N e u r o A n a l y s i s
By introducing complex system sciences, such as computational neuroscience, the currently differed disciplines of Neurology, Psychiatry and Psychology can be unified into one comprehensive complete discipline that merits the title of "NeuroAnalysis."
NeuroAnalysis will be the future discipline of all brain disorders and disturbances, hence the term "Neuro." As a clinical discipline "Analysis" stands for the diagnostics and therapeutic outlooks of this unifying filed of brain disturbances.
The current divide between the disciplines, results from present limited understanding of the way in which the brain accomplishes higher-level mental functions, such as personality and feelings, thus lacking the basic clinical science about the causes of a spectrum of disorders currently titled mental disorders.
The brain is a physical biological system; it is the most complex system known to us, to understand the brain we should apply complex-system-sciences to study its functions and dysfunctions. One such relevant scientific discipline is computational neurosciences where mathematical models of the brain begin to provide insights to how the brain works as a complex system.
With such disciplines we can begin to conceptualize mental disorders as brain disorders, and thus bring back psychiatry and psychology to the realm of brain-related sciences allowing them to merge with neurology and create a unified field of brain-related disorders.
In neurology we are dealing essentially with illnesses that have a clear identifiable damage to brain tissue, in psychiatry it seems that we are dealing with disorders of organization and function of neuronal ensembles within the brain tissue, in other words disturbances of the neural circuitry function instead of structure. This is evident from novel findings related to applications of neural computation methods to brain research.
Three major disturbances are predicted to play a role in all mental disorders, 1) disturbances of basic neuronal organizations responsible for internal representations and contextual processing, 2) disturbances to the optimal matching dynamics of activated neuronal ensembles and 3) disturbances to the connectivity dynamics of brain circuitry.
1) Disturbances of internal representations and contextual processing,
Basic neuronal organizations responsible for internal representations and contextual processing result from Hebbian dynamics, and develop by means of experience-dependent-plasticity, thus allowing for the formation of internal representations of external occurrences.
Such internal representations are conceptualized by psychologists as 'Object Relationships' were objects are the internal representations of others in our past and current psychosocial environment. Object Relationships are the contexts which govern our patterns of perceiving, reacting to, and behaving with others, or in other words, relevant to our personality styles within psychosocial settings.
Consequentially disturbances and biases of internal representations are directly relevant to personality disorders. In personality disorders the internal representations can be immature with general inadequacies toward the psychosocial adaptations needed, or they can be partially, specifically biased in certain contexts only. I any case, - general or specific, - these biases cause non-adaptive interactions with others and are the source of distress within psychosocial settings.
Because a psychotherapeutic session is an interpersonal experience, actually an experience-dependent-plasticity process, - then psychological interventions are in fact brain-changing interventions and can easily integrate into a unified brain-based discipline. This is especially true if psychotherapy is done correctly involving corrective experiences that allow for new internal formations to increase adaptability and coping with psychosocial occurrences thus alleviating sufferings resulting from non-adaptive interactions.
2) Disturbances to the optimal matching dynamics
The process of experience-depended-plasticity involves a continuous update of internal representations according to the ongoing external occurrences, thus there is a continuing process of 'matching' between the internal representations of the individual and his experiences in the world.
A well-adaptive, well-functioning, neuronal system will provide for optimal matching dynamics, one that reduces the 'distances' between internal representations and external events, however if for any reason the resilience of the neuronal systems is hampered, or on the other hand, the occurrences in the real world are abruptly or greatly modified, then the mismatch, or the 'distances,' between internal representations and external events increase and a non-optimal matching dynamics ensues.
We know that depressed mood involves hampered neural resilience, caused by cell death dendrite spines reductions and hormonal metabolic causes, and we know that depressed mood can also be caused by stressful events, which are actually occurrences in the real world that are characterized by abrupt vast modification of occurrences (death of a loved one, loss of a job ect').
As a result we can begin and conceptualize depression as ensuing form de-optimized matching dynamics. 'Matching Complexity' is the neuroscientific neurocomputational mathematical tool (Tononi et al 1996) to conceptualize depression as a brain-related deoptimization dynamic process.
3) Disturbances to the connectivity dynamics of brain circuitry
Connectivity between and within neuronal ensembles in the brain is critical for internal representations to subsist and matching dynamics to transpire. As Hebbian neural ensembles connect to represent information and form memories, they have to disconnect in order to loose and forget the non relevant information.
Remembering and forgetting information relevant for functioning in the dynamic ever-changing world of tasks and challenges calls for connectivity balances between connectivity dynamics and disconnectivity dynamics. In other words connectivity dynamics and disconnectivity dynamics have to go hand in hand, - disconnection dynamics to forget irrelevant information and connection dynamics for the formation of new upcoming memories.
The brain is also hierarchically connected and unimodal specialize processes interconnect to form higher-level multimodal associative experiences,- which in turn globally integrate into whole Transmodal brain organizations allowing for coherent integrative conscious experience and for the highest-most brain functions such as 'motivation' and 'volition. (Mesulam 1998)'
"Neural Complexity" is the mathematical neurocomputational formulation of optimal connectivity balance in the brain (Tononi et al 1994), disorders of neural complexity can result in 1) disconnection dynamics that fragments conscious experience as occur in psychosis, and 2) over-connection dynamics that constrains and limits brain organization hampering hierarchical formation, resulting in the so-called negative deficiency signs and symptoms of schizophrenia process where volition, motivation and high mental functions are lost. In effect the alternating manifestations of positive and negative signs of schizophrenia reflect a disorder to the optimal connectivity balance of brain organization, - where disconnection and over-connection dynamics replace the normal optimal connectivity balance.
To summarize we can see how all mental disorders, - starting from personality disorders, through mood disorder to psychosis and schizophrenia, - can be reconceptualized as brain disorders using knowledge about normal brain dynamics and complex organization (for details read the book titled NeuroAnalysis Peled 2008).
A novel brain-related diagnostic framework can be generate by substituting descriptive diagnostic terms such as 'Depression' with "disorder to neural resilience and matching complexity" or "Schizophrenia" with "disturbance to neural complexity," this novel psychiatric diagnostic framework can be titled "Clinical Brain Profiling" (Peled 2009) making way for a natural scientific merge with neurology.
At first the current descriptive diagnosis can be applied to CBP generating testable predictions toward the real disturbances of the patients, - for example, calling a 'Psychotic' patient 'Disconnection Syndrome' is a prediction that once scanned and imaging-processed in a relevant way,- one will find a disconnection disturbances in the patient's brain.
Once testable predictions of CBP are validated, then the brain-related etiology of mental disorders is unraveled, and the grand-unification with Neurology and Psychology is attainable.
Mesulam, M. From Sensation to Cognition. Brain 1998;121: 1013-1052.
Peled, A. NeuroAnalysis, Bridging the Gap between Neuroscience Psychoanalysis and Psychiatry (Routledge, New York, 2008).
Peled A. Neuroscientific psychiatric diagnosis. Med Hypotheses. 2009;73(2):220-229
Tononi, G., Sporns, O., Edelman, G.M. A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc Natl Acad Sci USA. 1994;91: 5033-5037.
Tononi, G., Sporns, O., Edelman, G.M. A complexity measure for selective matching of signals by the brain. Proc Natl Acad Sci U S A 1996; 93:3422-3427.
This group does not have any discussions yet.