Assignment: Neurocognitive Profile of Diabetes and Depression

Neurocognitive Profile of Diabetes and Depression

Neurocognitive involves a person’s capacity to think and reason. Additionally, it involves the ability to concentrate, process information, remembers several things, learns, understands, and speak. These neurocognitive functions relate to the function of neural pathways or cortical networks located in the brain. Therefore, these regions are associated with the six domains of cognition, including attention, learning and memory, executive functioning, language, visuospatial, and motor or perceptual. While neurocognitive is associated with various disorders, this paper will focus on its connection with diabetes and depression.

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The Neurocognitive Profile of Diabetes

The Connection between Cognitive Domains and Diabetes

Studies show that diabetes has an impact on some cognitive domains. Decrements in cognitive function and changes in the brain structure are associated with diabetes mellitus. Neuropsychological testing indicates mild to moderate cognitive function reductions in individuals with both T1DM and T2DM (Moheet et al., 2015). According to Moheet et al. (2015), persons with T2DM perform poorly in various cognitive domains, including attention and executive function, information-processing speed, psychomotor efficiency, memory, verbal fluency, and learning. Some elements of diabetes, including poor glycemic control, increased period of diabetes, hypoglycaemic and hyperglycaemic events, and the presence of microvascular complications such as peripheral neuropathy and diabetic retinopathy, are responsible for poor performance in cognitive functions among individuals diagnosed with T2DM.

Additionally, Zilliox et al. (2016) indicate that diabetes impairs cognitive functioning. Both T1DM and T2DM result in abnormal functional and structural brain magnetic resonance imaging (MRI), thereby declining performance on several cognitive function domains. Two screening tests were performed to evaluate cognitive functioning, including the Montreal Cognitive Assessment (MOCA) and the mini-mental state examination. These tests reveal that about five cognitive domains, including abstract reasoning; attention and executive function; information processing speed; visuospatial skills; and memory with its subdomains such as the working memory, forgetting rate, immediate memory and learning rate, and incidental memory are affected by diabetes (Zilliox et al., 2016). People with diabetes might experience cognitive deficits at the earliest stages of this condition but its exacerbated further by metabolic syndrome. The severity and type of cognitive impairment are influenced by glycemic control and the duration of diabetes.

On the contrary, diabetes treatments, including insulins and oral hypoglycemic agents (OHAs) that reduce diabetes symptoms, tend to prevent several complications such as a decline in cognitive functioning. According to Herath et al. (2016), exogenous insulin is used to treat patients with type 2 diabetes when OHAs cannot control their hyperglycemia. Insulin is a hormone with various significant functions in the central nervous system. Insulin enhances cognitive functioning by improving glycemic control and minimizing diabetes complications (Herath et al., 2016).

The Connection between Cognitive Domains and the Brain Regions affected by Diabetes

The impacted regions correspond to the neuropathological effects of diabetes on the human brain since diabetes affects various brain regions involved in cognitive functioning, including the hippocampus and frontal subcortical. A case study was conducted where two people with diabetes were involved (Chomova, 2014). The researchers reported a neuronal loss in various brain regions, including frontal cortex, hippocampus, and the white matter atrophy of frontal and temporal regions. Neurobehavioral alterations resulted from the neurostructural changes, thus compromising cognitive functions associated with these structures. For instance, some brain regions, including the amygdala, the cerebellum, the hippocampus, and the prefrontal cortex, play a significant role in learning and memory. Therefore, altering the structure of the hippocampus impaired patients’ learning and memory.

Other neuro-psychological studies involving T1DM children were conducted to evaluate the effect of diabetes on brain regions and neurocognitive functions (Chomova, 2014). These studies demonstrated shortcomings in various cognitive domains, including attention, executive function, processing speed, intelligence, and memory. Impairment in these cognitive functions attributed to brain regions’ damage involved in these functions in T1DM children. Damage in the cerebral cortex and prefrontal cortex led to impairment in processing speed and attention, respectively. Additionally, memory impairment occurred due to damage in some parts of the brain, including the amygdala, the cerebellum, the hippocampus, and the prefrontal cortex. Finally, the patients experienced impairment in executive function and intelligence due to the damage caused by depression in prefrontal lobe regions, the frontal, parietal, and temporal lobes, respectively. Moreover, studies involving T2DM patients demonstrated cognitive deficits in various domains, including psychomotor speed, memory skills, executive functions, verbal fluency, visuospatial abilities, and attention (Chomova, 2014). These impairments were caused by damage in various parts of the brain involved in cognitive functioning, such as prefrontal regions of the frontal lobe, amygdala, cerebellum, hippocampus, and prefrontal cortex.

The Relationship between Diabetes and Alzheimer’s, and Vascular Dementia

Diabetes is attributed to several complications, including Alzheimer’s and vascular dementia. First, diabetes is among the major risk factor for vascular dementia due to brain damage and aging, which results in cognitive dysfunction in older adults. Additionally, Type 2 diabetes increases the risk for cerebrovascular and cardiovascular disease. It might raise susceptibility to caliber vessel–mediated injury to the brain, including ischemia, hypoxic events, and blood-brain barrier leakage. Insulin resistance and inflammation also lead to dysfunction of vascular endothelial cells, and neuroimaging in type 2 diabetes patients indicates disruption of white matter networks (Kapasi & Schneider, 2016). Furthermore, poorer cognitive performance in diabetes patients than in people without this condition is caused by white matter dysfunction. A meta-analysis of prospective studies was recently conducted to evaluate the risk of dementia in individuals with type 2 diabetes (Hao et al., 2015). The study findings reported an increased risk for vascular dementia among this patient population

Secondly, diabetes increases the risk of developing Alzheimer’s disease. About 56% increase in the risk for Alzheimer’s disease among type 2 diabetes patients has been demonstrated in meta-analytic data (Cholerton et al., 2016). A study conducted in community-based in Rotterdam indicated a substantial increase in the risk of Alzheimer’s disease among individuals diagnosed with type 2 diabetes (Haroon et al., 2015). Alzheimer’s disease in this population was characterized by a mild cognitive impairment, where individuals experienced more cognitive and memory issues than those present during the normal course of aging. Alzheimer’s disease is either preceded or accompanied by mild cognitive impairment (McFall et al., 2015). Diabetes and Alzheimer’s disease are connected due to various reasons. The neuropathological changes of Alzheimer’s disease are induced by type 2 diabetes through various mechanisms.

First, insulin resistance in leads to Alzheimer’s disease. According to Cholerton et al. (2016), the blood-brain barrier allows for insulin to be readily transported into the CNS through a receptor-mediated process, increasing the amount of insulin available in the brain. Additionally, the brain produces insulin in a mechanism controlled by a pathway located in the hypothalamus (Cholerton et al., 2016). In some cases, insulin resistance compromises insulin use in treating diabetes among individuals diagnosed with this condition. Vitro and animal studies indicate that the predominant pathological features of Alzheimer’s disease are exacerbated by insulin resistance (Cholerton et al., 2016). Thereby, insulin resistance is among the mechanisms of diabetes that result in Alzheimer’s disease. Another factor that leads to Alzheimer’s disease among diabetes patients is the damage of the blood vessel and inflammation. According to Cholerton et al. (2016), inflammation is among the major characteristics of diabetes type 2 Mellitus. High blood sugar levels cause some bouts of inflammation, thus exerting stress on the blood vessels. The damaged blood vessels then lead to Alzheimer’s disease.

The Neurocognitive Profile of Depression

Perspectives on Neurocognitive Impact of Depression

The neurocognitive impact of depression has raised conflicting views between individuals. Some people support the genuine neurocognitive impact of depression, while others believe that patients’ effortful engagement causes depression. Some studies support the genuine neurocognitive impact of depression. Neurocognitive deficits are among the major characteristics of MDD in adults (Morey-Nase et al., 2019). Young adults and adolescents with MDD are reporting a significant increase in the prevalence of neurocognitive impairments. In particular, the prevalence of neurocognitive impairments in adolescents with depression is about 83%. Recently, a piece of meta-analytic evidence was pooled from 23 studies. It indicated substantially poorer neurocognitive performance in the various domains, including attention (standardized mean difference [SMD]: 0.50), visual memory (SMD: 0.65), verbal reasoning/knowledge (SMD: 0.46), verbal memory (SMD: 0.78), and IQ (SMD: 0.32) among young adults aged between 12 and 25 years with depression than healthy controls (Goodall et al., 2018). Furthermore, cognitive deficits were reported in cohorts involving younger children between 9 and 15 years with MDD. Specifically, evidence indicated compromised sustained attention, verbal memory, working memory, and executive functions (Wagner et al., 2015).

On the other hand, some studies indicate that depression results from patients’ effortful engagement in neuropsychological testing. Cognitive theories claim that depression is influenced by multiple factors, including attitudes, thoughts, and how individuals attend to, interpret, and remember particular information (Abigail et al., 2019). Emotional responses are influenced by the way a person processes information. Thereby, depression is caused by bias in the processing of emotional material (“cognitive biases”). More so, depression among vulnerable groups is triggered by difficulties processing non-emotional information (“poor cognitive control”). According to Abigail et al. (2019), depression-linked biases are likely to occur in the interpretation and memory of emotional materials, attention, and problematic cognitive processing of both emotional and non-emotional materials.

Effortful Engagement

Some studies associate depression with individuals’ effortful engagement in various neurocognitive domains. First, depression is attributed to attention biases, which involve allocating attention towards or away from negative over non-negative stimuli. The depressive effect is influenced and maintained by an increase in a person’s focus on negative materials over positive ones, thereby magnifying perceived negativity in the environment (Abigail et al., 2019). Youths tend to prefer negative stimuli, especially those presented for long periods. Some studies indicate a connection between depressive symptoms and negative attention bias for negative faces. Therefore, attention biases are considered as risk factors for depression. Studies that involved depressed mothers and non-depressed children indicated an attention bias towards sad faces (Abigail et al., 2019). Additionally, a study was conducted to investigate attention bias in the mother and child. The study findings indicated that a negative attention bias to negative stimuli was shown by youth of depressed mothers if the mothers portrayed declined attention bias to positive information (Abigail et al., 2019).

Secondly, depression is attributed to memory biases in which individuals recall negative material and avoid remembering positive things in their lives. A study was conducted to assess the connection between depressed youths and memory bias. The results indicated that the study population tends to recall negative material and reduced recall of positive materials (Platt et al., 2017). The risk of memory biases for self-referent words representing depression was assessed in another study that involved a depressed mother and her daughters (Asarnow et al., 2015). The findings did not indicate any negative memory bias in daughters of depression than those of non-depressed mothers. Additionally, a recent review indicated that the risk of depression in young people increases by over general memory (OGM). Individuals experience difficulty retrieving particular autobiographical memories in overgeneral memory, and instead, they generate extended memories (Hitchcock et al., 2014). Moreover, studies have been conducted to assess if OGM characterizes depression. OGM was experienced a year later in females with elevated symptoms of depression (Abigail et al., 2019). Similarly, OGM was experienced a year later in girls with depression aged 10 to 18 years. Also, a relationship between OGM and trauma exposure, which increases the risk for adolescent depression, is supported by several studies. Studies involving young people have been conducted across a range of various types of trauma (Abigail et al., 2019).

Finally, depression is attributed to interpretation biases, which refer to the tendency to draw negative inferences, outcomes, or causes from ambiguous cues. Depressed youth tend to select more negative meanings of words in tasks. Additionally, they tend to embrace more negative interpretations over positive interpretations (Orchard et al., 2016). Moreover, the fewer positive interpretations that are endorsed by depressed youths tend to have ambiguous information. A positive correlation exists between interpretation biases and the severity of depressive symptom severity (Abigail et al., 2019). Nonetheless, this relationship is influenced by anxiety due to the high co-occurrence of anxiety among individuals diagnosed with depression. Most studies indicated a connection between biased threat interpretations and anxiety. Therefore, the risk for depression increases due to interpretation bias. For instance, an increase in depression symptoms in a student sample was predicted 4 to 6 weeks later by interpretation biases (Abigail et al., 2019). More so, the probability of experiencing depressive symptoms was relatively high among maltreated young adults with negative interpretation bias (Well et al., 2014).

The Domains Impacted by Depression

Depression has an impact on various neurocognitive domains. First, depression impairs executive control, which refers to the higher-level processes entailed in behaviour. It includes various sub-elements such as planning, working memory, and the inhibition of dominant responses. Executive processes have been localized by human lesion studies and functional imaging to the lateral and dorsal aspects of the PFC (Shibeshi & Engidawork, 2017). Multiple paradigms in MDD compromise executive function significantly. Unmedicated MDD patients demonstrate these deficits, which are exacerbated in bipolar depression than in MDD. Some remitted cases demonstrate persistence in impairment as depressive episodes subside despite substantial improvement in executive function.

Secondly, depression impairs memory, which is evident in multiple paradigms, including paragraph recall. Impairment in paragraph recall involves delaying remembering the details of a complex incident 10 minutes after its occurrence. The functional outcomes are highly predicted by mnemonic impairment, and it has a positive correlation with the chronicity of the illness. In most cases, patients with depression indicate decreased delayed paragraph recall with every episode of depression up to the fourth one. Thus, these cognitive domain cumulative effects can be prevented through early detection and management of depressive symptoms. Additionally, major depressive disorder impairs hippocampal function, especially during memory encoding tasks and lowers hippocampal volume (Katsuki, A et al., 2020).

Overall, neurocognitive functions are influenced by both diabetes and depression. These conditions affect brain regions involved in various cognitive domains, including attention, learning and memory, executive functioning, language, visuospatial, and motor or perceptual. Therefore, impairment in these cognitive functions occurs due to alteration in the structure of these brain regions such as prefrontal regions of the frontal lobe, amygdala, the cerebellum, the hippocampus, and the prefrontal cortex. Additionally, the brain structure’s alteration increases the risk of some conditions such as Alzheimer’s and vascular dementia. Diabetes is among the major risk factor for vascular dementia due to brain damage and aging, which results in cognitive dysfunction in older adults. Additionally, Type 2 diabetes increases the risk for cerebrovascular and cardiovascular disease and might raise susceptibility to caliber vessel–mediated injury to the brain. Secondly, diabetes increases the risk of developing Alzheimer’s disease due to an increase in cognitive and memory issues than those present during the normal course of aging. The neurocognitive impact of depression has raised conflicting views between individuals. Some people support the genuine neurocognitive impact of depression, while others believe that patients’ effortful engagement causes depression.

References

Abigail, O., Victoria, P., Deborah, E., & Lau. J, Y. (2019). The Cognitive Neuropsychology of Depression in Adolescents. Current Behavioral Neuroscience Reports; 6: 227–235.

Asarnow, L, D., Thompson, R, J., Joormann, J, & Gotlib, I, H. (2015). Children at risk for depression: memory biases, self-schemas, and genotypic variation. J Affect Disord; 159:66–72.

Cholerton, B., Baker, L., D., Montine, T, J., Craft, S. (2016). Type 2 Diabetes, Cognition, and Dementia in Older Adults: Toward a Precision Health Approach. Diabetes Spectrum. 29(4): 210-219. https://doi.org/10.2337/ds16-0041

Chomova, M. (2014). Inside the Diabetic Brain. Acta Medica Martiniana; 14(3):21-29

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Goodall, J., Fisher, C, A., Hetrick, S., Phillips, L., Parrish, E, M., Allott K. (2018). Neurocognitive functioning in depressed young people: a systematic review and meta-analysis. Neuropsychol Rev; 28(2):216–31.

Hao, K., Di, Narzo AF., & Ho, L., et al. (2015). Shared genetic etiology underlying Alzheimer’s disease and type 2 diabetes. Mol Aspects Med; 43–44, 66–76.

Haroon, N, N., Austin, P, C., Shah, B, R., Wu, J., Gill, S, S., & Booth, G, L. (2015). Risk of dementia in seniors with newly diagnosed diabetes: a population-based study. Diabetes Care; 38:1868–1875

Herath, P, M., Cherbuin, N., Eramudugolla, R., & Anstey, K, J. (2016). The Effect of Diabetes Medication on Cognitive Function: Evidence from the PATH Through Life Study. BioMed Research International; 1-7. https://doi.org/10.1155/2016/7208429

Hitchcock, C., Nixon, R, V., & Weber, N. (2014). A review of overgeneral memory in child psychopathology. Br J Clin Psychol;53(2):170–93. https://doi.org/10.1111/bjc.12034

Kapasi, A., & Schneider, J, A. (2016). Vascular contributions to cognitive impairment, clinical Alzheimer’s disease, and dementia in older persons. Biochim Biophys Acta; 1862: 878–886.

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McFall, G, P., Wiebe, S, A., Vergote, D., Anstey, K, J, & Dixon, R, A. (2015). Alzheimer’s genetic risk intensifies neurocognitive slowing associated with diabetes in non-demented older adults. Alzheimer’s Dement; 1:395–402.

Moheet, A., Mangia, S., Seaquist, E, R. (2015). Impact of diabetes on cognitive function and brain structure. Ann N Y Acad Sci; 1353: 60–71. doi:10.1111/nyas.12807.

Morey-Nase, C., Phillips, L, J., Bryce, S., Hetrick, S., Wright, A, L., Caruana E & Allott, K. (2019). Subjective experiences of neurocognitive functioning in young people with major depression. BMC Psychiatry; 19 (209): 2-9. https://doi.org/10.1186/s12888-019-2197-1

Orchard, F., Pass, L., & Reynolds, S. (2016). ‘It Was All My Fault’; negative interpretation bias in depressed adolescents. J Abnorm Child Psychol;44(5):991–8. https://doi.org/10.1007/s10802-015-0092-x.

Platt, B., Waters, A, M., Schulte-Koerne, G., Engelmann, L., & Salemink, E. (2017). A review of cognitive biases in youth depression: attention, interpretation and memory. Cognit Emot; 31(3):462–83. https://doi.org/10.1080/02699931.2015.1127215.

Shibeshi, W & Engidawork, E. (2017). Major Depressive Disorder: Pathophysiology and Clinical Management. J Depress Anxiety; 6 (1): 1-7. DOI: 10.4172/2167-1044.1000255

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Wells, T, T., Vanderlind, W, M., Selby, E, A., & Beevers, C, G. (2014). Childhood abuse and vulnerability to depression: cognitive scars in otherwise healthy young adults. Cognit Emot; 28(5):821–33. https://doi.org/10.1080/02699931.2013.864258.

Zilliox, L, A., Chadrasekaran, K., Kwan, J, Y., & Russell, J, W. (2016). Diabetes and Cognitive Impairment. Curr Diab Rep; 16(9): 87. doi: 10.1007/s11892-016-0775-x

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Instructions:

You are to consider the neurocognitive profile of diabetes and the neurocognitive profile of depression. Then provide a thorough, well-written, comprehensive, doctoral (Ph.D.) level scientific research analysis of what studies have stated regarding the neurocognitive profile of those with such conditions (i.e., diabetes and depression). You should approach this thoroughly and comprehensively.

The paper should be doubled spaced. However, each paragraph should include at least 10 sentences before starting a new one. The paper should be written in American Psychological Association standard format (APA format). In-text citations and reference pages written in APA format as well.

What is meant by neurocognitive? Neurocognitive has to do with the SIX domains of cognition:
Attention (processing speed, sustained attention, complex attention, etc.)
Learning & Memory (short-term, long-term, working memory, episodic, declarative memory, etc.)
Executive functioning (planning, decision-making abilities, mental flexibility, inhibition)
Language (Verbal and semantic fluency, Object naming, etc.)
Visuospatial (visual perception, visuo-constructional)
Motor (Perceptual motor coordination)

Paper Details
Provide a thorough understanding of the neurocognitive profile of diabetes (5 pages with 8-10 reference sources)
What do studies indicate are the cognitive domains (attention, learning & memory, executive functioning, etc.) impacted by diabetes?
How do those affected areas correspond to the neuropathological impact of diabetes on the brain? How do they correspond with what we know about the neurological areas affected by diabetes (i.e., the hippocampus, frontal-subcortical areas, etc.)?
Discuss the relationship between diabetes and Alzheimer’s disease and vascular dementia
Discuss the studies in detail when at all possible. Discuss sample participants, methodological approaches, measures, and findings in a comprehensive manner when possible to further embellish your writing.
Provide a thorough understanding of the neurocognitive profile of depression (4 pages with 8-10 reference sources)
Please understand that there is an ongoing debate between those who believe that depression is more of a question of patients’ effortful engagement on neuropsychological testing, and therefore, there is no legitimate neurocognitive impact that depression has on an individual. On the other hand, there are those who argue the legitimacy of the neurocognitive impact of depression.
Elaborate on studies for both perspectives (those who argue for effortful engagement and those who argue for a genuine neurocognitive impact of depression).
Highlight and explain clearly what researchers say about effortful engagement and what studies have found and suggest.
Highlight and explain clearly what researchers say regarding the domains impacted by depression (attention, learning and memory, executive functioning, etc.)
Discuss the studies in detail when at all possible. Discuss sample participants, methodological approaches, measures, and findings in a comprehensive manner when possible to further embellish your writing.