, Gispen-de Wied CC, Westenberg HG, Kemner C, Verbaten MN, Kahn RS. Haloperidol counteracts the ketamine-induced disruption of processing negativity, but not that of the P300 amplitude. Int J Neuropsychopharmacol . 2009 Jul ; 12(6):823-32. Abstract
Goff DC, Keefe R, Citrome L, Davy K, Krystal JH, Large C, Thompson TR, Volavka J, Webster EL. Lamotrigine as add-on therapy in schizophrenia: results of 2 placebo-controlled trials. J Clin Psychopharmacol . 2007 Dec ; 27(6):582-9. Abstract
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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia
Comment by: Alexandre Seillier
Submitted 9 September 2014
Posted 11 September 2014
The "Ketamine Model" Revived?
Despite the seminal review by Jentsch and Roth arguing that long-term, rather than acute administration of NMDA antagonists, such as phencyclidine (PCP) and ketamine, may more isomorphically model schizophrenia (Jentsch and Roth, 1999), acute ketamine remained one of the most widely utilized pharmacological models in both humans and rodents. Recently, Dawson and co-workers added to the accumulating body of evidence that "alterations in brain circuitry that result from chronic, but not from acute, NMDA receptor blockade most accurately reflect the systems level differences in brain network functioning seen in schizophrenia" (Dawson et al., 2014a; Dawson et al., 2014b). Indeed, using brain network connectivity, they reported that, "at a systems level, the mechanisms through which acute ketamine treatment induces schizophrenia-like symptoms may be profoundly divergent from those that contribute to these symptoms in the disorder."
This new study by Anticevic et al. (2014) might have resolved the paradox of acute ketamine-induced hyperfrontality given the hypofrontality observed in schizophrenia. As previously shown in both healthy humans and mice (Dawson et al., 2014a; Driesen et al., 2013), acute ketamine administration was associated with increased prefrontal cortex connectivity. On the other hand, whereas chronic schizophrenics had reduced prefrontal cortex functional connectivity, patients in the early stage of schizophrenia showed increased prefrontal cortex functional connectivity. As stated by the authors, "these data point to a qualitative difference between NMDAR antagonist and chronic schizophrenia effects, suggesting that ketamine's effect on prefrontal cortex connectivity may be more relevant to particular illness stages."
Longitudinal studies will be necessary to confirm that the "phase of illness is an important moderator of the prefrontal cortex functional connectivity in schizophrenia." The authors also addressed some discrepancies that need to be highlighted. First, the reduced and the increased prefrontal cortex functional connectivity in chronic versus early-stage schizophrenia, respectively, were observed in distinct prefrontal areas, namely the right middle frontal gyrus and the left superior frontal gyrus, respectively. Second, the cross-validation of the pharmacological and clinical analysis failed to reach significance; i.e., acute ketamine did not significantly change connectivity in the regions identified in the clinical study. Although it has limitations, this study should inform the application of acute ketamine as a translational model that may better approximate some early stage of schizophrenia.
Dawson N, McDonald M, Higham DJ, Morris BJ, Pratt JA (2014a) Subanesthetic Ketamine Treatment Promotes Abnormal Interactions between Neural Subsystems and Alters the Properties of Functional Brain Networks. Neuropsychopharmacology 39:1786-98. Abstract
Dawson N, Xiao X, McDonald M, Higham DJ, Morris BJ, Pratt JA (2014b) Sustained NMDA receptor hypofunction induces compromised neural systems integration and schizophrenia-like alterations in functional brain networks. Cereb Cortex 24: 452-464. Abstract
Driesen NR, McCarthy G, Bhagwagar Z, Bloch M, Calhoun V, D'Souza DC et al (2013) Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine. Mol Psychiatry 18:1199-1204. Abstract
Jentsch JD, Roth RH (1999) The neuropsychopharmacology of phencyclidine: from NMDA receptor hypofunction to the dopamine hypothesis of schizophrenia. Neuropsychopharmacology 20: 201-225. Abstract
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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia
Comment by: Albert Adell
Submitted 10 September 2014
Posted 16 September 2014
The paper by Anticevic and co-workers, as well as the commentary by Hugo Geerts, points to a very interesting issue on the similitude of the ketamine model with schizophrenia. In a previous mini-review, we anticipated that it would be conceivable that acute administration of NMDA receptor antagonists would lead to a reversible malfunctioning of PV-containing interneurons, whereas in schizophrenia, a damage of these neurons may take place at early stages of neurodevelopment (Adell et al., 2012). In summary, acute NMDA antagonism would resemble the early stage of schizophrenia, whereas chronic exposure better models the more chronic pathology of the illness.
Adell A, Jiminez-Sanchez L, Lopez-Gil X, Roman T. Is the Acute NMDA Receptor Hypofunction a Valid Model of Schizophrenia? Schizophr Bull 38(1): 9-14. Abstract
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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia
Comment by: Didier Pinault
Submitted 25 September 2014
Posted 26 September 2014
Acute Ketamine Dramatically Amplifies Network Gamma (30-80 Hz) and Higher-Frequency Oscillations
N-methyl D-aspartate receptors play a key role in synaptic plasticity, memory processes, and in the modulation of field oscillations. The non-competitive NMDAR antagonist ketamine has context-dependent and dose-dependent multiple properties, including positive and negative effects. For instance, a single sub-anesthetic administration can disturb cognitive and perceptual processes and induce schizophreniform psychosis in healthy subjects (Krystal et al., 1994; Adler et al., 1998; Newcomer et al., 1999; Hetem et al., 2000); puzzlingly, but of importance, ketamine can generate a durable antidepressant effect in patients refractory to conventional antidepressant therapies (Zarate et al., 2006; Fond et al., 2014; McGirr et al., 2014).
More specifically, Anticevic and colleagues (2014), using brain scans, recently revealed that a single sub-anesthetic administration of ketamine in healthy subjects at rest produces in the prefrontal cortex a state of hyperconnectivity, which resembles that recorded in people in the early stages of schizophrenia but not in patients with chronic (several years' duration) schizophrenia. Also, using fMRI in healthy human subjects, Driesen and colleagues (Driesen et al., 2013) demonstrated that the NMDA receptor antagonist ketamine increases global brain functional connectivity and reduces negative symptoms, suggesting that the ketamine-induced increase in connectivity corresponds to a state of enhanced cortical function. The acute ketamine effects appear quickly (~1-2 minutes) and are transient. In the following, we will see that these fresh clinical findings are consistent with preclinical studies demonstrating that, in rodents, non-competitive NMDAR antagonists increase the amount of field (or network) gamma frequency oscillations (GFOs; 30-80 Hz) in cortical and subcortical regions. In healthy human subjects, ketamine increases the power of GFOs and decreases that of delta oscillations during auditory-evoked network oscillations (Hong et al., 2010).
What does "hyperconnectivity" mean? From clinical imaging studies, functional connectivity is assessed by the degree of correlation between pairwise functional connections from multiple functional cortical and subcortical regions. What does it mean in terms of neural excitatory and inhibitory activities, network oscillations, and cellular firing?
In rodents a single sub-anesthetic administration of ketamine quickly and transiently induces abnormal behavior (hyperlocomotion, ataxia), memory deficits, and abnormally persistent and generalized hypersynchronized (200-400 percent increased power) ongoing GFOs (Ma and Leung, 2007; Chrobak et al., 2008; Pinault, 2008; Hakami et al., 2009; Ehrlichman et al., 2009; Kocsis, 2012). The gamma frequency at maximal power is significantly increased by approximately 10 Hz on average (Pinault, 2008). The amount of ongoing higher-frequency (>80 Hz) oscillations is also increased following a single sub-anesthetic administration (<10 mg/kg) of ketamine (Hakami et al., 2009; Hunt et al., 2006; Kulikova et al., 2012).
In addition, NMDAR antagonists transiently disrupt the expression, not the induction, of long-term potentiation in the thalamocortical system (Kulikova et al., 2012), disorganize action potential firing in rat prefrontal cortex (Molina et al., 2014), increase the firing in fast-spiking neurons, and decrease that in regularly spiking neurons (Homayoun and Moghaddam, 2007). These results suggest that the amount of ongoing GFOs is inversely related to synaptic potentiation in the thalamocortical system (Kulikova et al., 2012). They also suggest that the ketamine-induced state results in part from dysfunction of cortical GABAergic interneurons that would lead to hyperexcitation of projection glutamatergic neurons and to glutamate release (Homayoun and Moghaddam, 2007).
Following the subcutaneous administration of a low dose (<10 mg/kg) of ketamine, both the duration and the amplitude of spontaneously occurring GFOs significantly increase in the rat frontal, parietal, and occipital cortices (Pinault, 2008; Hakami et al., 2009). From a mathematical viewpoint (Cadonic and Albensi, 2014), it was proposed that natural, physiological ongoing GFOs operate like damped harmonic oscillators, which would leave room for synaptic potentiation, learning, and memory, whereas ketamine-induced persistently amplified GFOs run like forced harmonic oscillators, which would disrupt the network ability in information processing and reduce the expression of synaptic potentiation (Pinault, 2014). This might be a key neurophysiological substrate of the functional hyperconnectivity observed by Anticevic and colleagues (2014) and by Driesen and colleagues (Driesen et al., 2013).
There is a growing body of evidence suggesting that the NMDAR antagonist ketamine modulates not only GFOs and higher-frequency oscillations, as mentioned above, but also lower-frequency oscillations, including alpha, theta, and delta oscillations (Ehrlichman et al., 2009; Hong et al., 2010; Palenicek et al., 2011; Tsuda et al., 2007). This broad-spectrum effect depends on the injected dose, the experimental and recording conditions, and on the anatomo-functional properties of the structures under investigation. For instance, under in vivo conditions, a single low-dose (<10 mg/kg) ketamine administration alters specifically GFOs and higher-frequency oscillations (Pinault, 2008; Hakami et al., 2009; Ma and Leung, 2007), while higher doses in addition affect slower rhythms (Ehrlichman et al., 2009; Hunt et al., 2006; Palenicek et al., 2011; Caixeta et al., 2013; Hiyoshi et al., 2014; Nicolas et al., 2011; Buzsaki, 1991). Therefore, we must be prudent when comparing results and inferring mechanisms from studies using different doses of NMDAR antagonists and various and diverse animal and network models. This is fundamental for basic-clinical translational understanding.
Investigating the pathophysiology of schizophrenia in relation to "noise and signal-to-noise ratio" is an appealing basic-clinical translational way to understand the neural mechanisms underlying the multiple symptoms that characterize this complex and heterogeneous neurobiological disease (Rolls et al., 2008). I recently argued on the notion of network signal-to-noise ratio (Pinault, 2014). In any system, both the amount of the ongoing (background or baseline) activity and the amplitude (or power) of its global response to the activation of its inputs are indicators of its state and functionality. The possible noise-signal interplay(s) might in part explain some disparities between findings (e.g., increases and decreases in GFOs in patients with schizophrenia; see SRF Live Discussion organized by Peter Uhlhaas and Kevin Spencer).
More precisely, in the rat thalamocortical system, ketamine simultaneously increases the power of spontaneously occurring GFOs (signature of a change in the state of the system) and decreases sensory-evoked GFOs (signature of a disturbance of the functionality of the system) (Pinault, 2008; Hakami et al., 2009; Kulikova et al., 2012). Assuming that sensory-evoked GFOs include a "true" sensory-related component, the ketamine-induced gamma noise amplification decreases the ability of the thalamocortical system to discriminate the sensory-evoked gamma signal drowned in the noise. In other words, the NMDAR antagonist ketamine decreases the gamma signal-to-noise ratio during sensory information processing. Such a ratio may be considered as a suitable neurophysiological marker of neural networks to evaluate their function and dysfunction.
This dramatically excessive ongoing gamma noise, which might be involved in the ketamine-induced state of hyperconnectivity in healthy subjects (Anticevic et al., 2014; Driesen et al., 2013), is thought to affect global brain state and operation, and to contribute to psychosis. Moreover, continuous and stereotyped GFOs might be responsible for clinical positive symptoms (Llinas et al., 1999). Furthermore, ongoing abnormally hypersynchronized GFOs have been recorded in patients experiencing sensory hallucinations (Baldeweg et al., 1998; Behrendt, 2003; Spencer et al., 2004; Ffytche, 2008; Becker et al., 2009). Hypersynchronized GFOs in cortico-thalamo-cortical systems are thought to play a key role during the appearance of hallucinations (Baldeweg et al., 1998; Behrendt, 2003), raising the question as to whether persistent amplification of ongoing GFOs could somehow conceal function-related GFOs in the corresponding brain networks.
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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia
Comment by: Alan Anticevic, John Krystal (SRF Advisor)
Submitted 8 October 2014
Posted 8 October 2014
Linking Hyperconnectivity Induced via Acute Ketamine to Neuronal Mechanisms and Emerging System-Level Markers in Schizophrenia
We sincerely appreciate the recent engaging commentaries focusing on our paper. The constructive and thoughtful discussion has raised a number of important issues regarding the ketamine model in schizophrenia research. In particular, in the latest commentary Dr. Pinault has noted several hypotheses regarding our findings on which we would like to further comment.
First, what does the observed "hyperconnectivity" represent functionally? Does this "signature" relate to alterations in excitation (E) and inhibition (I) balance in cortical circuits and in turn reflect an elevation in shared signal between prefrontal areas in our analyses? It is important to note that the reported effect builds on basic preclinical studies and studies examining cortical metabolism, which have established that NMDAR antagonism elevates pyramidal cell activity (Moghaddam and Adams, 1998), extracellular glutamate levels (Homayoun and Moghaddam, 2007), cortical metabolism (Breier et al., 1997; Lahti et al., 1995; Lahti et al., 2001; Vollenweider et al., 1997; Vollenweider et al., 2000), and resting-state functional connectivity (Driesen et al., 2013; Pinault, 2008; Driesen et al., 2013). Moreover, a recent influential study by Schobel and colleagues demonstrated that NMDAR antagonism caused elevated "spreading" of hippocampal activation and metabolism (Schobel et al., 2013). Strikingly, they showed that repeated NMDAR antagonist dosing eventually caused chronic hippocampal atrophy, resembling observations after longer periods of illness. A possible corollary of this preclinical finding suggests that aberrant increases in excitation, and perhaps connectivity induced by NMDAR antagonism, are likely pathological. Therefore, the "hyperconnectivity" pattern may reflect increased pyramidal cell excitability, reduced pyramidal input selectivity, or other sources of aberrant cortical hypersynchrony.
One mechanism could involve reductions in the inhibitory component of cortical connectivity, which may alter excitatory connections. It is possible that such deficits not only increase excitability, but also reduce the input selectivity of cortical excitation (i.e., pathologically increase cortical functional connectivity). It will be critical for future studies to establish whether the observed "hyperconnectivity" measured via BOLD fMRI also relates to concurrently abnormal oscillations measured via EEG and in what frequency band. We comment on this specific issue below. Relatedly, follow-up clinical and pharmacological investigations should more carefully decompose the "correlation" measures between pairwise regions by considering both shared and unshared signal components (Friston, 2011). Put differently, it will be critical to show that the alterations in BOLD functional connectivity measures actually reflect elevations in aberrant shared signal (not just alterations in the variance structure), which could also be altered in schizophrenia (Yang et al., 2014). Pinpointing the precise nature of signal alteration that induces "hyperconnectivity" will have key implications for interpreting this effect and, in turn, for treatment studies designed to reverse this effect.
Second, what might be the precise synaptic contributions to such aberrant "hyperconnectivity"? Dr. Pinault elegantly argues for the role of GABAergic interneurons in the reported effect. We are in full agreement here; a number of studies have implicated interneurons as playing a key role in the effects of NMDAR antagonists (Krystal and Moghaddam, 2011; Krystal et al., 1994; Krystal et al., 2003; Anticevic et al., 2012). It remains unknown, however, which interneuron subtype is predominantly involved in their effects. We posit that the combination of preclinical animal work and computational modeling approaches is well positioned to address this question. For instance, studies that carefully experimentally dissect the potential contributions of specific neuronal subtypes to the observed "hyperconnectivity" pattern will be important to constrain our mechanistic understanding of acute NMDAR antagonist effects on cortical microcircuits (Kwan and Dan, 2012). Similarly, computational studies that incorporate multiple interneuron subtypes will help generate predictions for both electrophysiological and functional connectivity experiments that can be tested in animals and humans (Lisman et al., 2010; Lisman, 2012). It is well established that there are two broad classes of interneurons—fast-spiking cells that are critical for gamma oscillations and slower-spiking cells that strongly contribute to theta oscillations (Lisman, 2012). As noted, it remains unknown which GABAergic interneuron contribution "drives" the hyperconnectivity and at which frequency band (i.e., gamma or theta). It is demonstrated that systemic ketamine administration attenuates theta power but concurrently increases gamma power in mice (Ehrlichman et al., 2009; Lazarewicz et al., 2010), rats (Sabolek, H., et al., 2006), and humans (Hong et al., 2010). Computational simulations established that manipulating NMDAR currents on slow-spiking GABAergic cells (as opposed to fast-spiking cells) captured these dissociable gamma/theta experimental observations in silico (Neymotin et al., 2011). Forthcoming computational studies should strive to extend such micro-circuit models to capture neural system-level connectivity alterations in schizophrenia and following pharmacological challenge (Anticevic et al., 2013). In turn, these computational models can generate cell-specific predictions for NMDAR antagonist effects that can be tested experimentally, both preclinically and in human neuroimaging studies (Kwan and Dan, 2012).
Third, is there a dose effect of acute NMDAR antagonists? We believe that there might be a dose effect, which needs to be carefully considered when interpreting present effects—as argued by Dr. Pinault. Perhaps cognitive activation studies can speak to this issue. For instance, in a recent related study, we found that acute NMDAR antagonism in humans reduced cognitive performance—namely delayed spatial working memory (WM) by preferentially increasing error rates to non-target probes at specific spatial locations that were proximal to original WM locations (Murray et al., 2014). Put differently, volunteers administered ketamine were more likely to report a false alarm than report a memory at a location that they had not previously seen (a miss). We qualitatively and quantitatively captured this effect in our computational model by mildly reducing NMDAR drive onto inhibitory cells in the model—effectively inducing disinhibition and a "blurring" of the WM representation (Murray et al., 2014). The model performance mimicked that of healthy human volunteers at low levels of NMDAR antagonism but not at higher levels, where recurrent excitation on pyramidal cells was also reduced (Wang et al., 2013).
In a related animal study, Arnsten and colleagues examined effects of acute ketamine administration in monkeys during performance of a similar delayed spatial WM task (Wang et al., 2013). In their experiment the animals produced random saccades at previously unseen probe locations (i.e., misses), suggesting a complete loss of memory representation, accompanied by reduced delay-related firing of prefrontal neurons. In our computational simulations we were able to capture both behavioral results as reflecting distinct levels of NMDAR antagonism. In that sense, it may be the case that distinct dose-dependent levels of NMDAR antagonism produce different E/I balance regimes. Put differently, at higher doses of ketamine, where both the inhibitory and excitatory NMDAR synaptic components are affected, the "hyperconnectivity" regime may be replaced by functional connectivity reductions—a hypothesis that needs systematic experimental testing in animals. Therefore, we argue for the importance of carefully dissecting the dose-dependent contributions of ketamine on both behavior and functional connectivity in humans.
Fourth, how might the prefrontal "hyperconnectivity" effect relate to emerging "thalamo-cortical" markers of schizophrenia? An excellent observation in Dr. Pinault's commentary raises the importance of linking the observed "hyperconnectivity," which may possibly reflect alterations in gamma-band oscillations, to the thalamo-cortical gating abnormalities that underlie many theoretical models of schizophrenia (Andreasen, 1997). Unifying these effects constitutes an important theoretical and experimental goal in light of several recent empirical reports showing elevated sensory-thalamic functional connectivity in chronic schizophrenia patients (Woodward et al., 2012; Klingner et al., 2014; Anticevic et al., 2013). It may be the case that NMDAR antagonism "elevates" this sensory-thalamic coupling, either by decreasing the gamma signal-to-noise ratio or possibly by affecting the prefrontal "top-down" control aspect of sensory-thalamic information flow. These scenarios remain to be systematically tested.
In addition, it will be important to establish whether the thalamo-cortical disconnectivity in schizophrenia also exhibits functional dissociations along illness stages or appears during initial illness onset, as reported here for prefrontal hyperconnectivity. In that sense, some neural markers may show "dynamic" change along illness stages or perhaps reflect state-dependent functional causes (e.g., transient symptom exacerbation), whereas other functional connectivity markers may reflect a "trait-like" signature that persists across the illness course. Further establishing how the ketamine model maps onto these distinct neural signatures across illness stages and functional states represents a key goal for harnessing the ketamine model for targeted drug development for schizophrenia.
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