Depression Affects Working Memory Performance: A Functional Near Infrared Spectroscopy (fNIRS) Study*

Abstract

Depression is a complex disorder that can be caused by psychosocial and biological conditions and it not only effects mood disorders, but also cognitive functions such as memory, decision making, psychomotor speed and attention. As a result of the studies, some findings indicate that depressed individuals perform worse in neuropsychological tests than healthy individuals, while other studies indicate there is no difference between the two groups. According to neuroimaging studies on this subject, functional and anatomical differences were detected at the cortex and subcortical levels in the prefrontal lobe. This study is consisting of two parts, behavioral and neuroimaging using fNIRS. BDI was applied to the participants. The average age of the group with lower BDI score is 23,9±3,04; the average age of the higher group with higher BDI score is 22,2+2,28. A visuospatial 2-back task, which includes 4 different stimulus types with neutral, emotional, verbal, and non-verbal qualities, was applied to the participants. No significant differences were observed between the two groups in behavioral data. However, when fNIRS results were examined, it was found that the group with the high BDI scores showed more activation in the right PFC during the visuospatial 2-back task compared to the group with low BDI scores. Although the fNIRS results are consistent in the literature, behavioral findings support some of the findings in literature, while contradicting others. It is thought that the reason for this may be that participants are young, and the 2-back task is not difficult enough.

Introduction

Depression affects some cognitive functions such as attention, memory, learning, and decision making, although this disorder is included within the category of mood disorders in the DSM-5 (1–4). Cognitive disorders observed in depression are difficulties in making decisions due to slowing down of the thought system and tendency to negative thoughts, memory impairment increases with the severity of depression, delusions that may lead to suicide due to mood disorders and attention disorders (2).

In depression, anatomical and functional changes are also observed in the brain (5). Although attention, memory and executive functions have been shown to be negatively affected (3, 4, 6), some studies have not found any abnormal results regarding these cognitive processes, but neuroimaging findings have been shown to indicate a difference in neural activity (7). These abnormalities were seen in the prefrontal cortex (PFC) and in subcortical structures such as some regions of the striatum, amygdala, and thalamus (8).

A study published in 2016 applied a neuropsychological test battery to people diagnosed with major depressive disorder to examine the relationship between the severity of major depression symptoms and subjective memory complaints, and showed that the scores of patients with depressive disorder were significantly lower than the healthy controls (9). It has been reported that people with high depression scores have low scores in some functions specific to the right hemisphere (10).

According to the results of the NIRS study conducted by Liu et al., which deals with the differentiation in brain activity in depression, the oxyhemoglobin (oxyHb) changes were observed in bilateral PFC and anteromedial PFC in the MDD (11).

In a review study, it is said that people with depression perform poorly in cognitive tests related to areas such as recognizing emotional faces, line direction, 3-D structure perception, spatial learning, pattern recognition, and it is shown that the severity of depression negatively affects these cognitive functions (10).

There are many neuroimaging studies examining working memory (WM) and brain connectivity. According to the neuroimaging studies, places that show increased activity in tasks related to WM include the posterior cingulate cortex and medial frontal areas, which are also parts of the resting state network (12). Studies provide evidence that the frontal cortex is associated with WM (12–16).

Research using NIRS has generally focused on verbal fluency, and publications on visuospatial WM are limited. In the verbal fluency experiment of Kawano et al. with functional near infrared spectroscopy (fNIRS), a negative correlation was observed between depression score and frontal lobe activity (17). In the study of Kinou et al., people with MDD showed reduced frontopolar PFC and DLPFC activity compared to the healthy controls (18). In an fNIRS study using the n-back task, it is stated that MDD patients show a decreased activation in the inferior prefrontal region compared to the healthy controls (19). In the visual-spatial WM experiments of Schecklmann et al. using NIRS, groups with depressive features showed reduced PFC activity, ventrolateral and dorsolateral, compared to the healthy controls (20). In another study, although there was no behavioral difference between the MDD and the healthy control groups during the verbal fluency task, it was reported that there was hypoactivation in the left DLPFC as a result of brain imaging performed with NIRS in the MDD group (21). In another NIRS study, hypoactivation in the bilateral frontal cortex was observed in depressed individuals in the n-back task performed before the ECT application, and an increase in the bilateral frontal cortex activation was observed after the ECT application (22).

In addition to emotional problems, depressed individuals also experience cognitive impairments in the form of visuospatial WM impairment. Therefore, understanding the brain structures and processes that mediate these cognitive functions will facilitate the planning of cognitive rehabilitation based on neuromodulation.

With this study, it was desired to examine the effect of high depression symptoms on visuospatial WM performance, to examine the topographical representation of visuospatial WM in the PFC with fNIRS.

Method

Results

Discussion

The primary aim of this study is to investigate whether there will be a difference between behavioral and brain hemodynamic responses during the visual-spatial WM task in groups with low and high depression scores, although there is no clinical diagnosis. Considering the average age of the participants and the difficulty of the visuospatial 2-back task, it is predicted that the groups will not show a behavioral difference, but there will be a difference in the hemodynamic brain response, and this difference will be observed as an increase in the right PFC. In this section, the findings of the study are discussed in the light of previous studies in the literature.

When sociodemographic characteristics were examined, studies were generally conducted with groups in which individuals between the ages of 35-45 participated, some of the patient participants were treated with drugs in the past/currently using drugs, and the duration of education was equalized in years (7, 17, 18, 20–22, 35–39).

This research was conducted with equal groups according education norms, and the number of participants in the groups with low and high BDI scores was equal. Since the relationship between depression symptoms and WM in the young population is curious, the mean age is smaller than other studies in the literature (high BDI score mean±sd=22.2±2.28, BDI score low mean±sd=23.9±3.04). While some studies were conducted with only the patient group without a control group, some of them included both the patient and the control group. Our study also differs from some studies in the literature in that it includes a control group. Our study differs from most studies in the literature in that it was conducted with participants who were not diagnosed with depression and determined according to their BDI scores.

Tasks used to measure WM are generally n-back (7, 19, 22, 35, 38, 40) and verbal fluency tests (17, 18, 21, 37), but different experiments (20, 36, 39) are available.

In this study, a structured n-back task was designed on the visuospatial component of WM. It was expected that the participants would keep in mind the place of the stimulus that came out 2 before the stimulus they saw and decide whether it should be in the same place with the stimulus they saw by making a comparison. While designing this task, the stimuli used in the experiment were divided into emotional and neutral to see whether the behavioral performance and the brain hemodynamic response of the participants with a high BDI score differed when an emotional stimulus was present. The fact that the locations of the stimuli are kept in the mind and manipulated during the experiment is a cognitive task that serves the visual spatial sketchpad component of Baddeley and Hitch's memory model. In addition, the visuospatial n-back task is a unique paradigm in that it consists of both verbal and visual stimuli and allows measuring emotional and neutral stimuli together.

While some of the studies reported that there were behavioral differences between MDD and healthy control groups during the WM task, some found no difference. The inconsistent results of different studies with similar years of education show that a consensus cannot be reached in the literature. In this study, no significant difference was observed between the two groups in behavioral data. The reason for this is thought to be that the sample is from the young population. Even if the BDI score is high, the participants performed the same as the healthy group. Emotional stimuli also did not have a negative effect on the performance of the group with a high BDI score. The reason for this brings to mind the idea that emotional stimuli are not stimulating enough. When we ignore group and condition differences, right VLPFC activity appears to be increased in the visuospatial WM task. On the other hand, it was observed that the group with high depression scores showed increased activation during the WM task and in the right DLPFC.

This research was carried out using the NIRS method, which has been used frequently in recent years and has come to the fore with its easy and fast applicability. Although it is similar to magnetic resonance imaging (MRI) in the principle of measuring hemodynamic activity, but it cannot reach the activation of subcortical brain regions. Due to the similarity with MRI, MRI and NIRS studies were emphasized while examining the literature for this research.

In line with the studies examined in the literature, it is seen that the findings of our study are compatible with some information, but also contradictory with some results. The reason for this may be the average age of the participants, as well as the fact that the groups with MDD received medical treatment, the variety of WM tasks used, the difference in the difficulty of these tasks, the difference in the number of participants in the groups and the higher average age compared to our study. In our study, even though they were not diagnosed with MDD, people with high scores on BDI showed the same performance as people with low scores, and increased oxyHb change was observed in the right PFC, especially in DLPFC. In line with this finding, it is observed that the group with depressive features exhibited more PFC activation to achieve the same success.

The findings in the literature state that there is a hemispheric asymmetry in depression, and this asymmetry is observed as either hypoactivation in the left PFC or hyperactivation in the right PFC. Our study also supports the theory of hyperactivation in the right PFC (41).

Conclusion

No behavioral difference was observed between the groups with low and high Depression scores during the WM task. This may be because the task was not difficult enough. According to fNIRS results, the group with high depression scores showed increased activation in the right MPFC and right DLPFC during the WM task. As a result, the group with high depression scores showed more PFC activation to achieve the same performance.

Declarations

Contributions:

EY and ÖV designed the study. ÖV collected the data. EY and ÖV processed the data and wrote the manuscript. EY helped with statistical analysis and revised the manuscript. All authors reviewed the paper and approved the final version to be published.

Funding

No support was received for this study.

Author Information

 Erol Yıldırım and Özge Vural have contributed equally to this work.

Conflict of interest

All authors declare that they have no conflict of interest.

Informed consent

All participants were given written informed consents. 

Consent to publish 

All authors consent to publication of the work.

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.

Ethics Approval

This study was approved by the ethics committee of Istanbul Medipol University non-interventional clinical research.

* This study was produced from the master's thesis titled "The Relationship Between Brain Hemodynamic Response During the Working Memory Task and The Depression Score" prepared by the first author under the supervision of the second author.

1) Program of Neuroscience, Institute of Health Sciences, Istanbul Medipol University, Turkey.  

ORCID: 0000-0003-1932-960X

2) Department of Psychology, Faculty of Humanities and Social Sciences, Istanbul Medipol University, Turkey.

ORCID: 0000-0002-0575-7278

3) Regenerative and Restorative Medical Research Center, Istanbul Medipol University, Istanbul, Turkey

References

1. Akiyama, T., Koeda, M., Okubo, Y., & Kimura, M. (2018). Hypofunction of left dorsolateral prefrontal cortex in depression during verbal fluency task: A multi-channel near-infrared spectroscopy study. Journal of Affective Disorders, 231, 83–90. https://doi.org/10.1016/j.jad.2018.01.010
2. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.). Washington D.C.: American Psychiatric Association
3. Baker, J. M., Bruno, J. L., Gundran, A., Hosseini, S. M. H., & Reiss, A. L. (2018). Fnırs measurement of cortical activation and functional connectivity during a visuospatial working memory task. PloS One, 13(8), e0201486. https://doi.org/10.1371/journal.pone.0201486
4. Baune, B. T., Miller, R., McAfoose, J., Johnson, M., Quirk, F., & Mitchell, D. (2010). The role of cognitive impairment in general functioning in major depression. Psychiatry Research, 176(2-3), 183–189. https://doi.org/10.1016/j.psychres.2008.12.001
5. Daniel Lundqvist, A., & Flykt (1998). Arne Öhman The Karolinska Directed Emotional Faces (KDEF)1998
6. Drevets, W. C. (2000). Neuroimaging studies of mood disorders. Biological Psychiatry, 48(8), 813–829. https://doi.org/10.1016/S0006-3223(00)01020-9
7. Edward, E., Smith, Stephaen, M., & Kosslyn (Eds.). (2013). Cognitive Psychology: Pearson new international edition: Mind and brain.
8. Evans, V. C., Iverson, G. L., Yatham, L. N., & Lam, R. W. (2014). The relationship between neurocognitive and psychosocial functioning in major depressive disorder: A systematic review. The Journal of Clinical Psychiatry, 75(12), 1359–1370. https://doi.org/10.4088/JCP.13r08939
9. Fatmagül, H., & Çiçek, H. (2016). ‘Major Depresif Bozukluk’ Tanımı, Etyolojisi ve Epidemiyolojisi: Bir Gözden Geçirme. Journal of Contemporary Medicine, 6(1), 51–66
10. Fitzgerald, P. B., Maller, J. J., Hoy, K. E., Thomson, R., & Daskalakis, Z. J. (2009). Exploring the optimal site for the localization of dorsolateral prefrontal cortex in brain stimulation experiments. Brain Stimulation, 2(4), 234–237. https://doi.org/10.1016/j.brs.2009.03.002
11. Fletcher, P. C., & Henson, R. N. (2001). Frontal lobes and human memory: İnsights from functional neuroimaging. Brain: A Journal of Neurology, 124(Pt 5), 849–881. https://doi.org/10.1093/brain/124.5.849
12. Golby, A. J., Poldrack, R. A., Brewer, J. B., Spencer, D., Desmond, J. E., Aron, A. P., & Gabrieli, J. D. (2001). Material-specific lateralization in the medial temporal lobe and prefrontal cortex during memory encoding. Brain: A Journal of Neurology, 124(Pt 9), 1841–1854. https://doi.org/10.1093/brain/124.9.1841
13. Hampson, M., Driesen, N. R., Skudlarski, P., Gore, J. C., & Constable, R. T. (2006). Brain connectivity related to working memory performance. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 26(51), 13338–13343. https://doi.org/10.1523/JNEUROSCI.3408-06.2006
14. Harvey, P. O., Fossati, P., Pochon, J. B., Levy, R., Lebastard, G., Lehéricy, S., & Dubois, B. (2005). Cognitive control and brain resources in major depression: An fMRI study using the n-back task. NeuroImage, 26(3), 860–869. https://doi.org/10.1016/j.neuroimage.2005.02.048
15. Hirano, J., Takamiya, A., Yamagata, B., Hotta, S., Miyasaka, Y., Pu, S., & Mimura, M. (2017). Frontal and temporal cortical functional recovery after electroconvulsive therapy for depression: A longitudinal functional near-infrared spectroscopy study. Journal of Psychiatric Research, 91, 26–35. https://doi.org/10.1016/j.jpsychires.2017.02.018
16. Hugdahl, K., Rund, B. R., Lund, A., Asbjørnsen, A., Egeland, J., Ersland, L., & Thomsen, T. (2004). Brain activation measured with fMRI during a mental arithmetic task in schizophrenia and major depression. The American Journal of Psychiatry, 161(2), 286–293. https://doi.org/10.1176/appi.ajp.161.2.286
17. Jamovi [Computer software] (2021). : The jamovi project (2021). jamovi. (Version 1.8) [Computer Software]. Retrieved from https://www.jamovi.org
18. Kapucu, A., Kılıç, A., Özkılıç, Y., & Sarıbaz, B. (2018). Turkish Emotional Word Norms for Arousal, Valence, and Discrete Emotion Categories. Psychological Reports, 1–22. https://doi.org/10.1177/0033294118814722
19. Karakulak, E. Z. (2018). MULTİPL SKLEROZ HASTALARINDA KRONİK ÖZÜRLÜLÜK OLUŞTURAN SEMPTOMLAR ÜZERİNDE TRANSKRANYAL DİREKT AKIMIN (TDCS) ETKİLERİNİN ARAŞTIRILMASI. İstanbul: Sinir BilimDoktora
20. Kawano, M., Kanazawa, T., Kikuyama, H., Tsutsumi, A., Kinoshita, S., Kawabata, Y., & Yoneda, H. (2016). Correlation between frontal lobe oxy-hemoglobin and severity of depression assessed using near-infrared spectroscopy. Journal of Affective Disorders, 205, 154–158. https://doi.org/10.1016/j.jad.2016.07.013
21. Kelley, W. M., Miezin, F. M., McDermott, K. B., Buckner, R. L., Raichle, M. E., Cohen, N. J., & Petersen, S. E. (1998). Hemispheric Specialization in Human Dorsal Frontal Cortex and Medial Temporal Lobe for Verbal and Nonverbal Memory Encoding. Neuron, 20(5), 927–936. https://doi.org/10.1016/S0896-6273(00)80474-2
22. KIRCHNER, W. K. (1958). Age differences in short-term retention of rapidly changing information. Journal of Experimental Psychology, 55(4), 352–358. https://doi.org/10.1037/h0043688
23. Kinou, M., Takizawa, R., Marumo, K., Kawasaki, S., Kawakubo, Y., Fukuda, M., & Kasai, K. (2013). Differential spatiotemporal characteristics of the prefrontal hemodynamic response and their association with functional impairment in schizophrenia and major depression. Schizophrenia Research, 150(2-3), 459–467. https://doi.org/10.1016/j.schres.2013.08.026
24. Klojčnik, M., Kavcic, V., & Bakracevic Vukman, K. (2017). Relationship of Depression With Executive Functions and Visuospatial Memory in Elderly. International Journal of Aging & Human Development, 85(4), 490–503. https://doi.org/10.1177/0091415017712186
25. Kring, A. M., Davison, G. C., Neale, J. M., & Johnson, S. L. (2007). Abnormal psychology.
26. Lee, R. S. C., Hermens, D. F., Porter, M. A., & Redoblado-Hodge, M. A. (2012). A meta-analysis of cognitive deficits in first-episode Major Depressive Disorder. Journal of Affective Disorders, 140(2), 113–124. https://doi.org/10.1016/j.jad.2011.10.023
27. Levin, R. L., Heller, W., Mohanty, A., Herrington, J. D., & Miller, G. A. (2007). Cognitive Deficits in Depression and Functional Specificity of Regional Brain Activity. Cognitive Therapy and Research, 31(2), 211–233. https://doi.org/10.1007/s10608-007-9128-z
28. Liu, X., Sun, G., Zhang, X., Xu, B., Shen, C., Shi, L., & Liu, P. (2014). Relationship between the prefrontal function and the severity of the emotional symptoms during a verbal fluency task in patients with major depressive disorder: A multi-channel NIRS study. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 54, 114–121. https://doi.org/10.1016/j.pnpbp.2014.05.005
29. Matsuo, K., Glahn, D. C., Peluso, M. A. M., Hatch, J. P., Monkul, E. S., Najt, P., & Soares, J. C. (2007). Prefrontal hyperactivation during working memory task in untreated individuals with major depressive disorder. Molecular Psychiatry, 12(2), 158–166. https://doi.org/10.1038/sj.mp.4001894
30. Mohn, C., & Rund, B. R. (2016). Neurocognitive profile in major depressive disorders: Relationship to symptom level and subjective memory complaints. BMC Psychiatry, 16, 108. https://doi.org/10.1186/s12888-016-0815-8
31. Necla, & Öner, & W. Ayhan LeCompte (1983). Durumluk-sürekli kaygı envanteri el kitabı. İstanbul:Boğaziçi Üniversitesi
32. Norbury, R., Godlewska, B., & Cowen, P. J. (2014). When less is more: A functional magnetic resonance imaging study of verbal working memory in remitted depressed patients. Psychological Medicine, 44(6), 1197–1203. https://doi.org/10.1017/S0033291713001682
33. Nystrom, L. E., Braver, T. S., Sabb, F. W., Delgado, M. R., Noll, D. C., & Cohen, J. D. (2000). Working memory for letters, shapes, and locations: Fmrı evidence against stimulus-based regional organization in human prefrontal cortex. NeuroImage, 11(5 Pt 1), 424–446. https://doi.org/10.1006/nimg.2000.0572
34. Okada, G., Okamoto, Y., Morinobu, S., Yamawaki, S., & Yokota, N. (2003). Attenuated left prefrontal activation during a verbal fluency task in patients with depression. Neuropsychobiology, 47(1), 21–26. https://doi.org/10.1159/000068871
35. Okamoto, M., Dan, H., Sakamoto, K., Takeo, K., Shimizu, K., Kohno, S., & Dan, I. (2004). Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10-20 system oriented for transcranial functional brain mapping. NeuroImage, 21(1), 99–111. https://doi.org/10.1016/j.neuroimage.2003.08.026
36. Psychology Software Tools. E-Prime (Version 2) [Computer software]. Pittsburgh, PA
37. Savitz, J., & Drevets, W. C. (2009). Bipolar and major depressive disorder: Neuroimaging the developmental-degenerative divide. Neuroscience and Biobehavioral Reviews, 33(5), 699–771. https://doi.org/10.1016/j.neubiorev.2009.01.004
38. Schecklmann, M., Dresler, T., Beck, S., Jay, J. T., Febres, R., Haeusler, J., & Fallgatter, A. J. (2011). Reduced prefrontal oxygenation during object and spatial visual working memory in unpolar and bipolar depression. Psychiatry Research, 194(3), 378–384. https://doi.org/10.1016/j.pscychresns.2011.01.016
39. Sheremata, S. L., Bettencourt, K. C., & Somers, D. C. (2010). Hemispheric asymmetry in visuotopic posterior parietal cortex emerges with visual short-term memory load. The Journal of Neuroscience: The Official Journal of the Society for Neuroscience, 30(38), 12581–12588. https://doi.org/10.1523/JNEUROSCI.2689-10.2010
40. Soveri, A., Antfolk, J., Karlsson, L., Salo, B., & Laine, M. (2017). Working memory training revisited: A multi-level meta-analysis of n-back training studies. Psychonomic Bulletin & Review, 24(4), 1077–1096. https://doi.org/10.3758/s13423-016-1217-0
41. Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R., & Jacobs, G. A. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psychologists Press
42. Şahin Hisli, N., Batıgün, D., A., & Uğurtaş, S. (2002). Kısa Semptom Envanteri (KSE): Ergenler İçin Kullanımının Geçerlik, Güvenilirlik ve Faktör Yapısı. Türk Psikiyatri Dergisi, 13(2), 125–135
43. Thibodeau, R., Jorgensen, R. S., & Kim, S. (2006). Depression, anxiety, and resting frontal EEG asymmetry: A meta-analytic review. Journal of Abnormal Psychology, 115(4), 715–729. https://doi.org/10.1037/0021-843X.115.4.715
44. Vermeij, A., van Beek, A. H. E. A., Reijs, B. L. R., Claassen, J. A. H. R., & Kessels, R. P. C. (2014). An exploratory study of the effects of spatial working-memory load on prefrontal activation in low- and high-performing elderly. Frontiers in Aging Neuroscience, 6, 303. https://doi.org/10.3389/fnagi.2014.00303
45. Wagner, A. D., Desmond, J. E., Glover, G. H., & Gabrieli, J. D. (1998). Prefrontal cortex and recognition memory. Functional-MRI evidence for context-dependent retrieval processes. Brain: A Journal of Neurology, 121 (Pt(10), 1985–2002. https://doi.org/10.1093/brain/121.10.1985
46. Wagner, G., Sinsel, E., Sobanski, T., Köhler, S., Marinou, V., Mentzel, H. J., & Schlösser, R. G. M. (2006). Cortical inefficiency in patients with unipolar depression: An event-related FMRI study with the Stroop task. Biological Psychiatry, 59(10), 958–965. https://doi.org/10.1016/j.biopsych.2005.10.025
47. Yüksel, D., Dietsche, B., Konrad, C., Dannlowski, U., Kircher, T., & Krug, A. (2018). Neural correlates of working memory in first episode and recurrent depression: An fMRI study. Progress in Neuro-Psychopharmacology & Biological Psychiatry, 84, 39–49. https://doi.org/10.1016/j.pnpbp.2018.02.003
48. Zaninotto, L., Guglielmo, R., Calati, R., Ioime, L., Camardese, G., Janiri, L., & Serretti, A. (2015). Cognitive markers of psychotic unipolar depression: A meta-analytic study. Journal of Affective Disorders, 174, 580–588. https://doi.org/10.1016/j.jad.2014.11.027
49. Zhu, Y., Quan, W., Wang, H., Ma, Y., Yan, J., Zhang, H., & Yu, X. (2018). Prefrontal activation during a working memory task differs between patients with unipolar and bipolar depression: A preliminary exploratory study. Journal of Affective Disorders, 225, 64–70. https://doi.org/10.1016/j.jad.2017.07.031