“Clinical brain profiling”: A neuroscientific diagnostic approach for mental disorders

Medical Hypotheses 83 (2014) 450–464

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Medical Hypotheses journal homepage: www.elsevier.com/locate/mehy

‘‘Clinical brain profiling’’: A neuroscientific diagnostic approach for mental disorders Abraham Peled a,b,⇑, Amir B. Geva c a

Sha’ar Menashe Mental Health Center, Hadera, Israel Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa, Israel c Electrical and Computer Engineering Department, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel b

a r t i c l e

i n f o

Article history: Received 22 April 2014 Accepted 22 July 2014

a b s t r a c t Clinical brain profiling is an attempt to map a descriptive nosology in psychiatry to underlying constructs in neurobiology and brain dynamics. This paper briefly reviews the motivation behind clinical brain profiling (CBP) and presents some provisional validation using clinical assessments and meta-analyses of neuroscientific publications. The paper has four sections. In the first, we review the nature and motivation for clinical brain profiling. This involves a description of the key aspects of functional anatomy that can lead to psychopathology. These features constitute the dimensions or categories for a profile of brain disorders based upon pathophysiology. The second section describes a mapping or translation matrix that maps from symptoms and signs, of a descriptive sort, to the CBP dimensions that provide a more mechanistic explanation. We will describe how this mapping engenders archetypal diagnoses, referring readers to tables and figures. The third section addresses the construct validity of clinical brain profiling by establishing correlations between profiles based on clinical ratings of symptoms and signs under classical diagnostic categories with the corresponding profiles generated automatically using archetypal diagnoses. We then provide further validation by performing a cluster analysis on the symptoms and signs and showing how they correspond to the equivalent brain profiles based upon clinical and automatic diagnosis. In the fourth section, we address the construct validity of clinical brain profiling by looking for associations between pathophysiological mechanisms (such as connectivity and plasticity) and nosological diagnoses (such as schizophrenia and depression). Based upon the mechanistic perspective offered in the first section, we test some particular hypotheses about double dissociations using a meta-analysis of PubMed searches. The final section concludes with perspectives for the future and outstanding validation issues for clinical brain profiling. Ó 2014 Elsevier Ltd. All rights reserved.

Motivation for clinical brain profiling In this section, we review the clinical and theoretical literature in neuroscience to motivate the pathophysiological basis of clinical brain profiling. In brief, we will see that two cardinal dimensions or axes emerge. The first is the degree of connectivity in the brain that can be too high or too low. Variations in connectivity can then be interpreted functionally in terms of false inference associated with psychosis, in particular schizophrenia. The second key dimension is plasticity that we will associate with abnormalities of mood, which can be associated with aberrant neuromodulation and plasticity in the brain. ⇑ Corresponding author at: Sha’ar Menashe Mental Health Center, Mobile Post Hefer 37806, Israel. Tel.: +972 52 2844050. E-mail address: [email protected] (A. Peled). http://dx.doi.org/10.1016/j.mehy.2014.07.013 0306-9877/Ó 2014 Elsevier Ltd. All rights reserved.

A common theme in this section will be abnormal connectivity and its plastic changes that underlies perceptual inference and learning respectively. This will be considered from a point of view of graph theory and free energy formulations of the Bayesian brain hypothesis. The latter is particularly pertinent for psychopathology that usually can be reduced to some form of false believe or inference. The optimal brain probably assumes a small-world-network organization [2]. This is an organization in which most units are not neighbors of one another, but most units can be reached from every other one through a small number of hops or steps (i.e., connections). This entails optimal information transfer and thus optimal brain organization. Such organization requires a certain balanced connectivity between near-by clustered units and faraway long-path connections when such a balance is disturbed then the network can become unstable with different parts of the

A. Peled, A.B. Geva / Medical Hypotheses 83 (2014) 450–464

network becoming ‘‘disconnected’’ thus different units of the network become statistically independent of each other (randomly). Optimal integrated brain system can become disintegrated when biased from the optimal small-world organization [2]. Small-world organization is characterized by ‘‘Hubs’’ that are network junctions with numerous connections. Hubs allow for brain hierarchy of information processing. ‘‘Unimodal’’ processors (e.g., auditory visual somatosensory) integrate at ‘‘multimodal’’ levels (i.e., associative cortices) and these further integrate at whole brain ‘‘transmodal’’ levels [3] to create the integrated conscious experience of a well-organized coherent familiarity. Thus, hubs allow integration of multiple modalities and the higher-level networks of hubs create integrated transmodal global whole-brain organization. With hierarchy comes bottom-up top-down hierarchical balance, and well organized sophisticated global integrations that are both stable and changeable at the same time, offering the brain its complexity, flexibility and adaptability required for its extremely intricate activity [4]. The connectivity of the brain allows the brain to acquire ‘‘emergent properties’’ that are synergistic. The system as a whole demonstrates phenomena that are not achievable at the level of its elements. For example, the brain realizes phenomena such as consciousness, personality, mood and feelings. Single neurons, or groups of neurons do not have such characteristics. Here we approach the philosophical issue of ‘‘psychophysics’’; higher mental phenomena implemented in mental disorders are emergent properties from global brain organizations, and mental disorders themselves are thus disturbances to the optimal global brain configurations, i.e., ‘‘Globalopathies’’ [5]. Global workspace theory explains consciousness as an emergent property of global transmodal brain organization [6]. Partial parallel unconscious processes integrate into a momentary unitary event of whole brain integration, each emerging as an instantaneous conscious experience. This is why consciousness is experienced as a serial phenomenon in time, even though the brain is a parallel processing machine [7]. Global organizations give conscious experience its integrity; it is always unitary complete, and cannot disintegrate (e.g., Necker cube). One can conceive what would happen to conscious experience if global brain organizations were to disintegrate. We know that vast disintegration of brain organization is accompanied by loss of consciousness, but milder forms of disintegration can result in distortions and misrepresentations within the conscious experiencing of events. Plasticity is another major organizational phenomena in the brain. We know that the brain continually creates new connections and loses old ones. This is implemented by synaptogenesis and synaptic-deletion which is governed by incoming input stimuli, i.e. governed by experience [8]. ‘‘Experience-dependent-plasticity’’ is the term used to indicate that brain connectivity is determined by experience. Donald Hebb [9] stated the famous axiom of ‘‘fire together wire together’’ implying that if within a certain experience (input) if two neurons are excited simultaneously repeatedly, than the connection between them is strengthened. The opposite is also correct, if they do not fire together (desynchronized) than the connection between them is weakened. This mechanism has been useful in embedding information within neuronal network structures [10], implying that memories in the brain are probably acquired by similar mechanisms of plasticity increase of connection strength. If a certain experience is represented by activation of neuronal ensembles then the reactivation of these units strengthens connectivity among the units of the ensemble embedding the experience within the network connectivity formation. Recall is achieved once some of the units of the ‘‘memory ensemble’’ are activated by input, activating the entire

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memory construct by virtue of strong connections that excite all the units strongly bounded by the strengthened connectivity. This mechanism explains the acquisition of internal representations of the outer world archived by the brain. During development, experiences of the individual are gradually embedded in the developing brain by Hebbian mechanisms of plasticity. Thus, an internal representation of experience is gradually developing; the mature brain is capable of representing its external physical and psychosocial environment. Furthermore, the brain uses the internal representations as guidance for action, i.e., the internal representations govern the reactions and behaviors within the psychosocial world, thus it is of utmost importance that the internal representations ‘‘match’’ and reliably represent the occurrences of the reality of one’s life. The adaptability of the brain is achieved by plasticity using a ‘‘Bayesian brain’’ dynamics [11], the brain continually predicts the patterns of incoming stimuli and acts to adapt to them continually reducing the differences, i.e., reducing the ‘‘free energy’’ the diversity in terms of thermodynamic entropy calculation [12]. In this context, free energy is a statistical measure of the goodness of fit between sensory input and the brain’s best guess or hypothesis about the causes of those inputs. Put simply, free energy can be regarded as the amount of prediction error; where prediction error is the actual sensory input minus the predicted sensory input. The plastic brain achieves low free energy by increasing matching capabilities [13]. Thus, it is adaptable and equipped with an optimal reliable internal representation system that effectively governs the individual in the constantly changing events of everyday contemporary life. One can immediately conceive what would happen if plasticity is impaired, internal representations are compromised, and if adaptability fails and the individual afflicted begins to make erroneous actions and reactions to everyday occurrences. In this progression of plasticity and internal representations there are two interdependent processes. The first is that of internal configurations embedded in the form of strengthened connections, the second is free-energy dynamics, which increases and decreases based on both the plasticity and the degree of change in the environment. If plasticity is impaired, the brain cannot adapt to the dynamic environment and free energy increases; if plasticity is not affected, but the alterations in the environment are abrupt and large, the plastic brain does not have enough time to adapt and free energy increases anyway. Thus, two interdependent processes can increase free energy, aberrant plasticity, and environmental changes. If both occur together, i.e., plasticity is compromised and the environment changes substantially, free energy will increase [5]. Disturbed plasticity, as well as stress (abrupt changes) are correlated with depressed mood, thus it is reasonable to conceive mood as an emergent property from global free energy dynamics of the brain. With reduced plasticity and increased stressful events free energy increases accompanied by depressed mood, thus we can conceptualize depression as the emergent property of free energy dynamics of the brain. Inversely increased plasticity is at the basic mechanism of antidepressant medications, thus reduced free energy due to plasticity-induced environmental-matching is accompanied by the emergent property of elevated mood [5]. Although it may sound a bit abstract to cast brain function in terms of free energy minimisation, there is in fact a fairly simple rationale for this. The minimisation of free energy referred to here is a way of describing Bayesian inference. This is important because one can cast many symptoms and signs in terms of false inference or beliefs. This is obvious for things like delusions and hallucinations; however, it also covers beliefs about movement and agency that could even be relevant to things like Parkinson’s

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disease. Furthermore, there is a quantitative mapping between the changes in free energy over different timescales and mood (see [6]). This allows us to also accommodate a mechanistic explanation for disorders of mood. Note that there is an alternative perspective on emotional regulation, afforded by interoceptive inference and its abnormalities that can be found in Seth [7]. The link between mood and personality can be conceived via mal-adaptability of internal representations characterizing personality disorders. Internal representations are non-matching, non-adapting, to the occurrences in their surroundings, and such non-adaptive dynamics increase free energy resulting in an emergent property of depressed mood. Since these mismatches continue, those suffering from personality disorders typically complain about long-lasting continuous depression (dysthymia). To summarize; small-world network organization is a fundamental requisite for the stability of a hierarchal brain and thus of coherent stable conscious experience. Plasticity is essential for adaptability, development and learning. The adaptable brain develops mature internal representations capable of optimal psychosocial achievements (i.e., mature adaptable personality). Thus the high mental functions of ‘‘consciousness’’, ‘‘mood’’ and ‘‘personality’’ can be linked to ‘‘connectivity,’’ ‘‘on plasticity’’ and ‘‘Hebbian internal representations’’. Mental disorders in the domains of consciousness such as psychosis, mood such as depression, and personality such as personality disorders, can be linked to disturbances of connectivity, plasticity and ‘‘Hebbian internal representations’’.

Translation matrix In the general sense, the conscious experience of the psychotic patient is distorted and biased because of experiences such as delusions hallucinations and owing to disorganization of thought process with loosening of associations and disturbances of logic. As explained above, coherent stable conscious experience is related to optimal connectivity, then psychotic experience can be related to disintegration of connectivity optimization. Here ‘‘Cs’’ connectivity segregation is the dimension of CBP related to pathology of connectivity, with segregation and disconnection (see also Table 1). For example, if auditory and speech-processing cortices act independently from visual and the rest of the cortex then talking voices can be experienced even though there is no one around. Thus a perception without stimulus occurs (i.e., hallucinations). If concepts are activated as memories of neuronal ensembles linked by pathways of associations, then a disintegrated brain will display fragmented thought processes with loosening of associations and

Table 1 Clinical brain profiling – diagnoses. Symbol

Brain dynamic disturbance

Assumed clinical correlate

DMN

Personality disorders

Cs

Undeveloped disturbed DMN organization Disconnectivity dynamics

Ci

Overconnectivity dynamics

Hbu

Hierarchical bottom-up insufficiency Hierarchical top-down shift Deoptimization dynamic shift

Htd D O CF CFb

Hyper-optimization dynamic shift Constrain frustration Stimulus bound constrain frustration

Psychosis and positive signs schizophrenia Repetitive poverty ideation perseverations Avolition and negative signs schizophrenia Systemized organized delusions Symptoms and signs of depression Symptoms and signs of mania Symptoms and signs of anxiety Symptoms and signs of phobias

illogical references. Illogical thinking results in erroneous conclusions leading to delusional ideation. Thus, one can conceive how disintegrated cortical activity may lead to psychotic phenomenology (Cs in Table 1). In the post-psychotic progression of schizophrenia, negative signs arise as the patient becomes deficient, with poverty of thought and perseverative ideations. Overly connected networks tend to converge into few repeated states reactivating the same neuronal ensembles repeatedly due to the overly connected mutual excitations [14]. ‘‘Ci’’ connectivity integration in Table 1 encodes this type of overly connected pathology. If initially the system could activate multiple states, now with over-connectivity taking hold, the system becomes constricted to those few repeatedly activated states. This description corresponds to the phenomenology of negative signs schizophrenia where poverty of speech with perseveration occurs. Moreover if hierarchal connectivity disrupts, as probably happens when connectivity is disturbed, then higher mental functions, those of higher-level brain integration (e.g., volition) fade and the debilitating loss of motivation and ‘‘zombie-like’’ schizophrenia phenomenology takes over [15]. This is the hierarchal bottom up ‘‘Hbu’’ disturbance of CBP shown in Table 1. Disturbances of hierarchical connectivity may also cause top-down biased control with delusional ideations (schemata) biasing experience leading to systemized delusions. This is the CBP dimension of hierarchal top-down ‘‘Htd’’ shown in Table 1. CBP describes schizophrenia spectrum phenomenology as ‘‘imbalanced connectivity’’ alternating between the two types of dynamics, Cs and Ci, as the disease progresses from one psychotic episode to the next. Over time the cortical organization is reduced due to the repeated perturbation and in-between psychotic episodes deficiency syndrome increases. Thus the disease progresses alternating between disconnection and over-connection imbalance over time [15]. Such instability probably modifies brain hierarchy destroying it and eliminating higher mental function and alternatively fixating delusional ideations. The entire spectrum of the schizophrenias phenomenology can be related to globally distributed connectivity and hierarchical brain pathology [5]. In mood disorders, other aspects of brain organization become relevant. Currently the most effective antidepressant treatment is the group of SSRI medications. These have been known to increase plasticity [16]. Electro Convulsive Therapy ECT is also a known effective antidepressant treatment, and increases plasticity [17]. Neuronal death and brain atrophy are also related to depression, for example in dementia [18]. From the theoretical foundations above, the plastic brain is adaptable in the sense that it reduces free energy by executing its Bayesian function of predicting and adapting to incoming stimuli. During development this process generates the incorporation of experiences (as memories) that create an internally represented model of reality (physical and psychosocial). The model is dynamic as it changes and adapts to incoming real-world environmental changes. The environment offers continually changing stimuli because the environment is highly dynamic. Thus there continued adjustment of optimization of the internal configurations to the actual occurrences depends on plasticity. When the optimization succeeds, elevated mood is maintained but when the system is de-optimized because the differences between the internal representations and environmental occurrences increase (increased free energy) then deoptimization occurs and depressed mood arises as an emergent property [5]. Thus ‘‘D’’ deoptimization is the CBP dimension for depressed patients. Opposing, optimization dynamics causes elevated mood thus ‘‘O’’ is the CBP dimension for manic phenomenology, see Table 1 below. Thus, two sources can contribute to initiate depression; plasticity in general, when hampered causes depression, but also altered internal representation when biased from (not matching) external

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occurrences increases free energy and causes depression. This is why personality disorders phenomenologically present in clinical settings with complaints of depression [19]. Here personality disorders are presumed to occur when developmental experiences create biased immature internal representations which are non-adaptive and continually mismatch with real-world occurrences. Thus there are elevated peaks of freeenergy that are expressed as depressive episodes. The internal representations are embedded in the developed brain organization, or in other words the basic ‘‘at rest’’ neuronal networks that are typically also called ‘‘Default Mode Networks’’ (DMN). They have obtained this name because they are active as default when cognitive-task-related networks are not active, i.e., at rest [20]. The default mode resting-state network organization probably incorporates information in the form of memories using Hebbian-like mechanisms, which create ‘‘attractor’’ formations to represent the internal model of the outer world (i.e., attractors states to which the system is attracted to when reactivating a memory). It is probable that resting-state networks are also characterized by SWN organization, and those suffering from personality disorders will show altered SWN organization in addition to immature organization levels of attractor-formations [5]. The altered immature biased resting state networks are easily destabilized leading to deoptimization (depression) and even disruptions of the system (tendencies to psychosis) as typically seen in patients with personality disorders. As a CBP dimension such disturbance to the ‘‘DMN’’ is ironed for those suffering from personality disorders in Table 1 below. The model of optimization dynamics for mood changes is also useful to explain reactive depression from stressful events. A stressful event always implies a massive abrupt change in the environment, (e.g., losing a close family member, or being fired from work). These changes in environmental occurrences will inevitably mismatch the internal configurations that represented the prestress environmental configurations. These major abrupt changes in the environment cause an abrupt increase of free energy which the brain struggles to avoid. Deoptimization dynamics are triggered as the mismatch between the internal representations and the altered environment increase drastically. The resulting emergent property is depressed mood. Using similar reasoning anxiety is conceptualized as an emergent property of widespread whole-brain neural network perturbation [5]. Normally during brain computation and organization the neural networks are more or less stable. Such stability can be conceptualized using the idea of ‘‘multiple constraint satisfaction.’’ Each unit in the system, in our case each neuron or group of neurons, exerts connectivity constraints on all the other units connected to it. Similarly it receives multiple constraints from all the other neurons connected to it, thus each unit assumes activity values which can be defined as ‘multiple-constraint-satisfaction.’ As such the entire network follows this law of constraint-satisfaction which is in accord with the free energy principle. Any perturbation to the network will inevitably increase the ‘‘values’’ of constraints dissatisfaction as ‘surprises’ increased free-energy and spreads in the network. Such destabilization and increases in free-energy is assumed to emerge as a sensation of anxious mood. In the translation of Table 1 below CF (constraint frustration) is the dimension preserved for generalized anxiety patient and when phobia arises with ‘‘bounding’’ of fear to a recognized object stimuli CFb (‘‘b’’ for bound) is chosen, see Table 1. Most, if not all types of perturbation presumably involve the emergent-property of anxiety. We know from clinical experience that most mental disorders are accompanied with concomitant anxious and depressed mood. Patients suffering from personality disorders, depression and psychosis frequently also suffer also from anxiety and depression.

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Table 1 proposes a novel outline where clinical manifestations are translated to their presumed correlated brain-disturbances. With the outline of Table 1, a ‘‘translating matrix’’ can be composed where clinical phenomenology is translated to neuroscientific brain disorders. The task is to assign to each clinical descriptive phenomenology of mental disorders its presumed brain disturbances. Thus in the CBP matrix, clinical evaluations are input entries and the proposed neuroscientific brain disturbances are outputs. The input item entries of clinical evaluations are represented by the left column in Table 2 and the proposed neuroscientific brain disturbances are represented by values of the top row in Table 2. Assignment of symptoms to brain disturbances is made using scores of ‘‘ones,’’ for example in the fourth row, motor slowness is attributed to connectivity integration (Ci) Hierarchical bottom up insufficiency (Hbu) and De-optimization dynamics (D), these are the depressed and deficient, negative signs, of schizophrenia patients. As evident the motor slowness is specifically assigned to few predicted brain disturbances, other findings can be of a more general attribute for example in the top row the finding of a disorderly patient, is attributed to nearly all brain disturbances. Even though the matrix uses only ‘‘ones’’ and ‘‘zeroes’’ it still accounts also for the severity of symptoms, for example in the second line of Table 2, finding the patient ‘‘very messy’’ which is a degree worse than ‘‘disorderly’’ is manifested in the matrix by adding an additional score to the relevant proposed brain disturbance. The values of the first line in Table 2 indicating neuroscientific brain disturbances are represented by accumulated scores of ‘‘ones’’ calculated as percentages of the total list of 54 signs, 18 symptoms and 14 history items, in all 86 of the items entries of clinical evaluations represented at the left column in Table 2. Thus, with the CBP format, the neuroscientific prediction is extracted as a percentage value from the ‘‘phenomenological field’’ of 86 ‘‘phenomenological entries’’ (Eq. (1)).

Equation 1 : phenomenological field ¼ phenomenological entries  100=86 The translation matrix actuated in Table 2 is faithful to the CBP formulations of Table 1 as for example, all the signs and symptoms of Psychosis and positive signs schizophrenia will be translated into predicted ‘‘disconnection dynamics’’ with segregated global brain organization as the presumed cause. The negative signs will be translated to connectivity integration (Ci) Hierarchical bottom up insufficiency (Hbu) and so on until all CBP predictions are covered. To summarize; the CBP translation uses binary 1, 0 scoring. Going from top rows downward, the clinical findings are ordered according to (1) signs, (2) symptoms and (3) clinical history of psychiatric manifestations. Each clinical finding contributes a ‘one’ value score to its relevant correlated brain disturbance. The disordered neuroscientific brain profile is a numerical vector constructed by a set of values for ‘CSPD,’ ‘Cs,’ ‘Ci,’ ‘Hbu,’ ‘Htd,’ ‘D,’ ‘O,’ ‘CF’ and ‘CFb’ each composed of a summary of scores divided by the number of all possible observations (i.e., the number of all clinical observation entries which is 87). As explained above, ‘‘grading’’ of clinical findings is also incorporated in the CBP matrix, for example ‘Is the patient very messy?’ is a higher degree finding than ‘Is the patient disorderly?’ Thus if the patient is very messy rather than just disorderly, his score will be higher in the matrix. A web-based CBP program is available open access at: http://neuroanalysis.org.il/? page_id=114. To increase the reliability of CBP, Table 3 describes each entry for a consistent recording of patient’s phenomenology. As evident the recording of phenomenology attempts to adhere to the current descriptive consensual modes of diagnosing patients. Artificially

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Table 2 CBP translation matrix. Detected

CSPD

Cs

Ci

Hbu

Htd

D

Is the patient disorderly? Is the patient very messy Is the patient with excessive jewelry makeup and colored clothing? Moves slowly? Stiff frozen? Restless moves a lot? Agitated looks as on verge of blowing up? Bizarre unexplainable movement Repetitive stereotype movements? Speaks slowly? Speaks little, gives short responses? Speaks little, few words only or non at all Speech at low tone or whisper Speaks fast? Speaks a lot, gives long spontaneous responses? Speaks without stopping jumping from one issue to another? Speech with elevated tone? Speech associations are loose; jumps from one sentence to another each different topic? Words are unrelated within sentences ‘word salad’? Repeating same topics of conversation? Repeating perseverating the same sentences? Responding to previous question? Obsessions and compulsions? Delusion, false unshakable belief? Systemized delusion? Illogical conclusions are non logical? Mood incongruent delusion? Flight of ideas Speech content includes mainly issues of despair, hopelessness, and pessimism Speech content includes mainly issues of megalomania, over empowerment and unrealistic optimism (and plans) Bizarre or overly abstract response to categorization (proverbs) and abstraction? Concrete interpretation of proverbs and low abstraction? Auditory hallucinations? Visual tactile olphactory hallucinations? Hypomimic affect Blunt affect? Expansive mood elevated affect? Dysphoric (suffering) affect? Depressed affect? Anxious affect? Detached from examiner? Perplex ambivalent? Inappropriately close to examiner (no boundaries)? Suspicious with examiner? Threatening to examiner? Seductive toward examiner (theatrical)? Sensitive easily offended? Childish dependent regressive? Manipulating demanding? Stubborn obsessive non adaptable? Tend to idealize or devaluate examiner? Egocentric un-empathic? Distractible? Disoriented? Memory lose? Complaining of insomnia or hypersomnia? Complaining of early insomnia? Complaining of late insomnia? Complaining of anorexia wight loss Complaining of palpitations, dizziness, abdominal cramps and tingling Complaining of anxiety fear of dying or loosing control panic Complaining of fear of dying or loosing control panic in specific conditions Complaining of tension restlessness and agitation Complaining of avolition indifference apathy anhedonia Complaining of depressed mood Complaining of depressed mood especially in the morning Complaining about flight of ideas? Complaining that thing are strange unfamiliar changing not as usual (dereism depersonalization) Complaining of external control, mind reading, bugging, persecution (about delusions) Complaining related to systemized delusion Complaining of low self esteem Complaining about being easily offended, oversensitive? Complaining of being impulsive, over imposing? History of delusions?

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0

1 1 0 0 0 1 1 1 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 1 0 1 1 1 0 0 1 0 1 0 0 0

1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 0 0 0 0 1 1 0 1 1 0 1 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1

1 1 0 1 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0

1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1

1 1 0 1 1 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1

0 0 1 0 1 1 1 1 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 0 0 1 0 0 0 1 1 1 0 0 0 0 1

1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0

1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 1 1 1 0 0 0 0 1 0 0 0

O 0 1 0 0 1 1 0 0 0 0 0 0 1 1 0 1 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0

CF

CF (b)

1 0 0 0 0 1 1 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 1 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0

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A. Peled, A.B. Geva / Medical Hypotheses 83 (2014) 450–464 Table 2 (continued) Detected History History History History History History History History History History History History History

of of of of of of of of of of of of of

hallucinations? thought disorders loosening of associations thought disorders perseverations poverty of thought? depressions? mania? anxiety phobias disturbed upbringing, parental loose behavioral problems coping deficiency work and social? instable interpersonal relationships psychosocial or other stress (regular life stressors) trauma (stressor exceeding regular life stress)

CSPD

Cs

Ci

Hbu

Htd

D

O

CF

CF (b)

0 0 0 0 0 0 0 1 1 1 1 0 0

1 1 0 0 0 0 0 0 0 0 0 0 1

0 0 1 0 0 0 0 0 0 0 0 0 1

0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 1 0 0 0 0 0 0 0 1 1

0 0 0 0 1 0 0 0 0 0 0 0 0

0 0 0 0 0 1 0 0 0 0 0 1 1

0 0 0 0 0 0 1 0 0 0 0 1 1

Table 3 Scoring criteria for reliability. Detected

Description for scoring

Is the patient untidy?

Appearance is somewhat disheveled i.e., greasy hair, dirty clothes as in ‘Grooming and Hygiene’ section (1) Subject’s clothes, body and environment are dirty and foul smelling as in ‘Grooming and Hygiene section’ (1) It is evident that the clothing makeup and jewelry are grossly exaggerated. Excessiveness is the criteria. This score should not be assigned to people who are well groomed Obvious decrease of motor activity at interview as described in level ‘2’ of retardation on the Hamilton Depression Scale (3) together with reduction of usage of expressive body gestures as in ‘marked’ level of ‘paucity of expressive gestures’ in the section of ‘affective flattening’ (1) Subject never gesticulates as in ‘severe’ rating of ’paucity of expressive gestures’ in the section of ‘affective flattening’ (1). In addition motor activity is reduced as rated for ‘stupor’ in the ‘retardation’ item of the Hamilton Depression Scale As in ‘fidgets’ in the ‘behavior at interview’ score according to the Hamilton Anxiety scale (4) the patient finds it difficult to remain seated during the interview, moves a lot in the chair, moves arms legs, changes position often, he is ‘Restless’ as in the ‘Tension’ score (4) As in ‘Paces’ in the ‘behavior at interview’ score according to Hamilton Anxiety scale (4) looks as if making the effort to restrain himself from becoming violent. Finds it hard to remain seated during the interview Makes movements that are bizarre and non-purposeful, to the extent that they must be effortlessly noticed as such by interviewer and others. If the movements are explainable and their oddity is questionable then this item must not be scored as ‘present’ Movements that are repeated in the same (similar) manner; they can be ‘repetitive stereotyped behavior’ at the ‘marked’ level of the SANS (1) Speech is slow, words are pronounced slowly and pauses between words are longer than usual, speech must be slower than those who speak slowly. It should be easily and readily evident for the examiner, if there is doubt then this item must not be scored Restriction in the amount of spontaneous speech as in ‘Alogia’ section of the SANS (1) answers in single words or very short sentences, no spontaneous speech; the interview takes the form of investigation where the examiner repeatedly asks questions and the patient responds only briefly Restriction in the amount of spontaneous speech as in ‘Alogia’ section of the SANS (1) Subject says almost nothing and frequently fails to answer ‘Lack of Vocal inflection’ speaks in monotone, as in ‘affective flattening’ section of SANS (1). In addition voice is distinguishably weak Sentences are uttered rapidly – word follows word immediately. All speech is distinguishably fast more than the regular higher spectrum of normal speech. It should be easily and readily evident for the examiner, if there is doubt, this item should not be scored Here the emphasis is on the volume of speech (rather than speed, the patient starts to speak continuously even when not asked any questions, once starting he never ends and it is difficult to stop him or insert a question while he is speaking) In addition to the description of the above previous score, here the patient is practically unstoppable and speech content is disturbed in the sense that jumping from one concept to unrelated (or loosely related) concepts is the rule Tone is elevated to the extent that the patient seems to be shouting. The tone is higher than the normal range of voice tones, if there is doubt then this item should not be scored As in ‘marked derailment’ of the SAPS (2) ‘Frequent instances of derailment: subject is often difficult to follow’ only ‘marked’ levels warrant a score here, ‘moderate’ and ‘mild’ do not As in ‘severe derailment’ of the SAPS (2) ‘derailment so frequent and/or extreme that the subject’s speech is almost incomprehensible’ here also the ‘marked and severe incoherence’ items of the SAPS (2) apply, ‘at least half of the subject’s speech is incomprehensible’ The patient is pre-occupied by a set of thoughts and repeatedly expresses them in speech. Typically this is expressed in conversation; no matter where the examiner takes the topics of discussion, the patient inevitably returns to his set of concerns. The examiner cannot divert the patient from his repeated issues for long and the patient returns to his original thoughts Here sentences are concretely repeated over and over again

Is the patient very messy Is the patient with excessive jewelry makeup and colored clothing? Moves slowly?

Stiff or frozen?

Restless, moves a lot?

Agitated looks as if on verge of ‘‘exploding’’?

Bizarre unexplainable movement

Repetitive stereotype movements? Speaks slowly?

Limited verbal communication, gives short responses?

Limited verbal communication, few words only or non at all Speech at low tone or whisper Speaks fast?

Speaks a lot, gives long spontaneous responses?

Speaks without stopping, jumps from one issue to another?

Speech with elevated tone? Speech associations are loose; jumps from one sentence to another each a different topic? Words are unrelated within sentences ‘word salad’?

Repeating same topics of conversation?

Repeating/perseverating the same sentences?

(continued on next page)

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Table 3 (continued) Detected

Description for scoring

Responding to previous question?

The patient is ‘stuck’ answering the first question although other additional questions were already asked. For example what is your name? John, where do you live? John. . . and so on As in DSM As in all delusions of the ‘delusions’ chapter of the SAPS (2) rated ‘moderated’ ‘marked’ or ‘severe’ Delusion is non-bizarre stable over time tends to grow incorporating new events in the experience of the patient. As in the delusional disorder of the DSM As in ‘illogicality’ SAPS (2) rated ‘moderated’ ‘marked’ or ‘severe’ As in ‘inappropriate affect’ SAPS (2) rated ‘moderate’ ‘marked’ or ‘severe’ As in ‘pressure of speech ‘ SAPS (2) rated ‘moderate’ ‘marked’ or ‘severe’ As in Hamilton Depression Scale (3) items ‘guilt’, ‘helplessness,’ ‘hopelessness’ and ‘worthlessness’ – scores 1–4 The subject is concerned with issues of megalomania, over empowerment and unrealistic optimism (and plans). This must be self-evident and obvious Bizarre or overly abstract response to categorization (proverbs) and abstraction

Obsessions and compulsions? Delusion, false unshakable belief? Systemized delusion? Illogical conclusions? Inappropriate affect? Flight of ideas Speech content includes mainly issues of despair, hopelessness, and pessimism Speech content includes mainly issues of megalomania, over empowerment and unrealistic optimism (and plans) Bizarre or overly abstract response to categorization (proverbs) and abstraction? Concrete interpretation of proverbs?

Auditory hallucinations? Visual tactile olphactory hallucinations? Constricted affect

Blunt affect? Expansive mood elevated affect? Dysphoric (suffering) affect? Depressed affect? Anxious affect? Detached from examiner?

Perplexed, ambivalent? Inappropriately close to examiner (no boundaries)?

Suspicious with examiner? Threatening to examiner? Seductive toward examiner (theatrical)? Sensitive easily offended? Childish dependent regressive?

Manipulating demanding? Stubborn, obsessive non adaptable? Tend to idealize or devaluate examiner?

Egocentric un-empathic? Distractible? Disoriented? Memory loss? Complaints of Insomnia or hypersomnia? Complaints of Early insomnia? Complaints of Late insomnia? Complaints of Anorexia Wight loss Complaints of palpitations, dizziness, and/or abdominal cramps and/or tingling Complaints of anxiety fear of dying or loosing control panic

Concrete interpretation of proverbs for example the common characteristic of table chair and cupboard are that they are made of wood instead of that they are all furniture. Concrete responses are given even after assisting the patient with examples of abstraction from related issues – for example ‘‘apple banana orange are fruit’’ As in ‘auditory hallucinations’ including voices commenting and conversing of the SAPS (2) rated ’mild’ ‘moderate’ ‘marked’ or ‘severe’ As in the other ‘hallucinations’ Visual tactile and olphactory of the SAPS (2) rated ’mild’ ‘moderate’ ‘marked’ or ‘severe’ As in ‘unchanging facial expression’ in the SANS (1) ‘moderate: subject’s expressions are dulled overall, but not absent’ and ‘‘marked: subject’s face has a flat ‘set’ look, but flickers of affect arise occasionally’’ As in ‘unchanging facial expression’ in the SANS (1) ‘‘severe: subject’s face looks ‘wooden’ and changes little, if at all throughout the interview’’ The subject seems elated overly happy, mood is excessive in a self-evident unquestionable manner Facial expression of suffering; uneasy as in an uncomfortable state of mind. Must be evident, if questionable no score is applied Facial expression is of painful sadness (typical triangle form of eyebrow). Must be evident, if questionable no score is applied Facial expression is of anxious form, constricted facial muscles, and bulging eye expression. Startled and/or crying expression. Must be evident, if questionable no score is applied The patient behaves as if the examiner (and others), are not there, seems to be reflecting on inner thoughts and is not available for whatever is occurring in the interview or around him. Must be evident, if questionable no score is applied Face expression is similar to that of a person seeing something extraordinary for the first time, and seems to be lost, not knowing where to turn. Must be evident, if questionable no score is applied Attitude toward the examiner is as if he were a ‘buddy’ of the patient or a close intimate relative. Asks intimate embarrassing intruding questions, sits close to the examiner (may touch or hug him). Must be evident, if questionable no score is applied Suspicious attitude toward the examiner as if the examiner is a threat, or wants to harm the patient. Must be evident, if questionable no score is applied Seems as if about to get up and hit the examiner. Must be evident, if questionable no score is applied Attitude toward the examiner is as if he were a ‘buddy’ of the patient or a close intimate relative but with a seducing actively probing attitude. Must be evident, if questionable no score is applied Overly reactive easily offended, tends to respond to regular instructions as if they were harsh criticism. Must be evident, if questionable no score is applied Attitude of the patient gives an impression of a little child, with childish facial expression and intonation of speech. Needs instructions and guidance even for simple tasks. Must be evident, if questionable no score is applied The examiner senses a constant uneasy feeling of being pressed or utilized to say, feel or do uncomfortable things. Must be evident, if questionable no score is applied Attitude to examiner and other events are obstinate, inflexible, and repeatedly insisted upon. Must be evident, if questionable no score is applied Attitude to the examiner as if he is the most wonderful and best therapist in the world, or the worst person ever; these attitudes can interchange frequently. Must be evident, if questionable no score is applied Thinks of no one but himself, unable to see the view point of others, cannot put himself in ‘‘others shoes’’ Must be evident, if questionable no score is applied Every stimulus from the environment causes the subject to turns his attention from the main course of the interview. Must be evident, if questionable no score is applied Unable to orient himself, does not know the time and day, may not recognize faces of relatives Unable to remember things of recent past days and weeks. Recall is typically preserved and long term memory is typically present Insomnia or hypersomnia Early insomnia, hard to fall asleep Late insomnia, early wake Anorexia, weight loss Palpitations, dizziness, and/or abdominal cramps and/or tingling Fear of dying or loosing control panic

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Table 3 (continued) Detected

Description for scoring

Complaints of conditions Complaints of Complaints of Complaints of Complaints of

fear of dying or loosing control panic in specific

Fear of dying or loosing control; panic in specific conditions

tension, restlessness and agitation avolition indifference apathy anhedonia depressed mood depressed mood especially in the morning

Tension, restlessness and agitation Avolition, indifference, apathy, anhedonia Being sad as in the Hamilton Depression Scale items and major depression Being sad as in the Hamilton Depression scale items and major depression especially in the morning Head full of racing thoughts A sense that something is not usual, there are hidden meanings to things, there are forces acting behind things, things are connected in a meaningful way to the individual. Must be evident, if questionable no score is applied Feeling as if controlled by external sources, others can read his mind; he is being persecuted. Others intend and plan to hurt him. Must be evident, if questionable no score is applied There is a dominating non-bizarre false idea that gradually grows and incorporates all occurrences and aspects of life. Must be evident, if questionable no score is applied Feeling worthless Easily offended, oversensitive to criticism and insinuations. Interprets even the slightest inattention from others as rejection and humiliation. Must be evident, if questionable no score is applied Reacts immediately without giving it another thought, unable to change the decision or reaction once taken. Must be evident, if questionable no score is applied As above As above As above As above As in DSM criteria As in DSM criteria As in DSM criteria As in DSM criteria Parents were not available (or orphan) the family history is of turmoil, instability and frequent changes. Subject deprived of needed attention care and love, or/and abused maltreated. Must be evident from anamnesis, if questionable no score is applied Problems at school, patient often reprimanded in school because of misbehavior, must be more than regular child’s mischief; later problems with the law are typical. Must be evident from anamnesis, if questionable no score is applied Unable to remain employed for an extended period of time, interpersonal relationships. Are generally short and unstable; and frequently changes partners. Must be evident from anamnesis, if questionable no score is applied Interpersonal relationships chaotic, characterized by turmoil. Must be evident from anamnesis, if questionable no score is applied As in Holmes–Rahe life changes scale (5): changes to different line of work, change in number of arguments with spouse, mortgage over $100,000, foreclosure of mortgage or loan, change in responsibilities at work, son or daughter leaving home, trouble with in-laws, outstanding personal achievement, wife begins or stops work, begin or end school, change in living conditions, revision in personal habits, trouble with boss, change in work hours or conditions, change in residence, change in schools, change in recreation, change in church activities, change in social activities, mortgage or loan less than $30,000, change in sleeping habits, change in number of family gettogethers, change in eating habits, vacation, christmas alone, Minor violations of the law As in Holmes-Rahe life changes scale (5): death of spouse, divorce, martial separation, jail term, death of close family member, personal injury or illness, marriage, fired at work, marital reconciliation, retirement, change in health of a family member, pregnancy, sex difficulties, gain of new family member, business readjustment, change in financial state, death of close friend

Complaints about Flight of ideas? Complaints that things are strange and unfamiliar – changing not as usual (dereism? depersonalization) Complaints of external control, mind reading, bugging, persecution (about delusions) Complaints related to Systemized delusion Complaints of low self esteem Complaints bout being easily offended, oversensitive?

Complaints of being impulsive, over imposing? History History History History History History History History History

of of of of of of of of of

Delusions? Hallucinations? thought disorders loosening of associations thought disorders perseverations poverty of thought? depressions? mania? anxiety phobias disturbed upbringing, parental loose

History of behavioral problems

History of inability to maintain employment and social relationships? History of unstable interpersonal relationships History of psychosocial or other stress (regular life stressors)

History of trauma (stressor exceeding regular life stress)

Appendix references: (1) Andreasen N.C., The scale for the assessment of negative symptoms (SANS). Iowa City: University of Iowa, 1983. (2) Andreasen N.C., The scale for assessment of positive symptoms (SAPS). Iowa City: University of Iowa, 1984. (3) Hamilton M. Development of a rating scale for primary depressive illness. Br J Clin Soc Psychol 1967;6:278–296. (4) Hamilton M. The assessment of anxiety states by rating. Br J Med Psychol. 1959;32(1):50–5. (5) Holmes & Rahe (1967). Holmes–Rahe life changes scale. J Psychosom Res, vol. 11, pp. 213–218.

generated archetypes are used to demonstrate how the CBP translation can be manifested in the clinical setting (Fig. 1) and to exemplify CBP in an intuitive manner. These are prototypes of ideal cases where symptoms and signs where limited to the typical, ‘‘by the book,’’ clinical consensus for each of the phenomenological disease-entity. The archetypes (Fig. 1) are chosen to represent major diagnostic phenomenological classification that every clinician uses when trying to assign diagnosis to his patient. Schizophrenia of positive symptoms (psychosis), schizophrenia of negative (deficiency) symptoms, depression, mania, anxiety disorder, and personality

disorder are chosen for archetypes and are listed in Fig. 1. The first (left 1A) column lists the CBP entries. The middle graph column (1B) shows the graph morphology of the CBP results. Fig. 1C gives a short explanation of the graphs in terms of brain disturbances. Validation and metanalysis of CBP The computer program of CBP (linked above) was introduced to 4000 clinicians using ‘‘LinkedIn’’: web-based social network, asking them to diagnose their patients, using CBP. 642 CBP diagnostic profiles (vectors) were collected. The computer program was designed

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A

Archetype Phenomenology

B CBP Graph

C

Explanaon of CBP translaon

Archetype Schizophrenia Posive Signs The paent is undy Is the paent restless, in constant moon? Does the paent look agitated, on the verge of exploding Does the paent exhibit bizarre unexplainable movements? Does the paent speak without stopping jumping from one subject to another? Are the paent’s speech associaons loose? Delusion, false unshakable beliefs Inappropriate affect Bizarre or overly abstract response to categorizaon (proverbs) and abstracon Auditory hallucinaons Detached from examiner Perplex ambivalent Complains that things are strange, unfamiliar, changing, not as usual Complaints of external control, mind reading, bugging, persecuon (about delusions) History of Delusions History of Hallucinaons History of thought disorders loosening of associaons

“Cs” is dominant meaning connecvity segregaon, or in other words disconnecon syndrome spread in the brain with unstable disrupted brain organizaon causing fragmentaon of consciousness with psychosis

Archetype Schizophrenia Negave Signs Is the paent undy? Is the paent very messy Does the paent move slowly Does he paent have limited verbal communicaon e.g., short responses Does the paent answer with only a few words or none at all? The paent repeats the same topics of conversaon Concrete interpretaon of proverbs and low abstracon Constricted affect Blunt affect Detached from examiner Complains of avolion, indifference, apathy and anhedonia

“Ci” connecvity integraon, overconnected brain network organizaon and “Hbu” boom-up hierarchal insufficiency are dominant, the brain organizaon is fixated, and few states can be acvated repeatedly because of the overconnecvity. In addion, due to boomup hierarchal insufficiency higher-level hierarchical brain organizaon is hampered resulng in reducon of high mental funcons such as volion and movaon

Archetype Schizoaffecve Does the paent move slowly Does the paent speak slowly Are the paent’s speech associaons loose Delusion, false unshakable beliefs Inappropriate affect Speech content includes mainly issues of despair, hopelessness, and pessimism. Auditory hallucinaons Constricted affect Depressed affect Complaints of depressed mood Complains that things are strange, unfamiliar, changing, not as usual History of Delusions History of Depression

“Cs,” “Ci” and “Hbu” are all dominant destabilizing the brain to create schizophrenia spectrum phenomenology (see above). With connecvity unbalanced and hierarchy unstable the brain cannot opmize adapve acvity, thus deopmizaon, high “D” values, results with increase of free energy and emergent property of depressed mood is dominant.

Archetype Depression “D” is dominant indicang that Deopmizaon dynamics takes over brain organizaon, either due to plascity reducon, or to stressful events, or both, brain adaptability is hampered and cannot “match” dynamic requirements of adaptability thus, free energy increases and the emergent property of depressed mood ensues.

Is the paent undy? Does the paent move slowly Does the paent speak in a low tone or whisper Speech content includes mainly issues of despair, hopelessness, and pessimism. Depressed affect Complaints of depressed mood Complains of late insomnia History of Depression

Archetype Mania Is the paent wearing excessive jewelry makeup and eccentric clothing? Is the paent restless, in constant moon Does the paent speak fast Does the paent speak with an elevated tone Speech content includes mainly issues of megalomania, over empowerment and unrealisc opmism (and plans). Expansive mood elevated affect Inappropriately close to examiner (no boundaries) Complaints of tension restlessness and agitaon Complaints about flight of ideas History of mania

“O” is dominant indicang that Opmizaon dynamics takes over brain organizaon, due to increased plascity, brain adaptability is improved and matching dynamic requirements of adaptability are increased, free energy decreases and the emergent property of elevated mood ensues.

Archetype Anxiety Is the paent restless, in constant moon Anxious affect Complaints of early insomnia Complains of palpitaons, dizziness, abdominal cramps and ngling Complaints of anxiety fear of dying or losing control, panic Complaints of tension restlessness and agitaon History of anxiety

“CF” is dominant, frustraon of constraints destabilize the corcal neural network organizaon with resulng emergent property of anxiety.

Archetype Personality Disorder Is the paent restless, in constant moon Disphoric (suffering) Depressed affect Inappropriately close to examiner (no boundaries) Seducve toward examiner Sensive easily offended Childish dependent regressive Manipulang demanding Stubborn non obsessive non adaptable Tends to idealize or devaluate examiner Egocentric not empathic Complaints of depressed mood History of disturbed upbringing and parental lose History of behavioral problems History of deficiencies in coping at work and in social situaons History of unstable interpersonal relaonships History of psychosocial or other stress (regular life stressors)

“DMN” the default-mode-network in these paents is disturbed, undeveloped unstable and immature, thus inevitably unable to adapt and match to ongoing alternang circumstances. Connuous mismatch results in endured increases of freeenergy and destabilizaon (frustraon) of constraints, thus a certain degree of D” and “FC” always also present with depression and anxiety typical to personality disorders created by the biased disturbed Default Mode Network

Fig. 1. CBP of archetypes.

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so that it does not collect identifiable information of clinician and patient alike, thus, all gathered information is anonymous. The Internal Review Board of Sha’ar Menashe Mental Health Center in Israel approved the study. The average age of diagnosed patients was 36 (SD ± g10.6). There were 400 men and 242 women. On average education of patients reached 11.1 (SD ± n3.8). Sixty-seven patients suffered acute illness and 150 were chronic patients the remaining 425, had fluctuating changing manifestations. 379 patients received antipsychotic medications, 84 patients received Selective Serotonin Reuptake Inhibitors (SSRI’s), 100 patients were not taking medication on the day of diagnosis was done. Seventy-nine patients had combined treatment of whom 19 were treated with common mood stabilizers. Three hundred and four patients were diagnosed with schizophrenia; 34 patients with Schizoaffective Disorder; 59 patients received the diagnosis of depression, 94 suffered from Anxiety; 40 received the diagnosis of personality disorders. Of those diagnosed with schizophrenia 27 seemed to be psychotic with positive symptoms but most of the schizophrenia sample was not divided into subtypes; 111 patients were grouped as others due to small numbers of different diagnoses. For example there were only two manic patients, and four with ‘‘organic brain syndromes’’ and ‘‘drug abuse’’. ‘‘PTSD,’’ ‘‘conversion disorders’’ and ‘‘autism’’ were grouped as ‘‘others’’ because there were not enough patients with each diagnosis to create specific groups. Two interdependent features in the results were expected from the diagnostic data collected, grouping of diagnosis in the form of clinically-relevant archetypes. Fig. 2 compares the artificially generated CBP diagnosis from Fig. 1 to the diagnostic data for both adherence and grouping given by the clinicians. The archetypes are listed in Fig. 2A (left column), the archetype for mania is excluded due to missing data for comparison. In the middle column, in Fig. 2B diagnostic results are shown when grouped according to the diagnosis given by the clinicians. Comparison, i.e., correlation statistics, of the results to the archetypes is given and listed in-between the archetype column A, and the results data of column B. Most comparisons show good correlations (0.56–0.9) between the archetypes and the actual results in the data, best correlations were between diagnosed personality disorders and the archetype of ‘‘personality disorder’’ (0.9). The weakest correlation was between ‘‘positive signs schizophrenia’’ archetype and the data diagnosed as schizophrenia. This lower correlation results is probably because clinicians grouped schizophrenia diagnosis in one group, which seems to correlate better with negative signs schizophrenia (0.8). From Fig. 2A and B it seems that CBP complies with adherence to DSM-like phenomenological archetypes. For assessment of grouping, we chose to apply Unsupervised Fuzzy Clustering (UFC; 24–25) to the data. UFC is a method for carrying out fuzzy classification without a priori assumptions regarding the number of clusters in the data set. Assessment of cluster validity is based on performance measures using hypervolume and density criteria. The algorithm is derived from a combination of the fuzzy K-means algorithm and the fuzzy maximum likelihood estimation (FMLE). The UFP-ONC (unsupervised fuzzy partitionoptimal number of classes) algorithm performs well in situations of large variability of cluster shapes, densities, and number of data points in each cluster. It has been tested on a number of simulated and real data sets [21]. Cluster analysis is based on partitioning a collection of data points into a number of subgroups, where the objects inside a cluster (a subgroup) show a certain degree of closeness or similarity. Hard clustering assigns each data point (feature vector) to one and only one of the clusters, with a degree of membership equal to one, assuming well defined boundaries between the clusters.

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This model often does not reflect the description of real data, where boundaries between subgroups might be fuzzy, and where a more nuanced description of the object’s affinity to the specific cluster is required. We chose UFC because it captures the internal structure of the grouping providing support to the linkage with archetypes. Interestingly, the UFC algorithm cluster validity criteria were recommending mainly two preferred partitions, the first of two clusters and the second of seven clusters. As such we first investigate the clinical usefulness of UFC application to the CBP data divided it into two clusters and then into seven clusters. Fig. 3 shows the results UFC of the patients into very symptomatic schizophrenia psychotic patients in one group, and milder, less-symptomatic, nonpsychotic non-schizophrenic in the other group. Accordingly, the first cluster was composed of 97% schizophrenia patents while the second cluster was composed of 80% mixture of milder psychiatric disorders personality disorders and anxiety depression patients. When UFC clustered the data into 7 groups they represented good resemblance to both the archetypes as well as to the actual diagnostic groups of the data. Fig. 2C shows the resembling graphs and percentages of diagnosis given by the clinicians. As evident clusters 6, and 1, readily correlated with the archetypes of personality disorders and anxiety disorders respectively. Clusters 3 and 2 correlated with the archetypes of depression and schizoaffective as well as schizophrenia of negative signs, but in effect cluster 3 had only 30% of the patients diagnosed with depression. Thus, the UFC separation was not good at differentiating depression from schizoaffective and negative-signs schizophrenia. However clusters 5 and 7 achieved good correlations with the archetype of positive-signs schizophrenia, something that clinicians did not separate, thus, it had the capability of separating the two subtypes of schizophrenia from the data, where this information was concealed by the tendency of clinicians to group all types of schizophrenia in one group. From these results, it seems that the CBP diagnostic format when used by clinicians using the CBP computer-program in the clinical settings has generated concordance diagnostic prototypes. Larger samples of diagnosis are required to evaluate if more diagnoses such as those currently grouped as ‘‘Others’’ (Fig. 2B) can become included in specific CBP profiles. However, as a preliminary result it seems that CBP ‘‘carves psychiatric nature at its clinical joints.’’ It seems to concord with the currently descriptive psychiatry as reflected by clinical practice (archetypes) as well as DSMlike approaches; it seems also, that CBP can reach reliability levels, which are similar to those currently characterizing the descriptive DSM like approach. With such reliability the advantage of CBP in comparison to the DSM-approach is manifest within its brainrelated formulation, one that can now be validated (or refuted) to discover the pathophysiological underlying disease mechanisms of mental disorders.

Discussion In the first part of this discussion we will provide a brief review of the literature that substantiates the associations and mappings established in the previous two sections. In particular, we will be looking for empirical evidence that ties abnormalities of connectivity to psychosis and schizophrenia on the one hand, and disorders of plasticity to mood disorders on the other. We base this discussion on a survey of relevant publications over the past few years. In the case of CBP only large-scale imaging studies with largedata analyses and signal processing can begin to validate the testable predictions generated by CBP. Thus, an initial validation can be attempted using the currently available scientific literature, or in other words using PUBMED literature searches. Assuming that published work is typically reporting positive results, the number

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B

A Archetype

C Fuzzy Clustering and cluster percentage

Diagnosis results N=642 (Averages )

Cluster 7

Archetype schizophrenia posive signs

80% Schizo 15% Depp 5% Drug 9

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2

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Corr = 0.56

1

Schizophrenia N= 304

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23% psych Archetype schizophrenia Negaves signs

53% Schizo 9

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Schizoaffecve N=34

Archetype Schizoaffecve

99% Schizo 1% Other 9

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Corr = 0.87

Archetype Depression

Depression N=59

Cluster 3

70% Schizo 30% Depp

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Cluster 1

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69% PD 15% Adjust 15% other 9

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Corr = 0.9 LEGEND: Y axis = % percentage Corr = Correlaons Schizo = Schizophrenia Psych = psychosis Dep+Anx Depression and Anxiety PD= Personality disorder Depp= Depression Adjust = Adjustment disorder Cluster = results of fuzzy clustering 9 8 1 = DMN Default Mode Network 2= D De-opmizaon 3 = O Opmizaon 4 = CF Constraint Frustraon 5= CF Constraint Frustraon bound 6 = Cs Connecvity segregaon 7= Ci Connecvity integraon 8= Hbu Hierarchical boom-up 9 = Htd Hierarchical top- down

7

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45% PD 28% Anxiety 7

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Fig. 2. Comparison of results to archetypes.

6

5

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1

27% Dep+Anx

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HFC 2 groups 12

10

Cluster 1 = 97% schizophrenia

8

6

Axis Y= Percentages

4 Axis X : 1 = DMN Default Mode Network 2= D De-opmizaon 3 = O Opmizaon 4 = CF Constraint Frustraon 5= CF Constraint Frustraon bound 6 = Cs Connecvity segregaon 7= Ci Connecvity integraon 8= Hbu Hierarchical boom-up 9 = Htd Hierarchical top- down

Cluster 2= 80% others Personality disorders Anxiety 2

0 1

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9

Fig. 3. Clustering of data into two groups.

of papers with relevant combinations of keywords would reflect findings linking evidence for those relevant keywords. For example, a large number of publications resulting from a search of ‘‘plasticity’’ and ‘‘depression’’ compared to ‘‘plasticity’’ and ‘‘schizophrenia’’ would indicate that in the literature mechanisms of plasticity are associated more with depression than with schizophrenia, thus pointing to more relevance of plasticity in depression than in schizophrenia. One major postulation predicted by the CBP theory is that schizophrenia-spectrum disorders are related to findings of disturbed connectivity within brain neural network while depression (mood disorders) are more relevant to brain plasticity dynamics and the Bayesian brain. A literacy search was conducted in this respect. Fig. 4 shows the results of numbers of publications resulting from different combination of searches. It is evident that combined search of keywords ‘‘connectivity’’ and ‘‘schizophrenia’’ yielded 1000 publications in comparison to a search of the keywords ‘‘connectivity’’ and ‘‘depression’’ that have yielded only about half, 615 publications. On the other hand when keywords ‘‘plasticity’’ and ‘‘schizophrenia’’ were searched only 1041 publications were found in comparison to 4784 for keywords ‘‘plasticity’’ and ‘‘depression,’’ more than fourfold the publications related plasticity to depression than to schizophrenia. As evident in Fig. 4 the cross over between schizophrenia and depression occurs when searching ‘‘connectivity disturbances’’ and ‘‘Bayesian’’ this indicates that more publications related connectivity disturbances to schizophrenia and more papers related Bayesian evaluations to depression. Assuming, as already mentioned, that publications typically inform about positive findings than the number of publications probably signifies positive relationships between these keyword concepts, indicating the relevant trend in the literature. In other words, if we use the literature search as an initial indicator for validation, than these results propose a preliminary validation for the general prediction of CBP that relates schizophrenia spectrum disorders to disturbances of neuronal network connectivity, while mood disorders are related to dynamics of plasticity and entropy parameters within the neuronal networks of the brain. Specific publications may increase the resolution of predicting validation of a CBP search of ‘‘connectivity schizophrenia review’’ yields 237 papers with the most recent by van den Heuvel and Fornito [22] who reviewed the explanatory finding about ‘‘brain disorders such as schizophrenia arising from abnormal brain network

wiring and dynamics’’ while most papers talk about connectivity alterations meaning mostly disconnections there are also papers mentioning over-connectivity in the disease [23,24]. Altered hierarchical organization has also been found to be disturbed. For example Zhang and colleagues [25] used imaging graph analysis in un-medicated first-episode schizophrenias patients and found that most of the regions that showed significantly decreased nodal parameters belonged to the top-down control systems. Sharma and colleagues [26] found that impaired cognitive control in schizophrenia might be driven by disrupted communication between the frontal and posterior brain areas, long-range connectivity being a more consistent deficit in schizophrenia as compared to locally evoked activity. This reflects altered hierarchy because frontal brain areas relate to higher-level processing thus consisting of higher hierarchical levels. Hampered plasticity and neuronal degeneration have been repeatedly found to correlate with depression [27–30]. A review by Masi and Brovedani [31] describes recent studies indicating that an impairment of synaptic plasticity (neurogenesis, axon branching, dendritogenesis and synaptogenesis) in specific areas of the CNS, particularly the hippocampus, may be a core factor in the pathophysiology of depression. Accordingly they proposed that new possible targets for the pharmacotherapy of depression could involve agents such as neurotrophic factors, their receptors and related intracellular signaling cascades; agents counteracting the effects of stress on hippocampal neurogenesis (including antagonists of corticosteroids, inflammatory cytokines and their receptors); and agents facilitating the activation of gene expression and increasing the transcription of neurotrophins in the brain. Similarly, according to Hayley and Litteljohn [32] the ‘‘next wave’’ of antidepressant treatments, whether used alone or in combination, is at least partially tied to their ability to modulate neuroplasticity. The CBP theory argues that plasticity alteration generates mood alteration by optimization and de-optimization dynamics that can be estimated by entropy and Bayesian measurements of neuronal networks spread in the brain. In the case of personality disorders the validity of the disturbed resting-state network can be divided into (1) relationships to psychoanalytic theory and (2) initial literature linking resting-state networks to personality and personality-related phenomena. As for relationships to psychoanalytic theory, in effect the internal map of representations has been well described for many years by ‘‘object relationship’’ psychologists

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PUBMED Search January 2014 2500

"4784 2000

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0 Adaptability

Brain Dynamics

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schizophrenia

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connecvity disturbances schizophrenia

depression

Fig. 4. Partial validation of CBP based on PUNMED publication search.

[33] who described the internal representations of others, such as parents, teachers friends as, ‘‘objects’’. In this case objects relate to memories and these are embedded in attractors. The individual also has a representation of himself in his brain that is composed of his experiences toward himself, and was termed ‘‘self-object’’ by object relationship psychologists. Thus one can see how even higher coding ‘‘maps’’ of social occurrences are represented in the brain as dynamic attractor formations in state-space. Object relationship theories have been useful in explaining why and how individuals experience, adapt and react to the psychosocial surrounding. These individual adaptation behavioral reactions have been related to personality styles, showing that internal representations shape our personality. Additionally Carl Rogers [34] described internal maps ‘‘organismic maps’’ as internal representations that determine the way we interpret experiences and react to psychosocial occurrences. These descriptions link internal representations and configurations to ‘‘personality’’ because personality is typically defined as the individual’s set of interpretations, experiences and reactions to psychosocial occurrences. Based on these insights the link between development of default mode network and the maturation of personality is created. The default mode network encodes internal representations as attractor configurations of state-space and these in turn determine and guide our psychosocial adaptation and psychological behavioral reactions, related to our experience-dependent individual style, i.e., personality traits. A direct prediction from these insights is that individuals suffering from personality disorders will demonstrate altered default

mode network development which will manifest as biased organization in terms of altered small-world network organization. Initial validation for such alterations is beginning to appear in the literature. Lei et al. [35] provide evidence for an association between individual differences in personality and scaling dynamics in the default mode network. Default mode network of rsfMRI in 20 healthy individuals was significantly associated with the extraversion score of the revised Eysenck Personality Questionnaire. Specifically, longer memory in default mode network corresponded to lower extraversion. Wei et al. explored brain disturbances underlying extraversion and neuroticism in 87 healthy individuals using fractional amplitude of low-frequency fluctuations on resting-state functional magnetic resonance imaging, they showed a positive correlation between low-frequency fluctuations amplitude at Slow-5 waves and extraversion in medial prefrontal cortex and precuneus, (important portions of the default mode network), thus suggesting a link between default network activity and personality traits. Overall, these findings suggest the important relationships between personality and low-frequency fluctuations. Amplitude dynamics depend on specific frequency bands. Patients with borderline personality disorder demonstrate an increase in functional connectivity in the left frontopolar cortex and the left insula, whereas decreased connectivity was found in the left cuneus. Within a network comprising predominantly right lateral prefrontal and bilateral parietal regions, patients with borderline personality disorder showed decreased connectivity of the left inferior parietal lobule and the right middle temporal cortex compared with healthy controls. Correlations between

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functional connectivity of the frontopolar cortex and measures of impulsivity as well as between connectivity of the insula/cuneus and dissociation tension were found. These data suggest that abnormal functional connectivity of temporally coherent restingstate networks may underlie certain symptom clusters in patients with borderline personality disorder. Tang et al. [36] designed an exploratory data-driven classifier based on machine learning to investigate changes in functional connectivity in the brains of patients with antisocial personality disorder. They used resting state functional magnetic resonance imaging (fMRI) data for 32 subjects with antisocial personality disorder and 35 controls. The results showed that the classifier achieved satisfactory performance (86.57% accuracy, 77.14% sensitivity and 96.88% specificity) and could extract stable information regarding functional connectivity that could be used to discriminate antisocial personality disorder individuals from normal controls. More important, they found that the greatest change in the antisocial personality disorder subjects was uncoupling between the default mode network and the attention network. A voxelbased morphometry analysis showed that the gray matter volumes in the parietal lobule and white matter volumes in the precuneus were abnormal in antisocial personality disorder compared to controls. In summary, this study used resting-state fMRI to identify abnormal functional connectivity in antisocial personality disorder patients. The authors suggest that their analysis can be used to improve the diagnosis of antisocial personality disorder, and elucidate the pathological mechanism of antisocial personality disorder from a resting-state functional integration viewpoint. Servaas et al. [37] showed that individuals scoring higher on neuroticism showed altered functional connectivity between the clustered seed regions and brain areas involved in the appraisal, expression and regulation of negative emotions. The seed-based functional connectivity method and subsequent clustering were used to analyze the resting state data, thus linking personality traits such as being more self-critical and overly sensitive to criticism by others. To summarize this section, it can be concluded, that the emerging literature of the past and recent years consistently conforms to the CBP conceptualizations promising an initial potential for a general-literature validation, one that can be sufficient to begin a detailed comprehensive research program, to fully validate CBP in a focused manner as explained in the next section. Future directions and implications ‘‘Personalized medicine’’ is an important trend in modern medicine, CBP is personalized because it is constructed from the personal clinical profile of the specific patient, however it is also classifiable phenomenologically allowing it to become relevant to knowledge about treatments and readily available for research. We show that in addition to being a personalized diagnosis, CBP has the chance to become a reliable diagnostic approach thus becoming ‘‘as good as’’ the DSM-like approach. However, the CBP format has the advantage of being readily available for a neuroscientific validation. This is in accord with Nick Craddock’s recommendations for a system that ‘‘better reflects the underlying functions and dysfunctions of the brain and that, hence, maps more readily the experiences of patients’’ [1]. CBP strives to bridge the current descriptive diagnosis with future neuroscientific diagnosis, believing that science advances in evolution rather than revolution, i.e., building the future diagnostic system without discarding the current one, but rather building on it. This is why the CBP entries are formulated based on the currently in-use, mental status, signs, symptoms and history. Obviously, the critical future of CBP lays in the challenge of validation (or refutation). Validity of CBP will be obtained simply by following

463

Table 4 Signal processing needed to validate CBP. Brain signal processing DMN Cs

Ci Hbu

Htd D O CF CFb

Age-related changes of all of the below (especially to normal controls) Correlations, synchrony, granger causality mutual information, dimension estimation Bayesian statistics dynamic causal modeling independent components analysis, neural complexity (correlation matrix) graph assessment of overall small wordiness ‘‘ Estimating hierarchy with hub composition K-shell decomposition, fractal geometry estimations, integrated information theory estimations ‘‘ Whole brain matching complexity, estimations. Free energy estimations. Entropy measurements ‘‘ ‘‘ ‘‘

the testable predictions. Such a study will inevitably require large data, from multiple centers, and will require extensive collaboration of many imaging labs synchronized in their assessment methodologies. Results of all signal processing methods will be classified into indicators of CBP predictions, for example for the signal processing methods such as correlation analysis and sensitive to connectivity dynamics that could indicate disconnection or over-connection in the brain. Those signal processing methods sensitive to dynamics of entropy alterations can become indicative to optimization dynamics, and so on. Table 4 proposes possible classification for signal processing methods relevant for validating specific CBP predations. Validation of CBP will offer a brain-related pathophysiological psychiatric diagnosis, ridding psychiatry of the current descriptive diagnostic system, thus adjoining psychiatry to the medical community of pathophysiological diagnosis. Validation of CBP paves the way to cure mental disorders by offering the blue-print, or road-map, for new therapeutic interventions in the brain. Currently multiple neuromodulation technologies are being developed and tested. Deep Brain Stimulation technology is already in use for severe Parkinson disease, and tested for depression [38]. Transcranial Magnetic (TMS) and Direct Current (tDCS), and Alternating Current Stimulations (tACS) are noninvasive methods being tested [39]. Optogentic is another promising technology [40] able to selectively and precisely control neuronal activations. Focused Ultrasound technology is also developing to intervene precisely in neuronal tissue [41]. Any neuromodulator technology will eventually require the knowledge about the disease-specific disturbance in order to try and correct it. Such knowledge will require specific to the resolution of sub-millimeter in space and millisecond in time in addition to the multiple parallel and time-related synchronizations, or other divergent, complicated stimulus-algorithms that shall be required to rebalance neuronal networks and re-optimize brain functions, for eliminating symptoms and deficiencies of mental disorders. Thus, with these upcoming novel brain-stimulating technologies. It is hard to envision progress in psychiatry without a validation of a CBP-like system or a similar research track, prior to designing interventions [42]. This said, it is important to emphasize that the CBP conceptualization is a preliminary starting point, a pointer of direction, rather than an advanced or finite schema. As such it has a heuristic value for future research in the field of neuroscientific psychiatry.

Conflict of interest No conflict of interest of any sort commercial or other is declared.

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