Ocular motor differences between melancholic and non-melancholic depression

Differentiating melancholic and non-melancholic depression via biological markers: A review

OBJECTIVES

Melancholia is a severe form of depression that is typified by greater genetic and biological influence, distinct symptomatology, and preferential response to physical treatment. This paper sought to broadly overview potential biomarkers of melancholia to benefit differential diagnosis, clinical responses and treatment outcomes. Given nuances in distinguishing melancholia as its own condition from other depressive disorder, we emphasised studies directly comparing melancholic to non-melancholic depression.

METHODS

A comprehensive literature search was conducted. Key studies were identified and summarised qualitatively.

RESULTS

105 studies in total were identified. These studies covered a wide variety of biomarkers, and largely fell into three domains: endocrinological (especially cortisol levels, particularly in response to the dexamethasone suppression test), neurological, and immunological (particularly inflammatory markers). Less extensive evidence also exists for metabolic, genetic, and cardiovascular markers.

CONCLUSIONS

Definitive conclusions were predominantly limited due to substantial heterogeneity in how included studies defined melancholia. Furthermore, this heterogeneity could be responsible for the between- and within-group variability observed in the candidate biomarkers that were examined. Therefore, clarifying these definitional parameters may help identify underlying patterns in biomarker expression to improve diagnostic and therapeutic precision for the depressive disorders.

Abnormal eye movement features in patients with depression: Preliminary findings based on eye tracking technology

BACKGROUND

Saccadic eye movement (SEM) has been considered a non-invasive potential biomarker for the diagnosis of depression in recent years, but its application is not yet mature. In this study, we used eye-tracking technology to identify the eye movements of patients with depression to develop a new method for objectively identifying depression.

METHODS

Thirty-six patients with depression as the depression group, while thirty-six matched healthy individuals as the control group were recruited and completed eye movement tests, including two tasks: the prosaccade task and the antisaccade task. iViewX RED 500 eye-tracking instruments from SMI were used to collect eye movement data for both groups.

RESULTS

In the prosaccade task, there was no difference between the depression and control groups(t = 0.019， P > 0.05). In general, with increasing angle, both groups showed significantly higher peak velocity (F = 81.72， P < 0.0001), higher mean velocity (F = 32.83, P = 0.000), and greater SEM amplitude (F = 24.23, P < 0.0001). In the antisaccade task, there were significant differences in correct rate (t = 3.219, P = 0.002) and mean velocity (F = 3.253， P < 0.05) between the depression group and the control group. In the anti-effect analysis, there were significant differences in correct rate (F = 67.44, P < 0.0001) and accuracy (F = 79.02, P < 0.0001) between the depression group and the control group. Both groups showed longer latency and worse correct rate and precision in the antisaccade task compared with the prosaccade task.

CONCLUSION

Patients with depression showed different eye movement features, which could be potential biomarkers for clinical identification. Further studies must validate these results with larger sample sizes and more clinical populations.

Deep Neural Networks for Depression Recognition Based on 2D and 3D Facial Expressions Under Emotional Stimulus Tasks

The proportion of individuals with depression has rapidly increased along with the growth of the global population. Depression has been the currently most prevalent mental health disorder. An effective depression recognition system is especially crucial for the early detection of potential depression risk. A depression-related dataset is also critical while evaluating the system for depression or potential depression risk detection. Due to the sensitive nature of clinical data, availability and scale of such datasets are scarce. To our knowledge, there are few extensively practical depression datasets for the Chinese population. In this study, we first create a large-scale dataset by asking subjects to perform five mood-elicitation tasks. After each task, subjects' audio and video are collected, including 3D information (depth information) of facial expressions via a Kinect. The constructed dataset is from a real environment, i.e., several psychiatric hospitals, and has a specific scale. Then we propose a novel approach for potential depression risk recognition based on two kinds of different deep belief network (DBN) models. One model extracts 2D appearance features from facial images collected by an optical camera, while the other model extracts 3D dynamic features from 3D facial points collected by a Kinect. The final decision result comes from the combination of the two models. Finally, we evaluate all proposed deep models on our built dataset. The experimental results demonstrate that (1) our proposed method is able to identify patients with potential depression risk; (2) the recognition performance of combined 2D and 3D features model outperforms using either 2D or 3D features model only; (3) the performance of depression recognition is higher in the positive and negative emotional stimulus, and females' recognition rate is generally higher than that for males. Meanwhile, we compare the performance with other methods on the same dataset. The experimental results show that our integrated 2D and 3D features DBN is more reasonable and universal than other methods, and the experimental paradigm designed for depression is reasonable and practical.

Computer Vision for Brain Disorders Based Primarily on Ocular Responses

Real-time ocular responses are tightly associated with emotional and cognitive processing within the central nervous system. Patterns seen in saccades, pupillary responses, and spontaneous blinking, as well as retinal microvasculature and morphology visualized via office-based ophthalmic imaging, are potential biomarkers for the screening and evaluation of cognitive and psychiatric disorders. In this review, we outline multiple techniques in which ocular assessments may serve as a non-invasive approach for the early detections of various brain disorders, such as autism spectrum disorder (ASD), Alzheimer's disease (AD), schizophrenia (SZ), and major depressive disorder (MDD). In addition, rapid advances in artificial intelligence (AI) present a growing opportunity to use machine learning-based AI, especially computer vision (CV) with deep-learning neural networks, to shed new light on the field of cognitive neuroscience, which is most likely to lead to novel evaluations and interventions for brain disorders. Hence, we highlight the potential of using AI to evaluate brain disorders based primarily on ocular features.

Evaluating the severity of depressive symptoms using upper body motion captured by RGB-depth sensors and machine learning in a clinical interview setting: A preliminary study

BACKGROUND

Mood disorders have long been known to affect motor function. While methods to objectively assess such symptoms have been used in experiments, those same methods have not yet been applied in clinical practice because the methods are time-consuming, labor-intensive, or invasive.

METHODS

We videotaped the upper body of each subject using a Red-Green-Blue-Depth (RGB-D) sensor during a clinical interview setting. We then examined the relationship between depressive symptoms and body motion by comparing the head motion of patients with major depressive disorders (MDD) and bipolar disorders (BD) to the motion of healthy controls (HC). Furthermore, we attempted to predict the severity of depressive symptoms by using machine learning.

RESULTS

A total of 47 participants (HC, n = 16; MDD, n = 17; BD, n = 14) participated in the study, contributing to 144 data sets. It was found that patients with depression move significantly slower compared to HC in the 5th percentile and 50th percentile of motion speed. In addition, Hamilton Depression Rating Scale (HAMD)-17 scores correlated with 5th percentile, 50th percentile, and mean speed of motion. Moreover, using machine learning, the presence and/or severity of depressive symptoms based on HAMD-17 scores were distinguished by a kappa coefficient of 0.37 to 0.43.

LIMITATIONS

Limitations include the small number of subjects, especially the number of severe cases and young people.

CONCLUSIONS

The RGB-D sensor captured some differences in upper body motion between depressed patients and controls. If much larger samples are accumulated, machine learning may be useful in identifying objective measures for depression in the future.

The Potential of Game-Based Digital Biomarkers for Modeling Mental Health

BACKGROUND

Assessment for mental health is performed by experts using interview techniques, questionnaires, and test batteries and following standardized manuals; however, there would be myriad benefits if behavioral correlates could predict mental health and be used for population screening or prevalence estimations. A variety of digital sources of data (eg, online search data and social media posts) have been previously proposed as candidates for digital biomarkers in the context of mental health. Playing games on computers, gaming consoles, or mobile devices (ie, digital gaming) has become a leading leisure activity of choice and yields rich data from a variety of sources.

OBJECTIVE

In this paper, we argue that game-based data from commercial off-the-shelf games have the potential to be used as a digital biomarker to assess and model mental health and health decline. Although there is great potential in games developed specifically for mental health assessment (eg, Sea Hero Quest), we focus on data gathered "in-the-wild" from playing commercial off-the-shelf games designed primarily for entertainment.

METHODS

We argue that the activity traces left behind by natural interactions with digital games can be modeled using computational approaches for big data. To support our argument, we present an investigation of existing data sources, a categorization of observable traits from game data, and examples of potentially useful game-based digital biomarkers derived from activity traces.

RESULTS

Our investigation reveals different types of data that are generated from play and the sources from which these data can be accessed. Based on these insights, we describe five categories of digital biomarkers that can be derived from game-based data, including behavior, cognitive performance, motor performance, social behavior, and affect. For each type of biomarker, we describe the data type, the game-based sources from which it can be derived, its importance for mental health modeling, and any existing statistical associations with mental health that have been demonstrated in prior work. We end with a discussion on the limitations and potential of data from commercial off-the-shelf games for use as a digital biomarker of mental health.

CONCLUSIONS

When people play commercial digital games, they produce significant volumes of high-resolution data that are not only related to play frequency, but also include performance data reflecting low-level cognitive and motor processing; text-based data that are indicative of the affective state; social data that reveal networks of relationships; content choice data that imply preferred genres; and contextual data that divulge where, when, and with whom the players are playing. These data provide a source for digital biomarkers that may indicate mental health. Produced by engaged human behavior, game data have the potential to be leveraged for population screening or prevalence estimations, leading to at-scale, nonintrusive assessment of mental health.

Regional cerebral metabolism alterations affect resting-state functional connectivity in major depressive disorder

Background

¹⁸F-FDG positron emission tomography (PET) is a reliable technique to quantify regional neural glucose metabolism even with major depressive disorder (MDD) heterogeneous features. Previous study proposed that in the resting-state (RS), pairs of brain regions whose regional glucose metabolic rates were significantly correlated were functionally associated. This synchronicity indicates a neuronal metabolic and functional interaction in high energy efficient brain regions. In this study, a multimode method was used to identify the RS-FC patterns based on regional metabolism changes, and to observe its relationship with the severity of depressive symptoms in MDD patients.

Methods

The study enrolled 11 medication-naive MDD patients and 14 healthy subjects. All participants received a static ¹⁸F-FDG PET brain scan and a resting-state functional magnetic resonance imaging (RS-fMRI) scan. SPM5 software was used to compare brain metabolism in MDD patients with that in healthy controls, and designated regions with a change in metabolism as regions of interest (ROIs). The glucose metabolism-based regional RS-FC Z values were compared between groups. Then group independent component analysis (ICA) was used to identify the abnormal connectivity nodes in the intrinsic function networks. Finally, the correlation between abnormal RS-FC Z values and the severity of depressive symptoms was evaluated.

Results

Patients with MDD had reduced glucose metabolism in the putamen, claustrum, insular, inferior frontal gyrus, and supramarginal gyrus. The metabolic reduction regions impaired functional connectivity (FC) to key hubs, such as the Inferior frontal gyrus (pars triangular), angular gyrus, calcarine sulcus, middle frontal gyrus (MFG), located in dorsolateral prefrontal cortex (DLPFC)/parietal lobe, salience network (SN), primary visual cortex (V1), and language network respectively. There was no correlation between aberrant connectivity and the severity of clinical symptoms.

Conclusions

This research puts forward a possibility that focal neural activity alteration may share RS-FC dysfunction and be susceptible to hubs in the functional network in MDD. In particular, the metabolism and function profiles of the Inferior frontal gyrus (pars triangularis) should be emphasized in future MDD studies.

The properties and utility of the CORE measure of melancholia

BACKGROUND

The CORE measure was designed to assess a central feature of melancholia - signs of psychomotor disturbance (PMD) - and so provide an alternate non-symptom based measure of melancholia or of its probability. This review evaluates development and application studies undertaken over the last 25 years to consider how well it has met its original objectives.

METHODS

All studies published using the CORE measure as either the only or an adjunctive measure of melancholia were obtained and are considered in this review.

RESULTS

Findings suggest high reliability in quantifying CORE scores can be achieved and that it has construct validity as a measure of PMD. A number of application studies assessing socio-demographic factors, cognitive and motor impairment, dexamethasone suppression and thyrotropin-releasing hormone, response to psychotherapy and to electroconvulsive therapy support its validity as a measure of melancholia, while functional brain imaging studies suggest that the measure identifies regions of decreased connectivity.

LIMITATIONS

Use of the CORE benefits from rater training and for subjects to be assessed at or near nadir of their depressive episode. There have been insufficient studies evaluating genetic factors, and the treatment response of CORE-defined melancholic patients to antidepressant drugs of differing classes.

CONCLUSIONS

The CORE, either as a proxy or direct measure of melancholia, provides a strategy for assigning depressed subjects a diagnosis or melancholic or non-melancholic depression or for estimating the probability of melancholia.

Eye Movement in Unipolar and Bipolar Depression: A Systematic Review of the Literature

BACKGROUND

The analysis of eye movements (EM) by eye-tracking has been carried out for several decades to investigate mood regulation, emotional information processing, and psychomotor disturbances in depressive disorders.

METHOD

A systematic review of all English language PubMed articles using the terms "saccadic eye movements" OR "eye-tracking" AND "depression" OR "bipolar disorders" was conducted using PRISMA guidelines. The aim of this review was to characterize the specific alterations of EM in unipolar and bipolar depression.

RESULTS

Findings regarding psychomotor disturbance showed an increase in reaction time in prosaccade and antisaccade tasks in both unipolar and bipolar disorders. In both disorders, patients have been reported to have an attraction for negative emotions, especially for negative pictures in unipolar and threatening images in bipolar disorder. However, the pattern could change with aging, elderly unipolar patients disengaging key features of sad and neutral stimuli. METHODological limitations generally include small sample sizes with mixed unipolar and bipolar depressed patients.

CONCLUSION

Eye movement analysis can be used to discriminate patients with depressive disorders from controls, as well as patients with bipolar disorder from patients with unipolar depression. General knowledge concerning psychomotor alterations and affective regulation strategies associated with each disorder can also be gained thanks to the analysis. Future directions for research on eye movement and depression are proposed in this review.

Saccadic eye movements in depressed elderly patients

The primary aim of this study was to characterize oculomotor performances in elderly depressed patients. The second aim was to investigate whether cognitive inhibition measured by the antisaccade task was associated with a psychomotor retardation or rather with a more specific cognitive-motor inhibition deficit. Twenty patients with a major depressive disorder and forty-seven healthy subjects performed two eye movement tasks. Saccadic reaction time and error rates were analyzed in the prosaccade task to obtain basic parameters of eye movements. Saccade latency, error rates and correction rates were evaluated in the antisaccade task to investigate inhibition capacities. Performances were impaired in patients, who exhibited a higher reaction time and error rates compared to controls. The higher time cost of inhibition suggested that the reaction time was not related to global psychomotor retardation alone. The higher time cost of inhibition could be explained by a specific alteration of inhibition processes evaluated by the antisaccade task. These changes were associated with the severity of depression. These findings provide a new perspective on cognitive inhibition in elderly depressed patients and could have important clinical implications for our understanding of critical behaviors involving deficits in inhibitory processes in the elderly.

Psychomotor retardation in depression: a systematic review of diagnostic, pathophysiologic, and therapeutic implications

Psychomotor retardation is a central feature of depression which includes motor and cognitive impairments. Effective management may be useful to improve the classification of depressive subtypes and treatment selection, as well as prediction of outcome in patients with depression. The aim of this paper was to review the current status of knowledge regarding psychomotor retardation in depression, in order to clarify its role in the diagnostic management of mood disorders. Retardation modifies all the actions of the individual, including motility, mental activity, and speech. Objective assessments can highlight the diagnostic importance of psychomotor retardation, especially in melancholic and bipolar depression. Psychomotor retardation is also related to depression severity and therapeutic change and could be considered a good criterion for the prediction of therapeutic effect. The neurobiological process underlying the inhibition of activity includes functional deficits in the prefrontal cortex and abnormalities in dopamine neurotransmission. Future investigations of psychomotor retardation should help improve the understanding of the pathophysiological mechanisms underlying mood disorders and contribute to improving their therapeutic management.

Psychomotor retardation in depression: a systematic review of diagnostic, pathophysiologic, and therapeutic implications

Psychomotor retardation is a central feature of depression which includes motor and cognitive impairments. Effective management may be useful to improve the classification of depressive subtypes and treatment selection, as well as prediction of outcome in patients with depression. The aim of this paper was to review the current status of knowledge regarding psychomotor retardation in depression, in order to clarify its role in the diagnostic management of mood disorders. Retardation modifies all the actions of the individual, including motility, mental activity, and speech. Objective assessments can highlight the diagnostic importance of psychomotor retardation, especially in melancholic and bipolar depression. Psychomotor retardation is also related to depression severity and therapeutic change and could be considered a good criterion for the prediction of therapeutic effect. The neurobiological process underlying the inhibition of activity includes functional deficits in the prefrontal cortex and abnormalities in dopamine neurotransmission. Future investigations of psychomotor retardation should help improve the understanding of the pathophysiological mechanisms underlying mood disorders and contribute to improving their therapeutic management.

Ischaemic stroke: the ocular motor system as a sensitive marker for motor and cognitive recovery

OBJECTIVE

To evaluate the sensitivity of measuring cognitive processing in the ocular motor system as a marker for recovery of deficit in post stroke patients.

METHODS

15 patients (mean age 60.6 years, mean National Institutes of Health Stroke Scale (NIHSS) score 2.25) and 10 age matched control subjects (mean age 63.3 years) participated in the study. We included mildly affected acute stroke patients without a visual field defect or gaze palsy. Patients were examined at onset and at 1 month and 3 months post stroke by testing ocular motor function, NIHSS, modified Rankin Scale (mRS) and standard cognitive function assessments.

RESULTS

Significant differences were found in measures of ocular motor function between groups at stroke onset as well as between the first test and follow-up in patients. At 3 months, function had not returned to normal baseline. Ocular motor function was more sensitive in identifying cognitive dysfunction and improvement compared with NIHSS or mRS.

CONCLUSIONS

Standard neurological assessments of stroke patients are weighted significantly towards motor and sensory function, underestimating cognitive deficits. Ocular motor assessment demonstrates cognitive effects of even mild stroke and may provide improved quantifiable measurements of cognitive recovery post stroke. We demonstrated abnormality in patients just after onset, extending beyond 3 months, when there was apparent full recovery of motor and sensory function, implying more widespread disruption of cognitive mechanisms, consistent with the subjective complaints received from patients. This may provide insight into cognitive rehabilitation strategies leading to improved functional outcomes.

Saccadic eye movement applications for psychiatric disorders

OBJECTIVE

The study presented here analyzed the patterns of relationship between oculomotor performance and psychopathology, focusing on depression, bipolar disorder, schizophrenia, attention-deficit hyperactivity disorder, and anxiety disorder.

METHODS

Scientific articles published from 1967 to 2013 in the PubMed/Medline, ISI Web of Knowledge, Cochrane, and SciELO databases were reviewed.

RESULTS

Saccadic eye movement appears to be heavily involved in psychiatric diseases covered in this review via a direct mechanism. The changes seen in the execution of eye movement tasks in patients with psychopathologies of various studies confirm that eye movement is associated with the cognitive and motor system.

CONCLUSION

Saccadic eye movement changes appear to be heavily involved in the psychiatric disorders covered in this review and may be considered a possible marker of some disorders. The few existing studies that approach the topic demonstrate a need to improve the experimental paradigms, as well as the methods of analysis. Most of them report behavioral variables (latency/reaction time), though electrophysiological measures are absent.

Temporal discounting of reward and the cost of time in motor control

Why do movements take a characteristic amount of time, and why do diseases that affect the reward system alter control of movements? Suppose that the purpose of any movement is to position our body in a more rewarding state. People and other animals discount future reward as a hyperbolic function of time. Here, we show that across populations of people and monkeys there is a correlation between discounting of reward and control of movements. We consider saccadic eye movements and hypothesize that duration of a movement is equivalent to a delay of reward. The hyperbolic cost of this delay not only accounts for kinematics of saccades in adults, it also accounts for the faster saccades of children, who temporally discount reward more steeply. Our theory explains why saccade velocities increase when reward is elevated, and why disorders in the encoding of reward, for example in Parkinson's disease and schizophrenia, produce changes in saccade. We show that delay of reward elevates the cost of saccades, reducing velocities. Finally, we consider coordinated movements that include motion of eyes and head and find that their kinematics is also consistent with a hyperbolic, reward-dependent cost of time. Therefore, each voluntary movement carries a cost because its duration delays acquisition of reward. The cost depends on the value that the brain assigns to stimuli, and the rate at which it discounts this value in time. The motor commands that move our eyes reflect this cost of time.

Eye tracking dysfunction in schizophrenia: characterization and pathophysiology

Eye tracking dysfunction (ETD) is one of the most widely replicated behavioral deficits in schizophrenia and is over-represented in clinically unaffected first-degree relatives of schizophrenia patients. Here, we provide an overview of research relevant to the characterization and pathophysiology of this impairment. Deficits are most robust in the maintenance phase of pursuit, particularly during the tracking of predictable target movement. Impairments are also found in pursuit initiation and correlate with performance on tests of motion processing, implicating early sensory processing of motion signals. Taken together, the evidence suggests that ETD involves higher-order structures, including the frontal eye fields, which adjust the gain of the pursuit response to visual and anticipated target movement, as well as early parts of the pursuit pathway, including motion areas (the middle temporal area and the adjacent medial superior temporal area). Broader application of localizing behavioral paradigms in patient and family studies would be advantageous for refining the eye tracking phenotype for genetic studies.

Impaired implicit learning and reduced pre-supplementary motor cortex size in early-onset major depression with melancholic features

BACKGROUND

Major depression is a heterogeneous disorder. Biological markers and cognitive tasks have been employed to distinguish clinical subtypes but results have been inconclusive.

METHODS

The current study assessed implicit learning with the Serial Reaction Time Task (SRTT) known to be sensitive to frontostriatal dysfunctions and regional brain volumes of the anterior supplementary motor area (pre-SMA) in participants with early-onset major depression (MD) of either melancholic (n=26) or non-melancholic (n=9) subtype, and 26 matched controls.

RESULTS

Depressive subjects with melancholic features but not those with non-melancholic depression showed implicit learning deficits. This deficit could not be explained in terms of more severe depression or psychomotor retardation. Regional volumes of the right pre-SMA were reduced in depressive subjects with melancholic features.

LIMITATIONS

Medication effects in depressive subjects and the small size of the non-melancholic sample should be taken into consideration when reviewing the implications of these results.

CONCLUSIONS

Deficits in implicit motor sequence learning seem to be an additional characteristic of the melancholic subtype of depression. It might be linked to dysfunction within structural or functionally altered frontostriatal circuits. Use of implicit sequence learning tasks could offer useful diagnostic and aetiological cues for future research.

The tell-tale tasks: a review of saccadic research in psychiatric patient populations

This review focuses on saccade research with adult psychiatric patients. It begins with an introduction of the various types of saccades and the tasks used to evoke them. The functional significance of the different types of eye movements is briefly discussed. Research findings regarding the saccadic performance of different adult psychiatric patient populations are discussed in detail, with particular emphasis on findings regarding error rates, response latencies, and any specific task parameters that might affect those variables. Findings regarding the symptom, neurocognitive, and neural correlates of saccadic performance and the functional significance of patients' saccadic deficits are also discussed. We also discuss the saccadic deficits displayed by various patient groups in terms of circuitry (e.g. cortical/basal ganglia circuits) that may be implicated in the underlying pathophysiology of several of these disorders. Future directions for research in this growing area are offered.

Inhibitory control and spatial working memory: a saccadic eye movement study of negative symptoms in schizophrenia

The negative symptoms of schizophrenia are perhaps the most unremitting and burdensome features of the disorder. Negative symptoms have been associated with distinct motor, cognitive and neuropathological impairments, possibly stemming from prefrontal dysfunction. Eye movement paradigms can be used to investigate basic sensorimotor functions, as well as higher order cognitive aspects of motor control such as inhibition and spatial working memory - functions subserved by the prefrontal cortex. This study investigated inhibitory control and spatial working memory in the saccadic system of 21 patients with schizophrenia (10 with high negative symptoms scores and 11 with low negative symptom scores) and 14 healthy controls. Tasks explored suppression of reflexive saccades during qualitatively different tasks, the generation of express and anticipatory saccades, and the ability to respond to occasional, unpredictable ("oddball") targets that occurred during a sequence of well-learned, reciprocating saccades between horizontal targets. Spatial working memory was assessed using a single and a two-step memory-guided task (involving a visually-guided saccade during the delay period). Results indicated significant increases in response suppression errors, as well as increased response selection impairments, during the oddball task, in schizophrenia patients with prominent negative symptoms. The variability of memory-guided saccade accuracy was also increased in patients with prominent negative symptom scores. Collectively, these findings provide further support for the proposed association between prefrontal dysfunction and negative symptoms.

Inhibitory control and spatial working memory in Parkinson's disease

Patients with Parkinson's disease (PD) have difficulty performing tasks relying on inhibitory control and working memory, functions of the prefrontal cortex. Eye movement paradigms can be used to investigate basic sensorimotor functions and higher order cognitive aspects of motor control. This study investigated inhibitory control and spatial working memory in the saccadic system of 13 individuals with mild-moderate PD and 13 age-matched controls. Tasks explored suppression of reflexive saccades during qualitatively different tasks, generation of express and anticipatory saccades, and the ability to respond to occasional, unpredictable ("oddball") targets that occurred during a sequence of well-learned, reciprocating saccades between horizontal targets. Spatial working memory was assessed using single and two-step (involving a visually guided saccade during the delay period) memory-guided tasks. Results for the PD group indicated an increased percentage of response selection errors during an oddball task, reduced suppression of inappropriate reflexive saccades during memory-guided tasks (but not during fixation or saccade-engagement tasks), and an increased percentage of express and anticipatory saccades. Spatial working memory was preserved in the PD group during single and two-step memory-guided tasks. These findings are consistent with dysfunction within fronto-striatal and prefrontal-collicular pathways influencing suppression and selection of eye movements.

Disorders of saccades

Saccades are rapid eye movements that assist vision by pointing the fovea of the retina, which contains the highest density of photoreceptors, at features of interest in the visual environment. A great deal is now known about the properties and neurobiology of saccades in both health and disease states. They have consequently become a valuable diagnostic and research tool. In this review, we describe the common saccadic disorders and their causes. We also highlight recent insights into the pathophysiologic mechanisms underlying these disorders and discuss how these insights have helped increase our understanding of the saccadic system as a whole.

Does dopamine dysfunction drive depression?

OBJECTIVE

To examine the evidence that dopamine (DA) dysfunction contributes to melancholic depression.

METHOD

Database (EMBASE, PsychLit and MEDLINE) searches using relevant key words were conducted and citations were scrutinized.

RESULTS

In this paper, we assume that the definition of melancholia is contingent upon the presence of psychomotor disturbance (PMD). In melancholic depression PMD comprises both a cognitive and motor component and DA is found to be important in both. DA neurotransmission modulates cognition in particular in attention, adaptation and motivational processes and has a pivotal role in motor function.

CONCLUSION

DA is a credible aetiological candidate for the PMD in melancholic depression. However, melancholia needs first to be characterized both clinically and in terms of its pathophysiology. In this regard, illnesses such as bipolar depression and Parkinson's disease warrant consideration as they provide suitable models of both the cognitive and motor aspects of PMD, and hold the necessary markers to better define melancholia.