Related
references in English language, see at the end of this page
"Complex
Mental Processing and Psychophysiology"
University
of Bremen
Academic
Unit 11
(Fachbereich
11)
Human-
and Health Sciences
(Human- und Gesundheitswissenschaften)
Habilitation
Thesis
(Habilitationsschrift)
Fehr, T. (2007): The Schrift is in
preparation to be published as a book
Referees of
the present Schrift:
Prof. Dr.
Dr. Herrmann, University of Bremen, Germany
Prof. Dr.
Erol Basar, University of Istanbul, Turkey
Prof. Dr.
Dr. Onur Gόntόrkόn, University of Bochum, Germany
Introduction
In psychophysiology it is not only a scientific challenge to circumscribe psychological terms and concepts, but also to define, which physiological parameters and methods may allow adequate approaches and significant insights into the investigated topic. This especially applies to research questions on complex mental processing, which is the main scope of this issue. During the last century, different methodological approaches addressing psychophysiological research questions have been improved dramatically. Research applying biosignalanalysis on data obtained from human brain electrical activity, as prominently represented by electroencephalography (EEG) and magnetoencephalography (MEG), has produced various strategies and analyses procedures in spatial and temporal domains. Despite the long tradition and consensus in many research fields involving biosignalanalysis, there is still a broad variety of opinions in many sub-domains on what has to be considered as adequate parameters and as state of the art analysis procedures.
Particularly in
functional brain imaging, there is only a sparse basis of agreement on how and
which parameters should be obtained and examined. In this field, statements on
the so-called state of the art can change every year. This seems not only to be
caused by a certain lack in tradition to follow a consecutive line of research
in the examination of specific topics, as present in the EEG research
community. Many scientists find themselves involved with many completely
different research topics that are often and inevitably treated in a relatively
superficial way. To some extent this might be due to the complex nature and a putatively extensive neural cross-linking
between the mental processes examined. Hypotheses inferred are often
based on insufficient previous knowledge
provided by former studies. E.g., in many imaging studies completely new
experimental designs have been applied, without appropriately tying up to procedures established by former studies
addressing similar research questions. Since, even minor changes in
experimental set-ups can produce remarkable output differences, most studies
are not directly comparable. Thus, identical or similar scientific questions
have often been examined and compared across studies using incomparable
experimental and/or statistical designs, which inevitably produced inconsistent
results. Applying so-called regions of interest analyses is an attempt to
handle incompatibility problems between studies and/or reduce an unmanageable
amount of data, which, however, risks a dramatic over-simplification of complex
research questions and potentially ignores putative complexities in psychophysiological
data.
Trying to bridge the gap
between psychological, neuro-scientific questions and different methodological
problems and approaches, the author of the present issue investigates different
domains of complex cognition using and comparing various methods and analysis
procedures. The presented empirical data and theoretical discussions address
several themes with respect to inherent methodological problems. Specifically,
different strategies of data analysis applied on psychophysiological data, obtained
during complex mental processing, such as mental calculation (chapter 1-2),
exceptional mental performance in savants or experts (chapter 3), addiction
memory (chapter 4) and complex social cognition (chapter 5), are described and
discussed in an integrative way. Data were obtained during different studies
using functional magnetic resonance imaging (fMRI), EEG and MEG.
Summary
Whereas, it
is, of course, not possible to include all critical aspects concerning
the analyses of neuronal correlates related to complex mental processing in one
single issue, the author especially emphasises topics such as inter-study-comparability and
inter-individuality of brain physiological parameters, functional modularity of
brain regions and other, partially method-inherent, problems of the respective
data analyses. Possible solutions to solve the mentioned problems are suggested
and extensively discussed.
The first chapter
is dedicated to fMRI studies addressing several questions related to complex
mental processing examined by the example of mental calculation or mental
arithmetic. After an introduction to the topic, the author discusses possible
misunderstandings between theoretical aspects of modularism and their impact on
cognitive neurosciences. An alternative to the assumption of massive modular
organisation of the neural architecture of complex mental processing is
introduced and discussed. The presented empirical data suggest that different
arithmetic operations are neurally processed in predominantly distinct neural
networks. Furthermore, different presentation modalities of arithmetic tasks
appear to trigger different neural networks during mental calculation
processing. Several regions, e.g., in middle and/or medial frontal and
intra-parietal areas will be shown to be activated across individuals,
arithmetic operations, and task presentation modalities. Most other regions
appear to be differentially involved in the processing of different arithmetic
operations triggered by different task presentation modalities. The author
proposes a model for complex mental calculation, which assumes particular
regions to be involved from the start of initial arithmetic learning history.
These regions, from which more and more inter-individual different neural
network parts, distributed across multi-modal association cortices, become
integrated during individual learning history, represent rudimentary forms of
magnitude representation (intra-parietal) and working memory capacity
(fronto-lateral and medial frontal). Following these model assumptions, it is
concluded that complex mental arithmetic neither follows the notions of massive
modularism nor pure holistic rules. It seems that complex mental arithmetic is
represented by a combination of both. These ideas are
further supported by functional imaging data showing similar and/or adjacent
distributed activation patterns in a mental calculation prodigy when compared
to a control group of normal calculators calculating usual tasks.
Interestingly, the calculation prodigy also produces similar activation
patterns for exceptionally difficult arithmetic tasks. Thus, exceptional
calculation performance seems not to be a miracle, but rather follow the rules
of regional neural plastic changes of usually recruited neural resources due to
excessive training.
A further topic
addressed in chapter one is the question, whether different baseline conditions
for contrasting procedures in fMRI analyses may differently influence results.
It is concluded that the involvement of different baseline conditions in
contrasting procedures reveal remarkably different activation patterns, which
limits the comparability of different studies dramatically. Therefore, in
relation to many research questions in cognitive neuroscience, a pre-scientific
state must be assumed, since numerous studies involved in hypothesising must be
assumed to be incomparable to each other. The author suggests two strategies to
solve this problem: (1) Studies should better tie up to experimental designs
developed in former studies, and/or (2) new scientific questions should be
preceded by a complete pilot study, sufficiently exploring the data, from which
conclusions can be drawn for appropriate hypothesising and for an independent
follow-up study (preferably performed in double-blind manner). This would
provide first steps towards real science according to the notions of classical
test theory.
In the second chapter,
the processing dynamics of the regional activations, revealed from the studies
described in chapter one, are examined by a combined fMRI and MEG study.
Putative partial inconsistencies between the methods are identified and
discussed. It is concluded, that if both methods would identify task related
brain activation foci at similar locations, then signal amplitudes revealed by
means of biosignalanalyses must not necessarily be related to statistical
parameters, as revealed by BOLD fMRI contrasting procedures, but rather to
oscillatory communication codes of the respective regions and neural networks.
Intra-individual inter-trial variations in time locked source space activities,
and inter-individual inter-trial variations in the processing of complex
cognitive tasks are discussed to be a crucial source of invalidity in time
locked data analysis strategies. The more complex a processes appears, the more
variation might be caused by changing processing order of the involved mental
sub-components from trial to trial. Thus, the author suggests a non-time-locked
methodological approach for an appropriate identification of spatio-temporal
attractors, potentially reflecting neural correlates of cognitive
sub-components participating in the respective complex mental process, namely
irrespective of their processing order in single trials.
Exceptional mental
skills and their neural organisation are assumed to provide deeper insights
into the neural architecture of complex mental processing. In the third
chapter, the author presents three fMRI studies addressing exceptional
calendar performance (date-weekday matching in two experts), a repeated
examination of exceptional mental calculation performance in the mental
calculation prodigy already mentioned above, and expert backward speaking
performance in the same study participant. Imaging results suggest that brain
activation patterns in relation to a particular complex mental domain
(date-weekday matching) can vary almost completely between different experts,
despite comparable performance. This is explained by the different cognitive
strategies used by the two calendar experts. Furthermore, the neural
architecture of even well trained cognitive skills is shown to change
dramatically over time. This is explained by the integration of new cognitive
elements caused by contextual demands, and a partial reorganisation (shift) of
the involvement of originally recruited brain regions to adjacent areas. During
expert backward speaking, an additional skill of the above-mentioned mental
calculation prodigy, predominantly parietal activation patterns are produced.
Interestingly, the mental calculation prodigy shows a remarkable overlap of
superior parietal activation patterns for different tasks concerning
qualitatively different mental domains (e.g., calculation, calendar
performance, backward speaking). This, in combination with the conclusion about
differential cognitive strategy related neural network recruitment, lead to the
assumption that the neural architecture of complex mental processing might
rather be related to individual cognitive style (spatial, verbal, visual, etc)
than to fixed modular functional neuroanatomic organisation.
In the fourth chapter,
the author discusses the impact of emotion on cognition illustrated by the
example of addiction memory. The presented results show group-related
differences in the neural processing of drug-cue related stimuli in smokers
compared to non-smokers apparent in two different stimulus domains (words and
pictures). This leads to the conclusion of a certain generalisation of the
addiction memory concept in smokers. The impact of drug cue induced, emotionally
driven activation of addiction memory related perception-action cycles are
discussed in relation to sudden relapse into addiction after years of
abstinence. The author proposes a model of human addiction development
considering common brain physiological development aspects, personality traits
and individual learning history. Following the notions of the proposed model,
it is empathically suggested to start smoking, if at all, earliest after the
third life decade.
The last chapter
of the present issue is dedicated to complex social cognitions. Continuous MEG
data were obtained during mental contrasting of pros and cons related to an
individually relevant career decision and mental indulging in potentially
positive outcomes of the respective decision. These data are compared to a
resting condition. Classic approaches in analysing the continuous task related
multi-channel MEG data are shown to fail to discriminate between the
conditions. The author applies a newly developed strategy, including
multi-source modelling on bandpass filtered data. Filtering is based on
differences in individual task-related power spectra. The applied method is
shown to reveal a regional discrimination of the tasks. Thus, combining the
data and discussions of the present issue, the author concludes that the neural
architecture of complex mental processing might rather be represented by
inter-individual differently distributed neural networks, communicating by
inter-individually different compositions of oscillatory codes, than by small
portions of more or less hard-wired neural tissue, as massive modularism would
predict. Modular neural architecture in the latter mentioned sense, however, is
suggested to be present in primary sensory and motor processing, and possibly
in other regions providing a certain starting point of the development of
higher cognition networks, but not in differentiated complex mental processing.
Moreover, regional distribution of recruited neural networks and respective
oscillatory communication codes related to complex mental processing, are
discussed to potentially vary across individual learning history and brain
development.
Summarising, the author emphasises the
importance to include more secondary information obtained from participating
individuals in studies addressing complex cognitions, such as learning history,
processing strategies, emotional valence of tasks, etc, in order to get a
better basis for data interpretation. Additionally, inter-individual
differences should be considered at physiological level by the applied methods.
Index
of contents
|
1. Complex mental processing - Mental
calculation and neuroimaging
...
|
1 |
|||
|
|
1.1. Models of mental calculation and
modularity - A short introduction
.
...
.. |
1 |
||
|
|
|
Number notation of simple and bigger numbers
.
..
|
2 |
|
|
|
|
What is mental calculation?
.
..
... |
3 |
|
|
|
|
Subitizing
.
..
|
6 |
|
|
|
|
Different models related to
mental number processing
.
..
. |
6 |
|
|
|
|
Modularity and complex mental processing
.
..
.. |
10 |
|
|
|
|
Is
there a misunderstanding in the concept of functional neuroanatomic
modularity?
.
..
|
14 |
|
|
|
|
Complex neural network dynamics - An alternative to massive modularity
hypothesis
.
..... |
18 |
|
|
|
|
Do number processing models fit
the criteria for modularity?
..
..
. |
23 |
|
|
|
|
Examining mental calculation
..
..
... |
24 |
|
|
|
1.2. Mental processing of different
arithmetic operations
.
..
... |
25 |
||
|
|
|
Summary
..
..
|
25 |
|
|
|
|
1.2.1.
Mental calculation and the brain - Implications from neuromaging studies
....
.. |
26 |
|
|
|
|
|
A neurocognitive model of mental
calculation
..
..
. |
27 |
|
|
|
|
Neurophysiological correlates of complex
mental processing
....
. |
27 |
|
|
|
|
Which brain activation patterns are expected during complex in
contrast to simple mental arithmetic?
..... |
28 |
|
|
|
1.2.2. A study design for the examination of neural correlates due to
different mental arithmetic
operations - Methods and results
...
..... |
29 |
|
|
|
|
|
Participants
..
...
.. |
29 |
|
|
|
|
Task design
...
..... |
30 |
|
|
|
|
FMRI/MRI-data acquisition and
analyses
...
..
... |
31 |
|
|
|
|
Behavioural data
...
..
.. |
33 |
|
|
|
|
FMRI data results: Complex vs.
simple calculation tasks
....
|
34 |
|
|
|
|
FMRI data results: Complex calculation vs. number recognition tasks
... |
36 |
|
|
|
|
FMRI data results: Simple calculation
vs. number recognition tasks ...
... |
38 |
|
|
|
|
FMRI data results: number
recognition vs. simple calculation tasks ...
... |
39 |
|
|
|
|
Laterality of BOLD-fMRI
activation foci
..
|
41 |
|
|
|
1.2.3.
Different mental arithmetic operations appear to be processed in predominantly distinct neural networks
|
42 |
|
|
|
|
|
|
|
|
|
|
|
Is a direct comparison of data reported in different studies
addressing mental arithmetic warrantable?
... |
43 |
|
|
|
|
Are brain regions involved in mental
arithmetic of exclusive modular nature? .. |
45 |
|
|
|
|
Differential involvement of
parietal cortex in mental arithmetic
. |
46 |
|
|
|
|
The motor system and mental
arithmetic
.. |
47 |
|
|
|
|
Simple mental calculation: The
real baseline for complex mental calculation? .. |
49 |
|
|
|
|
Conclusive remarks
... |
51 |
|
|
1.3. Presentation modality and neural
recruitment during arithmetic task processing ... |
53 |
||
|
|
|
Summary
|
53 |
|
|
|
|
1.3.1.
Task presentation form and environmental factors potentially modulate
complex mental processing
. |
53 |
|
|
|
|
|
Summary
... |
53 |
|
|
|
1.3.2. A study design for the examination of neural correlates of
auditory presented mental arithmetic tasks - Methods and results
|
55 |
|
|
|
|
|
Participants
... |
55 |
|
|
|
|
Task design
|
55 |
|
|
|
|
FMRI/MRI-data acquisition and
analyses
|
55 |
|
|
|
|
Behavioural data
... |
56 |
|
|
|
|
FMRI data results: Complex vs.
simple calculation tasks
|
57 |
|
|
|
|
FMRI data results: Complex
calculation tasks vs. number recognition
... |
59 |
|
|
|
|
FMRI data results: Simple
calculation tasks vs. number recognition
.. |
60 |
|
|
|
|
FMRI data results: Number
recognition vs. simple calculation tasks
.. |
62 |
|
|
|
|
Laterality of BOLD-fMRI
activation foci
.. |
64 |
|
|
|
|
The direct comparison of response time data obtained during visually
(see chapter 1.2.2) and auditory (present chapter) presented tasks
|
65 |
|
|
|
|
FMRI data results: Conjunction analysis comprising all visually and
auditory complex versus simple addition, subtraction, multiplication and
division contrasts
|
65 |
|
|
|
1.3.3.
Modality matters - To see or to hear a task modulates the recruitment of
neural resources during task solution
.. |
66 |
|
|
|
|
|
Parallel processing and possible complex interactions between task
modality and mental processing?
|
66 |
|
|
|
|
Possible reasons for similarities and differences in task modality
related brain activation patterns during mental calculation
.. |
68 |
|
|
|
|
The putative necessity of the involvement of perisylvian regions in
mental arithmetic
.. |
70 |
|
|
|
|
|
|
|
|
|
|
Are there transcoding requirements for more efficient handling of
input information?
.. |
72 |
|
|
|
|
Similarities and differences between the BOLD activation patterns
related to visual and auditory induced mental calculation processing - A
complex topic ... |
74 |
|
|
|
|
Further aspects potentially modulate the processing of visually and/or
auditory presented complex tasks
|
78 |
|
|
|
|
Final conclusions
.. |
79 |
|
|
1.4. Neural correlates of exceptional performance in mental
calculation: Neural modularism and neural plasticity
.
|
79 |
||
|
|
|
Summary
|
79 |
|
|
|
|
1.4.1 Exceptional mental
abilities - Assumptions of their neural architecture
.. |
80 |
|
|
|
|
1.4.2 An
experimental design to compare single calculation prodigies with a
reference group of participants: Methods and results
.. |
81 |
|
|
|
|
|
Participants
.. |
81 |
|
|
|
|
Task and procedures
. |
81 |
|
|
|
|
FMRI data
acquisition
.. |
82 |
|
|
|
|
FMRI data analysis
... |
83 |
|
|
|
|
Behavioural data and personality scores
.. |
85 |
|
|
|
|
RG compared to control participants (imaging
data)
.. |
85 |
|
|
|
|
Exponentiation
compared to complex/simple calculation in RG (imaging data)
... |
85 |
|
|
|
1.4.3
Exceptional mental performance - A matter of practice and
neural plasticity?
... |
87 |
|
|
|
|
|
The
social costs of special mental abilities: A shift in individual social
architecture?
. |
87 |
|
|
|
|
Does transcoding help prodigies to perform at
high levels?
|
87 |
|
|
|
|
Models of mental calculation and
exceptional mental arithmetic performance .. |
88 |
|
|
|
|
Neural plasticity and excessive training
... |
89 |
|
|
|
|
Modularity and the nature of exceptional
performance in higher cognition
|
90 |
|
|
|
|
Exceptional calculation
performance - Subitizing at higher levels?
|
92 |
|
|
|
|
Acknowledgements
|
93 |
|
|
1.5. Additional analyses and comments
.. |
93 |
||
|
|
|
1.5.1.
Inter-individuality - Does everyone use the same brain regions during
calculation?
.. |
93 |
|
|
|
|
1.5.2.
What discriminates mental calculation from other complex mental
processes?
|
100 |
|
|
|
|
|
|
|
|
|
1.6. Synopsis - a model for complex mental
processing in the human brain
. |
103 |
||
|
|
|
Neuroanatomical model of mental calculation revisited
.. |
106 |
|
|
|
1.7. Acknowledgements .. |
109 |
||
|
|
1.8. References
|
109 |
||
|
|
|
|
|
|
|
2.
Spatio-temporal dynamics of complex mental processing - FMRI, MEG and mental
arithmetic
... |
121 |
|||
|
|
Summary . |
121 |
||
|
|
2.1. Biosignalanalysis and mental calculation
- a short introduction
. |
121 |
||
|
|
|
Biosignalanalysis and mental
arithmetic - A long tradition
. |
123 |
|
|
|
|
Oscillatory brain activity and mental arithmetic - From 3- to
4-dimensional approaches
|
123 |
|
|
|
|
ERPs and mental arithmetic
. |
125 |
|
|
|
|
Source analyses and regional
constraints revealed by means of fMRI
. |
127 |
|
|
|
|
The present study
... |
128 |
|
|
|
2.2. An experimental design for the examination of neural correlates
due to complex and simple mental arithmetic - Methods and results
... |
129 |
||
|
|
|
Study participants .. |
131 |
|
|
|
|
Task design
|
131 |
|
|
|
|
Behavioural data
... |
132 |
|
|
|
|
MEG, MRI and fMRI data acquisition
.. |
134 |
|
|
|
|
2.2.1 Task-related fast Fourier
transform (FFT)
... |
135 |
|
|
|
|
|
Applying task related fast Fourier transform (FFT) on multi-channel MEG data
.. |
135 |
|
|
|
|
FFT results: Complex vs. simple
calculation task processing and resting
... |
137 |
|
|
|
2.2.2. Appliance of a multiple source model based on fMRI activity
peaks - A classic approach including event-related MEG data
(mERP)
.
|
142 |
|
|
|
|
|
FMRI data analysis and results
|
143 |
|
|
|
|
Transformation of Talairach coordinates into individual head/brain dimensions
. |
144 |
|
|
|
|
Averaging of task related data
sweeps to produce mERPs for further analyses .. |
146 |
|
|
|
|
Appliance of individual adapted
source models on mERP data: results
.. |
149 |
|
|
|
|
Intermediate annotations and
conclusions for further procedures
... |
155 |
|
|
|
2.2.3. Application of a multiple source model based on regional fMRI
constraints - approach on single trial data based on band-pass
filtered data
. |
158 |
|
|
|
|
|
Applying source constraints on
FFT constrained data - methods
|
158 |
|
|
|
|
Applying source constraints on
FFT constrained data - results
... |
159 |
|
|
2.3. Spatio-temporal dynamics in complex mental processing - a major
challenge on methodology
... |
161 |
||
|
|
|
Magnetic event related responses
(mERP) and mental arithmetic
... |
161 |
|
|
|
|
Brain magnetic oscillatory
activity and mental arithmetic
... |
163 |
|
|
|
|
The visual inspection of source
moment wave forms of complex mental processes . |
164 |
|
|
|
|
Can we statistically identify what we cannot recognise by visual
exploration? Statistical analyses on mERP related source moment wave forms
... |
165 |
|
|
|
|
Single trial source analyses on
bandpass filtered task related data sweeps
. |
170 |
|
|
|
|
General discussion
|
172 |
|
|
|
|
Limitations of the present study
. |
174 |
|
|
|
2.4. The need of new
methodological innovations and future directions
... |
175 |
||
|
|
|
The main basis of good empirical
(neuro-)science - Annotation
.. |
182 |
|
|
|
2.5. Acknowledgements
.. |
182 |
||
|
|
2.6. References
|
182 |
||
|
|
|
|
|
|
|
3. Exceptional mental
performance - A savant and a prodigy savant
.. |
189 |
|||
|
|
Summary
. |
189 |
||
|
|
Technical note
. |
189 |
||
|
|
3.1. A
savant and a prodigy savant: Two strategies of weekday-date matching in a
calendar task
|
190 |
||
|
|
|
How to supply a weekday of a date
.
.. |
191 |
|
|
|
|
Where is exceptional calendar performance
localised in the brain?
.
... |
193 |
|
|
|
|
Experimental design and data analysis
.
|
193 |
|
|
|
|
Behavioural data: Results
. |
195 |
|
|
|
|
FMRI data: Results
... |
196 |
|
|
|
|
Two
qualitatively different strategies, and comparable exceptional mental
performance
.
.. |
198 |
|
|
|
|
Intuition, pre-attentiveness and visual representation might
facilitate exceptional skill
.
.
.
.
|
199 |
|
|
|
|
Algorithm and knowledge about calendrical structures might facilitate
exceptional skill
.
.
.
.
|
200 |
|
|
|
|
Same expert skills Different
strategy - Different brain activation patterns?
.
|
201 |
|
|
|
|
Is exceptional calendar calculation
localisable in the brain?
.
... |
202 |
|
|
|
|
Summary and conclusive remarks
.
|
203 |
|
|
|
|
|
Limitations of the present study
|
205 |
|
|
3.2
Exceptional mental calculation performance - Same applied strategy, but
different recruited neural resources?
. |
205 |
||
|
|
|
Experimental design and data analysis
. |
206 |
|
|
|
|
Behavioural data: Results
. |
208 |
|
|
|
|
FMRI data: Results
... |
208 |
|
|
|
|
What happened during
20 months expert training in RG΄s brain?
... |
215 |
|
|
|
|
Possible
reasons for extensive changes in brain activation patterns from one to the
next measurement
|
217 |
|
|
|
|
Could the results of the study published by Mauro Pesenti et al.
(2001) be replicated by the present examination?
. |
220 |
|
|
|
|
Baseline contrast is not baseline contrast
. |
220 |
|
|
|
|
An
intermediate annotation - Similarities of recruited neural networks and whole
brain work
. |
221 |
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Neural
plasticity, and de-activation and/or activation cannot be linked to mental
performance - A chance to abolish a putative paradox
|
221 |
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Change appears to be the only stable phenomenon, or, multiplication in
the expert RG 2001 is not the same in 2006
... |
223 |
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Conscious and unconscious processing dynamics
|
224 |
|
|
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Does
the uncus help to integrate expert memory elaborated by obsessive and/or
motivated training behaviour?
.. |
224 |
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|
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The modularity discussion
. |
225 |
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What can we learn from the present
replication study?
|
226 |
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3.3
Exceptional performance in qualitatively different complex mental domains -
Are there really modular centres in the brain for complex cognition?
.. |
228 |
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Experimental design and data analysis
. |
229 |
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FMRI data: Results
... |
231 |
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Does
RG recruit spatio-temporal processing skills for all of his exceptional
abilities?
|
231 |
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3.4 A short synopsis of chapter 3
|
234 |
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3.5 Acknowledgements ... |
236 |
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3.6 References . |
236 |
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4. Emotional modulation of cognition -
Addiction memory and EEG
. |
241 |
|||
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Emotional modulation of cognitive
processing
.. |
241 |
||
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Neural networks and
perception-action cycle
|
242 |
||
|
|
4.1. Addiction memory
... |
242 |
||
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4.1.1. The
development of addiction and addiction memory
|
243 |
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4.1.2. Persisting physiological and cognitive
effects of nicotine consumption
|
245 |
|
|
|
|
|
Animal studies on persisting physiological
effects of nicotine administration
|
245 |
|
|
|
|
Human
studies on persisting physiological and/or cognitive effects of nicotine
consumption
.. |
246 |
|
|
|
4.1.3.
Early history of nicotine consumption and persisting effects on EEG parameters ... |
248 |
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|
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|
4.1.4.
Physiological parameters, craving and "smoking behaviour" in humans
... |
249 |
|
|
|
|
4.1.5. Drug-related
cues, emotion and cognition
..
|
250 |
|
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4.2. Nicotine Stroop and addiction memory
... |
252 |
||
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|
4.2.1. Addiction memory and the
concept of Stroop-interference
|
253 |
|
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|
|
4.2.2. A modified Stroop-design and nicotine-Stroop Methods, procedures
and results
.. |
254 |
|
|
|
|
|
Participants
.. |
254 |
|
|
|
|
Task and procedure
.. |
255 |
|
|
|
|
EEG
recordings and statistical analyses
.. |
256 |
|
|
|
|
Behavioural data ... |
258 |
|
|
|
|
ERP
differences in the nicotine Stroop task
.. |
259 |
|
|
|
|
Early ERP differences in the
nicotine Stroop task
|
260 |
|
|
|
|
Late ERP differences in the
nicotine Stroop task
.. |
261 |
|
|
|
|
ERP
Stroop-task differences
. |
261 |
|
|
|
4.2.3. The link between nicotine
Stroop and addiction memory
... |
263 |
|
|
|
|
|
Early
ERP differences in nicotine Stroop and classic Stroop
... |
263 |
|
|
|
|
Late ERP
differences in nicotine Stroop
... |
264 |
|
|
|
|
Behavioural results versus ERP results
|
265 |
|
|
4.3. Smoking-related pictures modulate colour
matching processing in smokers and
non-smokers
.
|
267 |
||
|
|
|
4.3.1. Smoking- related picture
content and addiction memory
... |
267 |
|
|
|
|
|
Nicotine consumption and event related
potentials
.. |
267 |
|
|
|
|
Drug-related cues
and event related potentials
|
268 |
|
|
|
4.3.2. A colour matching design including smoking-related and neutral
pictures - Methods, procedures
and results
..
... |
432 |
|
|
|
|
|
Participants
... |
269 |
|
|
|
|
Task and
procedure
... |
269 |
|
|
|
|
ERP recording and
averaging
.. |
271 |
|
|
|
|
Data
analyses
|
271 |
|
|
|
|
Multivariate non-parametric
permutation tests and omnibus statistics
... |
271 |
|
|
|
|
Behavioural data
... |
272 |
|
|
|
|
ERP differences
. |
273 |
|
|
|
|
Multivariate non-parametric permutation
tests and omnibus statistics: Results . |
276 |
|
|
|
4.3.3. Linking cognitive
interference processing and addiction memory
. |
277 |
|
|
|
|
|
Interference induced by smoking-related cues
in both smokers and non-smokers
. |
279 |
|
|
|
|
Functional
integration of memory and action
.. |
280 |
|
|
|
|
Linking
the present ERP differences to neuropharmacological implications
.. |
280 |
|
|
4.4. ERP studies - Further remarks and
extended data exploration
|
282 |
||
|
|
|
4.4.1. A methodological contribute to the nature of complex mental
processing - Extended data exploration
... |
286 |
|
|
|
|
|
Profound visual inspection of ERP curves to sufficiently detect
putative group differences
. |
286 |
|
|
|
|
Statistical analyses and results
. |
286 |
|
|
|
4.4.2 Did the a priori formulated hypotheses in chapter 4.3 provide a
sufficient basis for the applied statistical testing?
|
288 |
|
|
|
4.5. Smoking, emotion and
personality
.. |
290 |
||
|
|
|
The somatic marker hypothesis and
addiction
.
. |
291 |
|
|
|
|
Personality traits in smokers
.
...
|
291 |
|
|
|
|
Exploring the relationship between personality and smoking picture
category related ERPs
.
.
|
292 |
|
|
|
|
Evidence for a differential relationship between personality traits
and the processing of smoking-related cues
..
|
296 |
|
|
|
|
Limitations of the present PCA
results
.
.
|
298 |
|
|
|
4.6. Addiction memory and emotional
modulation of cognition - A synopsis
... |
299 |
||
|
|
|
Addiction memory forever
.
|
299 |
|
|
|
|
The adolescence as an especially critical life period for addiction
memory establishment
.
|
300 |
|
|
|
|
Conclusive remarks
...
|
302 |
|
|
|
4.7. Acknowledgements
.. |
303 |
||
|
|
4.8. References
|
303 |
||
|
|
|
|
|
|
|
5.
Oscillatory brain activity in higher cognition: Inter-individual differences
- Different methodological approaches in the analysis of continuous MEG data
.. |
313 |
|||
|
|
Summary
. |
313 |
||
|
|
5.1 What
is a complex mental process? - About the processing of higher mental
concepts
|
313 |
||
|
|
|
Contrasting and indulging
.
|
314 |
|
|
|
|
Which brain regions can be expected to be
activated during contrasting and indulging?
..
|
315 |
|
|
|
5.2 Inter-individuality and ecological
validity - A challenge for methodology
. |
317 |
||
|
|
5.3 An
experimental design for the examination of higher cognition - Methods and
results
|
319 |
||
|
|
|
Pre-test
..
|
219 |
|
|
|
|
Data acquisition, participants and MEG study protocol .. |
322 |
|
|
|
|
Regional fast Fourier transformation (FFT) . |
323 |
|
|
|
|
Dipole density (DD) .. |
323 |
|
|
|
|
Minimum-Norm L2 |
324 |
|
|
|
|
Multiple Dipole Density (MDD)
|
325 |
|
|
|
|
Results of regional fast Fourier transform
(FFT) procedures
..
|
327 |
|
|
|
|
Results of dipole density plot (DDP)
procedures
..
|
328 |
|
|
|
|
Results revealed by minimum norm L2 (MMN)
estimations
.
|
328 |
|
|
|
|
Results revealed by the appliance of multiple dipole density (MDD) procedures .. |
328 |
|
|
|
5.4 The scientific value of the present
results for social psychology
. |
331 |
||
|
|
|
Regional
oscillatory brain activation patterns and the concepts of mental contrasting
and indulging
. |
331 |
|
|
|
|
Implications for social psychology |
333 |
|
|
|
|
Final remarks
|
334 |
|
|
|
5.5 If
you do not see it, then you might be blind for it - A collapse of classical
approaches in complex problems?
|
335 |
||
|
|
|
Limitations and the need of methodological inspirations
|
335 |
|
|
|
5.6
Methodological implications of the present study for psychophysiological
research
.
|
337 |
||
|
|
|
Inter-individuality
..
|
337 |
|
|
|
|
Nature of oscillatory brain activation
changes over time
.
|
339 |
|
|
|
|
The
modularity discussion of complex mental processing - Do we need new
physiological parameters?
|
341 |
|
|
|
|
|
|
|
|
|
5.7 Acknowledgements
... |
341 |
||
|
|
5.8 References
. |
342 |
||
|
|
|
|
|
|
|
6. Abbreviations
. |
347 |
|||
|
|
|
|
|
|
|
7. Index of figures
.. |
349 |
|||
|
|
|
|
|
|
|
8. Index of tables
|
357 |
|||
|
|
|
|
|
|
|
9. General Acknowledgements
. |
360 |
|||
|
|
|
|
|
|
General Acknowledgements
First of all, the author is very
grateful to his wife Christina and to his son Tristan for excellent social and
emotional support during the extensive night and day shifts in particular
throughout the final phase of manuscript production for the present issue.
The author is especially grateful to
Christina Fehr for scientific proof and language editing, and to Rita Gehlhoff
for language editing of major parts of the present issue.
Further the author thanks his
fathers and mothers, Karl-Heinz Fehr, Gudrun Eiffert, Susanne Fischer, Dieter
Eiffert, Birgit and Jόrgen Dόx, and, of course, his brothers, Norbert and
Andreas Bradula, for their more than one decade lasting surrender of appropriate
social contact with respect to the author΄s scientific work. The author is also
grateful to his parents-in-law, Ulla and Gόnther Schmiedt for frequently
looking after Tristan.
The author want to especially thank
his mentors, Manfred Herrmann, Canan Basar-Eroglu, Herrmann Hinrichs and
Hans-Jochen Heinze from Bremen and Magdeburg Universities for providing
facilities, administrative and personal support, and many more. Additionally,
the author also thanks his former mentors, Brigitte Rockstroh and Rudolf Cohen,
from Konstanz University, who encouraged him to stay in cognitive neusoscience
many years ago. It appears that this was the right decision.
Last but not least, the author
thanks all his friends and colleagues for social and aministrative support,
especially in the months, during which the habilitation thesis has been
finished.
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