Subscribe to RSS
DOI: 10.1055/s-2007-992769
© Georg Thieme Verlag KG Stuttgart · New York
Assessing the State Space of the Brain with fMRI: An Integrative View of Current Methods
Publication History
Publication Date:
17 December 2007 (online)

Abstract
Systems biology has gained substantial benefit from the application of systems modeling in engineering sciences. In general, methods as employed for construction and simulation of technical devices and buildings are applicable to modeling of biological systems. A number of modeling approaches originally derived from different areas such as engineering, econometrics and genetics have been adapted to functional brain imaging datasets in the recent years. However, despite a number of analogies, the complexities of brain systems might be much higher than those observed in technical systems. A dynamical system can be described as a state space in which a certain state of the system is specified by a single point. Varying states of the system over time can be described by a trajectory of states. Different modeling algorithms focus on certain aspects of this state space. The covariance of the state-space variables can be examined by correlational analysis (targeting normalized covariance) and principal component analysis. One of the principle aims in any systems identification approach is to identify parameters of the state matrix, i.e. the rules of transitions between different states of the system. Dynamic approaches with temporal information include the full state space model, vector autoregressive model and dynamic causal modeling. Structural equation modeling focuses on the instantaneous relationship between functional nodes. Directional analysis strategies are available in temporal and frequency domain. Depending on general assumptions as to how neuronal representation is established, the approaches present complementary information about the underlying neuronal interactions. The present article attempts to provide an integrative overview of the most established models and methods which are currently being applied for modeling dynamic brain systems.
References
- 1
Arnold M, Miltner WH, Witte H, Bauer R, Braun C.
Adaptive AR modeling of nonstationary time series by means of Kalman filtering.
IEEE transactions on bio-medical engineering.
1998;
45
553-562
Reference Ris Wihthout Link
- 2
Astolfi L, Cincotti F, Mattia D. et al .
Estimation of the effective and functional human cortical connectivity with structural
equation modeling and directed transfer function applied to high-resolution EEG.
Magn Reson Imaging.
2004;
22
1457-1470
Reference Ris Wihthout Link
- 3 Aström KJ, Wittenmark B.
Adaptive control . Rading: Addison-Wesley Publishing Company 1995Reference Ris Wihthout Link - 4
Basar-Eroglu C, Brand A, Hildebrandt H. et al .
Working memory related gamma oscillations in schizophrenia patients.
Int J Psychophysiol.
2007;
64
39-45
Reference Ris Wihthout Link
- 5
Bender W, Albus M, Moller HJ, Tretter F.
Towards systemic theories in biological psychiatry.
Pharmacopsychiatry.
2006;
39
(Suppl 1)
S4-S9
Reference Ris Wihthout Link
- 6
Bhattacharya S, Ringo Ho MH, Purkayastha S.
A Bayesian approach to modeling dynamic effective connectivity with fMRI data.
Neuroimage.
2006;
30
794-812
Reference Ris Wihthout Link
- 7 Boomsma A, Hoogland JJ. The robustness of LISREL modeling revisited. In: Cudeck R, du Toit S, Sörbom D eds,
Structural Equation Modeling: Present and Future . Lincolnwood, IL: Scientific Software International 2001: 139-168Reference Ris Wihthout Link - 8 Brogan WL. Modern control theory. 3 ed.
Upper Saddle River . NJ: Prentice Hall 1991Reference Ris Wihthout Link - 9
Buchel C, Friston KJ.
Modulation of connectivity in visual pathways by attention: cortical interactions
evaluated with structural equation modelling and fMRI.
Cereb Cortex.
1997;
7
768-778
Reference Ris Wihthout Link
- 10
Buchel C, Friston KJ.
Dynamic changes in effective connectivity characterized by variable parameter regression
and Kalman filtering.
Hum Brain Mapp.
1998;
6
403-408
Reference Ris Wihthout Link
- 11
Bullmore E, Horwitz B, Honey G. et al .
How good is good enough in path analysis of fMRI data?.
Neuroimage.
2000;
11
289-301
Reference Ris Wihthout Link
- 12 Byrne BM.
Structural equation modeling with AMOS. Basic concepts, applications, and programming . Mahwah, New Jersey: Lawrence Erlbaum Associates 2001Reference Ris Wihthout Link - 13
Carmeli C, Knyazeva MG, Innocenti GM, Feo O De.
Assessment of EEG synchronization based on state-space analysis.
Neuroimage.
2005;
25
339-354
Reference Ris Wihthout Link
- 14 Chatfield C.
The analysis of time series: An introduction . Boca Raton: Chapman & Hall/CRC 2004Reference Ris Wihthout Link - 15
Cordes D, Haughton VM, Arfanakis K. et al .
Mapping functionally related regions of brain with functional connectivity MR imaging.
AJNR Am J Neuroradiol.
2000;
21
1636-1644
Reference Ris Wihthout Link
- 16
Deco G.
A dynamical model of event-related FMRI signals in prefrontal cortex: predictions
for schizophrenia.
Pharmacopsychiatry.
2006;
39
(Suppl 1)
S65-S67
Reference Ris Wihthout Link
- 17
Dempster AP, Laird NM.
Maximum likelihood estimation from incomplete data via the EM algorithm.
J Roy Statist Soc B.
1977;
39
1-38
Reference Ris Wihthout Link
- 18 Doya K, Ishii S, Pouget A. Bayesian Brain: Probabilistic Approaches to Neural Coding MIT Press 2007
Reference Ris Wihthout Link
- 19 Eliasmith C, Anderson CH.
Neural Engineering . Cambridge, Massachusetts: MIT Press 2003Reference Ris Wihthout Link - 20
Etkin A, Egner T, Peraza DM, Kandel ER, Hirsch J.
Resolving emotional conflict: A role for the rostral anterior cingulate cortex in
modulating activity in the amygdala.
Neuron.
2006;
51
871-882
Reference Ris Wihthout Link
- 21
Fell J, Fernandez G, Klaver P, Elger CE, Fries P.
Is synchronized neuronal gamma activity relevant for selective attention?.
Brain Res Brain Res Rev.
2003;
42
265-272
Reference Ris Wihthout Link
- 22
Friman O, Farneback G, Westin CF.
A Bayesian approach for stochastic white matter tractography.
IEEE transactions on medical imaging.
2006;
25
965-978
Reference Ris Wihthout Link
- 23
Friston K.
A theory of cortical responses.
Philosophical transactions of the Royal Society of London.
2005;
360
815-836
Reference Ris Wihthout Link
- 24
Friston KJ, Harrison L, Penny W.
Dynamic causal modelling.
Neuroimage.
2003;
19
1273-1302
Reference Ris Wihthout Link
- 25
Gallinat J, Heinz A.
Combination of multimodal imaging and molecular genetic information to investigate
complex psychiatric disorders.
Pharmacopsychiatry.
2006;
39
(Suppl 1)
S76-S79
Reference Ris Wihthout Link
- 26 Gelman A, Carlin JB, Stern HS, Rubin DB. Bayesian data analysis. Boca Raton: Cahpman & Hall 2003
Reference Ris Wihthout Link
- 27 Gerstner W.
Kistler w, Spiking Neuron Models: Single Neurons, Populations, Plasticity . Cambridge: Cambridge University Press 2002Reference Ris Wihthout Link - 28
Geweke J.
Measurement of linear dependence and feedback between multiple time series.
Journal of the American Statistical Association.
1982;
77
304-313
Reference Ris Wihthout Link
- 29
Goebel R, Roebroeck A, Kim DS, Formisano E.
Investigating directed cortical interactions in time-resolved fMRI data using vector
autoregressive modeling and Granger causality mapping.
Magn Reson Imaging.
2003;
21
1251-1261
Reference Ris Wihthout Link
- 30
Gossl C, Fahrmeir L, Putz B, Auer LM, Auer DP.
Fiber tracking from DTI using linear state space models: detectability of the pyramidal
tract.
Neuroimage.
2002;
16
378-388
Reference Ris Wihthout Link
- 31
Granger CWJ.
Investigating causal relations by econometric models and cross-spectral methods.
Econometrica.
1969;
37
424-438
Reference Ris Wihthout Link
- 32 Grewal MS, Andrews AP. Kalman Filtering: Theory and practice using MATLAB: Wiley-Interscience 2001
Reference Ris Wihthout Link
- 33
Haavisto O, Hyotyniemi H, Roos C.
State space modeling of yeast gene expression dynamics.
Journal of bioinformatics and computational biology.
2007;
5
31-46
Reference Ris Wihthout Link
- 34
Harrison L, Penny WD, Friston K.
Multivariate autoregressive modeling of fMRI time series.
Neuroimage.
2003;
19
1477-1491
Reference Ris Wihthout Link
- 35
Ho RM, Ombao H, Shumway R.
A state-space approach to modeling brain dynamics.
Statistica Sinica.
2005;
15
407-425
Reference Ris Wihthout Link
- 36
Honey G, Fu C, Kim J. et al .
Effects of verbal working memory load on corticocortical connectivity modeled by path
analysis of functional magnetic resonance imaging data.
Neuroimage.
2002;
17
573-582
Reference Ris Wihthout Link
- 37
Honey GD, Suckling J, Zelaya F. et al .
Dopaminergic drug effects on physiological connectivity in a human cortico-striato-thalamic
system.
Brain.
2003;
126
1767-1781
Reference Ris Wihthout Link
- 38
Horwitz B, MacIntosh AR, Haxby JV, Grady CL.
Network analysis of brain cognitive function using metabolic and blood flow data.
Behav Brain Res.
1995;
66
187-193
Reference Ris Wihthout Link
- 39 Hyvärinen A, Karhunen J, Oja E.
Independent component analysis . New York: John Wiley & Sons, Inc 2001Reference Ris Wihthout Link - 40
Kalman RE.
A new approach to linear filtering and prediction problems.
Trans of the ASME - Journal of Basic Engineering.
1960;
35-45
Reference Ris Wihthout Link
- 41
Kaminski M, Ding M, Truccolo WA, Bressler SL.
Evaluating causal relations in neural systems: granger causality, directed transfer
function and statistical assessment of significance.
Biological cybernetics.
2001;
85
145-157
Reference Ris Wihthout Link
- 42
Kim J, Zhu W, Chang L, Bentler PM, Ernst T.
Unified structural equation modeling approach for the analysis of multisubject, multivariate
functional MRI data.
Hum Brain Mapp.
2006;
Reference Ris Wihthout Link
- 43 Kline RB.
Principles and practice of structural equation modeling . 2nd ed. New York: The Guilford Press 2005Reference Ris Wihthout Link - 44
Kobayashi R, Shinomoto S.
State space method for predicting the spike times of a neuron.
Physical review.
2007;
75
011925
Reference Ris Wihthout Link
- 45
Koch C, Hepp K.
Quantum mechanics in the brain.
Nature.
2006;
440
611
Reference Ris Wihthout Link
- 46
Koechlin E, Ody C, Kouneiher F.
The architecture of cognitive control in the human prefrontal cortex.
Science.
2003;
302
1181-1185
Reference Ris Wihthout Link
- 47 Lathi BP.
Linear Systems and Signals . 2 ed. Oxford: Oxford University Press 2005Reference Ris Wihthout Link - 48 Ljung L.
System identification: Theory for the User . 2nd edition ed. London: Prentice Hall 1999Reference Ris Wihthout Link - 49
MacArdle J.
Causal modeling applied to psychonomic systems simulation.
Behavior Research Methods and Instrumentation.
1980;
12
193-209
Reference Ris Wihthout Link
- 50
MacIntosh AR, Bookstein FL, Haxby JV, Grady CL.
Spatial pattern analysis of functional brain images using partial least squares.
Neuroimage.
1996;
3
143-157
Reference Ris Wihthout Link
- 51
MacIntosh AR, Grady CL, Ungerleider LG. et al .
Network analysis of cortical visual pathways mapped with PET.
J Neurosci.
1994;
14
655-666
Reference Ris Wihthout Link
- 52
Mechelli A, Price CJ, Noppeney U, Friston KJ.
A dynamic causal modeling study on category effects: bottom-up or top-down mediation?.
J Cogn Neurosci.
2003;
15
925-934
Reference Ris Wihthout Link
- 53
Musso F, Konrad A, Vucurevic G. et al .
Distributed BOLD-response in association cortex vector state space predicts reaction
time during selective attention.
Neuroimage.
2006;
29
1311-1318
Reference Ris Wihthout Link
- 54
Noppeney U, Josephs O, Hocking J, Price CJ, Friston KJ.
The effect of prior visual information on recognition of speech and sounds.
Cereb Cortex.
2007;
Reference Ris Wihthout Link
- 55
Paulus MP, Frank L, Brown GG, Braff DL.
Schizophrenia subjects show intact success-related neural activation but impaired
uncertainty processing during decision-making.
Neuropsychopharmacology.
2003;
28
795-806
Reference Ris Wihthout Link
- 56
Penny WD, Stephan KE, Mechelli A, Friston KJ.
Modelling functional integration: a comparison of structural equation and dynamic
causal models.
Neuroimage.
2004;
23
(Suppl 1)
S264-S274
Reference Ris Wihthout Link
- 57 Petrides M. Mapping prefrontal cortical systems for the control of cognition. In: Toga A, Mazziotta JC eds,
Brain mapping: the systems . San Diego: Academic Press 2000: 157-176Reference Ris Wihthout Link - 58 Posner MI.
Chronometric Explorations of Mind . Hillsdale, N.J.: Lawrence Erlbaum Associates 1978Reference Ris Wihthout Link - 59 Rao RPN. Neural models of Bayesian belief propagation. In: Doya K, Ishii S, Pouget A, Rao RPN eds,
Bayesian Brain: Probabilistic Approaches to Neural Coding Cambridge . MA: MIT Press 2007: 235-264Reference Ris Wihthout Link - 60
Roebroeck A, Formisano E, Goebel R.
Mapping directed influence over the brain using Granger causality and fMRI.
Neuroimage.
2005;
25
230-242
Reference Ris Wihthout Link
- 61
Sato JR, Junior EA, Takahashi DY. et al .
A method to produce evolving functional connectivity maps during the course of an
fMRI experiment using wavelet-based time-varying Granger causality.
Neuroimage.
2006;
Reference Ris Wihthout Link
- 62
Schild D.
Coordination of neuronal signals as structures in state space.
The International journal of neuroscience.
1984;
22
283-297
Reference Ris Wihthout Link
- 63
Schlösser R, Gesierich T, Kaufmann B. et al .
Altered effective connectivity during working memory performance in schizophrenia:
a study with fMRI and structural equation modeling.
Neuroimage.
2003;
19
751-763
Reference Ris Wihthout Link
- 64
Schlösser R, Gesierich T, Kaufmann B, Vucurevic G, Stoeter P.
Altered effective connectivity in drug free schizophrenic patients.
Neuroreport.
2003;
14
2233-2237
Reference Ris Wihthout Link
- 65
Steele JD, Meyer M, Ebmeier KP.
Neural predictive error signal correlates with depressive illness severity in a game
paradigm.
Neuroimage.
2004;
23
269-280
Reference Ris Wihthout Link
- 66
Summerfield C, Egner T, Greene M. et al .
Predictive codes for forthcoming perception in the frontal cortex.
Science.
2006;
314
1311-1314
Reference Ris Wihthout Link
- 67
Toni I, Rowe J, Stephan KE, Passingham RE.
Changes of cortico-striatal effective connectivity during visuomotor learning.
Cereb Cortex.
2002;
12
1040-1047
Reference Ris Wihthout Link
- 68 Heijden F van der, Duin R, Ridder D de, Tax DMJ.
Classification, Parameter Estimation and State Estimation: An Engineering Approach Using MATLAB . New York: John Wiley & Sons 2004Reference Ris Wihthout Link - 69
Winterhalder M, Schelter B, Hesse W. et al .
Detection of directed information flow in biosignals.
Biomedizinische Technik.
2006;
51
281-287
Reference Ris Wihthout Link
- 70
Wright JJ, Kydd RR, Lees GJ.
State-changes in the brain viewed as linear steady-states and non-linear transitions
between steady-states.
Biological cybernetics.
1985;
53
11-17
Reference Ris Wihthout Link
- 71
Zhan Y, Halliday D, Jiang P, Liu X, Feng J.
Detecting time-dependent coherence between non-stationary electrophysiological signals-A
combined statistical and time-frequency approach.
Journal of neuroscience methods.
2006;
Reference Ris Wihthout Link
1 Supported by grants BMBF FKZ01ZZ0105 and IZKF, TMWFK B30701-015/-016
Correspondence
R. G. M. SchlösserMD
Department of Psychiatry and Psychotherapy
University of Jena
Philosophenweg 3
07740 Jena
Germany
Phone: +49/3641/9 352 84
Fax: +49/3641/9 354 44
Email: Ralf.Schloesser@uni-jena.de