According to the current version of the international classification of diseases (ICD-10, Version 2007) schizophrenic disorders are characterised by „distortions of thinking and perception, and affects that are inappropriate or blunted. Clear consciousness and intellectual capacity are usually maintained although certain cognitive deficits may evolve over the course of time. The most important psychopathological phenomena include thought echo; though insertion or withdrawal; thought broadcasting; delusional perception and delusions of control; influence or passivity; hallucinatory voices or discussing the patient in the third person; thought disorders and negative symptoms.“
There are three main clusters of symptoms in schizophrenia: cognitive, negative and positive. Cognitive symptoms include poor attention, working-memory deficits and a deficit in planning and completing tasks (Liddle, 1987; Green, 1996; Mueser and McGurk, 2004; Rolls et al., 2008). Negative symptoms include apathy, lack of emotion, motor retardation, lack of motivation, blunted affect and passive behavior (Liddle, 1987;
Mueser and McGurk, 2004). Positive symptoms of schizophrenia include disordered thoughts and speech, hallucinations and delusions (Liddle, 1987; Mueser and McGurk, 2004). Schizophrenic disorders are heterogeneous and can thus be sub-divided into different forms of schizophrenia, paranoid schizophrenia being the most common diagnosis in Europe (Tateyama, M. et al., 1999). Paranoid schizophrenia is dominated by relatively stable, often paranoid delusions, usually accompanied by hallucinations, particularly auditory, and perceptual disturbances. Disturbances of affect, volition, speech and catatonic symptoms are either absent or relatively inconspicuous.
The prevalence of schizophrenic disorders is estimated to be 1% (Jablensky , 1997). The first symptoms of schizophrenia typically appear between the ages of 16 and 30 years, and infrequently after the age of 45 years (Almeida et al., 1995). Usually the symptoms accompany schizophrenia patients their entire life, although many patients experience remissions of symptoms later in life (Häfner et al., 2003b).
Genetic and environmental factors are known to play a role in the aetiology of schizophrenia. The probability of developing schizophrenia among relatives of patients is higher than in people without any relatives having the disorder (McGuffin et al.,
16 1995). The risk of developing schizophrenia is especially high for people with schizophrenic parents and for those having a monozygotic twin with schizophrenia (Cardno et al., 1999).
Besides the genetic factors mentioned above some environmental factors might also increase the risk of developing schizophrenia. Prenatal events like maternal influenza, rubella, malnutrition, diabetes mellitus, and smoking during pregnancy have been shown to have some influence on the frequency of occurrence of the disorder (Susser and Lin, 1992; Takei et al. 1996; Thomas et al., 2001).
Regarding the neuropathology two main facts characterize schizophrenia:
ventricular enlargement (Wright et al., 2000) and decreased cortical volume (Andreasen et al., 1994; Powchik et al., 1998). Brain structures like the frontal lobes, amygdala, hippocampus, parahippocampus, thalamus and medial temporal lobe, cingulate gyrus, and superior temporal gyrus have decreased volumes in patients with schizophrenia compared with controls (Wright et al., 2000; Byne et al., 2002; Lawrie and Abukmeil, 1998, Narr et al., 2000).
Schizophrenia is characterised by alterations in brain structure and functionality.
It has been shown that certain brain regions of patients with schizophrenia tend to be less asymmetric compared to control participants (Petty, 1999). For example, Planum temporale (PT) asymmetry reversal has been reported in schizophrenia patients (Rossi et al., 1992, 1994; Petty et al., 1995; Barta et al., 1997; Hirayasu et al., 2000; Kasai et al., 2003). In addition to structural alterations, schizophrenic patients have been shown to have difficulties with a wide range of cognitive tasks: short-term and long-term memory (Aleman et al., 1999), maintaining attention and initiating action (Cornblatt and Kellp, 1994), or decision making (Shurman et al., 2005). However, it is still not clear, whether functional abnormalities are the consequence or the cause of structural abnormalities.
A lot of electroencephalographic (EEG) and magnetoencephalographic (MEG) research has focused on investigating auditory mechanisms and their disturbance in schizophrenia. The three most popular and most stable functional measures of an auditory perception impairment in schizophrenia are the mismatch negativity (MMN) (Näätänen, 1978), the auditory sensory gating ratio (SGR) derived from the P50 double-click paradigm (Adler and colleges, 1982) and brain response variability (also called
“cortical noise” (Winterer and colleagues, 2000) or variability index (VI)). A reduced MMN is believed to be evidence for deficits in automatic auditory sensory processing,
17 pre-attentive auditory perception and discrimination (Pekkonen et al., 2002; Näätänen and Kähkönen, 2009; Magno et al., 2008; Turetsky and Moberg, 2009), or decreased recruitment of brain areas during task performance (Bates et al., 2009). Impaired sensory gating (i.e. a high SGR) is generally considered to be a neurophysiological marker of an attention impairment (Thoma et al., 2004). Clinical studies of the M50 component (the MEG equivalence to P50) have shown that sensory gating predicts performance on neuropsychological tests of attention, working memory, general memory, and executive function in schizophrenia. Right-hemispheric SGR is correlated with severity of negative symptoms in schizophrenia (Thoma et al., 2005), whereas left-hemispheric SGR is related to positive symptoms (Irwin et al., 2003). An increased VI is related to an increased amount of slow wave activity, impairment of phase locking during stimulus processing and deficient bilateral temporal lobe coherence in schizophrenia patients (Winterer et al., 1999; 2000; 2004). It is found to negatively correlate with working memory scores (Winterer et al., 2004) and reaction time (Winterer et al., 2000). Various experimental and computational observations of cortical actions of dopamine have supported the notion that diminished mesocortical dopamine signaling and the resulting increased response variability of prefrontal neurons might be involved in cognitive and behavioral deficits in schizophrenia (Weinberger, 1987;
Weinberger et al., 1988; Goldman-Rakic, 1994; Goldman-Rakic et al., 2000).
The treatment of schizophrenia can be divided into pharmacological and psychosocial treatment. Antipsychotics are mainly used for the reduction of psychotic symptoms and prevention of relapses (Kane and Marder, 1993) though having more modest effects on negative symptoms and cognitive impairment (Greden and Tandon, 1991). Psychosocial intervention aims to enhance functioning in areas such as independent living, relationships, and work.
Recently, new alternative strategies for treatment of schizophrenia have been developed. With the growth of the computer industry, computer programs for training the perception in schizophrenia have become available. For example the Cognitive Exercise (CE) package (PositScience, San Francisco, USA) aims to enhance discrimination ability in the auditory system. It is an adaptive training involving different auditory tasks. One task involves listening to pairs of two frequency-modulated tones that can either sweep upwards or downwards. It is then required to reproduce the order of the two sound-sweeps (up-up, up-down, down-up, down-down). Another task
18 involves listening to syllable pairs and judging, which syllable was played first. Other tasks involve identifying arrays of open and closed syllables in spatial and sequential context, discriminating tone frequencies, and remembering details of a short narrative.
The training is adaptive in that it varies task difficulty with the performance of the patient. Increase of difficulty level is achieved by shortening the frequency-modulation period of the tones or the formant transition period of the syllables. The inter-stimulus-interval between the tones and the syllables also becomes shortened with increasing task performance. If the patient makes a mistake, the tasks become easier accordingly.
The CE training has been shown to improve verbal memory (Fisher et al., 2009a; 2009b) and to normalize the M100 “attenuation’’ that represents the normal suppression of neural activity associated with second syllable presentation due to ongoing first syllable processing (Adcock et al., 2009). Another training which is used in schizophrenia treatment (despite not exclusively aiming at schizophrenia as the sole disorder) is the Cogpack (CP) training package (Marker Software). In contrast to the CE training, it not only targets the auditory modality, but involves 64 exercises of visuomotor skills (manipulate, follow or mark a moving figure with the computer mouse; divide lines or pies; reproduce or mirror a drawing; catch a bouncing ball), vigilance (scanning, catch falling star, continuous performance), comprehension (character recognition), language (word finding upon clues, text-content, authors or titles of quoted poems, place words or syllables in order, anagrams), memory (words, images and labels, patterns, signs, addresses, routes, life scenes), logic (mental arithmetic, geometry, numbers and number words, quantities, simple and deductive comparisons, block or series completion), everyday skills (times and dates, compass, geography, money, weights and measures, road signs, license plates, abbreviations; Olbrich, 1998; Geibel-Jakobs et al., 1998;
Sartory et al., 2006).
This new way of treating schizophrenia patients may also be considered as another sub-group of the psychosocial treatment methods. This is because computer trainings are often used in combination with role playing and discussion of the program results with therapists. It is likely that a computer-based training alone is not enough to cure schizophrenic symptoms. Rather, only a combination of different treatment methods will result in substantial improvement in schizophrenia patients. However, in order to get an impression of the effectiveness of a computer training it needs to be evaluated when applied separately.
19 There are already several studies reporting computer-training effects using clinical and behavioural measures as dependent variables (Twamley et al. 2003) but there are almost no studies investigating the effects of computer trainings using functional brain imaging techniques like MEG or EEG.
In order to investigate, whether a training or therapy has an effect on brain activity, several things need to be considered. For example, a training-program can change the function of a cortical structure, i.e. it can improve its activity, without changing the morphological characteristics of that structure. Alternatively it might cause brain structural changes and consequently also changes in the functionality of these brain structures. Thus, in order to clarify which effect a training program has on the brain, both the structure and the function of a cortical area need to be considered.
Another challenge for uncovering training effects on cortical measures is noise in MEG/EEG data. This can be caused by various sources. In the case of MEG, participants rest their head in the MEG-sensor, where there is the chance that the position of the head changes slightly throughout the experiment. Additionally every test person lies in a slightly different way in the MEG sensor compared to another subject. The different position of the head in the MEG-sensor can be determined and corrected with the help of the digitized fiducial points and the digitized head shape. Nevertheless, the variability caused by head movement during the measurement is not possible to be corrected because there is no possibility to detect every movement of the test subject during the measurement.
There are also other sources of variability during an MEG measurement – the influence of external non-physiological magnetic sources like the Earth’s magnetic field, magnetic fields caused by electric devices, train vibrations, car engine disturbance etc.
Other physiological but not brain-related magnetic fields like eye-blinks, muscle contractions, heart beat etc. can contribute to greater signal variability in the MEG data as well. Even after elimination of the variability sources not originating from the brain there still remains a great amount of variability due to inter-individual differences in the brain structure and functionality. The brain of every individual person is unique. This is an obstacle for uncovering potential training effects, as the same cortical area might be located at slightly different regions, might be oriented in a different way, or might differ in size between different people. Apart from inter-personal variability, there is also variability within one person. For example, the brain does not always respond in exactly
20 the same way at exactly the same time to identical stimuli. The cortical reaction might vary in magnitude and may also jitter in time after a stimulus. Patterson and colleges (2000) manifested that the schizophrenia patients have significantly more intra-individual temporal variability than normal controls in the P50 peak which contributes to the SGR differences between both groups. These could imply that the SGR depends on the VI which is measure of the signal variability (both – latency and magnitude variability). It is not clear, whether the same applies for the MMN as well, i.e. it is not clear, whether a reduced MMN in schizophrenia is a consequence of higher VI or a stand-alone effect. It is very important to clarify this, as a reduced MMN as the consequence of a higher VI would mean that the automatic signalling of changes in the acoustic stream is not necessarily deficient but the result of less orchestrated neural firing.
The present thesis aimed to (1) identify, whether functional differences between people with and without schizophrenia can be attributed to (i) anatomical differences or (ii) increased cortical noise; (2) investigate, whether cortical correlates of schizophrenia can be altered by training.
The first study (p. 10, Jordanov et al., 2010) of the present thesis tried to determine, whether the typically reported asymmetric localisation of the primary auditory sources (Heim et al., 2004; Teale et al., 2003) is the result of a reduced anatomical asymmetry, or whether auditory processing takes place in a different cortical region. If the latter were the case, it would mean that schizophrenia is not only characterised by structural cortical differences but that cortical processing is organised in a different way than in healthy control participants. It was then investigated, whether training could change the localisation of the M50 (p. 40, Jordanov et al., Posterpresentation, SPR, 2010). The training procedure will be described below.
The second study of the present thesis (p. 24, Jordanov et al., in press) investigated, whether the reduced MMNm in schizophrenia is related to an increased variability of brain activity. For this purpose, MMNm and VI were compared between patients with and without schizophrenia. VI was determined during auditory processing and during resting state in different frequency bands. If MMNm amplitude was related to increased VI in schizophrenia it might imply that the disturbed automatic auditory processing is a result of less orchestrated neural firing.
The third study (p. 40, Jordanov et al., Posterpresentation, SPR, 2010) looked for dependencies between the dipole parameters of an auditory M50 response model (e.g.
21 localization, orientation and latency) in a paired-click paradigm and the symptomatic and functional characteristics in schizophrenia. Additionally, the chosen dipole parameters were investigated for training-induced changes after four weeks computer-based cognitive training.
The fourth study (p. 51) investigated, whether VI can be influenced by the CE and CP training programs. Matching the subjectively described effort of the training (based on a pilot trial) rather than the total training time, the more game-like CE-training comprised 60-min sessions on 20 consecutive workdays (4 weeks), whereas Cogpack-training followed the standard instructions of three 60-min sessions per week over 4 weeks yielding in approximately similar absolute training hours. Given that the CE training focuses more specifically on auditory processing, it is expected that it has a greater effect on the localization of the auditory M50 and the VI in auditory areas than the CP training, which trains more wide-spread cognitive skills.
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