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Current Opinion in Psychiatry:
doi: 10.1097/YCO.0b013e32835a0b63
MOOD AND ANXIETY DISORDERS: Edited by Cornelius Katona and Gordon Parker

Integrative neuroimaging in mood disorders

Keedwell, Paul A.; Linden, David E.J.

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MRC Centre for Neuropsychiatric Genetics and Genomics and Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, UK

Correspondence to David Linden, School of Medicine, Cardiff University, Henry Wellcome Building, Heath Park, Cardiff CF14 4XN, UK. Tel: +44 29 20 687 064; fax: +44 29 20 687 068; e-mail: lindend@cardiff.ac.uk

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Purpose of review: Neuroimaging has become a central technique of biological psychiatry and is uniquely suited to assess functional and structural brain changes in psychiatric patients in vivo. In this review, we highlight several recent developments that may enable the transition of psychiatric neuroimaging from laboratory to clinic.

Recent findings: We describe recent trends in refining imaging techniques for brain microstructure (diffusion imaging) and neurochemistry (magnetic resonance spectroscopy of neurotransmitters and metabolites) and their application to patients with mood disorders and individuals at risk, such as first-degree relatives. We also survey recent progress in imaging-guided deep brain stimulation (DBS), imaging-based (neurofeedback) therapies and studies looking at their convergent anatomical targets. These new interventional techniques, which aim to modulate brain circuits of emotion and motivation highlighted by functional imaging studies, have shown promising effects in several small studies.

Summary: The mapping of brain patterns associated with risk to develop mood disorders may pave the way for diagnostic/prognostic applications of neuroimaging. The neuromodulation techniques of DBS and neurofeedback, which target dysfunctional or compensatory circuits identified by functional imaging, may take neuroimaging into a new, therapeutic domain.

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Functional imaging has revealed interesting information about altered responses to emotional information in mood disorders. For example, the heightened response of the amygdala and other limbic and paralimbic areas to negative stimuli in patients with major depressive disorder (MDD) was confirmed by a meta-analysis and fits into models of abnormal emotion processing and regulation [1]. Recent functional MRI (fMRI) studies reported that the increased response of the amygdalae to sad faces [2] or during anticipation of negative pictures [3] was reduced after antidepressant treatment.

However, functional biomarkers of MDD still lack the sensitivity and specificity to be used diagnostically, even with pattern recognition software, and this is also true for bipolar disorder. This mirrors the situation in the other major psychiatric disorders, with the possible exception of Alzheimer's disease [4]. In clinical practice, imaging is still largely used to screen for gross organic diseases [5].

However, the use of multimodal imaging experiments, combining structural, functional and molecular imaging with the application of multivariate analysis techniques, has the potential to bridge this translational gap. Meanwhile, new imaging-based or imaging-guided therapies offer more immediate benefits [4]. Hence, this review will focus on recent developments across imaging modalities and end with a focus on deep brain stimulation (DBS) and neurofeedback.

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Mood disorders are increasingly understood as disorders of connectivity between brain regions known to be important for mood recognition, generation and regulation. Improved understanding of the white matter architecture connecting these regions in mood disorder, and in those at risk of the disorder, will better inform aetiological models and may lead to better treatments. Major advances are being made in the in-vivo dissection of the white matter skeleton, enabling researchers to investigate variations from normal microarchitecture in clinical populations. The main method for in-vivo imaging of white matter is diffusion MRI, which maps out differences in water diffusion produced by obstacles to the free movement of water, for example myelin sheets. Diffusion tensor imaging (DTI), which reconstructs fibre tracts on the basis of the anisotropy of water flow along axons, has been progressively refined to reduce the directional uncertainty at junctions of crossing fibres. New diffusion-based computational techniques such as constrained spherical deconvolution [6▪▪] are now poised to supersede DTI in reconstructing the connectome from seed regions but have yet to make a significant impact in the clinical literature. A recent review by Jones et al.[7▪▪] highlights the pitfalls inherent in overinterpreting findings from DTI due to their inherent uncertainty. However, with these cautions in mind, interesting findings have emerged from the latest diffusion imaging studies in clinical populations.

Altered white matter architecture in the cingulum bundles – core components of limbic system – might increase vulnerability to MDD by perturbing the functional connectivity of important mood regulation circuits. A DTI study [8▪▪] employing reconstruction of the cingulum bundles in individuals at risk of depression (by virtue of family history) demonstrated reduced fractional anisotropy, which is an index of fibre integrity. Changes were most marked in the subgenual region – a target for DBS in the management of treatment-resistant MDD. The reduction in fractional anisotropy was primarily due to increased axonal radial diffusivity, which is influenced by a number of factors, including axonal membrane integrity, axonal diameter, axon packing density and architectural complexity, including crossing fibres. This finding is consistent with previous DTI findings in acute MDD [9] and in adolescents with a parental history of depression [10▪▪], raising the possibility that reduced cingulum bundle fractional anisotropy is a potential endophenotype of the disorder. In addition, altered cingulum fractional anisotropy was associated with subclinical anhedonia, lending support to the assertion that relative anhedonia might represent a prodrome of MDD.

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The uncinate fasciculus is the main fronto-limbic tract, connecting both orbitomedial and ventrolateral aspects of the prefrontal cortex with the ipsilateral temporal pole, uncus, hippocampal gyrus and amygdala [11]. Recent studies of MDD patients have demonstrated reduced fractional anisotropy in the right uncinate fasciculus [12▪▪], previously related to illness duration in the elderly [13]. Some studies have also shown a correlation with age in bipolar depression, in which fractional anisotropy is reportedly increased [14], but, conversely, reduced uncinate fractional anisotropy has recently been demonstrated in adolescent depression [9], and in adolescents at familial risk for MDD [10▪▪]. This raises the possibility that disturbance of microarchitecture in another major tract linking critical mood regulating regions could also be a vulnerability marker for mood disorder.

Many factors can affect fractional anisotropy, and more refined white matter imaging techniques are therefore needed to disentangle the microstructural changes observed in mood disorders. Evolving noninvasive white matter mapping techniques offer promise in determining which specific features of the microstructure might be implicated, including axon density [15▪▪], diameter [16▪] and myelination. Myelination is of particular interest in mood disorders, given the link between demyelinating diseases and depression, the presence of white matter hyperintensities in late-life depression and the apparent deleterious effect of stress hormones on glial cell production in preclinical work. New methods for measuring myelin water fraction in vivo[17▪▪,18▪▪] offer promise in the study of stress-related demyelination in MDD.

In summary, interesting findings are emerging which suggest that aberrations in the microstructure of the connectome could represent vulnerability markers of MDD and bipolar disorder, but larger cross-sectional and longitudinal studies employing whole brain and specific tract reconstruction techniques and quantitative estimates of axonal density, diameter and myelin water fraction are required. These studies could be combined with resting state fMRI studies of effective and functional connectivity to assess the impact of structural changes on network activity.

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For any true understanding of the neurobiological pathways of depression, anatomical analysis needs to be complemented by neurochemical measures. Peripheral measures of neurotransmitter metabolism have not yielded reliable biomarkers of depression [5]. Hence, much hope is being invested in the noninvasive imaging techniques that allow direct quantification of neurotransmitter concentrations [magnetic resonance spectroscopy (MRS)] or receptor binding (PET) in vivo. Their scope, though, is limited by the availability of ligands of sufficiently specific binding capacity, in the case of PET, and the visibility of neurotransmitters along the chemical shift axis in MRS. Compared with PET, MRS is noninvasive and quicker and cheaper to perform, especially with the increasing availability of spectrum editing methods such as mega-Point-RESolved Spectroscopy [19▪▪]. A major disadvantage of MRS is that it cannot quantify the monoamines. However, it can be used to noninvasively quantify concentrations of gamma-amino butyric acid (GABA) and glutamate – the major inhibitory and excitatory neurotransmitters of the brain.

GABA is increasingly implicated in the pathophysiology of MDD [20]. MRS studies have consistently demonstrated reduced cortical GABA concentrations in individuals with acute MDD, with greater reductions in more melancholic forms. Antidepressant treatments have been shown to reverse cortical GABA deficits. The relationship between GABA and acute depression might be mediated by anhedonia. In unmedicated depressed adolescents, GABA levels in the anterior cingulate were negatively correlated with anhedonia, whereas depressed individuals with relatively spared hedonic tone did not differ in their GABA levels from nondepressed controls [21▪▪]. A previous study [22] had made a link between negative Blood Oxygen Level Dependent (BOLD) responses to positive stimuli in MDD and increased glutamate levels, whereas nondepressed individuals had shown a positive correlation between negative BOLD responses and GABA.

However, evidence for a persistent deficit during remission, which would suggest that GABA dysfunction is a possible trait marker of depression, is equivocal [23▪▪]. The one study [24] showing reduced levels in remission recruited individuals with recurrent depression. Conversely, a study [25] revealing no reduction included individuals with a past history of mild or brief episodes and the capacity to remain well while unmedicated for long periods. The implication is that GABA deficits might represent a marker of vulnerability for more recurrent forms of depression. Recent work at Cardiff University, currently under review, corroborates the findings of the latter study in demonstrating normal GABA levels in occipital, inferior frontal and subcortical voxels in young individuals with a history of a predominantly single-episode melancholic depression [26]. Hence, further work is needed to replicate the finding of reduced GABA in remitted but recurrent illness. Another pressing need is to measure GABA in subcortical regions, which do not necessarily correlate with those in cortical regions. Abnormal subcortical GABA function has been demonstrated in animal models of depression [27], and a small study of [(11)C]flumazenil binding in MDD [28]. Investigations of GABA levels in the subcortical regions of MDD individuals and their relatives are therefore indicated, but are technically challenging due to reduced signal to noise ratios.

Findings for glutamate are more equivocal than those for GABA in mood disorder [23▪▪]. However, a pattern is emerging of decreased and increased glutamate concentration in MDD and bipolar disorder, respectively [29]. Most studies have used unmedicated participants. Findings appear to be highly dependent on illness status in MDD but perhaps less so in bipolar disorder: larger studies, including individuals in depressed and manic states, are indicated [29]. Thus far, most studies have not reported pure glutamate concentrations, but combined estimates of glutamate and glutamine (GLX), due to the technical difficulty in separating their similar resonant frequencies at 3T. Although the concentrations of both are probably highly correlated in healthy individuals, it is possible that the two substrates could be differentially affected in psychiatric disease. Higher gradient scanners (7T) are now being used in humans and will provide better separation of glutamate and glutamine spectra in future studies.

Other sources of variation include individual differences in illness and treatment histories. Of particular interest, therefore, is a recent study [30] of high-risk, never-depressed individuals with a first-degree family history of MDD, which demonstrated significantly higher levels of glutamate in parieto-occipital cortex in high-risk individuals than in controls. Hence, abnormalities in glutamate neurotransmission may reflect a trait marker of vulnerability to depression. Measures of GLX in frontal and limbic areas in similar populations are indicated.

A recent report demonstrating that intravenous ketamine, an N-methyl-D-aspartic acid (NMDA) glutamate receptor antagonist, increases GLX concentration in the prefrontal cortex [31▪▪] is of particular interest, given ketamine's potential to cause a rapid and significant elevation in mood in depressed individuals. It is argued that subcortical NMDA antagonism disinhibits largely α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptor-mediated glutamate activity in the cortex. Conversely, another recent study [32▪] reported no effect of ketamine on occipital GABA or glutamate, but ketamine's effects might be confined to the prefrontal cortex, given the strong glutamatergic projections from subcortical to frontal regions.

The functional significance of changes in bulk measures of intracellular and extracellular GABA and glutamate concentrations that MRS provides are difficult to intepret. Neurotransmitter dysfunction in mood disorders may occur at the presynaptic (production, release and reuptake) and postsynaptic levels. Computer modelling suggests that GABA interneuron activity might govern fast neuronal oscillations (gamma oscillations) in thalamo-cortical loops, whereas NMDA antagonists might be expected to increase gamma power [33] and AMPA agonists reduce gamma power in preclinical studies. Gamma oscillations are preferentially induced during efficient performance of a cognitive task, and may be altered in psychiatric disease [34]. Meanwhile, MRS GABA levels correlate with gamma oscillation frequency in nonclinical male volunteers [35], although it is not yet clear whether they may be uncoupled in mood disorders. Translational approaches that include the validation of human MRS data through parallel animal imaging and histology and/or radioligand imaging are needed in order to elucidate the potential biochemical processes leading to changes of GABA and glutamate spectra in MRS studies.

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One potential clinical use of functional imaging is to identify foci of abnormal activation and then use these as targets for invasive or noninvasive interventions. Motivated by the success of DBS in Parkinson's disease, similar protocols have been applied to the white matter underlying the subgenual cingulate gyrus [36] and the nucleus accumbens [37]. These areas have been implicated in the abnormal regulation of emotion and motivation in depression, although group differences on imaging did not receive strong support from the recent meta-analysis [1]. White matter tracts connecting the frontal lobes and the limbic system have also long been targeted in surgical approaches for treatment-refractory depression. Both DBS [36,37] and surgery [38] seem to be effective, but these procedures have only been evaluated in small and highly selected patient groups and do not lend themselves easily to the control of placebo effects.

Probabilistic tractography studies [39,40] in regions targeted by surgery and DBS for depression reveal that anatomical substrates of clinical effects may not be confined to the target area alone; for example, the medial forebrain bundle and nucleus accumbens seem to be affected across procedures. These converging findings confirm the importance of the modulation of motivation networks in the treatment of depression. They do not reveal, however, whether the net effect is enhancement or suppression of specific pathways, which would need to be explored with functional imaging.

Another new therapeutic approach derived from neuroimaging is fMRI-based neurofeedback. Here, fMRI data are analysed in real time and the result is fed back to the patient, who is instructed to modify this output. It is possible to localize brain areas responsive to negative [41] and positive [42] emotions and train participants in the upregulation of these areas through mental imagery, for example. Recent work has applied multivariate classifiers to discriminate between different emotional states [43▪]. Self-regulation training can rectify an existing abnormality in the activation of brain networks. It might also be possible to simultaneously train downregulation of a hyperactive area and upregulation of a compensatory network. The first clinical pilot study [44] of neurofeedback in depression was based on the rationale that self-control of positive emotion areas would promote the experience of such emotions and enhance patients’ experience of self-efficacy. Participants upregulated individually localized areas that were responsive to positive affective stimuli over four training sessions. Target areas varied across individuals and included lateral prefrontal, limbic and paralimbic areas. A control group of MDD individuals performed an intervention on the basis of positive imagery alone without feedback on the associated brain activation. Hamilton Depression Rating Scale scores reduced by 30% in the active group compared with the control group. Although this clinical improvement can be attributable to a multitude of factors, including the mere experience of gaining control over one's brain, this proof of concept study shows that imaging protocols can be integrated in treatment plans: direct brain modulation might be used to promote specific aspects of neuroplasticity or to provide a feedback control of prescribed mental or cognitive strategies in which patient engagement is often difficult to ascertain. We will have to wait for the outcome of formal clinical efficacy studies to judge the therapeutic potential of imaging-based neurofeedback, but its potential use to elucidate mechanisms of psychopathology by evaluating the subjective effects of modulation of specific brain areas is already apparent.

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Recent advances in multimodal (combining structural, neurochemical and functional) imaging and real-time data analysis and feedback techniques have advanced our understanding of putatively abnormal brain circuits in depression and other mood disorders. Altered connections between the neuromodulatory nuclei in the brainstem, the relay stations for emotion and motivation in the basal ganglia and limbic system, and the cognitive control regions in prefrontal cortex have been particularly implicated. These are also the targets for traditional (surgery) and newer (DBS) invasive approaches, which are currently being refined on the basis of multimodal imaging findings. Through the application of real-time functional imaging to neurofeedback, imaging finally has the potential of becoming a therapeutic technique in its own right.

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The authors are supported by MRC grant G1100629 (Development Clinical Studies – fMRI-based neurofeedback as a treatment tool for depression).

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Conflicts of interest

There are no conflicts of interest.

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Papers of particular interest, published within the annual period of review, have been highlighted as:

▪ of special interest

▪▪ of outstanding interest

Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 126).

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1. Hamilton JP, Etkin A, Furman DJ, et al. Functional neuroimaging of major depressive disorder: a meta-analysis and new integration of baseline activation and neural response data. Am J Psychiatry 2012; 169:693–703.

2. Arnone D, McKie S, Elliott R, et al. Increased amygdala responses to sad but not fearful faces in major depression: relation to mood state and pharmacological treatment. Am J Psychiatry 2012; 169:841–850.

3. Rosenblau G, Sterzer P, Stoy M, et al. Functional neuroanatomy of emotion processing in major depressive disorder is altered after successful antidepressant therapy. J Psychopharmacol 2012. [Epub ahead of print]

4. Linden DE. The challenges and promise of neuroimaging in psychiatry. Neuron 2012; 73:8–22.

5. Linden D. The biology of psychological disorders. Hampshire, UK: Palgrave Macmillan; 2012.

6▪▪. Jeurissen B, Leemans A, Jones DK, et al. Probabilistic fiber tracking using the residual bootstrap with constrained spherical deconvolution. Hum Brain Mapp 2011; 32:461–479.

A new diffusion-based technique that provides better mapping of crossing fibres.

7▪▪. Jones DK, Knosche TR, Turner R. White matter integrity, fiber count, and other fallacies: the do's and don’ts of diffusion MRI. NeuroImage 2012. [Epub ahead of print]

A useful review of what diffusion-weighted imaging can and cannot do.

8▪▪. Keedwell PA, Chapman R, Christiansen K, et al. Cingulum white matter in young women at risk of depression: the effect of family history and anhedonia. Biol Psychiatry 2012; 72:296–302.

This study confirms altered microstructure of limbic connections as a trait marker of depression.

9. Cullen KR, Klimes-Dougan B, Muetzel R, et al. Altered white matter microstructure in adolescents with major depression: a preliminary study. J Am Acad Child Adolesc Psychiatry 2010; 49:173–183.

10▪▪. Huang H, Fan X, Wlliamson DE, Rao U. White matter changes in healthy adolescents at familial risk for unipolar depression: a diffusion tensor imaging study. Neuropsychopharmacology 2011; 36:684–691.

A well-conducted study using tract-based spatial statistics as opposed to a region of interest tract reconstruction approach.

11. Catani M, Howard RJ, Pajevic S, Jones DK. Virtual in vivo interactive dissection of white matter fasciculi in the human brain. Neuroimage 2002; 17:77–94.

12▪▪. Zhang A, Leow A, Ajilore O, et al. Quantitative tract-specific measures of uncinate and cingulum in major depression using diffusion tensor imaging. Neuropsychopharmacology 2012; 37:959–967.

A similar approach to [8▪▪], which is potentially more sensitive than the whole brain, nonhypothesis-driven approaches.

13. Taylor WD, MacFall JR, Gerig G, Krishnan RR. Structural integrity of the uncinate fasciculus in geriatric depression: relationship with age of onset. Neuropsychiatr Dis Treat 2007; 3:669–674.

14. Versace A, Almeida JR, Hassel S, et al. Elevated left and reduced right orbitomedial prefrontal fractional anisotropy in adults with bipolar disorder revealed by tract-based spatial statistics. Arch Gen Psychiatry 2008; 65:1041–1052.

15▪▪. Zhang H, Schneider T, Wheeler-Kingshott CA, Alexander DC. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. NeuroImage 2012; 61:1000–1016.

A practical and quick method for estimating axonal density in a tract, but which is confounded by fibre crossing, just like DTI.

16▪. Zhang H, Dyrby TB, Alexander DC. Axon diameter mapping in crossing fibers with diffusion MRI. Med Image Comput Comput Assist Interv 2011; 14 (Pt 2):82–89.

A potentially important method for assessing axonal diameter, which can take into account crossing fibres.

17▪▪. Kitzler HH, Su J, Zeineh M, et al. Deficient MWF mapping in multiple sclerosis using 3D whole-brain multicomponent relaxation MRI. NeuroImage 2012; 59:2670–2677.

A real-life application of the multicomponent driven equilibrium single pulse observation of T1 and T2 technique, which can estimate intralaminar water between myelin sheaths. This study suggests that this is a sensitive measure of white matter degeneration.

18▪▪. Deoni SC, Dean DC 3rd, O’Muircheartaigh J, et al. Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping. NeuroImage 2012; 63:1038–1053.

Another mcDESPOT study in which changes in myelination are in concordance with histological studies in infants.

19▪▪. Puts NA, Edden RA. In vivo magnetic resonance spectroscopy of GABA: a methodological review. Prog Nucl Magn Reson Spectrosc 2012; 60:29–41.

A wide-reaching review of the current state of GABA measurement and its application in clinical and nonclinical populations.

20. Luscher B, Shen Q, Sahir N. The GABAergic deficit hypothesis of major depressive disorder. Mol Psychiatry 2011; 16:383–406.

21▪▪. Gabbay V, Mao X, Klein RG, et al. Anterior cingulate cortex gamma-aminobutyric acid in depressed adolescents: relationship to anhedonia. Arch Gen Psychiatry 2012; 69:139–149.

A well-conducted examination of the importance of examining symptom dimensions in MDD. Anhedonia is a core feature of depression and can predict response to antidepressants.

22. Walter M, Henning A, Grimm S, et al. The relationship between aberrant neuronal activation in the pregenual anterior cingulate, altered glutamatergic metabolism, and anhedonia in major depression. Arch Gen Psychiatry 2009; 66:478–486.

23▪▪. Hasler G, Northoff G. Discovering imaging endophenotypes for major depression. Mol Psychiatry 2011; 16:604–619.

An excellent review placing MRS findings in the context of the search for trait markers of MDD.

24. Bhagwagar Z, Wylezinska M, Jezzard P, et al. Low GABA concentrations in occipital cortex and anterior cingulate cortex in medication-free, recovered depressed patients. Int J Neuropsychopharmacol 2008; 11:255–260.

25. Hasler G, Neumeister A, van der Veen JW, et al. Normal prefrontal gamma-aminobutyric acid levels in remitted depressed subjects determined by proton magnetic resonance spectroscopy. Biol Psychiatry 2005; 58:969–973.

26. Shaw A, Brealy J, Richardson H, et al. Marked reductions in visual evoked responses but not GABA concentrations or gamma-band measures in remitted depression. Biol Psychiatry (submitted).

27. Alcaro A, Panksepp J, Witczak J, et al. Is subcortical-cortical midline activity in depression mediated by glutamate and GABA? A cross-species translational approach. Neurosci Biobehav Rev 2010; 34:592–605.

28. Klumpers UM, Veltman DJ, Drent ML, et al. Reduced parahippocampal and lateral temporal GABAA-[11C]flumazenil binding in major depression: preliminary results. Eur J Nucl Med Mol Imaging 2010; 37:565–574.

29. Yuksel C, Ongur D. Magnetic resonance spectroscopy studies of glutamate-related abnormalities in mood disorders. Biol Psychiatry 2010; 68:785–794.

30. Taylor MJ, Mannie ZN, Norbury R, et al. Elevated cortical glutamate in young people at increased familial risk of depression. Int J Neuropsychopharmacol 2011; 14:255–259.

31▪▪. Stone JM, Dietrich C, Edden R, et al. Ketamine effects on brain GABA and glutamate levels with 1H-MRS: relationship to ketamine-induced psychopathology. Mol Psychiatry 2012; 17:664–665.

This study came from a schizophrenia perspective, but there are implications for mood disorders.

32▪. Valentine GW, Mason GF, Gomez R, et al. The antidepressant effect of ketamine is not associated with changes in occipital amino acid neurotransmitter content as measured by [(1)H]-MRS. Psychiatry Res 2011; 191:122–127.

An interesting study but other brain regions need to be examined.

33. Spencer KM. The functional consequences of cortical circuit abnormalities on gamma oscillations in schizophrenia: insights from computational modeling. Front Hum Neurosci 2009; 3:33.

34. Haenschel C, Linden D. Exploring intermediate phenotypes with EEG: working memory dysfunction in schizophrenia. Behav Brain Res 2011; 216:481–495.

35. Muthukumaraswamy SD, Edden RA, Jones DK, et al. Resting GABA concentration predicts gamma frequency and fMRI amplitude in response to visual stimulation in humans. PNAS 2009; 106:8356–8361.

36. Holtzheimer PE, Kelley ME, Gross RE, et al. Subcallosal cingulate deep brain stimulation for treatment-resistant unipolar and bipolar depression. Arch Gen Psychiatry 2012; 69:150–158.

37. Bewernick BH, Kayser S, Sturm V, Schlaepfer TE. Long-term effects of nucleus accumbens deep brain stimulation in treatment-resistant depression: evidence for sustained efficacy. Neuropsychopharmacology 2012; 37:1975–1985.

38. Christmas D, Eljamel MS, Butler S, et al. Long term outcome of thermal anterior capsulotomy for chronic, treatment refractory depression. J Neurol Neurosurg Psychiatry 2011; 82:594–600.

39. Schoene-Bake JC, Parpaley Y, Weber B, et al. Tractographic analysis of historical lesion surgery for depression. Neuropsychopharmacology 2010; 35:2553–2563.

40. Gutman DA, Holtzheimer PE, Behrens TE, et al. A tractography analysis of two deep brain stimulation white matter targets for depression. Biol Psychiatry 2009; 65:276–282.

41. Johnston SJ, Boehm SG, Healy D, et al. Neurofeedback: a promising tool for the self-regulation of emotion networks. Neuroimage 2010; 49:1066–1072.

42. Johnston S, Linden DE, Healy D, et al. Upregulation of emotion areas through neurofeedback with a focus on positive mood. Cogn Affect Behav Neurosci 2011; 11:44–51.

43▪. Sitaram R, Lee S, Ruiz S, et al. Real-time support vector classification and feedback of multiple emotional brain states. Neuroimage 2011; 56:753–765.

This study employed real-time classifiers to discriminate different emotional states from brain activation and was one of the first in which participants then trained to modulate these patterns.

44. Linden DEJ, Habes I, Johnston SJ, et al. Real-time self-regulation of emotion networks in patients with depression. PLoS One 2012; 7:e38115.


brain; cingulum; depression; gamma-amino butyric acid; neurofeedback

© 2013 Lippincott Williams & Wilkins, Inc.


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