Discuss about the Clinical Psychology for Implications Treatment.
Major depressive disorder (MDD) is a clinical condition associated with symptoms of low self-esteem, loss of interest in activities, impaired concentration and feeling of restlessness. The morbidity of the disease is associated with adverse outcome like poor interpersonal relationship as well as suicidal thoughts. The DSM-IV criteria for diagnosis of MDD depicts symptoms of anhedonia (loss of pleasures in rewarding things) should be every day till a minimum of two weeks (Henriques & Davidson, 2000). Recent studies indicate that continuous periods of depressive symptoms impairs the brain areas related to positive emotions and hence anhedonia becomes a cardinal symptoms of depression (Der-Avakian & Markou, 2012). The brain mechanisms underlying anhedonia is very elusive and it is necessary to study the contribution of the brain reward system in the symptoms of MDD. To analyze reward-based reinforcement learning in depression, many fMRI studies had been done to analyze brain activities in targets area and determine the extent to which brain’s reward system is influenced by the disease.
fMRI studies investigating reward processing in depression revealed that depressed patients mainly shows reduced activations to rewards and they had reduce anticipatory response after a winning trail (Pizzagalli, 2014). Behavioral studies have also indicated low-reward sensitivity in depressed participants and this was confirmed by the reinforcement learning parameters in the task. The study was done in control groups and depressed groups and the reinforcement learning model was applied in patient’s behavioral data. The findings showed that MDD patients had lacked reward-based decision making skills and they faced difficulties in carrying out many actions. Hence, people with depressive disorder show varying response to action (Kunisato et al., 2012). A study by (Naranjo, Tremblay, & Busto, 2001) indicates that alterations in the neurotransmitter and neuroendocrine systems lead to depression and dopamines and serotonins mostly play vital function in it. Tryptophan depression leads to decreased flow in certain regions of brain and lead to depressive symptoms due the activation of orbitifrontal cortex, septal region and amygdala. Hence there are neurobiological overlaps between MDD and brain reward system and anhedonic symptoms in depression is due impairment of the brain reward system.
There are also indications that impairment in brain reward system might reduce reward related learning outcomes of patients with MDD. This might also affect and challenge the maintenance of MDD in diagnose person. In such case person behavior will be affected as they will not be able to modify behavior in terms of pay-off condition of rewards. This factor explains why depressed patients mainly experience anhedonia and why anhedonia is a potential trait marker of MDD (Forbes & Dahl, 2012). The question now arises whether reduced learning might normalize with treatment and this is a new area of investigation to determine the impact of reduced reward learning due to depression. One study investigated the relation between reward learning and MDD after 8 weeks of treatment. The patients and control subjects had to complete reward task to determine how reward functions regulates behavior of participants. The comparison of reward responsiveness between control groups and depressed patients revealed that MDD patient have reduced learning and this is even higher in patients with high level of anhedonia than those with low level of anhedonia. It led to persisting symptom of depression even after treatment (Vrieze et al., 2013). Hence, it indicates that reduced reward learning might significantly affects treatment goals and new approach is needed to eliminate persisting symptoms of anhedonia in patients.
Anhedonia is the main focus of attention while defining treatment plan for patients with depression. It is the most vulnerable factors that might severely affect health condition of diagnosed person. The functional magnetic resonance imaging tests have indicated that there is difference in key nodes of brains reward system that affects anhedonia symptoms. Anhedonia is correlated with reduced nucleus accumbens (NAcc), reduced NAcc volume and increased resting delta current density. As NAcc reward response is inversely associated with resting delta activity, it is predicted that delta might have a role in the brain’s reward circuit activity (Wacker, Dillon, & Pizzagalli, 2009). Further research in this area might help in elucidating the neural basis of anhedonia. On research study tried to review the neural bases that lead to anhedonia and it was found that deficits in hedonic capacity mainly lead to the conditions and this has impact on reward related processes in the brain particularly in ventral striatum, prefrontal cortical regions and different projections. This understanding might play a great role in addressing reward related deficits in patients with MDD (Der-Avakian & Markou, 2012).
Further extension to thought can be given by the idea that MDD is associated with poor neurobiological response to pleasant stimuli and psychotherapy has the potential to normalize this response. A study with MDD adults was done who completed fMRI scans and received behavioral activation therapy. The findings showed that psychotherapy lead to functional changes in structures that mediate award response. Hence, it can help to improve reward related functions of patients (Dichter et al., 2009).
Diagnosis of MDD may lead to low striatal response and high medial prefrontal response to rewards. As there is change in the dopamine system and the reward functions due to aging, the altered reward functions is more prominent in depression (Forbes & Dahl, 2012). The purpose of this research is to study response to reward-based reinforcement learning in depression and investigate the implications of altered reward functions on treatment development. The fMRI study will help in in vivo identification of brain regions involved in cognitive and motor processes in participants (Chau et al., 2004). It is expected that findings from this study will have great clinical implications by suggesting target areas for treatment of depressive patients. The fMRI study will help determine the specific brains which get affected by MDD and accurate clinical intervention will be given based on this results.
The main aim of the research is to conduct and fMRI study in healthy controls and depressed participants to analyze reward-based reinforcement learning in depression.
The main objectives of the research are as follows:
The research questions for the study are as follows:
Tremblay and Mayberg (2005) have described the pathway called the brain reward system which plays a major in the mediation of reward behaviors and that of motivation. They have stated how the neurological pathway system that is involved is responsible for providing rewards which serve elicit approach and as well as consumatory behaviors that will be helpful in inducing subjective feelings based on pressure and also for positive emotional states. They also help to prevent extinction. While conducting research on it, it was suggested by them that there might be a neuroanatomical substrate which will be responsible for the feeling of anhedonia. Anhedonia takes place when an individual cannot experience pleasure as a rewarding attitude. To test this they used a compound called the destroamphetamine substrate in participants severely affected with the major depressive disorder. When tested it was seen that the compound was able to induce the release of dopamine form the mesocorticolimbic dopamine system. This resulted in enhanced rewarding effect which indicated altered reward processing in MDD. They have thereby used the functional magnetic resonance imaging called the fMRI along with that of the positron emitting tomography in order to study the varieties of the human neuroanatomical substrates that remain in close association with the positive subjective experiences after the reinforcement of the drugs such as destroamphetamine and also nicotine. The technique of the fMRI is used because it provides a higher superior temporal and spatial resolution (Clark, Chamberlain & Sahakian, 2009). It also helps in visualizing brain activity and also because it does not use radioactive tracers. These proved that dopamine related neuroanatomical substrates are intricately associated with altered rewarding processing in MDD (Der-Avakian & Markou, 2012).
A similar study was supported by Santesso et al. in the year 2008 which stated that the phasic modulation that take place in the dopamine neurons of the midbrain during the reinforcement learning is conveyed to the dACC which is often termed as the dorsal anterior cingulate cortex and alo in BG called the basal ganglion. They are mainly responsible for adaptive responding. The scientists used the electrophysiological studies of daCC function which mainly focuses on the probabilistic reward learning in healthy subjects. The task that they used, for the study, mainly corporated the integration of reinforcement history over time. When comparisons were made between the learners and the non learners, learners showed more positive feedback related negativity but greater dACC activation when they received reward for the proper identification of the stimulus. The patients were allowed to take part in a monetary incentive delay (MID) task that was administered during the Functional resonance imaging. When comparisons were made again, the learners showed stronger BG response in the reward for the MID task. All these prove that there is a higher possibility that learners who were under the probabilistic reinforcement task are characterized by stronger responses from dACC and BG in case of rewarding outcomes. These suggested that dACC indeed played a very important role in probabilistic reward learning in humans.
The above study was supported in the article of the scientists namely Di Martino et al. in the year 2008 which showed that indeed basal ganglion has a major role in clinical disorders of mental health and has been proved by the fMRI. Basal ganglia take part in a number of activities like motivational, cognitive motor and emotional processes and thereby plays a very crucial role in the varieties of neurological and psychiatric disorders (Foti and Hajkack, 2009). Researchers here also used the functional magnetic resonance imaging experiment for conducting a comprehensive functional connectivity analysis of the circuitry system of the basal ganglia. Voxelwise regression analysis has shown to provide the proof of the hypothesized cognitive motor and affective divisions mainly among the striatal subdivisions. It also provided a solid evidence of the functional organization consistence with the parallel and the integrative loop models. This process also helped them to identify subtle distinction in the striatal sub regions. They have shown that the inferior ventral striatum remains associated with the medial portions of the orbitofrontal cortex. They researched that superior striatal seed remains associated with medial and lateral portions. These had been a big help to the science world for the treatment of the disorders. This ability found to map the multiple distinct striatal circuits within a particular study in humans is the main strength of the fMRI technique. This approach therefore has been found to be extremely helpful for these disorders of the mental health that suffer from altered structure and function of the basal ganglia (Robinson et al., 2012).
Also other studies conducted by Henriques and Davidson (2000) have revealed that the left anterior hypoactivation remains present in the brain of the expressed individuals. Thos in turn have found to be the main result of the decrease in the approach related motivation and behavior in the depressed individual. For this the researchers conducted a trial between the depressed participants meeting the DSM IV criteria for major depression and another group of non depressed participants. The control group was successful in maintaining the reinforcement learning technique as they changed their pattern of responses in both the rewards and the punishment situations in relation to their neutral conditions so that they could have maximized their earning. However such a response was not shown by the depressed participants who were in the depressed categories. The findings from this study also reported of the decreased responsiveness to the reward in case of the depressed participants. Through thorough research they have been able to find out that the left prefrontal hypoactivation which is mainly found in cases of depression reflects a deficit in the approach related behavior.
Researcher Niv in the year 2009 had published his research which had shown that decision making processes that are adopted by different animals and also human beings usually follow a neural framework. It can be connected with specific learning pathways that have links to neural substrates having specific roles for each. These pathways are often found to link with the dopaminergic neurons signals in the mammalian brains and this is well observed from the various human brain imaging procedures (Chau, Roth & Green, 2004). He had clearly stated that reinforcement learning mainly helps in evaluating the activity of the decision making process and to earn the best reward from it. There are many cases where the mentally ill patient feels incomplete even when receiving rewards which might not be the best but can be pleasurable. Evidences have been given by Whitton, Treadway and Pizzagalli in the year 2015 that in many cases of disorders like bipolar disorders, depression, schizophrenia and others, reward processing abnormalities take place when the various parts of the neural processes are altered. They have proved this through experiments where they have dissected the different subcomponents of the reward processing components. They have studied these effects on the different neurobiological pathways and thereby investigated their dysregulation in different disorders of mental health patients. They have even suggested that this type of experiments holds a great strength in future. From these statements one can relate how reinforcement learning pathway may affect the reward based decision making and deliver better results.
Dayan and Niv (2008) have stated that neural reinforcement learning technique is a dynamic field that has not refined confined to its conventional approach of narrow confines of the trial and error reward learning method. It had now been exposed in a near overwhelming rate where they have been successful in connecting the substantial theoretically motivated and the informative animal studies with that of the human neuroimaging results. A new set of data have been also achieved by them like cyclic volta-metric measurements of the phasic dopamine concentrations, results on serotonin kevel, and many others. They have also observed the nascent t efforts to activate DA cells in vivo using the new types of optogenic methods like the targeted channel rhodopsin which is believed to help the reinforcement model to give more success in the future.
The research will be conducted on depressed participants and hence all the codes of ethics mentioned in the Australian Psychological Society will be followed to minimize any risk to participants. Before sample recruitment, all participants will be informed about the purpose of research and the detailed procedure of research. They will be ensured that their confidentiality will be protected and the identity of the participants will not be revealed at all circumstances (Ritchie et al., 2013). Hence, all participants will be selected after taking informed consent from them regarding the research.
As the research will also include patients with MDD, they will be diagnostically tested before the research to assess health risk or suicide related intentions in participants. Ethical issues related to the publication of the research findings will also be looked after and researcher will ensure that no confidentiality issue arises (Clarke & Cossette, 2016). As this research aims to modify the stimulate human brain through reward based activities, any devastating impact of brain related conditions will assessed before the research (Cabrera et al., 2014). The neuroethics related to fMRI will also be considered by addressing all the ethical and legal considerations in neuroscience clinical practice. The challenges may arise in fMRI techniques and this problem will be looked after by experts groups who have better understanding about the neural mechanism of conscience, emotion and social behavior in participants. It will also help to address reporting biasness in the fMRI results (David et al., 2013).
It is predicted that the findings of the results will give insight into the range of abnormalities in brain areas of participants and the effect of the structural impairment on reward based learning in participants. It will give idea whether the research finding has proved the hypothesis or conflicting results have been found. If the result is consistent with the research hypothesis, it is intended further extend the research to study the brain structure abnormalities on response rate of participants. Future research in this area could help to determine the sensitivity to reward functions of depressed patients and thinks of ways to treat their symptoms. It will give idea regarding a more efficacious treatment and interventions strategies for MDD patients. The research finding will help to answer several questions related to the pathophysiology of depression and confirm whether behavioral activation treatment will benefit patients depression or not. It also holds promise for studying basal ganglia dysfunction in MDD patients (Di Martino et al., 2008).
As the data collected after the experiment will be evaluated only after fMRI studies, some delay might also occur in the process. Furthermore the analysis of the brain structure will take time, hence it is planned to overcome this delay by engaging expert neurologist in the research. (Robinson et al., 2012). Behavioral and neuropsychological research also indicates delayed actions occur due to different neural substrates and it will lead to delay in visual or action related response. Based on these issues, the time required for completion of the research process will be determined accordingly (Singhal et al., 2013).
Reference
Cabrera, L. Y., Evans, E. L., & Hamilton, R. H. (2014). Ethics of the electrified mind: defining issues and perspectives on the principled use of brain stimulation in medical research and clinical care. Brain topography, 27(1), 33-45.
Chau, D. T., Roth, R. M., & Green, A. I. (2004). The neural circuitry of reward and its relevance to psychiatric disorders. Current psychiatry reports, 6(5), 391-399.
Clark, L., Chamberlain, S. R., & Sahakian, B. J. (2009). Neurocognitive mechanisms in depression: implications for treatment. Annual review of neuroscience, 32, 57-74.
Clarke, S. P., & Cossette, S. (2016). Secondary analysis: Theoretical, methodological, and practical considerations. Canadian Journal of Nursing Research Archive, 32(3).
David, S. P., Ware, J. J., Chu, I. M., Loftus, P. D., Fusar-Poli, P., Radua, J., … & Ioannidis, J. P. (2013). Potential reporting bias in fMRI studies of the brain. PloS one, 8(7), e70104.
Dayan, P., & Niv, Y. (2008). Reinforcement learning: the good, the bad and the ugly. Current opinion in neurobiology, 18(2), 185-196.
Der-Avakian, A., & Markou, A. (2012). The neurobiology of anhedonia and other reward-related deficits. Trends in neurosciences, 35(1), 68-77.
Di Martino, A., Scheres, A., Margulies, D. S., Kelly, A. M. C., Uddin, L. Q., Shehzad, Z., … & Milham, M. P. (2008). Functional connectivity of human striatum: a resting state FMRI study. Cerebral cortex, 18(12), 2735-2747.
Dichter, G. S., Felder, J. N., Petty, C., Bizzell, J., Ernst, M., & Smoski, M. J. (2009). The effects of psychotherapy on neural responses to rewards in major depression. Biological psychiatry, 66(9), 886-897.
Forbes, E. E., & Dahl, R. E. (2012). Research review: altered reward function in adolescent depression: what, when and how?. Journal of Child Psychology and Psychiatry, 53(1), 3-15.
Foti, D., & Hajcak, G. (2009). Depression and reduced sensitivity to non-rewards versus rewards: Evidence from event-related potentials. Biological psychology, 81(1), 1-8.
Henriques, J. B., & Davidson, R. J. (2000). Decreased responsiveness to reward in depression. Cognition & Emotion, 14(5), 711-724.
Kunisato, Y., Okamoto, Y., Ueda, K., Onoda, K., Okada, G., Yoshimura, S., … & Yamawaki, S. (2012). Effects of depression on reward-based decision making and variability of action in probabilistic learning. Journal of behavior therapy and experimental psychiatry, 43(4), 1088-1094.
Naranjo, C. A., Tremblay, L. K., & Busto, U. E. (2001). The role of the brain reward system in depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 25(4), 781-823.
Niv, Y. (2009). Reinforcement learning in the brain. Journal of Mathematical Psychology, 53(3), 139-154.
Palminteri, S., Justo, D., Jauffret, C., Pavlicek, B., Dauta, A., Delmaire, C., … & Pessiglione, M. (2012). Critical roles for anterior insula and dorsal striatum in punishment-based avoidance learning. Neuron, 76(5), 998-1009.
Pizzagalli, D. A. (2014). Depression, stress, and anhedonia: toward a synthesis and integrated model. Annual review of clinical psychology, 10, 393-423.
Ritchie, J., Lewis, J., Nicholls, C. M., & Ormston, R. (Eds.). (2013). Qualitative research practice: A guide for social science students and researchers. Sage.
Robinson, O. J., Cools, R., Carlisi, C. O., Sahakian, B. J., & Drevets, W. C. (2012). Ventral striatum response during reward and punishment reversal learning in unmedicated major depressive disorder. American Journal of Psychiatry, 169(2), 152-159.
Santesso, D. L., Dillon, D. G., Birk, J. L., Holmes, A. J., Goetz, E., Bogdan, R., & Pizzagalli, D. A. (2008). Individual differences in reinforcement learning: behavioral, electrophysiological, and neuroimaging correlates. Neuroimage, 42(2), 807-816.
Singhal, A., Monaco, S., Kaufman, L. D., & Culham, J. C. (2013). Human fMRI reveals that delayed action re-recruits visual perception. PLoS One, 8(9), e73629.
Treadway, M. T., & Zald, D. H. (2011). Reconsidering anhedonia in depression: lessons from translational neuroscience. Neuroscience & Biobehavioral Reviews, 35(3), 537-555.
Tremblay, L. K., Naranjo, C. A., Graham, S. J., Herrmann, N., Mayberg, H. S., Hevenor, S., & Busto, U. E. (2005). Functional neuroanatomical substrates of altered reward processing in major depressive disorder revealed by a dopaminergic probe. Archives of general psychiatry, 62(11), 1228-1236.
Vrieze, E., Pizzagalli, D. A., Demyttenaere, K., Hompes, T., Sienaert, P., de Boer, P., … & Claes, S. (2013). Reduced reward learning predicts outcome in major depressive disorder. Biological psychiatry, 73(7), 639-645.
Wacker, J., Dillon, D. G., & Pizzagalli, D. A. (2009). The role of the nucleus accumbens and rostral anterior cingulate cortex in anhedonia: integration of resting EEG, fMRI, and volumetric techniques. Neuroimage, 46(1), 327-337.
Whitton, A. E., Treadway, M. T., & Pizzagalli, D. A. (2015). Reward processing dysfunction in major depression, bipolar disorder and schizophrenia. Current opinion in psychiatry, 28(1), 7.
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download