Abstract
Psychomotor disturbances (PMD) are a classic feature of depressive disorder that provides rich clinical information. The aim our narrative review was to characterize the functional anatomy of PMD by summarizing findings from neuroimaging studies. We found evidence across several neuroimaging modalities that suggest involvement of fronto-striatal neurocircuitry, and monoaminergic pathways and metabolism. We suggest that PMD in major depressive disorder emerge from an alteration of limbic signals, which influence emotion, volition, higher-order cognitive functions, and movement.
Keywords: psychomotor performance, major depressive disorder, neuroimaging, frontal lobe, basal ganglia, monoamines
Introduction
Psychomotor signs are a classic feature of major depressive disorder that already attracted attention over a century ago (1). Emil Kraepelin gave a vivid and still valid description of psychomotor disturbances (PMD) in his chapter on general symptomatology in Lehrbuch des Psychiatrie, 1907: “The psychomotor retardation, which is the most important disturbance in the depressed states of manic-depressive insanity, is probably due to a […] increase in resistance […] In spite of every apparent exertion, the patients cannot utter a word or at best answer only in monosyllables, and are unable to eat, stand up, or dress. As a rule they clearly recognize the enormous pressure lying upon them, which they are unable to overcome” (2).
Psychomotor disturbances in depressive disorder can be broadly classified in to four subgroups of symptoms and signs based on three available clinical rating scales designed to characterize them [CORE, motor agitation and retardation scale (MARS), Widlöcher scale] (3–5): retardation, agitation, non-interactiveness, and mental slowing (Table 1). The symptoms and signs of PMD therefore entail a wide range of brain functions including motor performance, executive function, volition, and drive. These provide rich clinical information (i.e., diagnostic subgroup, prognosis, treatment) (6, 7).
Table 1.
Psychomotor signs in major depressive disorder.
| Subgroup of psychomotor disturbances | Example |
|---|---|
| Retardation | Slowed movements (motor slowness), facial immobility (lack of facial expressivity, downcast gaze, reduced voice volume, slurring of speech), body immobility (immobility of trunk/proximal limbs), postural slumping (postural collapse), delay in motor activity, delay in responding verbally (delayed speech onset), slowing of speech rate (monotone speech), abnormal gait |
| Agitation | Frightened apprehension (static facial expression, abnormal staring, increased blinking, erratic eye movement), facial agitation (movement/tension in mouth), motor agitation (increased axial truncal movement), stereotyped movements (tension in fingers and hands, hand movement, foot/lower leg movement), verbal stereotypy |
| Non-interactiveness | Response to social cues, emotional responsiveness, inattentiveness, poverty of associations, spontaneous speech, length of verbal responses |
| Mental slowing | Language and verbal flow, variety of themes spontaneously approached, richness of associations, subjective experience of ruminations, fatigability, perception of flow of time, memory, concentration, interest in habitual activities |
No previous review has focused specifically on neuroimaging findings related to PMD in major depressive disorder. The aim of this narrative review is to characterize the functional anatomy of PMD in major depressive disorder by summarizing findings from human neuroimaging studies that probe structure, function, neurochemistry, and connectivity.
Structural Neuroimaging
Structural aberrations in white matter are the most prominent structural neuroimaging findings associated with PMD in depressive disorder.
White-matter alterations (hyperintensities, WHI; and white-matter fiber integrity), are one of the most reproduced findings in mood disorders. White-matter hyperintensities (WHIs) are radiological hyperintense regions of white matter with elusive etiology in MRI images. They are primarily associated with late-life depression, but are also more common in major depressive disorder in younger age groups. The extent of WHIs correlates with illness severity, poor treatment response, and decreased psychomotor speed on several neuropsychological tests (8). White-matter tissue broadly comprises glial cells with myelin surrounding axons. Currently, the general understanding is that the WHIs alterations observed in depression arise from small vessel disease that lead to disruption of white-matter pathways (9). However, other disease mechanisms involving white-matter tissue may also lead to disruptions of specific neurocircuits and lead to psychiatric symptoms such as PMD (10).
White-matter fiber integrity can be assessed with diffusion-weighted imaging. One study by Walther et al. (11) who specifically addressed psychomotor functioning in depressive disorder used diffusion-weighted magnetic resonance imaging and actigraphy – an objective measure of the general activity level in an individual. It showed that lower activity levels correlate with measures of differential myelinization in the frontal lobe and posterior cingulate region, and that there is a negative correlation between the same measures in the white matter beneath the primary motor cortex and in the parahippocampal region. The authors conclude that changes in psychomotor function in depressive disorder may be linked to changes in white matter in motor regions. Bracht et al. used diffusion-weighted imaging to investigate white-matter microstructure in relation to PMD. They found a positive association between decreased physical motor activity and alterations in paralimbic and motor midline regions not only involved in volitional movement but also involvement of ascending mesocortical dopamine pathways in clinical states with prominent PMD (12, 13).
To this date, few studies have investigated the relation between gray matter volume and PMD in major depressive disorder. Current findings involve volume reductions in several pre-executive parts of the motor system. One volumetric study showed that thinning of the right presupplementary motor cortex (pre-SMA) is associated with impaired performance on a motor learning test (14). The pre-SMA is a part of the mesial premotor cortex that advances signals from the prefrontal regions, engaged in higher-order cognitive functions. In studies measuring subcortical volumes and regional shape alterations, no significant associations could be found between performance on a psychomotor task (trail making test variations) and the volumes of striatum, pallidum, and thalamus in depressed subjects (15, 16). Another study found that reduced caudate nucleus volumes predicts decreased psychomotor speed in depressed subjects >50 years old (17).
Only one study, using CT, has assessed cerebrospinal fluid space size. This study found that the size of the third ventricle was associated with clinical ratings of psychomotor retardation (18).
Functional Neuroimaging
Blood–oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is currently the most prevalent method for studying neural activation patterns during experimental tasks in patients with depressive disorder. A few research teams have specifically addressed PMD using fMRI and experimental motor tasks, clinical ratings of psychomotor disturbance, or motor physiology metrics (i.e., actigraphy, reaction time). Two types of studies have been employed – task and non-task based studies. Naismith et al. (19) used a motor sequence task (button press response) to study motor learning, and found increased activation of lateral prefrontal cortex, superior temporal regions, and the cerebellum. Caligiuri et al. (20, 21) studied motor execution using a manual reaction time task, and found increased activation during movement in the primary motor cortex, alongside motor asymmetry. Five other studies investigated motor speed using different finger-tapping variations (22–27), and suggest an increased activation in both motor and paralimbic regions, and with altered fronto-striatal coupling among patients. One non-task, resting-state study, by Yao et al. (28) corroborates the hyperactivation of paralimbic regions in patients.
Electroencephalography
Electroencephalography (EEG) is used to study power amplitude of particular frequency spectrums, hemisphere asymmetry, and chronometric features of cortical neural activation. PMD have been associated with greater variability and increased amplitudes in the delta (<4 Hz) and theta (4–7 Hz) spectrum, but not with hemisphere asymmetry (29). The post-imperative negative variation is a metric related to frontal lobe function, and has been associated with psychomotor slowing in a choice reaction task (30). Another frontal metric (P300) has also been correlated positively correlated with PMD (31). Interestingly, this study also showed that only clinical ratings more focused on PMD than the Hamilton depression ratings scale (HDRS) predicted P300 latency. In a group of patients receiving electroconvulsive treatment, clinical ratings of PMD were positively correlated with frequency decreases during initial improvement, whereas the reverse relationship was found during the later partial remission phase (32). One study by Nieber et al. (33) showed a positive correlation between decreased frequencies in particular regions of the theta and alpha (7–13 Hz) spectrum and overall retardation, with motor retardation, in particular. In that study, increased frequency in particular regions of in the alpha and beta spectrum was negatively correlated with PMD. Error-related negativity and positive-negativity are metrics associated with anterior and posterior cingulate cortex function, respectively (34, 35). These metrics have been associated with a slowing of psychomotor performance in subjects during action monitoring, but only positive-negativity differentiated patients and controls (36).
Molecular Neuroimaging
Single-photon emission tomography (SPECT), positron emission tomography (PET), and arterial spin labeling (ASL) are the three molecular neuroimaging methods that have been used to study PMD. These three methods measure regional cerebral blood flow, glucose metabolism, oxygen consumption, or synaptic transmission factors. Walther et al. (37) used ASL and actigraphy to measure the correlation between regional cerebral blood flow and general motor activity outside of the scanner environment in depressed subjects. The study showed a positive correlation between physical activity and blood perfusion in the right orbitofrontal cortex, and a negative correlation with left supplementary motor area perfusion. The available evidence from PET and SPECT studies also suggests that PMD in depression are associated with decreased DLPFC metabolism (38–40), increased ACC metabolism (41–43), and a lower dopaminergic tone and altered metabolism in striatal regions (41, 42, 44–47). However, a SPECT study by Graff-Guerrero et al. (48) failed to reproduce these associations between clinical rating of PMD and cerebral blood flow. One longitudinal study also suggests that improvement of psychomotor slowing is associated with increased activation in the dorsal ACC (49).
Transcranial Ultrasound
Hypo- or hyperechogenicity measured by transcranial sonography in vivo reflect changes in tissue impedance, likely due to alterations of microarchitecture such as shifts in cell density, changes in interstitial matrix composition, or alterations of fiber tract integrity (50, 51). Those transcranial ultrasound studies that have investigated PMD in major depression have focused on the serotonergic raphe nuclei and the dopaminergic substantia nigrae. A significantly reduced echogenicity of the mesencephalic midline raphe nuclei has been reported in depressed subjects (52). Hypoechogenicity of the raphe nuclei can be found in 50–70% of unipolar depressed subjects compared to 10% in healthy subjects (53). Hypoechogenicity of the raphe nuclei of the brain stem is associated with better treatment response to serotonin reuptake inhibitors (54) and with symptom severity in suicidal ideation (55). One study could not find any association between echogenicity of the raphe nuclei and PMD (51), another found a positive correlation with the degree of psychomotor retardation (56), and a third a negative correlation with psychomotor retardation (54). Hoeppner et al. showed that substantia nigra echogenic size correlates with motor asymmetry and reduced verbal fluency in unipolar depression. In that study, the association was stronger in patients ≥50 years, and in patients with reduced brain stem raphe nuclei hypogenicity (57).
Conclusion
In this review, we summarize the literature on the functional neuroanatomy of PMD in major depressive disorder (Table 2). Despite the clinical importance of PMD, we found relatively few studies. Indeed, the motor system has been relatively neglected in brain imaging studies of psychiatric disorders in general (58). We conclude that structural alterations that correlate with PMD have been found in gray- and white-matter regions within several nodes of cortico-subcortical circuits. Findings in functional neuroimaging studies show involvement of the same neurocircuitry nodes (along with their white-matter connections) as in structural neuroimaging studies, and further that limbic influences on the motor system may be important in the emergence of PMD. EEG studies suggest that frequency variations across many spectra, and an involvement of the frontal cortex, anterior, and posterior cingulate cortex, are associated with PMD. The molecular neuroimaging correlates of PMD resemble the functional anatomy of major depression described with functional and structural methods, but in addition also implicate disrupted monoamine transmission in PMD. The few available studies that use transcranial ultrasound primarily show an association between PMD and echogenic features of the substantia nigra, which then corroborates molecular neuroimaging findings of disrupted dopamine transmission.
Table 2.
Neuroimaging findings and their correlation to psychomotor disturbances.
| Study | N | Diagnosis | Method | Measure | Finding | |
|---|---|---|---|---|---|---|
| Structural CT and MRI | Hickie et al. (8) | 39 | MDD | MRI (WMH) | Mean decision time | ↑ White-matter hyperintensities |
| Walther et al. (11) | 21 | MDD | DTI (FA) | Actigraphy | ↓ White-matter in motor regions | |
| Bracht et al. (12) | 21/21 | MDD | DTI (FA) | Actigraphy | ↓ White-matter in ACC and midline motor regions connected with PFC | |
| Bracht et al. (13) | 22/21 | MDD | DTI (FA) | Clinical features of PMD | ↓ White-matter in medial forebrain bundle | |
| Exner et al. (14) | 9 | MDD | MRI (ROI) | Serial reaction time task | ↓ pre-SMA volume | |
| Liberg et al. (15) | 27 | BPD | MRI (ROI, shape) | Trail Making Tests, reaction Time | No significant findings in the striatum, pallidum, and the thalamus | |
| Liberg et al. (16) | 20 | BPD | MRI (ROI, shape) | Trail Making Tests | No significant findings in the striatum, pallidum, and the thalamus | |
| Naismith et al. (17) | 47 | MDD | MRI (ROI) | Trail Making Test A | ↓ Right caudate volume | |
| Schlegel et al. (18) | 44 | MDD | CT, ventricle size | Bech–Rafaelsen Melancholia Scale | ↑ Lateral ventricle size | |
| fMRI | Naismith et al. (19) | 19/20 | MDD | Task-based fMRI | Motor sequencing task | ↑ Middle frontal gyrus, superior temporal gyrus, and cerebellum |
| Caligiuri et al. (20) | 24/13 | BPD | Task-based fMRI | Manual reaction time task | ↑ Right primary motor cortex in patients | |
| Caligiuri et al. (21) | 18/13 | BPD | Task-based fMRI | Manual reaction time task | ↑ Left primary motor area in patients. Motor asymmetry in patients with a failure to suppress right hemisphere activation during movement | |
| Marchand et al. (22) | 10 | BPD | Task-based fMRI | Finger-tapping | ↑ Right anterior cingulate cortex and medial frontal gyrus (euthymia > depression) | |
| Liberg et al. (24) | 9/12 | BPD | Task-based fMRI | Finger-tapping | No significant findings | |
| Liberg et al. (25) | 9/12 | BPD | Task-based fMRI | Finger-tapping, Motor imagery, CORE, AS-18 | ↓ Primary motor cortex, lateral ventral premotor cortex in relation to clinical ratings. ↑ Medial posterior parietal cortex during motor imagery. ↑ Fronto-parietal regions, and insular cortex, during motor execution | |
| Liberg et al. (26) | 13/13 | MDD | Task-based fMRI | Finger-tapping | ↓ Fronto-striatal coupling between cingulate motor area and putamen. ↑ Left cingulate motor area. ↑ Functional coupling and clinical ratings | |
| Marchand et al. (27) | 14/15 | BPD | Task-based fMRI | Finger-tapping | ↑ Left pre- and post-central gyrus, bilateral cingulate, right striatum, and left striatum, in patients | |
| Yao et al. (28) | 22/22 | MDD | Resting-state fMRI | HDRS | ↑ Regional homogeneity in right posterior cingulate cortex and right insula | |
| EEG | Nyström et al. (29) | 25 | MDD | EEG power spectrum analysis | Comprehensive Psychopatho-logical Rating Scale | ↑ Delta-, theta-amplitude, and variability |
| Thier et al. (30) | 11/11 | MDD | ERP | Serial choice reaction task | ↑ Post-imperative negative variation | |
| Schlegel et al. (31) | 36 | MDD | ERP | Bech–Rafaelsen Melancholia Scale | ↑ P300 latency | |
| Silfverskiöld et al. (32) | 21 | MDD | Global EEG frequency | Rating Scale for Affective Symptoms | ↓ Acute effects ↑ Non-acute effects | |
| Nieber et al. (33) | 63 | MDD | EEG power spectrum analysis | Bech–Rafaelsen Melancholia Scale | ↑ Slow activity ↓ Fast activity | |
| Schrijvers et al. (36) | 26 | MDD | ERP, Eriksen Flanker’s Task | Salpêtrière Retardation Rating Scale | ↑ Error-related negativity potentials | |
| Molecular neuroimaging | Walther et al. (37) | 20/19 | MDD | ASL | Wrist actigraphy | ↑ Right orbitofrontal cortex, ↓ left SMA |
| Bench et al. (38) | 40 | MDD | PET | HDRS | ↓ rCBF in left DLPFC, left parietal cortex | |
| Dolan et al. (39) | 40 | MDD | PET | HDRS | ↓ rCBF in left DLPFC | |
| Videbech et al. (40) | 42 | MDD | PET | HDRS | ↓ rCBF in DLPFC and OFC | |
| Milak et al. (41) | 298 | MDD | FDG-PET | HDRS | ↑ Metabolism in the cingulate gyrus, thalamus, and basal ganglia | |
| Dunn et al. (42) | 58 | MDD | FDG-PET | Beck’s Depression Inventory | ↓ Metabolism in right insula, claustrum, anteroventral caudate/putamen, and temporal cortex. | |
| ↑ Metabolism in ACC | ||||||
| Mayberg et al. (43) | 13 | MDD | 99mTc-SPECT | Finger-tapping | ↑ rCBF in paralimbic cortex (frontal and temporal) and prefrontal | |
| Meyer et al. (44) | 9/21 | MDD | RTI-32-PET | Finger-tapping | ↓ Dopamine transporter binding potential in striatum | |
| Meyer et al. (45) | 21 | MDD | Raclopride PET | Finger-tapping | ↑ Dopamine D2 receptor binding potential in the putamen | |
| Ebert et al. (46) | 20 | MDD | IBZM-SPECT | – | ↑ Striatal IBZM-BP | |
| Perico et al. (47) | 15 | MDD | 99mTc-SPECT | HDRS | ↑ Left premotor cortex and right anterior medial orbitofrontal cortex metabolism | |
| Graff-Guerrero et al. (48) | 14 | MDD | 99mTc-SPECT | HDRS | No significant correlation between retardation and CBF | |
| Brody et al. (49) | 39 | MDD | FDG-PET | HDRS | Improvement in psychomotor symptoms is associated with metabolism in dorsal ACC | |
| Transcranial sonography | Berg et al. (51) | 31 | PD with MDD | Ncl raphe | Columbia University Rating Scale | No significant correlation |
| Walter et al. (53) | 55 | MDD | Ncl raphe, substantia nigra | Unified Parkinson’s Disease Rating Scale (Motor part) | ↓ Raphe echogenicity, ↑ Substantia nigra echogenecity | |
| Walter et al. (54) | 52 | MDD | Ncl raphe | Motor Retardation and Agitation Scale | ↑ Raphe echogenecity | |
| Becker et al. (56) | 30 | PD with MDD | Ncl raphe | Columbia University Rating Scale | ↓ Raphe echogenecity | |
| Höppner et al. (57) | 45 | MDD | Substantia nigra | Finger-tapping (motor asymmetry), verbal fluency | ↑ Substantia nigra echogenic size |
ACC, anterior cingulate cortex; AS-18, affektiv skattningsskala 18 (59); ASL, arterial spin labeling; BP, binding potential; BPD, bipolar disorder depression; CT, computed tomography; DTI, diffusion tensor imaging; DLPFC, dorsolateral prefrontal cortex; EEG, electroencephalography; ERP, event-related potentials; FA, fractional anisotropy; FDG-PET, fluorodeoxyglucose positron emission tomography; fMRI, functional magnetic resonance imaging; HDRS, Hamilton Depression Rating Scale; IBZM, iodobenzamide single-photon emission computed tomography; MDD, major depressive disorder; MRI, magnetic resonance imaging; OFC, orbitofrontal cortex; PD, Parkinson’s disease; PET, positron emission tomography; ROI, region of interest; rCBF, regional cerebral blood flow; RTI-32, (1R-2-exo-3-exo)-8-methyl-3-(4-methylphenyl)-8-azabicyclo[3.2.1]octane-2-carboxylate; SMA, supplementary motor area; SPECT, single-photon emission computed tomography; 99mTc, Technetium-99.
Structural and functional neuroimaging studies suggest that PMD involve alterations in large-scale cortico-striato-thalamo-cortical neurocircuits, and in particular fronto-striatal subdivisions. Findings from transcranial ultrasound, and molecular neuroimaging studies, suggest a putative underlying factor for these alterations in the form of disrupted influence of ascending dopamine tracts that emanate from deeper midbrain nuclei. This notion also fits with the broader picture of a depressive disorder with psychomotor disturbances, which also include alterations in cognitive function, drive, and emotional expression – phenomena that also map onto ascending monoamine tracts with targets in the frontal lobe. Taken together, the broad picture suggests that PMD in major depressive disorder emerges from altered limbic signals at the interface of emotion, volition, higher-order cognitive function, and movement.
Our review shows that PMD is an emerging field of research that has kept growing since over 20 years. However, the currently available studies also preclude firmer evidence when evaluated in the context of general research methodology. Most studies are cross-sectional, have <25 participants, and have not been reproduced. Furthermore, a wide variety of clinical psychomotor measures have been used. Thus, information about the anatomical specificity of PMD from future studies could be improved by the use of objective measurements of motor performance (i.e., finger-tapping, actigraphy) when investigating the different dimensions of PMD delineated by current clinical measurements (i.e., CORE, MARS), and using rating scales that probe PMD specifically. Further studies would also benefit from longitudinal experimental designs that disentangle the effects of brain changes on the functional components of PMD, and assess differences across neuropsychiatric disorders.
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
BL received funding from Svenska Läkaresällskapet (The Swedish Society of Medicine, SLS-403101), and the Strategic Research Committee, Karolinska Institutet/Stockholm County Council, Sweden. CR received funding from Schizofreniförbundet, Sweden. We also thank Dr. Caroline Wachtler for language revisions of the manuscript.
References
- 1.Wells FL. Motor retardation as a manic-depressive symptom. Am J Insanity (1909) LXVI(1):1–51. [Google Scholar]
- 2.Kraepelin E, Diefendorf AR. Clinical Psychiatry. (Vol. xvii). New York, NY: The Macmillan Company; (1907). 562 p. [Google Scholar]
- 3.Parker G, Hadzi-Pavlovic D, Brodaty H, Boyce P, Mitchell P, Wilhelm K, et al. Psychomotor disturbance in depression: defining the constructs. J Affect Disord (1993) 27(4):255–65. 10.1016/0165-0327(93)90049-P [DOI] [PubMed] [Google Scholar]
- 4.Sobin C, Mayer L, Endicott J. The motor agitation and retardation scale: a scale for the assessment of motor abnormalities in depressed patients. J Neuropsychiatry Clin Neurosci (1998) 10(1):85–92. 10.1176/jnp.10.1.85 [DOI] [PubMed] [Google Scholar]
- 5.Widlocher DJ. Psychomotor retardation: clinical, theoretical, and psychometric aspects. Psychiatr Clin North Am (1983) 6(1):27–40. [PubMed] [Google Scholar]
- 6.Malhi GS, Berk M. Does dopamine dysfunction drive depression? Acta Psychiatr Scand Suppl (2007) 433:116–24. 10.1111/j.1600-0447.2007.00969.x [DOI] [PubMed] [Google Scholar]
- 7.Malhi GS, Parker GB, Greenwood J. Structural and functional models of depression: from sub-types to substrates. Acta Psychiatr Scand (2005) 111(2):94–105. 10.1111/j.1600-0447.2004.00475.x [DOI] [PubMed] [Google Scholar]
- 8.Hickie I, Scott E, Mitchell P, Wilhelm K, Austin MP, Bennett B. Subcortical hyperintensities on magnetic resonance imaging: clinical correlates and prognostic significance in patients with severe depression. Biol Psychiatry (1995) 37(3):151–60. 10.1016/0006-3223(94)00174-2 [DOI] [PubMed] [Google Scholar]
- 9.Wang L, Leonards CO, Sterzer P, Ebinger M. White matter lesions and depression: a systematic review and meta-analysis. J Psychiatr Res (2014) 56:56–64. 10.1016/j.jpsychires.2014.05.005 [DOI] [PubMed] [Google Scholar]
- 10.Najjar S, Pearlman DM. Neuroinflammation and white matter pathology in schizophrenia: systematic review. Schizophr Res (2015) 161(1):102–12. 10.1016/j.schres.2014.04.041 [DOI] [PubMed] [Google Scholar]
- 11.Walther S, Hugli S, Hofle O, Federspiel A, Horn H, Bracht T, et al. Frontal white matter integrity is related to psychomotor retardation in major depression. Neurobiol Dis (2012) 47(1):13–9. 10.1016/j.nbd.2012.03.019 [DOI] [PubMed] [Google Scholar]
- 12.Bracht T, Federspiel A, Schnell S, Horn H, Hofle O, Wiest R, et al. Cortico-cortical white matter motor pathway microstructure is related to psychomotor retardation in major depressive disorder. PLoS One (2012) 7(12):e52238. 10.1371/journal.pone.0052238 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Bracht T, Horn H, Strik W, Federspiel A, Schnell S, Hofle O, et al. White matter microstructure alterations of the medial forebrain bundle in melancholic depression. J Affect Disord (2014) 155:186–93 10.1016/j.jad.2013.10.048 [DOI] [PubMed] [Google Scholar]
- 14.Exner C, Lange C, Irle E. Impaired implicit learning and reduced pre-supplementary motor cortex size in early-onset major depression with melancholic features. J Affect Disord (2009) 119(1–3):156–62. 10.1016/j.jad.2009.03.015 [DOI] [PubMed] [Google Scholar]
- 15.Liberg B, Ekman CJ, Sellgren C, Johansson A, Landen M. Vertex-based morphometry in euthymic bipolar disorder implicates striatal regions involved in psychomotor function. Psychiatry Res (2014) 221(3):173–8. 10.1016/j.pscychresns.2014.01.007 [DOI] [PubMed] [Google Scholar]
- 16.Liberg B, Ekman CJ, Sellgren C, Johansson AG, Landen M. Subcortical morphometry and psychomotor function in euthymic bipolar disorder with a history of psychosis. Brain Imaging Behav (2014). 10.1007/s11682-014-9313-0 [DOI] [PubMed] [Google Scholar]
- 17.Naismith S, Hickie I, Ward PB, Turner K, Scott E, Little C, et al. Caudate nucleus volumes and genetic determinants of homocysteine metabolism in the prediction of psychomotor speed in older persons with depression. Am J Psychiatry (2002) 159(12):2096–8. 10.1176/appi.ajp.159.12.2096 [DOI] [PubMed] [Google Scholar]
- 18.Schlegel S, Maier W, Philipp M, Aldenhoff JB, Heuser I, Kretzschmar K, et al. Computed tomography in depression: association between ventricular size and psychopathology. Psychiatry Res (1989) 29(2):221–30. 10.1016/0165-1781(89)90037-1 [DOI] [PubMed] [Google Scholar]
- 19.Naismith SL, Lagopoulos J, Ward PB, Davey CG, Little C, Hickie IB. Fronto-striatal correlates of impaired implicit sequence learning in major depression: an fMRI study. J Affect Disord (2010) 125(1–3):256–61. 10.1016/j.jad.2010.02.114 [DOI] [PubMed] [Google Scholar]
- 20.Caligiuri MP, Brown GG, Meloy MJ, Eberson SC, Kindermann SS, Frank LR, et al. An fMRI study of affective state and medication on cortical and subcortical brain regions during motor performance in bipolar disorder. Psychiatry Res (2003) 123(3):171–82. 10.1016/S0925-4927(03)00075-1 [DOI] [PubMed] [Google Scholar]
- 21.Caligiuri MP, Brown GG, Meloy MJ, Eyler LT, Kindermann SS, Eberson S, et al. A functional magnetic resonance imaging study of cortical asymmetry in bipolar disorder. Bipolar Disord (2004) 6(3):183–96. 10.1111/j.1399-5618.2004.00116.x [DOI] [PubMed] [Google Scholar]
- 22.Marchand WR, Lee JN, Thatcher J, Thatcher GW, Jensen C, Starr J. A preliminary longitudinal fMRI study of frontal-subcortical circuits in bipolar disorder using a paced motor activation paradigm. J Affect Disord (2007) 103(1–3):237–41. 10.1016/j.jad.2007.01.008 [DOI] [PubMed] [Google Scholar]
- 23.Marchand WR, Lee JN, Thatcher JW, Thatcher GW, Jensen C, Starr J. A longitudinal functional magnetic resonance imaging study of frontal-subcortical circuits in bipolar disorder using a paced motor activation paradigm. Bipolar Disord (2007) 9:74–5. [DOI] [PubMed] [Google Scholar]
- 24.Liberg B, Adler M, Jonsson T, Landen M, Rahm C, Wahlund LO, et al. The neural correlates of self-paced finger tapping in bipolar depression with motor retardation. Acta Neuropsychiatr (2013) 25(1):43–51 10.1111/j.1601-5215.2012.00659.x [DOI] [PubMed] [Google Scholar]
- 25.Liberg B, Adler M, Jonsson T, Landen M, Rahm C, Wahlund LO, et al. Motor imagery in bipolar depression with slowed movement. J Nerv Ment Dis (2013) 201(10):885–93. 10.1097/NMD.0b013e3182a5c2a7 [DOI] [PubMed] [Google Scholar]
- 26.Liberg B, Klauser P, Harding IH, Adler M, Rahm C, Lundberg J, et al. Functional and structural alterations in the cingulate motor area relate to decreased fronto-striatal coupling in major depressive disorder with psychomotor disturbances. Front Psychiatry (2014) 5:176. 10.3389/fpsyt.2014.00176 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Marchand WR, Lee JN, Thatcher GW, Jensen C, Stewart D, Dilda V, et al. A functional MRI study of a paced motor activation task to evaluate frontal-subcortical circuit function in bipolar depression. Psychiatry Res (2007) 155(3):221–30. 10.1016/j.pscychresns.2007.03.003 [DOI] [PubMed] [Google Scholar]
- 28.Yao Z, Wang L, Lu Q, Liu H, Teng G. Regional homogeneity in depression and its relationship with separate depressive symptom clusters: a resting- state fMRI study. J Affect Disord (2009) 115(3):430–8. 10.1016/j.jad.2008.10.013 [DOI] [PubMed] [Google Scholar]
- 29.Nystrom C, Matousek M, Hallstrom T. Relationships between EEG and clinical characteristics in major depressive disorder. Acta Psychiatr Scand (1986) 73(4):390–4. 10.1111/j.1600-0447.1986.tb02700.x [DOI] [PubMed] [Google Scholar]
- 30.Thier P, Axmann D, Giedke H. Slow brain potentials and psychomotor retardation in depression. Electroencephalogr Clin Neurophysiol (1986) 63(6):570–81. 10.1016/0013-4694(86)90144-6 [DOI] [PubMed] [Google Scholar]
- 31.Schlegel S, Nieber D, Herrmann C, Bakauski E. Latencies of the P300 component of the auditory event-related potential in depression are related to the Bech-Rafaelsen melancholia scale but not to the Hamilton rating scale for depression. Acta Psychiatr Scand (1991) 83(6):438–40. 10.1111/j.1600-0447.1991.tb05571.x [DOI] [PubMed] [Google Scholar]
- 32.Silfverskiold P, Rosen I, Risberg J, Gustafson L. Changes in psychiatric symptoms related to EEG and cerebral blood flow following electroconvulsive therapy in depression. Eur Arch Psychiatry Neurol Sci (1987) 236(4):195–201 10.1007/BF00383849 [DOI] [PubMed] [Google Scholar]
- 33.Nieber D, Schlegel S. Relationships between psychomotor retardation and EEG power spectrum in major depression. Neuropsychobiology (1992) 25(1):20–3. 10.1159/000118804 [DOI] [PubMed] [Google Scholar]
- 34.Miltner WH, Lemke U, Weiss T, Holroyd C, Scheffers MK, Coles MG. Implementation of error-processing in the human anterior cingulate cortex: a source analysis of the magnetic equivalent of the error-related negativity. Biol Psychol (2003) 64(1–2):157–66. 10.1016/S0301-0511(03)00107-8 [DOI] [PubMed] [Google Scholar]
- 35.Vocat R, Pourtois G, Vuilleumier P. Unavoidable errors: a spatio-temporal analysis of time-course and neural sources of evoked potentials associated with error processing in a speeded task. Neuropsychologia (2008) 46(10):2545–55. 10.1016/j.neuropsychologia.2008.04.006 [DOI] [PubMed] [Google Scholar]
- 36.Schrijvers D, de Bruijn ER, Maas Y, De Grave C, Sabbe BG, Hulstijn W. Action monitoring in major depressive disorder with psychomotor retardation. Cortex (2008) 44(5):569–79. 10.1016/j.cortex.2007.08.014 [DOI] [PubMed] [Google Scholar]
- 37.Walther S, Hofle O, Federspiel A, Horn H, Hugli S, Wiest R, et al. Neural correlates of disbalanced motor control in major depression. J Affect Disord (2012) 136(1–2):124–33. 10.1016/j.jad.2011.08.020 [DOI] [PubMed] [Google Scholar]
- 38.Bench CJ, Friston KJ, Brown RG, Frackowiak RS, Dolan RJ. Regional cerebral blood flow in depression measured by positron emission tomography: the relationship with clinical dimensions. Psychol Med (1993) 23(3):579–90. 10.1017/S0033291700025368 [DOI] [PubMed] [Google Scholar]
- 39.Dolan RJ, Bench CJ, Liddle PF, Friston KJ, Frith CD, Grasby PM, et al. Dorsolateral prefrontal cortex dysfunction in the major psychoses; symptom or disease specificity? J Neurol Neurosurg Psychiatry (1993) 56(12):1290–4. 10.1136/jnnp.56.12.1290 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Videbech P, Ravnkilde B, Pedersen TH, Hartvig H, Egander A, Clemmensen K, et al. The Danish PET/depression project: clinical symptoms and cerebral blood flow. A regions-of-interest analysis. Acta Psychiatr Scand (2002) 106(1):35–44. 10.1034/j.1600-0447.2002.02245.x [DOI] [PubMed] [Google Scholar]
- 41.Milak MS, Parsey RV, Keilp J, Oquendo MA, Malone KM, Mann JJ. Neuroanatomic correlates of psychopathologic components of major depressive disorder. Arch Gen Psychiatry (2005) 62(4):397–408. 10.1001/archpsyc.62.4.397 [DOI] [PubMed] [Google Scholar]
- 42.Dunn RT, Kimbrell TA, Ketter TA, Frye MA, Willis MW, Luckenbaugh DA, et al. Principal components of the Beck depression inventory and regional cerebral metabolism in unipolar and bipolar depression. Biol Psychiatry (2002) 51(5):387–99. 10.1016/S0006-3223(01)01244-6 [DOI] [PubMed] [Google Scholar]
- 43.Mayberg HS, Lewis PJ, Regenold W, Wagner HN, Jr. Paralimbic hypoperfusion in unipolar depression. J Nucl Med (1994) 35(6):929–34. [PubMed] [Google Scholar]
- 44.Meyer JH, Kruger S, Wilson AA, Christensen BK, Goulding VS, Schaffer A, et al. Lower dopamine transporter binding potential in striatum during depression. Neuroreport (2001) 12(18):4121–5. 10.1097/00001756-200112210-00052 [DOI] [PubMed] [Google Scholar]
- 45.Meyer JH, McNeely HE, Sagrati S, Boovariwala A, Martin K, Verhoeff NP, et al. Elevated putamen D(2) receptor binding potential in major depression with motor retardation: an [11C]raclopride positron emission tomography study. Am J Psychiatry (2006) 163(9):1594–602. 10.1176/ajp.2006.163.9.1594 [DOI] [PubMed] [Google Scholar]
- 46.Ebert D, Feistel H, Loew T, Pirner A. Dopamine and depression – striatal dopamine D2 receptor SPECT before and after antidepressant therapy. Psychopharmacology (1996) 126(1):91–4. 10.1007/BF02246416 [DOI] [PubMed] [Google Scholar]
- 47.Perico CA, Skaf CR, Yamada A, Duran F, Buchpiguel CA, Castro CC, et al. Relationship between regional cerebral blood flow and separate symptom clusters of major depression: a single photon emission computed tomography study using statistical parametric mapping. Neurosci Lett (2005) 384(3):265–70 10.1016/j.neulet.2005.04.088 [DOI] [PubMed] [Google Scholar]
- 48.Graff-Guerrero A, Gonzalez-Olvera J, Mendoza-Espinosa Y, Vaugier V, Garcia-Reyna JC. Correlation between cerebral blood flow and items of the Hamilton rating scale for depression in antidepressant-naive patients. J Affect Disord (2004) 80(1):55–63. 10.1016/S0165-0327(03)00049-1 [DOI] [PubMed] [Google Scholar]
- 49.Brody AL, Saxena S, Mandelkern MA, Fairbanks LA, Ho ML, Baxter LR. Brain metabolic changes associated with symptom factor improvement in major depressive disorder. Biol Psychiatry (2001) 50(3):171–8. 10.1016/S0006-3223(01)01117-9 [DOI] [PubMed] [Google Scholar]
- 50.Becker G, Berg D, Lesch KP, Becker T. Basal limbic system alteration in major depression: a hypothesis supported by transcranial sonography and MRI findings. Int J Neuropsychopharmacol (2001) 4(1):21–31. 10.1017/S1461145701002164 [DOI] [PubMed] [Google Scholar]
- 51.Berg D, Supprian T, Hofmann E, Zeiler B, Jager A, Lange KW, et al. Depression in Parkinson’s disease: brainstem midline alteration on transcranial sonography and magnetic resonance imaging. J Neurol (1999) 246(12):1186–93. 10.1007/s004150050541 [DOI] [PubMed] [Google Scholar]
- 52.Becker G, Struck M, Bogdahn U, Becker T. Echogenicity of the brainstem raphe in patients with major depression. Psychiatry Res (1994) 55(2):75–84. 10.1016/0925-4927(94)90002-7 [DOI] [PubMed] [Google Scholar]
- 53.Walter U, Hoeppner J, Prudente-Morrissey L, Horowski S, Herpertz SC, Benecke R. Parkinson’s disease-like midbrain sonography abnormalities are frequent in depressive disorders. Brain (2007) 130(Pt 7):1799–807. 10.1093/brain/awm017 [DOI] [PubMed] [Google Scholar]
- 54.Walter U, Prudente-Morrissey L, Herpertz SC, Benecke R, Hoeppner J. Relationship of brainstem raphe echogenicity and clinical findings in depressive states. Psychiatry Res (2007) 155(1):67–73. 10.1016/j.pscychresns.2006.12.001 [DOI] [PubMed] [Google Scholar]
- 55.Budisic M, Karlovic D, Trkanjec Z, Lovrencic-Huzjan A, Vukovic V, Bosnjak J, et al. Brainstem raphe lesion in patients with major depressive disorder and in patients with suicidal ideation recorded on transcranial sonography. Eur Arch Psychiatry Clin Neurosci (2010) 260(3):203–8. 10.1007/s00406-009-0043-z [DOI] [PubMed] [Google Scholar]
- 56.Becker T, Becker G, Seufert J, Hofmann E, Lange KW, Naumann M, et al. Parkinson’s disease and depression: evidence for an alteration of the basal limbic system detected by transcranial sonography. J Neurol Neurosurg Psychiatry (1997) 63(5):590–6. 10.1136/jnnp.63.5.590 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Hoeppner J, Prudente-Morrissey L, Herpertz SC, Benecke R, Walter U. Substantia nigra hyperechogenicity in depressive subjects relates to motor asymmetry and impaired word fluency. Eur Arch Psychiatry Clin Neurosci (2009) 259(2):92–7. 10.1007/s00406-008-0840-9 [DOI] [PubMed] [Google Scholar]
- 58.Kupferschmidt DA, Zakzanis KK. Toward a functional neuroanatomical signature of bipolar disorder: quantitative evidence from the neuroimaging literature. Psychiatry Res (2011) 193(2):71–9. 10.1016/j.pscychresns.2011.02.011 [DOI] [PubMed] [Google Scholar]
- 59.Adler M, Liberg B, Andersson S, Isacsson G, Hetta J. Development and validation of the affective self rating scale for manic, depressive, and mixed affective states. Nord J Psychiatry (2008) 62(2):130–5. 10.1080/08039480801960354 [DOI] [PubMed] [Google Scholar]
