Beyond mood — depression as a speed disorder: biomarkers for abnormal slowness

Biomarkers play a crucial role in clinical diagnosis and therapy. There are various types of biomarkers concerning diagnosis, monitoring, treatment response, outcome prediction, prognosis, safety, and susceptibility/risk.¹ In fields like internal medicine, biomarkers such as bilirubin and glucose are essential for identifying conditions like jaundice and diabetes. In contrast, there are no established biomarkers for diagnosing or treating mental disorders. A recent comprehensive review² highlighted some potential candidates for biomarkers in autism, schizophrenia, and anxiety disorders, though none have shown conclusive results.

This challenge is even more pronounced for mood disorders like major depressive disorder (MDD), which is characterized by symptoms such as persistent low mood, sadness, lack of motivation, and loss of interest or pleasure; identifying potential biomarkers for MDD has proven difficult.² The complexity is further heightened by the wide variety and individual variability of symptoms as well as by their intrinsic connections; that is, “symptom coupling,”^3,4 where cognitive changes (e.g., rumination, impaired working memory), neuro-vegetative alterations (e.g., chest pain, constipation, irritable bowel), social and interpersonal difficulties (e.g., social anxiety, withdrawal), psychomotor changes (retardation or agitation), and sensory-perceptual deficits (e.g., altered visual perception) are often coupled in varying degrees with each other in different individuals.^3,4,5

How (not) to search for biomarkers in mental disorders

How can one detect biomarkers for such variety and complexity of different symptom constellations? Current research strategies focus on finding psychological or neural biomarkers within each of these symptom domains — cognitive, affective, somatic, social, sensory, and motor. I propose an alternative strategy. Instead of looking for markers specific to each symptom domain, I identify a feature that links and is common to all these symptoms across their different domains. This leads me to search for a “basic disturbance” that underlies and is shared across the different symptom domains. ^5,6 My strategy of searching for a basic disturbance is akin to the field of internal medicine identifying, for instance, diabetes.⁷ We don’t search for markers in diabetes that are specific to each symptom, like retinopathy or foot gangrene; instead, we look for the common factor — elevated glucose levels — that underlies these varied symptoms of diabetes. Analogously, I suggest searching for markers that indicate a shared basic disturbance across the cognitive, sensory, motor, and emotional symptoms in MDD (Figure 1).

Figure 1.

Dynamic approach to biomarkers. Unlike the current approach, which seeks biomarkers in relation to specific symptom domains (e.g., affective, cognitive, sensory, motor), a dynamic approach searches for a basic disturbance on a deeper level that is shared across the different symptom domains. Such basic disturbance concerns dynamics, the pattern of change over time that can be measured, for instance, by variability, scale-free dynamics (i.e., a specific slow–fast frequency power distribution), timescales, and synchrony (bottom). This leads us to assume dynamic diagnostic markers in both the different symptoms domains (upper left) and the brain (upper right). Figure created with BioRender (www.biorender.com).

What is the basic dynamic disturbance in depression?

The prevailing view is that MDD is primarily a mood disorder. However, it is well known that MDD extends far beyond mood-related symptoms, affecting cognitive, social, sensory, and motor domains as well. This broader impact shifts the focus to what these various symptoms share and what might underlie them across their different domains. I propose that the common factor is reduced dynamics. To clarify, in physics, dynamics generally refers to changes over time that can follow specific patterns measurable through, for instance, variability, scale-free dynamics (i.e., a specific slow–fast frequency power distribution), synchronization, and timescales. ⁵ In this sense, dynamics encompass dimensions such as duration, precision, irregularity, stability or instability, and speed.⁷

I suggest that speed is the key dynamic dimension relevant to MDD. Speed, simply put, is the rate of change in the position of an object or the distance travelled per unit of time. A range of neuronal, psychological, and phenomenological evidence leads me to propose that the fundamental dynamic disturbance in MDD is a deficit in speed; in other words, individuals with MDD are simply too slow. This speed deficit underlies and connects the different symptom domains: patients with depression are slow in perception, action, emotion, and cognition. Further, slowness is also mirrored in the brain’s neural activity during both spontaneous and task-related activity.^5,7 Thus, I characterize the basic disturbance in MDD as a disorder of speed rather than just as a mood disorder. Labelling it solely as a mood disorder would be too limited to explain the intrinsic symptom coupling of cognitive, somatic, affective, sensory, and motor changes. Additionally, this perspective allows for considering subtypes of depression. Retarded depression is marked by abnormally slow speed in thoughts, emotions, and movements; conversely, agitated depression exhibits increased speed in the same symptom domains. Despite the opposite directions — slow versus fast — both share the same fundamental or basic disturbance in speed.

The question then arises: can measures of reduced (or increased) speed, reflecting abnormal slowness (or fastness) in the various symptom domains, serve as a strong candidate for a diagnostic biomarker of acute depression in MDD? I will explore this question in 3 steps, presenting empirical evidence that abnormal slowness, measured in various ways, is a basic or fundamental disturbance in MDD at both psychological and neural levels, and then providing evidence for using these measures of abnormal slowness as biomarkers for the diagnosis of MDD and its differential diagnosis from both bipolar disorder (BD) and schizophrenia.

The psychological perspective: from abnormal slowness to depressive symptoms in perception, cognition, and emotion

Slowed perception

While not typically the main focus of research, studies have shown that people with MDD often experience their visual world differently. They tend to see things as if through “grey-coloured glasses”⁸ and may feel that events unfold too quickly for them to follow comfortably.^9,10 These observations hint at a potential speed deficit in visual processing for individuals with MDD, an idea supported by recent research. For example, studies by Song and colleagues^11,12 and Liu and colleagues¹³ found that people with acute MDD needed more time to complete a specific visual task. In this task, participants had to identify the direction of moving patterns on a screen. The fact that patients with MDD consistently took longer to detect this motion suggests they process visual information, particularly movement, more slowly than others. This slower processing of dynamic visual information could explain why some people with depression feel the world moves too fast around them.

Researchers have also examined how people with depression perceive the size of moving visual stimuli. They used the suppression index (SI), which measures the degree to which participants can inhibit or suppress the moving boundaries of the stimuli; this compares responses to small and large stimuli to gauge how well the brain filters out unnecessary visual information.¹¹ People with MDD had lower SI scores than healthy individuals, and the scores worsened as depression symptoms increased. This finding suggests that along-side slower visual processing, people with depression may also experience changes in how they perceive spatial relationships in their environment. Some studies have hypothesized the changes to be related to lower levels of γ-aminobutyric acid (GABA), a brain chemical that helps regulate neural activity in the visual cortex.^11,13

Further evidence of speed deficits in visual processing in depression comes from studies examining how people’s responses change from trial to trial in visual tasks. Individuals with MDD show less variation in their responses over time than those without depression.¹² This reduced variability suggests that their visual perception remains more constant, which aligns with the common experience of people with depression feeling that “nothing changes in my acute depressed state.”¹⁰ Interestingly, this decreased variability in visual perception is linked to a slowing of physical movements, known as psychomotor retardation. The less variable a person’s visual responses are, the more likely they are to show signs of slowed movement and speech. This connection suggests that the slowing down seen in depression affects both how people take in visual information (input processing) and how they physically respond to their environment (output processing).¹⁴ These findings may help explain why people with severe depression often feel stuck in a world that seems unchanging and why they might move and react more slowly to things around them.¹²

Finally, a recent study by Song and colleagues¹² provides additional evidence for visual speed deficits in depression. They found that people with MDD had difficulty distinguishing between slower and faster visual stimuli, unlike healthy individuals. Specifically, individuals with MDD needed similar amounts of time to process both slow and fast visual information, suggesting they perceive these stimuli in a more uniform way. In essence, they tend to perceive both slow and fast visual stimuli similarly, as if viewing the world in a more static rather than dynamic manner. This “flattening” of speed perception adds to our understanding of how depression can alter a person’s visual experience of the world, making it seem less dynamic and more unchanging.

In summary, these studies show that people with acute MDD experience slower visual perception. These visual speed deficits have been shown in several ways: longer processing times for visual information, less variation in how they perceive things over time, and difficulty distinguishing between slow and fast visual stimuli. These measures could potentially serve as diagnostic biomarkers of depression for its speed disturbance in the visual domain.

However, it is important to note some limitations. While these findings are clear at the group level, we don’t yet know how well they can distinguish between individuals with and without depression. We also need to investigate how specific these markers are to depression. For instance, people with schizophrenia show increased rather than decreased perceptual variability in the same tasks,¹² which could help differentiate between these conditions. Moreover, understanding these visual speed deficits on both perceptual and neural levels of the visual cortex opens new possibilities for treatment. A recent study by Zhang and colleagues¹⁵ showed promising results using transcranial magnetic stimulation on the visual cortex to treat acute depression. These findings not only enhance our understanding of how depression affects visual perception, but also point toward potential new diagnostic tools and treatment approaches. However, more research is needed to fully realize these possibilities in clinical practice.

Slowed cognition

Major depressive disorder is characterized by several symptoms, including altered cognition and rumination — repetitive, negative thoughts. While most studies focus on the content of these thoughts (e.g., guilt, hopelessness), recent research has begun to examine thought dynamics — how thoughts change over time. A study by Rostami and colleagues¹⁶ investigated thought dynamics in patients with MDD, albeit with a small sample size of 24 participants. They tracked how participants’ thoughts shifted between internal (self-focused) and external (environment-focused) content over time. The resulting data were analyzed using power spectrum analysis. The study found that, compared with healthy individuals, who had more frequent and shorter external thoughts, patients with MDD had more internal thoughts that lasted longer. Patients with MDD also showed a lower frequency of shifts between internal and external thoughts, reflected in a lower power spectral density (PSD). Importantly, this lower PSD correlated with overall symptom severity (measured using the Beck Depression Inventory [BDI]), specific symptoms like loss of energy and difficulty concentrating, and higher levels of rumination, particularly brooding.

These findings suggest that the slowing of the thought processes themselves in MDD extends beyond just their contents, affecting the dynamics of thought patterns as well. This “cognitive slowness” manifests as reduced thought variability as well as slower shifts between internal and external thought contents. However, it is crucial to note that this study primarily applies to 1 subtype of MDD — the “retarded” type characterized by slow thoughts, psychomotor retardation, and sadness. Another subtype, “agitated MDD,” may show the opposite pattern, with racing thoughts and psychomotor agitation. Therefore, we can tentatively propose that MDD, in general, involves a disturbance in cognitive speed. This could manifest as abnormal slowness in some subtypes and abnormal fastness in others. This variation in thought dynamics could potentially serve as a diagnostic biomarker for different MDD subtypes, though more research with larger sample sizes is needed to confirm this hypothesis.

Slowed emotions

The phenomenon of decreased speed in MDD extends beyond cognitive processes to affect emotional dynamics as well. Research has shown that individuals with MDD experience reduced variability in their emotional states over time.

A study by Wichers and colleagues¹⁷ examined this emotional inertia in 6 participants with MDD using a method called experience sampling. Participants reported their subjective experiences 3 times daily over a period of 3–6 months. The researchers analyzed these time series data using a measure called the autocorrelation window (ACW), which reflects how long a particular emotional state persists. Interestingly, they found that the ACW became longer and showed higher variance about 1 month before the onset of an acute depressive episode. This prolongation of the ACW is interpreted as an early sign of “critical slowing down” in emotional dynamics, potentially signalling an impending depressive episode. Other studies with larger sample sizes have corroborated these findings.

Cramer and colleagues,¹⁸ Schreuder and colleagues,¹⁹ and van de Leemput and colleages²⁰ all observed similar prolongations of the ACW in the emotional time series of participants with MDD. This increased emotional inertia appears to be associated with greater interconnectedness among various behavioural and psychological variables within the network of depressive symptoms. In other words, as emotional states become more persistent, different aspects and symptoms of depression become more tightly linked with each other. It is worth noting that this pattern of increased slowing accompanied by increased connectivity isn’t limited to psychological phenomena. Similar patterns have been observed at the neural level, suggesting a potential parallel between psychological and neurobiological processes in MDD.

These findings collectively point to a broader pattern of slowing down in MDD that encompasses perceptual, cognitive, and emotional domains. This slowing, particularly when it manifests as increased emotional inertia, may serve as an early warning sign for depressive episodes and could potentially inform new approaches to prevention and treatment.

In summary, I have shown that slowness is a characteristic feature of MDD across multiple domains: visual perception, cognition, and affect/mood. In visual perception, a motion suppression task reveals psychophysical responses indicative of slowness. For cognition, analyzing the frequency and PSD of shifts between internal and external thought content can quantify cognitive slowness. In the affective domain, emotional changes can be examined using the “critical slowing down” index, revealing affective slowness. Crucially, these measures of slowness correlate with specific symptoms associated with each domain: static visual perception and slowed visual perception were related to psychomotor retardation; cognitive slowness in thoughts was associated with rumination; and in the affective domain, slowness was connected to persistently sad mood. Together, these findings suggest that slowness is not isolated to 1 symptom, but is a common thread running through various symptom domains in MDD. While not explicitly shown in this editorial, previous research has shown that abnormal slowness can also be observed in other symptom domains, such as psychomotor function, social interactions, and somatic (bodily) processes.^21,22 The pervasive nature of this slowness across different symptoms and aspects of experience and behaviour lends support to the assumption that slowness may be a basic disturbance of MDD.

Rather than being a secondary effect or consequence of other symptoms, slowness appears to be a core feature of the disorder itself: slowness is its basic disturbance that is manifest in various ways, depending on the specific symptom domain affected. This perspective on slowness as a basic disturbance in MDD could have important implications for our understanding of the disorder’s underlying mechanisms and could potentially inform new approaches to diagnosis and treatment.

The neural perspective — from abnormal slowness in the brain’s neural activity to depressive symptom severity

If abnormal slowness is indeed a basic disturbance of MDD, there would need to be corresponding slowness in the brain’s neural activity; this is the focus of the following section.

Reduced neural speed in the brain’s spontaneous activity relates to symptom severity

The brain’s neural activity can be investigated in terms of its functions (e.g., affective, cognitive, motor) when measuring task-related activity, or alternatively, its resting state activity can be targeted in terms of networks, such as with functional connectivity. Recent work has examined the brain’s neural dynamics by investigating its neural variability, scale-free dynamics, timescales, and synchronization.⁵ This approach allows for the investigation of the brain’s neural speed during both rest and task states. Initial studies in MDD have pursued this approach, showing that neural activity is literally too slow in these patients.

Functional MRI has shown resting state activity in acute MDD to be abnormally slow in the visual cortex and medial prefrontal cortex, as well as other regions.²³ This was measured by shifts in the power spectrum toward slower frequencies, indicating decreased power in faster frequencies as measured by median frequency (MF). Importantly, the reduced speed (MF) was directly related to symptom severity (BDI): the lower the MF indexing reduced speed, the more severe the depressive symptoms. These findings align with other resting state fMRI studies where participants with MDD were shown to exhibit longer dwelling times of their dynamic functional connectivity with lower variability in the default mode network (DMN) and frontoparietal regions.²⁴ This indicates higher and longer temporal stability, reflecting increased slowness of the brain’s spontaneous or resting state activity in MDD.

Collectively, these findings show that the speed of the brain’s spontaneous activity is reduced and thus abnormally slow, which relates to depressive symptom severity. This neural-level evidence supports the hypothesis of slowness as a basic disturbance in MDD, extending observations from the psychological level to the brain itself.

Delayed functional connectivity from global brain to motor cortex relates to psychomotor retardation

One of the most noticeable symptoms in acute MDD is an abnormal slowness in movement, known as psychomotor retardation. Actigraphy-based quantitative analyses have shown that individuals with MDD move more slowly and with less variability.²⁵

Resting-state fMRI studies have linked this psychomotor retardation to specific neural changes. Wuethrich and colleagues²⁶ found that psychomotor retardation in MDD was associated with increased functional connectivity between several cortical and subcortical areas, including the pre-motor and motor cortex, cerebellum, thalamus, and basal ganglia. Functional connectivity reflects the degree of synchronization between the activity time series of different brain regions.⁵ Therefore, these findings suggest that there is excessive neural synchronization within the subcortical–cortical motor system, making it difficult to initiate movements, as doing so would require a reduction in this intrinsic synchronization.

These findings leave open the source of such increased neural synchronization. This could originate within the motor system itself (the motor hypothesis) or from other brain regions, such as sensory areas or even from the brain’s global activity (the psychomotor hypothesis).³ Song and colleagues¹¹ investigated this further and observed reduced global synchronization in the motor cortex (e.g., degree centrality and regional homogeneity). Interestingly, these motor cortex measures did not correlate with psychomotor retardation. However, the medial temporal visual area (i.e., MT⁺ region of the visual cortex), along with its connection to both the brain’s global activity (e.g., degree centrality) and the motor cortex (e.g., MT^+/− motor cortex functional connectivity), was abnormally reduced in MDD. This reduction correlated with the severity of psychomotor retardation: the greater the global activity in the MT⁺ region and its functional connectivity to the motor cortex, the more severe the psychomotor retardation. This suggests that the motor cortex may become “enslaved” by other brain regions, particularly the visual cortex, reducing its autonomy and making it difficult to initiate movement.

The role of global brain activity in psychomotor retardation is further supported by Liang and colleagues.²⁷ Their study involving a large sample of patients with acute MDD showed that psychomotor retardation and agitation are linked to distinct temporal patterns of connectivity between global brain activity and the motor cortex. In patients with psychomotor retardation, the connectivity from global brain activity to the motor cortex was delayed, whereas in patients with psychomotor agitation this connectivity was more immediate. Hence, during psychomotor retardation, the subcortical–cortical motor system, including the motor cortex, receives delayed and thus decreased inputs from the other regions of the brain; that is, its global activity. This delayed input to the motor cortex seems to lead to its reduced activation,²⁶ ultimately hindering movement initiation.

Together, these findings suggest the root cause of psychomotor retardation and its impact on the motor cortex lie outside the motor system itself, specifically in the brain’s global activity whose delayed connectivity to the motor cortex results in psychomotor retardation. This points to a more global cortical, and thus psychomotor, rather than a local motor cortical source of psychomotor retardation.^3,12,27 This is closely linked to a dynamic deficit: the abnormal slowness in connectivity from the brain’s global cortex to the motor cortex, which directly relates to psychomotor retardation.^12,27

Task-related activity shows reduced neural response to fast stimuli, which relates to psychomotor retardation

The visual perceptual changes mentioned previously are also linked to the brain’s visual cortex. Song and colleagues¹¹ found that these changes were associated with reduced GABA levels in MT⁺, a region sensitive to visual motion. Additionally, Liu and colleagues¹³ showed abnormal neural variability in MT⁺, which also exhibits reduced global activity. ¹² This same MT⁺ region displays abnormally high functional connectivity with typical “depression regions” in the frontal cortex, such as the medial prefrontal cortex and the subgenual anterior cingulate cortex.^13,15

Lu and colleagues²⁸ studied medication-free, acutely depressed participants with MDD using both fast and slow visual stimuli, coupled with negative and neutral images. Participants had decreased task-related activity in the visual cortex and various DMN regions, particularly in response to fast, negative visual stimuli. Notably, this decreased response correlated with the severity of psychomotor retardation: the lower the activity in these regions in response to fast negative stimuli, the stronger the psychomotor retardation. Another fMRI study¹² reported reduced neural responses in higher-order motion-sensitive regions of the visual cortex (e.g., MT⁺) in patients with MDD, specifically during exposure to fast stimuli. These findings suggest that the brain of depressed individuals processes fast stimuli as if they were slow, leading to the perception of abnormal slowness.

Together, these studies provide evidence for an abnormal slowness in the brain’s spontaneous neural activity at rest; a decreased response to (especially) fast and negative stimuli during tasks; and a direct link between neural and behavioural slowness in acute MDD, as seen in psychomotor retardation. Consequently, measures of neural speed, such as MF, neural variability, time-lagged functional connectivity, and amplitude/response to slow versus fast stimuli, may serve as strong candidates for diagnostic biomarkers of acute MDD.

In summary, speed is reduced at the level of the brain. The brain’s spontaneous activity during rest is inherently too slow, and this slowness is linked to symptom severity and psychomotor retardation. Additionally, in MDD, the neural response to specific fast (and negative) stimuli during tasks is also reduced. Together, these findings show that abnormal slowness can be observed in both resting-state and task-related neural activities. This speed deficit is not confined to specific regions or networks; rather, it appears to be a global characteristic affecting the entire brain, including all its regions and the functional connectivity between them. Although future research is needed, this suggests that the speed deficit of the brain’s neural activity might be a fundamental disturbance affecting all symptom domains and their neural correlates in a similar manner. Because it is distributed across the whole brain, this slowness could influence all regions and networks involved in different symptoms and their domains — whether cognitive, affective, motor, or sensory — by making them abnormally slow. I, therefore, view MDD as a global topographic-dynamic brain disorder,⁵ which can be traced to a speed deficit with abnormal slowness as its basic disturbance, rather than a disorder localized to specific regions or networks.²⁹

One might argue that not all individuals with MDD have the same symptoms; some experience more severe psychomotor retardation, while others exhibit more pronounced cognitive dysfunction, such as rumination and working memory deficits, indicating the presence of distinct subtypes. ²⁹ I tentatively propose that these individual differences and potential subtypes may relate to varying topographic balances in global brain activity, such as between global and motor cortex activity or global and prefrontal cortex activity. Future research linking this interindividual variability and the subtypes to distinct global topographic-dynamic balances is needed to support this hypothesis. Initial evidence comes from the work of Liang and colleagues, ²⁷ who showed that psychomotor retardation and agitation in MDD can be distinguished by their temporal dynamics; that is, delayed versus early patterns in global-to-motor cortex functional connectivity.

The potential of abnormal slowness measures for differential diagnosis

An essential characteristic of effective diagnostic biomarkers is their ability to distinguish MDD from other mental health conditions. For simplicity, I focus on how these biomarkers can help differentiate acute MDD from 2 other conditions: BD and schizophrenia. I examine some previously mentioned studies and their measurements, concentrating on how they facilitate differential diagnosis.

MDD v. BD — psychological and neural markers

Rostami and colleagues¹⁶ investigated thought dynamics in MDD and BD. They found that both groups exhibited more internal thoughts and fewer external thoughts than healthy controls. However, participants with MDD showed longer durations of external thoughts than those with BD. Power spectral analyses of thought dynamics revealed similarities and differences. Both MDD and BD showed decreased PSD in thought changes compared with controls. However, patients with MDD showed lower frequency shifts than both those with BD and controls, while the BD and control groups did not differ from each other. These findings suggest that examining thought dynamics and speed may help distinguish MDD from BD.

At the neural level, similarities and differences were also observed. Scalabrini and colleagues²³ used fMRI to show that both participants with MDD and those with BD exhibit global topographic-dynamic shifts from sensory regions toward the DMN and prefrontal cortex. However, they differed in functional connectivity within specific networks; for example, decreased connectivity in the central-executive network (CEN) in those with BD. Lechner and Northoff³⁰ found similar patterns in resting-state electroencephalography (EEG). Both participants with MDD and those with BD showed decreased phase variability in frontal theta (θ). However, those with MDD uniquely exhibited increased delays in α phase variability in centro-parietal electrodes, highlighting subtle neural differences between the disorders that are embedded within their more basic neural similarities.

Biomarkers for distinguishing depression from non-depression, and MDD from BD

Initial findings indicate that dynamic speed measures have strong potential for distinguishing MDD frrom BD. Two types of possible biomarkers have been identified. The first type includes psychological and neural markers like internal thought duration, thought PSD, global neural shift from sensory areas to the DMN observed in fMRI, and reduced frontal θ phase variability seen in EEG. These markers represent common and thus shared features of depression present in both MDD and BD, making them useful for distinguishing depression from non-depression across these diagnostic categories. The second type of biomarkers includes psychological and neural markers like external thought duration; thought shift frequency; neural measures, such as activity in specific networks (e.g., the central executive network); and α phase variability. These markers may help differentiate MDD from BD as distinct diagnostic categories within the shared symptom or syndrome of depression.

In summary, the findings suggest that different speed markers can be used to distinguish depression from non-depression across the diagnostic boundaries of MDD and BD as well as to differentiate between the diagnostic categories of MDD and BD. One can thus differentiate “gradients of slowness” in individuals with MDD or BD whose measures show both their similarities and differences. Future research should examine the same data in 2 ways: first, using a dimensional, transdiagnostic approach (e.g., Research Domain Criteria) to explore shared aspects of depression as distinguished from non-depression, and second, using a more categorical, DSM-based framework to focus on the distinction between MDD and BD. Moreover, these results highlight the importance of measuring multiple aspects of the target features or processes; relying on a single measure, such as resting-state functional connectivity in fMRI or a single EEG power frequency (like α or θ), may be insufficient to capture both the dimensional trans-diagnostic and diagnostic-categorical complexity of MDD and BD.

MDD v. schizophrenia — measures of the dynamics of visual perception

Previous research has already shown altered visual perception in MDD. The same motion suppression task was investigated in individuals with acute schizophrenia.³¹ They examined irregularities in visual perception by measuring the variability in perceptual duration across different trials in the motion suppression task. Results showed that a subgroup of patients with schizophrenia exhibited increased variability, indicating irregular perceptual durations. In contrast, a second schizophrenia subgroup displayed “normal” variability, with no irregularity relative to healthy controls. Interestingly, the subgroup with high variability correlated with negative symptoms on the Positive and Negative Syndrome Scale (PANSS), while the subgroup with “normal” variability was associated with positive symptoms. Furthermore, it was found that the relationship between static measures of visual perception (e.g., SI) and negative symptoms was fully mediated by this variability, highlighting the importance of abnormal perceptual dynamics.

These findings emphasize the significance of variability in investigating psychological functions like perception and cognition. Moreover, they may have implications for differential diagnosis: while patients with schizophrenia show abnormally high trial-to-trial variability in visual perception, those with MDD exhibit reduced variability compared with healthy controls.¹² Collectively, these results suggest that dynamic measures of visual perception have the potential to facilitate the differential diagnosis of psychiatric conditions at a purely psychological or psychophysical level.

MDD v. schizophrenia — measures of time perception

Extensive research has explored time perception and experience in MDD and schizophrenia through phenomenological studies.^10,32–36 In MDD, the findings highlight experiences of abnormal slowness, loss of energy, and a focus on the past rather than the future. In contrast, time perception in schizophrenia is more characterized by temporal fragmentation, a disturbed synthesis of time, and premonitions. These differences in time perception between MDD and schizophrenia are further supported by studies that have directly compared the 2 conditions, confirming that these characteristics are relatively specific to each disorder.^10,30,32,37 This research has led to the development of time (and space) experience scales,^34,36,38 which may serve as initial screening tools for the differential diagnosis of MDD/BD, SZ, and anxiety.³⁸

MDD v. schizophrenia v. BD — measures of phase dynamics in EEG

Dynamic neural measures also offer a way to differentiate between MDD and schizophrenia. Lechner and Northoff^39,40 investigated EEG-based resting state activity, focusing on the spontaneous phase dynamics in schizophrenia, MDD, and BD. They examined the variability and specifically the regularity or irregularity of phase variability by measuring entropy. The results showed that patients with schizophrenia had increased entropy in frontal θ phase variability compared with healthy controls. In contrast, both patients with MDD and those with BD exhibited decreased frontal θ phase variability, indicating a different pattern than the increased irregularity observed in those with schizophrenia.

These EEG resting-state findings suggest that a detailed analysis of phase dynamics can help distinguish MDD from both BD and schizophrenia, as well as differentiate BD from schizophrenia.^30,39,40 Additionally, decreased task-related phase coherence, measured by the reduction of intertrial phase coherence, is emerging as a promising marker for schizophrenia, effectively distinguishing it from both BD and MDD.^39,41,42

Biomarkers for different basic disturbances in MDD and schizophrenia

The findings in schizophrenia suggest that its characteristics are not primarily related to speed, as seen in MDD and BD. Instead, schizophrenia is marked by abnormalities indicating temporal irregularity. Visual measures show increased variability, time perception is characterized by temporal fragmentation, and EEG results point to phase irregularities with increased entropy. Therefore, unlike the speed-related disturbances in MDD and BD, schizophrenia appears to involve a decrease in temporal precision, as indicated by heightened perceptual variability, neural phase entropy, and fragmented time experience.

Based on these and other findings, it is proposed that schizophrenia may involve a different basic dynamic disturbance than MDD. Specifically, schizophrenia may be characterized by temporal imprecision (in the millisecond range) as its basic disturbance, while MDD is more associated with abnormal slowness.^40–42 Although still in the early stages, this perspective of identifying different basic disturbances in MDD and schizophrenia has important implications for detecting biomarkers. Measures of temporal imprecision at both neural and psychological levels could serve as candidate biomarkers for schizophrenia, distinguishing it from MDD. Conversely, measures of speed, such as abnormal slowness, could help differentiate MDD from schizophrenia. Additionally, in BD, speed measures could be useful since BD might also involve a basic disturbance in speed — either abnormally slow, as in the depressive state of BD, or abnormally fast, as in the manic state of BD.¹⁴ Future research should explore the potential of these different measures as candidate biomarkers across MDD, BD, and schizophrenia (Figure 2).

Figure 2.

Dynamic markers for differential diagnosis between (left) major depressive disorder (MDD) and bipolar disorder (BD) as well as between (right) MDD and schizophrenia (SZ). One novel dynamic marker consists of the measurement of the duration and frequency of thoughts: people can report when their thought content changes which, if measured in multiple trials, provides a time series on which power spectrum and frequency can be calculated.¹⁶ The same can be done in the case of perception, where the duration of perceptual contents and their change can be measured on a purely psychological level.³¹ CEN = central executive network; EEG = electroencephalography; fMRI = functional magnetic resonance imaging. Figure created with BioRender (www.biorender.com).

Conclusion

My goal in this editorial was to highlight the potential utility of speed measures, such as abnormal slowness on both psychological and neural levels, as strong biomarker candidates for MDD. I pursued an approach that differs from the common strategy; rather than focusing on biomarkers related to specific symptoms as distinct from others, I sought to identify a common feature across various symptom domains (e.g., cognitive, motor, sensory, affective). Therefore, my focus has been on the fundamental or basic disturbance in MDD that underlies and connects these different symptoms through a common or shared feature.

I suggest that this shared feature consists of reduced speed, or abnormal slowness. I propose that the basic disturbance in MDD can be understood as a “speed disorder,” offering a broader comprehensive framework than the restrictive characterization of MDD as simply a “mood disorder.” I presented multiple lines of empirical evidence showing reduced speed, or abnormal slowness, in MDD at both psychological and neural levels. These findings also demonstrate a direct relationship between various speed measures and typical MDD symptoms, such as static perception, psychomotor retardation, overall symptom severity, rumination, and sadness. This pattern is particularly evident in a specific subtype of depression known as retarded MDD. On the other hand, agitated and anxious forms of MDD may also involve a speed disturbance, but characterized by abnormal fastness as manifest in racing thoughts, anxiety, and psychomotor agitation. Thus, to fully capture the complexity of MDD, I describe it as a basic disturbance of speed, which can manifest as either abnormally fast or slow.

Can these measures of reduced (or increased) speed on psychological and neural levels serve as potential biomarkers for diagnosing and differentiating MDD? Although the findings are preliminary, they suggest that various measures of abnormal slowness could help distinguish MDD from other conditions like BD and schizophrenia. For instance, schizophrenia is marked by a different basic disturbance (i.e., temporal imprecision), rather than a speed deficit with abnormal slowness or fastness (Figure 2). If this approach proves successful, it will demonstrate the scientific and clinical value of a primarily dynamic and spatiotemporal (rather than cognitive or affective) approach to understanding psychopathological symptoms and mental disorders.^6,36,43,44

To develop these speed measures into robust diagnostic biomarkers for MDD, several steps need to be taken: testing the utility of dynamic speed measures in larger groups of 500–1000 individuals with acute MDD; demonstrating their ability to distinguish between healthy and depressed individuals at the single-participant level, extending beyond current group-based results; examining their capacity to differentiate between different states of depression, such as acute, chronic, remitted, or at-risk depression, through longitudinal studies; identifying biomarkers that can differentiate depression as a syndrome in a transdiagnostic manner from non-depression and distinguish MDD from BD and schizophrenia in a categorical framework; identifying different degrees of the same speed markers in specific MDD subtypes, such as retarded (high slowness) and agitated (high speed) depression; exploring how other symptoms, like feelings of guilt, anhedonia, sleep disturbances, and somatic changes, relate to abnormal speed (either slow or fast) in MDD; and considering the possibility of a co-occurrence of both abnormally slow and fast speed between different symptom domains. Additional steps include connecting speed measures as diagnostic biomarkers to other types of biomarkers, such as monitoring, outcome prediction, therapy response, safety, and susceptibility/risk;¹ ideally linking speed measures to other biomarker candidates of depression in fields like proteomics, metabolomics, genomics, transcriptomics, and epigenetics;^1,2 relating these speed measures to biochemical levels of serotonin, GABA, and glutamate;^4,45,46 demonstrating the specificity of speed markers of abnormal slowness for MDD as distinct from BD, schizophrenia, anxiety, and other mental disorders; and exploring how speed markers of abnormal slowness can guide personalized therapy, for example, by individualizing the target regions for transcranial magnetic stimulation in the motor cortex, visual cortex, or lateral prefrontal cortex.^15,47