Schizophrenia and Music Cognition

When our own conscious experiences, if bestowed with great misfortune and burden, consist of paranoia, anxiety, and fear from something perceived to be outside of us, though is manifest solely in our own vessel, we will know what it is like to live with schizophrenia. This illness, schizophrenia, is a pervasive developmental disorder which can be characterized by a plethora of abnormal features in the domains of cognition and physiology (Larøi, F.,2000).

We shall venture through the literature to see precisely which cognitions are impaired and to find whereabout the abnormal physiological structures are located; even furthermore, we will also present evidence, allotted to us by tools like functional magnetic resonance imaging (FMRI) and diffusion tensor imaging (DTI), that localizes highly particular cognitive abilities to equally particular brain regions.

After doing so, we will make note of a potential therapeutic intervention for those encumbered with schizophrenia, of which will be based on evidence from not only magnetic resonance imaging (MRI) but also laboratory behavioral experiments conducted on both musicians and patients with schizophrenia.

From Then to Now: defining cognitive processes

The notion of a cognitive process arose from the tradition of idealism: namely, Kantian philosophy, Hume’s phenomenology, and so forth. In contra-position to positivism and, to some extent, associationism and behaviorism, idealism began to put forth ideas about the functions of the mind, like sensory impression, schemas, and mental imagery (Tulving, E., & Craik, F. I. M., 2000). This work was then carried into the realm of psychology and neuroscience, giving rise to both cognitive psychology and cognitive neuroscience (Bechtel 1998; Tulving et. al., 2000).

In light of cognitive neuroscience and cognitive psychology, the methods used to define a cognitive process have undergone dramatic change. Before, philosophers defined cognitive processes through introspection and phenomenology; even, as Ivan Pavlov points out in his criticisms of Lashley, Thorndike, and Watson, behaviourists relied, to some extent, on introspective language and were more like philosophers than physiologists; only because behaviourists never conducted experiments on physiology within a controlled lab. Rather, they relied on associations between macro-events, like associations between a stimulus and response – something Pavlov disliked deeply, to the point of accusing behaviourists of bastardizing his theory (Pavlov, I. P., 1955). Now, however, researchers use physiology and behavior to define a cognitive process, excluding psychometrists: they hold on to the habit of using only the stimulus-response paradigms (Bickle, 2009).

The modern method requires that we identify, through multiple tools, a physiological structure that has an inverse relationship with other neural-networks and favours some task-based activity more than other task-based activities (Kandel, 2013; Ledoux, 1996; Lakoff, 2009; Chaovalitwongse et. al., 2010). For example, the human Default Neural Network (DNN) has an inverse relationship with neural networks associated with logical reasoning (Dastjerdi et al., 2011), and the DNN also has a high-affinity to social activities, like playing co-operative games, face-to-face communication, and intentionality (Andrew-Hanna et al., 2012; Lieberman, 2015; Regev et al., 2013; Lerner et al., 2013). This means, the DNN turns off when people perform something logical, like mathematics, and then turns back on once we disengage from the logic task. So, the DNN is a distinct pattern of activation in the brain and is associated with specific tasks. That is how one empirically defines a cognitive process: doing so leaves no room for armchair speculation.

Schizophrenia: a messy illness with messy classifications

Schizophrenia is more than one illness; indeed, from the original researchers who labelled the illness “dementia praecox” to the more modern researchers there is an agreement that schizophrenia is a spectrum of disorders (Ritsner, M. S. 2011).

The etiology of these disorders is as of yet unknown, though we can certainly link the causation of them to the brain, at the very least. Some researchers believe the cause of the disorders to be a virus which remains dormant in human cells for up to 20 to 25 years (Crow, 1998), while others disagree (Bristow, 1988). Others have argued that the disorders stem from extreme stress or extremely stressful events, for the onset often has temporal congruence to stressful events (Mueser et al., 2008). Indeed, determining how both biological and sociological factors contribute to schizophrenia is a problem well known by the researchers in the field; for instance, schizophrenia researchers have been uncertain as to whether the abnormally high crime rates amongst schizophrenic populations is due to biology, social factors, or substance abuse (Hodgins et al., 2005; Soyka, 2000; Wallace et al., 2004). The illness is certainly a challenge.

So, as of now it is unclear what the primary causes of the disorders are, but one thing is for certain, however; namely, that both genes and environment have an influence (Ciaranello, 1982; Craddock, 2005; Jiang et al., 2013; Papiol et al., 2004), of which varies case-by-case.

Moving along, the symptoms of schizophrenia are also hotly debated, as some researchers argue for the classic categories of positive and negative symptoms, while others present evidence from a cognitive perspective that only makes sense if we collapse the distinction between positive and negative symptoms (Frith, 2015).

In the classical view, positive symptoms are qualities which a majority do not experience though a few nevertheless have. These include hallucinations, which can appear in any domain of sensory experience, delusions, disorganized speech and thought, and overall psychosis. Comparatively, negative symptoms relate to flat affect, lack of emotion, poor adjustment, and poor hygiene (Carson, 2000; Velligan, 2008).

If we collapse this distinction, we can see that both negative and positive features reflect a similar underlining neuropathology; therefore, becoming one symptom rather than two. For example, flat affect and paranoia, a negative and positive symptom, can be linked to the pathways between the frontal cortex and amygdala, which are responsible for appropriate emotional responses to a given context and emotional regulation (Ledoux, 1996; Ledoux, 2012; Kim et al., 2016). And there is evidence that the pathway from the basal-forebrain to the orbital frontal cortex, when hyper-active, damaged, or impaired alters how people experience anxiety (Damasio, 1994). The cognitive approach also finds a great deal of agreement with the other cognitive symptoms of schizophrenia as well, which the classical view of positive and negative symptoms seems to ignore.

The cognitive symptoms of schizophrenia are deficits in working memory, long-term memory, verbal declarative memory, semantic processing, episodic memory, and attention (Kurtz et al., 2001; Tan, 2016; Cirillo, 2003; Pomarol-Clotet, 2008; Goldberg, 2010; Lawrence et al., 2015). And as noted in this paper, attribution and meta-cognition also seem to be impaired. Indeed, some researchers even argue that emotion is a form of cognition (Damasio, 1994; Damasio, 2003), which would then lead to classifying the negative symptoms as cognitive deficits as well. These deficits need to be accounted for by any categorization model.

At any rate, it is evident that not only is the etiology of schizophrenias quite messy but so too is the categorization of symptoms. So, the conclusion from this section of the paper is that schizophrenia is a spectrum of illnesses which has yet to receive a conclusive set of symptom categories.

Methods and Results: having a closer look at reality.

Of the research I reviewed, there were three primary methods used to probe the human minds entangled with schizophrenia. The least technologically sophisticated being listening tasks, questionnaires, and word recognition tasks. The more technologically adept methods were FMRI and DTI.

Listening tasks usually consist of a researcher and a participant undergoing a task that requires the participant to listen to something; for example, placing headphones on a participant and asking them to identify sounds is a listening task. This method was traditionally used for “black-box” theorizing, which is an approach that develops mental models based on behavioral experiments, but the listening task is now used in-conjunction with neural evidence.

Moreover, word recognition tasks are also another classical black-box methodology used to theorize about cognitive processes. The gist of the method is as follows: give participants a list of words to memorize and then have them identify these words from a list of randomly selected words. This method is now frequently used with FMRI studies, though some researchers still use it in the classical way.

These two methods, although useful, have limitations. Both listening tasks and word recognition tasks have limitations in isolating neural structures. The tasks often require multiple cognitive functions, like retrieval, recognition, and semantic memory; as a result, it increases the overall activity of the brain, sometimes in areas of little to no interest. On top of that, when these methods are used without tools like FMRI, they lose all explanatory power. Reason being, there is no empirical way to verify what is precisely occurring when people perform these tasks, and so everything becomes a speculative philosophy; for example, suppose we show someone a list of words once and then ask them to write down each word they saw, on a piece of paper. Assuming the person scored perfect, we might infer they have a good memory. In doing so, we have done two things. On the one hand, we said the same thing that the test tells us; namely, the person performed well on the test (which isn’t useful). And on the other hand, we gave the brain some function without genuinely doing observation. We do not know if the brain has stored information about the words, or, alternatively, if the areas which contain those lexical items have simply become more excitable because of previous disturbance. The difference would entirely alter the claim made from the test.

Now, of these two limitations, the first remains, but the second can be handled by simply looking at neural data to support any hypothesized brain function. (For further clarifications on the difference between scientific and philosophical language, see Ayer, 1952; Skinner, 1957; Pavlov, 1955).

The other two methods which were used in the studies reviewed are FMRI and DTI. FMRI measures blood flow around the brain. This allows us to keep track of brain activity because blood delivers nutrients to cells which are being used. So, if there is a significant amount of blood flow in region X, then we assume that region X is doing something cognitively important. Comparatively, DTI is a measurement process that generates contrast MR images based on the diffusion of water-molecules throughout the brain, effectively allowing us to map the white matter tracts inside the brain.

The limitations that come with FMRI and DTI do influence the conclusions one can reach from using either to conduct research; however, we will not discuss the limitations because they have no influence on the logical coherence of the argument we will present, and so would only distract us, unnecessarily so, from our goal.

Listening Tasks and Word Recognition: where’d that come from?

A study interested in attribution cognition (Baker et al., 1998) administered the Kinderman’s Word Association Task to 15 patients with schizophrenia that had auditory hallucinations, to 15 patients with schizophrenia that had no auditory hallucinations, and to 15 healthy controls. The patients were asked to vocalize words which they generated in response to words read. After, the patients were given a Meta-Cognitive Belief Questionnaire, which was to measure the beliefs the patients had about where the sound, that being their own vocalizations, came from. Reliably so, those who suffered from auditory hallucinations attributed the vocalizations to something in the environment rather than themselves. This is evidence of a faulty auditory attribution process.

A second study (Bentall et al., 1985) conducted another listening task, though the test was different. The design consisted of three groups; one group consisted of healthy undergraduate students, another group consisted of patients with schizophrenia who lack auditory hallucinations, and the last group consisted of patients with schizophrenia who have auditory hallucinations. The listening test stimulus was a sound which sounded similar to “who” but was clearly not “who”. The only group to correctly identify the signal, on average, was the undergraduate group. The evidence supports, indirectly, the faulty attribution hypothesis as well as, directly, deficits in auditory cognition.

Another research group (Brébion et al., 1998) administered a word recognition task amongst a population of 80, 40 healthy and 40 with schizophrenia. The participants were given some time to memorize a list of words. After, they were to pick from a randomized list of words which ones they had previously seen. In addition to that, the patients were given a psychological inventory to measure their positive and negative symptoms. The results show that those who have both schizophrenia and a high score for positive symptoms, on average, falsely identify words on the random list as being previously learned. This further supports the hypothesis of faulty attribution cognition.

Another group of researchers (Margo et al., 1981), using the listening task paradigm, placed patients into a controlled environment. They put headphones on the patients and played various auditory signals, from white noise to words. Surprisingly, some signals evoked auditory hallucinations whereas others had no influence. This research further supports the notion that patients with schizophrenia have faulty attribution processes when it comes to auditory cognition.

Maps, Cognition, and Music: how music makes us connect

As any good journeymen know, a map is of the utmost importance in ensuring a venture that is equally safe as it is efficient. The reason being rather obvious, to reach destination B from position A requires one to know, precisely, where they are currently and how to get to where they need to be from where they are. Now, although we have no use for destinations, given we have little interest in anti-psychotic interventions – at least not in the context of this paper, we do, however, need to know where the cognitive function of attribution might be located. Therefore, we shall attempt to develop a coherent map of schizophrenia neuropathology.

As though our understanding of schizophrenia were not messy enough, we now have an even greater mess to consider: the joys of scientific research! There are, as far as the evidence shows, 17 different brain regions which show abnormalities in patients with schizophrenia (Shenton et al., 2001). And, on top of that, there are also cases where the entire cortical layer has thinned (Crespo-Facorro et al., 2011). Fortunately for us, we only need to focus on one brain region: namely, the corpus collosum. Not only can schizophrenia be predicted before onset by examining the corpus collosum, but the corpus collosum also shows deficits in 63% of the 193 reviewed FMRI studies in the meta-review conducted by Shenton and others; and on top of that, deficits in attribution can be linked to the corpus collosum (Carletti et al., 2012; Keshavan et al., 2002).

Interestingly, the corpus collosum is thicker in the brains of musicians (Hyde et al., 2009). The reason being, musicians have lateralized language abilities to a further degree than the average person, and so it necessarily follows that they would also require a greater degree of interhemispheric processing as well (Bouhali, 2017). Since the evidence shows that musicians have an increased ability for interhemispheric processing, based on our understanding of ohms law, it logically follows that their axons are thicker and more developed (Kandel, 2014).

And the last piece of evidence, evidence which will greatly increase our confidence in the argument to be laid out, is research performed on populations of people with schizophrenia. A team of researchers (De Bézenac et al., 2015) had found that attribution abilities vary amongst populations of those with schizophrenia, and the variance is determined by one factor. More specifically, patients who have schizophrenia and music training can correctly identify the sources of sounds more often than those who have schizophrenia and no music training. Those who correctly identify the sound can indicate the source as being external, whereas those who falsely identify the sound attribute it to being internal. This is evidence that musical ability, and, therefore, the corpus collosum, play a fundamental role in correctly attributing sounds to sources.

Conclusion: what now?

Based on the evidence from the studies conducted in both physiology and clinical labs, we now know that the corpus collosum is involved in attribution. And in addition to that, we know attribution is heavily impaired with those suffering from schizophrenia; indeed, faulty attribution is even argued to be reason for auditory hallucinations, as evident by the fact that patients with schizophrenia attribute self-produced sounds to external sources. We also know that patients with music training make this error far less than those without music training. So, it follows, therefore, that music training should be used in treating patients with schizophrenia, as this may slow down or stop the deterioration of the corpus collosum as well as mitigate auditory hallucinations.

The hypothesis for such a justification is that attribution is linked to the corpus collosum and the deterioration in that region, which is the case with schizophrenia, leads to faulty attribution cognition.

Future research on this topic should focus primarily on the implementation of music training for those that have no previous background in music and that have schizophrenia; only because this would either answer some of our questions about the efficacy of such a therapeutic strategy or negate the hypothesis entirely. Meaning, if it turned out to be the case that music training cannot develop the white matter tracts in patients who have already had schizophrenia for some time, or that the music training had no significant impact on reducing hallucinations, then we would have to go back to square one and re-examine the evidence for an alternative hypothesis.

References

Ayer, A. (1952). Language, truth and logic. New York: Dover.

Andrews-Hanna, Jessica R. (2012-06-01). “The brain’s default network and its adaptive role in internal mentation”. The Neuroscientist: A Review Journal Bringing Neurobiology, Neurology and Psychiatry. 18 (3): 251–270. doi:10.1177/1073858411403316.

Baker, C., & Morrison, A. (1998). Cognitive processes in auditory hallucinations: Attributional biases and metacognition. Psychological Medicine, 28(5), 1199-1208.

Bechtel, W., Graham, G., & Balota, D. A. (1998). A companion to cognitive science. Malden, Mass: Blackwell.

Bentall RP, Slade PD (1985) Reality testing and auditory hallucinations: a signal detection analysis. Br J Clin Psychol 24:159-169.

Bickle, J. (2009). The Oxford Handbook of Philosophy and Neuroscience (1st ed.). Oxford University Press.

Bouhali, F., Mongelli, V., & Cohen, L. (2017). Musical literacy shifts asymmetries in the ventral visual cortex. NeuroImage, 156, 445-455.

Brébion, G., Smith, M., Amador, X., Malaspina, D., & Gorman, J. (1998). Word recognition, discrimination accuracy, and decision bias in schizophrenia: Association with positive symptomatology and depressive symptomatology. The Journal of Nervous and Mental Disease, 186(10), 604-9.

Bristow, M. (1988). The Viral Theory of Schizophrenia. British Journal of Psychiatry, 153(2), 259-259. doi:10.1192/S0007125000222538.

Carletti, F., Woolley, J.B., Bhattacharyya, S., Perez-Iglesias, R., Poli, P.F., Valmaggia, L., Broome, M.R., Bramon, E., Johns, L., Giampietro, V., 2012. Alterations in white matter evident before the onset of psychosis. Schizophr. Bull. 38 (6), 1170–1179.

Carson VB (2000). Mental Health Nursing: The Nurse-patient Journey. W.B. Saunders. p. 638. ISBN 978-0-7216-8053-8. Archived from the original on 13 May 2016.

Chaovalitwongse, W. A., Pardalos, P. M., & Xanthopoulos, P. (2010). Computational neuroscience. New York: Springer.

Ciaranello, R., & Boehme, D. (1982). Genetic regulation of neurotransmitter enzymes and receptors: Relationship to the inheritance of psychiatric disorders. Behavior Genetics, 12(1), 11-35.

Cirillo MA, Seidman LJ (June 2003). “Verbal declarative memory dysfunction in schizophrenia: from clinical assessment to genetics and brain mechanisms”. Neuropsychology Review. 13 (2): 43–77. doi:10.1023/A:1023870821631.

Craddock, N. (March 01, 2005). The genetics of schizophrenia and bipolar disorder: dissecting psychosis. Journal of Medical Genetics, 42, 3, 193-204.

Crespo-Facorro, Roiz-Santiáñez, Pérez-Iglesias, Rodriguez-Sanchez, Mata, Tordesillas-Gutierrez, . . . Vázquez-Barquero. (2011). Global and regional cortical thinning in first-episode psychosis patients: Relationships with clinical and cognitive features. Psychological Medicine, 41(7), 1449-1460.

Crow, T. (1988). The viral theory of schizophrenia. The British Journal of Psychiatry: The Journal of Mental Science, 153, 564-6.

Dastjerdi, Mohammad; Foster, Brett L.; Nasrullah, Sharmin; Rauschecker, Andreas M.; Dougherty, Robert F.; Townsend, Jennifer D.; Chang, Catie; Greicius, Michael D.; Menon, Vinod (2011-02-15). “Differential electrophysiological response during rest, self-referential, and non-self-referential tasks in human posteromedial cortex”. Proceedings of the National Academy of Sciences of the United States of America. 108 (7): 3023–3028. doi:10.1073/pnas.1017098108.

Damasio, A. (1994). Descartes’ error: Emotion, reason, and the human brain. New York: G.P. Putnam.

Damasio, A. (2003). Looking for Spinoza: Joy, sorrow, and the feeling brain (1st ed.). Orlando, Fla.: Harcourt.

De Bézenac, Sluming, O’sullivan, & Corcoran. (2015). Ambiguity between self and other: Individual differences in action attribution. Consciousness and Cognition, 35, 1-15.

Frith, C. D. (2015). The cognitive neuropsychology of schizophrenia. London: Routledge.

Goldberg TE, Keefe RS, Goldman RS, Robinson DG, Harvey PD (April 2010). “Circumstances under which practice does not make perfect: a review of the practice effect literature in schizophrenia and its relevance to clinical treatment studies”. Neuropsychopharmacology. 35(5): 1053–62. doi:10.1038/npp.2009.211.

Hodgins, S., Tiihonen, J., & Ross, D. (2005). The consequences of Conduct Disorder for males who develop schizophrenia: Associations with criminality, aggressive behavior, substance use, and psychiatric services. Schizophrenia Research,78(2-3), 323-335. doi:10.1016/j.schres.2005.05.02.

Hyde, K.L., Lerch, J., Norton, A., Forgeard, M., Winner, E., Evans, A.C., Schlaug, G., 2009. The effects of musical training on structural brain development. Ann. N. Y. Acad. Sci. 1169 (1), 182–186.

Jiang, Z., Rompala, G. R., Zhang, S., Nakazawa, K., & Cowell, R. M. (May 15, 2013). Social isolation exacerbates schizophrenia-like phenotypes via oxidative stress in cortical interneurons. Biological Psychiatry, 73, 10, 1024-1034.

Kandel, E. R. (2013). Principles of neural science.

Keshavan, M., Diwadkar, V., Harenski, K., Rosenberg, D., Sweeney, J., Pettegrew, J.W., 2002. Abnormalities of the corpus callosum in first episode, treatment naive schizophrenia. J. Neurol. Neurosurg. Psychiatry 72 (6), 757–760.

Kim, M. J., Solomon, K. M., Neta, M., Davis, F. C., Oler, J. A., Mazzulla, E. C., & Whalen, P. J. (2016). A face versus non-face context influences amygdala responses to masked fearful eye whites. Social Cognitive and Affective Neuroscience. doi:10.1093/scan/nsw110.

Kurtz MM, Moberg PJ, Gur RC, Gur RE (December 2001). “Approaches to cognitive remediation of neuropsychological deficits in schizophrenia: a review and meta-analysis”. Neuropsychology Review. 11 (4): 197–210. doi:10.1023/A:1012953108158.

Lakoff, George, The Neural Theory of Metaphor (January 2, 2009). Available at SSRN: http://dx.doi.org/10.2139/ssrn.1437794.

Lawrence RE, First MB, Lieberman JA (2015). “Chapter 48: Schizophrenia and Other Psychoses”. In Tasman A, Kay J, Lieberman JA, First MB, Riba MB. Psychiatry (fourth ed.). John Wiley & Sons, Ltd. pp. 798, 816, 819. doi:10.1002/9781118753378.ch48.

Larøi, F. (2000). Schizophrenia from a neurocognitive perspective: Probing the impenetrable darkness. Nordic Journal of Psychiatry, 54(4), 293-294.

LeDoux, J. (2012). Rethinking the Emotional Brain. Neuron, 73(4), 653-676.

LeDoux, J. E. (1996). The emotional brain: The mysterious underpinnings of emotional life. New York: Simon & Schuster.

Lieberman, M. D. (2015). Social: Why Our Brains Are Wired to Connect.

Lerner, Yulia; Honey, Christopher J.; Silbert, Lauren J.; Hasson, Uri (2011-02-23). “Topographic mapping of a hierarchy of temporal receptive windows using a narrated story”. The Journal of Neuroscience. 31 (8): 2906–2915. doi:10.1523/JNEUROSCI.3684-10.2011.

Margo, A., Hemsley, D. R. & Slade, P. D. (1981). The effects of varying auditory input on schizophrenic hallucinations. British Journal of Psychiatry 139, 122–127.

Mueser, K., & Jeste, Dilip V. (2008). Clinical handbook of schizophrenia. New York: Guilford Press.

Papiol S, Rosa A, Gutiérrez B, et al Interleukin-1 cluster is associated with genetic risk for schizophrenia and bipolar disorder. Journal of Medical Genetics 2004;41:219-223.

Pavlov, I. P. (1955). Selected works. Moscow: Foreign Languages Pub. House.

Pomarol-Clotet E, Oh TM, Laws KR, McKenna PJ (February 2008). “Semantic priming in schizophrenia: systematic review and meta-analysis”. The British Journal of Psychiatry. 192 (2): 92–7. doi:10.1192/bjp.bp.106.032102.

Regev, Mor; Honey, Christopher J.; Simony, Erez; Hasson, Uri (2013-10-02). “Selective and invariant neural responses to spoken and written narratives”. The Journal of Neuroscience. 33 (40): 15978–15988. doi:10.1523/JNEUROSCI.1580-13.2013.

Ritsner, M. S. (2011). Handbook of schizophrenia spectrum disorders: Volume I. Dordrecht: Springer.

Shenton, Dickey, Frumin, & Mccarley. (2001). A review of MRI findings in schizophrenia. Schizophrenia Research, 49(1), 1-52.

Skinner, B. (1957). Verbal behavior. (The Century psychology series). New York: Appleton-Century-Crofts.

Soyka, M. (2000). Substance misuse, psychiatric disorder and violent and disturbed behaviour. The British Journal of Psychiatry,176(4), 345-350. doi:10.1192/bjp.176.4.345.

Tan BL (August 2009). “Profile of cognitive problems in schizophrenia and implications for vocational functioning”. Australian Occupational Therapy Journal. 56(4): 220–8. doi:10.1111/j.1440-1630.2008.00759.x. PMID 20854522. Archived from the original on 13 November 2016.

Tulving, E., & Craik, F. I. M. (2000). The Oxford handbook of memory. Oxford: Oxford University Press.

Velligan DI, Alphs LD (1 March 2008). “Negative Symptoms in Schizophrenia: The Importance of Identification and Treatment”. Psychiatric Times. 25 (3).

Wallace, C., Mullen, P. E., & Burgess, P. (2004). Criminal Offending in Schizophrenia Over a 25-Year Period Marked by Deinstitutionalization and Increasing Prevalence of Comorbid Substance Use Disorders. American Journal of Psychiatry,161(4), 716-727. doi:10.1176/appi.ajp.161.4.716.

🔴Social Media Accounts:

Follow My Facebook

Subscribe To My Youtube Channel