Understanding the abnormal brain activity in epilepsy as a potential predictor of the onset of an epileptic seizure

The Brain Research Institute (BRI) uses various types of indirect measurements, including EEG and fMRI, to understand and assess brain activity and function. As well as the recovery of generic information about brain function, research also focuses on the utilisation of such data and understanding to study the initiation, dynamics, spread and suppression of epileptic seizures. To assist with the future focussing of this aspect of their research, the BRI asked the MISG 2010 participants to examine how the available EEG and fMRI data and current knowledge about epilepsy should be analysed and interpreted to yield an enhanced understanding about brain activity occurring before, at commencement of, during, and after a seizure. Though the deliberations of the study group were wide ranging in terms of the related matters considered and discussed, considerable progress was made with the following three aspects. (1) The science behind brain activity investigations depends crucially on the quality of the analysis and interpretation of, as well as the recovery of information from, EEG and fMRI measurements. A number of specific methodologies were discussed and formalised, including independent component analysis, principal component analysis, profile monitoring and change point analysis (hidden Markov modelling, time series analysis, discontinuity identification). (2) Even though EEG measurements accurately and very sensitively record the onset of an epileptic event or seizure, they are, from the perspective of understanding the internal initiation and localisation, of limited utility. They only record neuronal activity in the cortical (surface layer) neurons of the brain, which is a direct reflection of the type of electrical activity they have been designed to record. Because fMRI records, through the monitoring of blood flow activity, the location of localised brain activity within the brain, the possibility of combining fMRI measurements with EEG, as a joint inversion activity, was discussed and examined in detail. (3) A major goal for the BRI is to improve understanding about ``when'' (at what time) an epileptic seizure actually commenced before it is identified on an eeg recording, ``where'' the source of this initiation is located in the brain, and ``what'' is the initiator. Because of the general agreement in the literature that, in one way or another, epileptic events and seizures represent abnormal synchronisations of localised and/or global brain activity the modelling of synchronisations was examined in some detail. References C. M. Michel, G. Thut, S. Morand, A. Khateb, A. J. Pegna, R. Grave de Peralta, S. Gonzalez, M. Seeck and T. Landis, Electric source imaging of human brain functions, Brain Res. Rev. , 36 (2--3), 2001, 108--118. doi:10.1016/S0165-0173(01)00086-8 S. Ogawa, R. S. Menon, S. G. Kim and K. Ugurbil, On the characteristics of functional magnetic resonance imaging of the brain, Annu. Rev. Bioph. Biom. , 27 , 1998, 447--474. doi:10.1146/annurev.biophys.27.1.447 C. D. Binnie and H. Stefan, Modern electroencephalography: its role in epilepsy management, Clin. Neurophysiol. , 110 (10), 1999, 1671--1697. doi:10.1016/S1388-2457(99)00125-X J. X. Tao, A. Ray, S. Hawes-Ebersole and J. S. Ebersole, Intracranial eeg substrates of scalp eeg interictal spikes, Epilepsia , 46 (5), 2005, 669--76. doi:10.1111/j.1528-1167.2005.11404.x S. Ogawa, D. W. Tank, R. Menon, J. M. Ellermann, S. G. Kim, H. Merkle and K. Ugurbil, Intrinsic signal changes accompanying sensory stimulation: Functional brain mapping with magnetic resonance imaging, P. Natl. Acad. Sci. USA , 89 (13), 1992, 5951--5955. doi:10.1073/pnas.89.13.5951 J. Engel Jr., Report of the ilae classification core group, Epilepsia , 47 (9), 2006, 1558--1568. doi:10.1111/j.1528-1167.2006.00215.x L. Lemieux, A. Salek-Haddadi, O. Josephs, P. Allen, N. Toms, C. Scott, K. Krakow, R. Turner and D. R. Fish, Event-related fmri with simultaneous and continuous eeg: description of the method and initial case r port, NeuroImage , 14 (3), 2001, 780--7. doi:10.1006/nimg.2001.0853 P. Federico, D. F. Abbott, R. S. Briellmann, A. S. Harvey and G. D. Jackson, Functional mri of the pre-ictal state, Brain , 128 (8), 2005, 1811-7. doi:10.1093/brain/awh533 C. S. Hawco, A. P. Bagshaw, Y. Lu, F. Dubeau and J. Gotman, bold changes occur prior to epileptic spikes seen on scalp eeg, NeuroImage , 35 (4), 2007, 1450--1458. doi:10.1016/j.neuroimage.2006.12.042 F. Moeller, H. R. Siebner, S. Wolff, H. Muhle, R. Boor, O. Granert, O. Jansen, U. Stephani and M. Siniatchkin, Changes in activity of striato-thalamo-cortical network precede generalized spike wave discharges, NeuroImage , 39 (4), 2008, 1839--1849. doi:10.1016/j.neuroimage.2007.10.058 V. Osharina, E. Ponchel, A. Aarabi, R. Grebe and F. Wallois, Local haemodynamic changes preceding interictal spikes: A simultaneous electrocorticography (ecog) and near-infrared spectroscopy (nirs) analysis in rats, NeuroImage , 50 (2), 2010, 600--607. doi:10.1016/j.neuroimage.2010.01.009 R. S. Fisher, W. Boas, W. Blume, C. Elger, P. Genton, P. Lee and J. Engel, Epileptic seizures and epilepsy: Definitions proposed by the international league against epilepsy (ilae) and the international bureau for epilepsy (ibe), Epilepsia , 46 (4), 2005, 470--472. doi:10.1111/j.0013-9580.2005.66104.x H. Berger, Electroencephalogram in humans, Arch. Psychiat. Nerven. , 87 , 1929, 527--570. C. M. Michel, M. M. Murray, G. Lantz, S. Gonzalez, L. Spinelli and R. G. de Peralta, eeg source imaging, Clin. Neurophysiol. , 115 (10), 2004, 2195--2222. doi:10.1016/j.clinph.2004.06.001 P. L. Nunez and R. B. Silberstein, On the relationship of synaptic activity to macroscopic measurements: Does co-registration of eeg with fmri make sense?, Brain Topogr. , 13 (2), 2000, 79--96. doi:10.1023/A:1026683200895 S. Ogawa, T. M. Lee, A. R. Kay and D. W. Tank, Brain magnetic resonance imaging with contrast dependent on blood oxygenation, P. Natl. Acad. Sci. USA , 87 (24), 1990, 9868--9872. doi:10.1073/pnas.87.24.9868 J. S. Gati, R. S. Menon, K. Ugurbil and B. K. Rutt, Experimental determination of the bold field strength dependence in vessels and tissue, Magn. Reson. Med. , 38 (2), 1997, 296--302. doi:10.1002/mrm.1910380220 P. A. Bandettini, E. C. Wong, R. S. Hinks, R. S. Tikofsky and J. S. Hyde, Time course EPI of human brain function during task activation, Magn. Reson. Med. , 25 (2), 1992, 390--397. K. K. Kwong, J. W. Belliveau, D. A. Chesler, I. E. Goldberg, R. M. Weisskoff, B. P. Poncelet, D. N. Kennedy, B. E. Hoppelm, M. S. Cohen and R. Turner, Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation, P. Natl. Acad. Sci. USA , 89 (12), 1992, 5675--5679. doi:10.1073/pnas.89.12.5675 J. Frahm, K. D. Merboldt and W. Hnicke, Functional mri of human brain activation at high spatial resolution, Magn. Reson. Med. , 29 (1), 1993, 139--144. P. A. Bandettini, A. Jesmanowicz, E. C. Wong and J. S. Hyde, Processing strategies for time-course data sets in functional MRI of the human brain, Magn. Reson. Med. , 30 (2), 1993, 161--173. K. J. Friston, P. Jezzard and R. Turner, Analysis of functional MRI time-series, Hum. Brain Mapp. , 1 (2), 1994, 153--171. B. Biswal, F. Z. Yetkin, V. M. Haughton and J. S. Hyde, Functional connectivity in the motor cortex of resting human brain using echo-planar mri, Mag. Reson. Med. , 34 (4), 1995, 537--541. doi:10.1002/mrm.1910340409 K. J. Friston, J. Ashburner, C. D. Frith, J. Poline, J. D. Heather and R. S. J. Frackowiak, Spatial registration and normalization of images, Hum. Brain Mapp. , 3 (3), 1995, 165--189. K. J. Friston, S. Williams, R. Howard, R. S. Frackowiak and R. Turner, Movement-related effects in fmri time-series, Magn. Reson. Med. , 35 (3), 1996, 346--355. G. H. Glover, T. Q. Li and D. Ress, Image-based method for retrospective correction of physiological motion effects in fmri: Retroicor, Magn. Reson. Med. , 44 (1), 2000, 162--167. doi:10.1002/1522-2594(200007)44:13.0.CO;2-E K. J. Friston, O. Josephs, G. Rees and R. Turner, Nonlinear event-related responses in fmri, Magn. Reson. Med. , 39 (1), 1998, 41--52. doi:10.1002/mrm.1910390109 K. Ugurbil, L. Toth and D. Kim, How accurate is magnetic resonance imaging of brain function?, Trends Neurosci. , 26 (2), 2003, 108--114. doi:10.1016/S0166-2236(02)00039-5 D. S. Kim, I. Ronen, C. Olman, S. G. Kim, K. Ugurbil and L. J. Toth, Spatial relationship between neuronal activity and bold functional mri, NeuroImage , 21 (3), 2004, 876--885. doi:10.1016/j.neuroimage.2003.10.018 A. Connelly, G. D. Jackson, R. S. Frackowiak, J. W. Belliveau, F. Vargha-Khadem and D. G. Gadian, Functional mapping of activated human primary cortex with a clinical mr imaging system, Radiology , 188 (1), 1993, 125--130. L. Allison, Hidden Markov Models, Technical Report , School of Computer and Software Engineering, Monash University, 2000. R. J. Elliott, L. Aggoun and J.B. Moore, Hidden Markov Models: Estimation and Control, Appl. Math.-Czech. , 2004. B. Bhavnagri, Discontinuities of plane functions projected from a surface with methods for finding these , Technical Report, 2009. B. Bhavnagri, Computer Vision using Shape Spaces , Technical Report,1996, University of Adelaide. B. Bhavnagri, A method for representing shape based on an equivalence relation on polygons, Pattern Recogn. , 27 (2), 1994, 247--260. doi:10.1016/0031-3203(94)90057-4 D. F. Abbott, A. B. Waites, A. S. Harvey and G. D. Jackson, Exploring epileptic seizure onset with fmri, NeuroImage , 36(S1) (344TH-PM), 2007. M. C. Mackey and L. Glass, Oscillation and chaos in physiological control systems, Science , 197 , 1977, 287--289. S. H. Strogatz, SYNC - The Emerging Science of Spontaneous Order , Theia, New York, 2003. J. W. Kim, J. A. Roberts and P. A. Robinson, Dynamics of epileptic seizures: Evolution, spreading, and suppression, J. Theor. Biol. , 257 (4), 2009, 527--532. doi:10.1016/j.jtbi.2008.12.009 Y. Kuramoto, T. Aoyagi, I. Nishikawa, T. Chawanya T and K. Okuda, Neural network model carrying phase information with application to collective dynamics, J. Theor. Phys. , 87 (5), 1992, 1119--1126. V. B. Mountcastle, The columnar organization of the neocortex, Brain , 120 (4), 1997, 701. doi:10.1093/brain/120.4.701 F. L. Silva, W. Blanes, S. N. Kalitzin, J. Parra, P. Suffczynski and D. N. Velis, Epilepsies as dynamical diseases of brain systems: Basic models of the transition between normal and epileptic activity, Epilepsia , 44 (12), 2003, 72--83. F. H. Lopes da Silva, W. Blanes, S. N. Kalitzin, J. Parra, P. Suffczynski and D. N. Velis, Dynamical diseases of brain systems: different routes to epileptic seizures, ieee T. Bio-Med. Eng. , 50 (5), 2003, 540. L.D. Iasemidis, Epileptic seizure prediction and control, ieee T. Bio-Med. Eng. , 50 (5), 2003, 549--558. L. D. Iasemidis, D. S. Shiau, W. Chaovalitwongse, J. C. Sackellares, P. M. Pardalos, J. C. Principe, P. R. Carney, A. Prasad, B. Veeramani, and K. Tsakalis, Adaptive epileptic seizure prediction system, ieee T. Bio-Med. Eng. , 50 (5), 2003, 616--627. K. Lehnertz, F. Mormann, T. Kreuz, R.G. Andrzejak, C. Rieke, P. David and C. E. Elger, Seizure prediction by nonlinear eeg analysis, ieee Eng. Med. Biol. , 22 (1), 2003, 57--63. doi:10.1109/MEMB.2003.1191451 K. Lehnertz, R. G. Andrzejak, J. Arnhold, T. Kreuz, F. Mormann, C. Rieke, G. Widman and C. E. Elger, Nonlinear eeg analysis in epilepsy: Its possible use for interictal focus localization, seizure anticipation, and prevention, J. Clin. Neurophysiol. , 18 (3), 2001, 209. B. Litt and K. Lehnertz, Seizure prediction and the preseizure period, Curr. Opin. Neurol. , 15 (2), 2002, 173. doi:10.1097/00019052-200204000-00008 B. Litt and J. Echauz, Prediction of epileptic seizures, Lancet Neurol. , 1 (1), 2002, 22--30. doi:10.1016/S1474-4422(02)00003-0 M. M{a}kiranta, J. Ruohonen, K Suominen, J. Niinim{a}ki, E. Sonkaj{a}rvi, V. Kiviniemi, T. Sepp{a}nen, S. Alahuhta, V. J{a}ntti and O. Tervonen, {bold} signal increase preceeds eeg spike activity--a dynamic penicillin induced focal epilepsy in deep anesthesia, NeuroImage , 27 (4), 2005, 715--724. doi:10.1016/j.neuroimage.2005.05.025 K. Lehnertz, F. Mormann, H. Osterhage, A. M{u}ller, J. Prusseit, A. Chernihovskyi, M. Staniek, D. Krug, S. Bialonski and C. E. Elger, State-of-the-art of seizure prediction, J. Clin. Neurophysiol. , 24 (2), 2007, 147. doi:10.1097/WNP.0b013e3180336f16 F. Mormann, T. Kreuz, C. Rieke, R. G. Andrzejak, A. Kraskov, P. David, C. E. Elger and K. Lehnertz, On the predictability of epileptic seizures, Clin. Neurophysiol. , 116 (3), 2005, 569--587. doi:10.1016/j.clinph.2004.08.025 F. Mormann, R. G. Andrzejak, C. E. Elger and K. Lehnertz, Seizure prediction: the long and winding road, Brain , 130 (2), 2007, 314--333. doi:10.1093/brain/awl241 Z. Rogowski, I. Gath and E. Bental, On the prediction of epileptic seizures, Biol. Cybern. , 42 (1), 1981, 9--15. Y. Salant, I. Gath, O. Henriksen, Prediction of epileptic seizures from two-channel eeg, Med. Biol. Eng. Comput. , 36 (5), 1998, 549--556. doi:10.1007/BF02524422 J. Gotman and D.J. Koffler, Interictal spiking increases after seizures but does not after decrease in medication, Evoked Potential , 72 (1), 1989, 7--15. J. Gotman and M. G. Marciani, Electroencephalographic spiking activity, drug levels, and seizure occurence in epileptic patients, Ann. Neurol. , 17 (6), 1985, 59--603. A. Katz, D. A. Marks, G. McCarthy and S. S. Spencer, Does interictal spiking change prior to seizures?, Electroen. Clin. Neuro. , 79 (2), 1991, 153--156. A. Granada, R. M. Hennig, B. Ronacher, A. Kramer and H. Herzel, Phase Response Curves: Elucidating the dynamics of couples oscillators, Method Enzymol. , 454 (A), 2009, 1--27. doi:10.1016/S0076-6879(08)03801-9 doi:10.1016/S0076-6879(08)03801-9 H. Kantz and T. Schreiber, Nonlinear time series analysis , 2004, Cambridge Univ Press. M. V. L. Bennett and R. S Zukin, Electrical coupling and neuronal synchronization in the mammalian brain, Neuron , 41 (4), 2004, 495 --511. doi:10.1016/S0896-6273(04)00043-1 L.D. Iasemidis, J. Chris Sackellares, H. P. Zaveri and W. J. Williams, Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizures, Brain Topogr. , 2 (3), 1990, 187--201. doi:10.1007/BF01140588 M. Le Van Quyen, J. Martinerie, V. Navarro, M. Baulac and F. J. Varela, Characterizing neurodynamic changes before seizures, J. Clin. Neurophysiol. , 18 (3), 2001, 191. J. Martinerie, C. Adam, M. Le Van Quyen, M. Baulac, S. Clemenceau, B. Renault and F. J. Varela, Epileptic seizures can be anticipated by non-linear analysis, Nat. Med. , 4 (10), 1998, 1173--1176. doi:10.1038/2667 A. Pikovsky, M. Rosenblum, J. Kurths and R. C. Hilborn, Synchronization: A universal concept in nonlinear science, Amer. J. Phys. , 70 , 2002, 655. H. R. Wilson and J. D. Cowan, Excitatory and inhibitory interactions in localized populations of model neurons, Biophys. J. , 12 (1), 1972, 1--24. D. Cumin and C. P. Unsworth, Generalising the Kuramoto model for the study of neuronal synchronisation in the brain, Physica D , 226 (2), 2007, 181--196. doi:10.1016/j.physd.2006.12.004 F. K. Skinner, H. Bazzazi and S. A. Campbell, Two-cell to N-cell heterogeneous, inhibitory networks: Precise linking of multistable and coherent properties, J. Comput. Neurosci. , 18 (3), 2005, 343--352. doi:10.1007/s10827-005-0331-1 W. W. Lytton, Computer modelling of epilepsy, Nat. Rev. Neurosci. , 9 (8), 2008, 626--637. doi:10.1038/nrn2416 R. D. Traub, A. Bibbig, F. E. N. LeBeau, E. H. Buhl and M. A. Whittington, Cellular mechanisms of neuronal population oscillations in the hippocampus in vitro, Ann. Rev. , 2004. R. D. Traub, A. Draguhn, M. A. Whittington, T. Baldeweg, A. Bibbig, E. H. Buhl and D. Schmitz, Axonal gap junc ions between principal neurons: A novel source of network oscillations, and perhaps epileptogenesis., Rev. Neuroscience , 13 (1), 2002, 1. doi:10.1146/annurev.neuro.27.070203.144303 M. Scheffer, J. Bascompte, W. A. Brock, V. Brovkin, S. R. Carpenter, V. Dakos, H. Held, E. H. van Nes, M. Rietkerk and G. Sugihara, Early-warning signals for critical transitions, Nature , 461 (7260), 2009, 53--59. doi:10.1038/nature08227 K. Murphy, A Brief Introduction to Graphical Models and Bayesian Networks , 2008, http://www.cs.ubc.ca/murphyk/Bayes/bnintro.html . R. C. Bradley, An elementary

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Human Preferences for Symmetry: Subjective Experience, Cognitive Conflict and Cortical Brain Activity

This study examines the links between human perceptions, cognitive biases and neural processing of symmetrical stimuli. While preferences for symmetry have largely been examined in the context of disorders such as obsessive-compulsive disorder and autism spectrum disorders, we examine various these phenomena in non-clinical subjects and suggest that such preferences are distributed throughout the typical population as part of our cognitive and neural architecture. In Experiment 1, 82 young adults reported on the frequency of their obsessive-compulsive spectrum behaviors. Subjects also performed an emotional Stroop or variant of an Implicit Association Task (the OC-CIT) developed to assess cognitive biases for symmetry. Data not only reveal that subjects evidence a cognitive conflict when asked to match images of positive affect with asymmetrical stimuli, and disgust with symmetry, but also that their slowed reaction times when asked to do so were predicted by reports of OC behavior, particularly checking behavior. In Experiment 2, 26 participants were administered an oddball Event-Related Potential task specifically designed to assess sensitivity to symmetry as well as the OC-CIT. These data revealed that reaction times on the OC-CIT were strongly predicted by frontal electrode sites indicating faster processing of an asymmetrical stimulus (unparallel lines) relative to a symmetrical stimulus (parallel lines). The results point to an overall cognitive bias linking disgust with asymmetry and suggest that such cognitive biases are reflected in neural responses to symmetrical/asymmetrical stimuli.

Blood flow and oxygen delivery to human brain during functional activity: Theoretical modeling and experimental data

Coupling of cerebral blood flow (CBF) and cerebral metabolic rate for oxygen (CMRO2) in physiologically activated brain states remains the subject of debates. Recently it was suggested that CBF is tightly coupled to oxidative metabolism in a nonlinear fashion. As part of this hypothesis, mathematical models of oxygen delivery to the brain have been described in which disproportionately large increases in CBF are necessary to sustain even small increases in CMRO2 during activation. We have explored the coupling of CBF and oxygen delivery by using two complementary methods. First, a more complex mathematical model was tested that differs from those recently described in that no assumptions were made regarding tissue oxygen level. Second, [15O] water CBF positron emission tomography (PET) studies in nine healthy subjects were conducted during states of visual activation and hypoxia to examine the relationship of CBF and oxygen delivery. In contrast to previous reports, our model showed adequate tissue levels of oxygen could be maintained without the need for increased CBF or oxygen delivery. Similarly, the PET studies demonstrated that the regional increase in CBF during visual activation was not affected by hypoxia. These findings strongly indicate that the increase in CBF associated with physiological activation is regulated by factors other than local requirements in oxygen.

The role of oscillatory brain activity in object processing and figure-ground segmentation in human vision

The perception of an object as a single entity within a visual scene requires that its features are bound together and segregated from the background and/or other objects. Here, we used magnetoencephalography (MEG) to assess the hypothesis that coherent percepts may arise from the synchronized high frequency (gamma) activity between neurons that code features of the same object. We also assessed the role of low frequency (alpha, beta) activity in object processing. The target stimulus (i.e. object) was a small patch of a concentric grating of 3c/°, viewed eccentrically. The background stimulus was either a blank field or a concentric grating of 3c/° periodicity, viewed centrally. With patterned backgrounds, the target stimulus emerged--through rotation about its own centre--as a circular subsection of the background. Data were acquired using a 275-channel whole-head MEG system and analyzed using Synthetic Aperture Magnetometry (SAM), which allows one to generate images of task-related cortical oscillatory power changes within specific frequency bands. Significant oscillatory activity across a broad range of frequencies was evident at the V1/V2 border, and subsequent analyses were based on a virtual electrode at this location. When the target was presented in isolation, we observed that: (i) contralateral stimulation yielded a sustained power increase in gamma activity; and (ii) both contra- and ipsilateral stimulation yielded near identical transient power changes in alpha (and beta) activity. When the target was presented against a patterned background, we observed that: (i) contralateral stimulation yielded an increase in high-gamma (>55 Hz) power together with a decrease in low-gamma (40-55 Hz) power; and (ii) both contra- and ipsilateral stimulation yielded a transient decrease in alpha (and beta) activity, though the reduction tended to be greatest for contralateral stimulation. The opposing power changes across different regions of the gamma spectrum with 'figure/ground' stimulation suggest a possible dual role for gamma rhythms in visual object coding, and provide general support of the binding-by-synchronization hypothesis. As the power changes in alpha and beta activity were largely independent of the spatial location of the target, however, we conclude that their role in object processing may relate principally to changes in visual attention.

Improved sensorimotor adaptation after exhaustive exercise is accompanied by altered brain activity

Acute exercise has been shown to exhibit different effects on human sensorimotor behavior; however, the causes and mechanisms of the responses are often not clear. The primary aim of the present study was to determine the effects of incremental running until exhaustion on sensorimotor performance and adaptation in a tracking task. Subjects were randomly assigned to a running group (RG), a tracking group (TG), or a running followed by tracking group (RTG), with 10 subjects assigned to each group. Treadmill running velocity was initially set at 2.0 m s− 1, increasing by 0.5 m s− 1 every 5 min until exhaustion. Tracking consisted of 35 episodes (each 40 s) where the subjects' task was to track a visual target on a computer screen while the visual feedback was veridical (performance) or left-right reversed (adaptation). Resting electroencephalographic (EEG) activity was recorded before and after each experimental condition (running, tracking, rest). Tracking performance and the final amount of adaptation did not differ between groups. However, task adaptation was significantly faster in RTG compared to TG. In addition, increased alpha and beta power were observed following tracking in TG but not RTG although exhaustive running failed to induce significant changes in these frequency bands. Our results suggest that exhaustive running can facilitate adaptation processes in a manual tracking task. Attenuated cortical activation following tracking in the exercise condition was interpreted to indicate cortical efficiency and exercise-induced facilitation of selective central processes during actual task demands.

Brain activity during the encoding, retention, and retrieval of stimulus representations

Studies of delayed nonmatching-to-sample (DNMS) performance following lesions of the monkey cortex have revealed a critical circuit of brain regions involved in forming memories and retaining and retrieving stimulus representations. Using event-related functional magnetic resonance imaging (fMRI), we measured brain activity in 10 healthy human participants during performance of a trial-unique visual DNMS task using novel barcode stimuli. The event-related design enabled the identification of activity during the different phases of the task (encoding, retention, and retrieval). Several brain regions identified by monkey studies as being important for successful DNMS performance showed selective activity during the different phases, including the mediodorsal thalamic nucleus (encoding), ventrolateral prefrontal cortex (retention), and perirhinal cortex (retrieval). Regions showing sustained activity within trials included the ventromedial and dorsal prefrontal cortices and occipital cortex. The present study shows the utility of investigating performance on tasks derived from animal models to assist in the identification of brain regions involved in human recognition memory.

Social perception and cognition : processing of gestures, postures and facial expressions in the human brain

Humans are a social species with the internal capability to process social information from other humans. To understand others behavior and to react accordingly, it is necessary to infer their internal states, emotions and aims, which are conveyed by subtle nonverbal bodily cues such as postures, gestures, and facial expressions. This thesis investigates the brain functions underlying the processing of such social information. Studies I and II of this thesis explore the neural basis of perceiving pain from another person s facial expressions by means of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG). In Study I, observing another s facial expression of pain activated the affective pain system (previously associated with self-experienced pain) in accordance with the intensity of the observed expression. The strength of the response in anterior insula was also linked to the observer s empathic abilities. The cortical processing of facial pain expressions advanced from the visual to temporal-lobe areas at similar latencies (around 300 500 ms) to those previously shown for emotional expressions such as fear or disgust. Study III shows that perceiving a yawning face is associated with middle and posterior STS activity, and the contagiousness of a yawn correlates negatively with amygdalar activity. Study IV explored the brain correlates of interpreting social interaction between two members of the same species, in this case human and canine. Observing interaction engaged brain activity in very similar manner for both species. Moreover, the body and object sensitive brain areas of dog experts differentiated interaction from noninteraction in both humans and dogs whereas in the control subjects, similar differentiation occurred only for humans. Finally, Study V shows the engagement of the brain area associated with biological motion when exposed to the sounds produced by a single human being walking. However, more complex pattern of activation, with the walking sounds of several persons, suggests that as the social situation becomes more complex so does the brain response. Taken together, these studies demonstrate the roles of distinct cortical and subcortical brain regions in the perception and sharing of others internal states via facial and bodily gestures, and the connection of brain responses to behavioral attributes.

Human brain mechanisms of auditory and audiovisual selective attention

Selective attention refers to the process in which certain information is actively selected for conscious processing, while other information is ignored. The aim of the present studies was to investigate the human brain mechanisms of auditory and audiovisual selective attention with functional magnetic resonance imaging (fMRI), electroencephalography (EEG) and magnetoencephalography (MEG). The main focus was on attention-related processing in the auditory cortex. It was found that selective attention to sounds strongly enhances auditory cortex activity associated with processing the sounds. In addition, the amplitude of this attention-related modulation was shown to increase with the presentation rate of attended sounds. Attention to the pitch of sounds and to their location appeared to enhance activity in overlapping auditory-cortex regions. However, attention to location produced stronger activity than attention to pitch in the temporo-parietal junction and frontal cortical regions. In addition, a study on bimodal attentional selection found stronger audiovisual than auditory or visual attention-related modulations in the auditory cortex. These results were discussed in light of Näätänen s attentional-trace theory and other research concerning the brain mechanisms of selective attention.

Human brain networks of auditory attention and working memory

This thesis examines brain networks involved in auditory attention and auditory working memory using measures of task performance, brain activity, and neuroanatomical connectivity. Auditory orienting and maintenance of attention were compared with visual orienting and maintenance of attention, and top-down controlled attention was compared to bottom-up triggered attention in audition. Moreover, the effects of cognitive load on performance and brain activity were studied using an auditory working memory task. Corbetta and Shulman s (2002) model of visual attention suggests that what is known as the dorsal attention system (intraparietal sulcus/superior parietal lobule, IPS/SPL and frontal eye field, FEF) is involved in the control of top-down controlled attention, whereas what is known as the ventral attention system (temporo-parietal junction, TPJ and areas of the inferior/middle frontal gyrus, IFG/MFG) is involved in bottom-up triggered attention. The present results show that top-down controlled auditory attention also activates IPS/SPL and FEF. Furthermore, in audition, TPJ and IFG/MFG were activated not only by bottom-up triggered attention, but also by top-down controlled attention. In addition, the posterior cerebellum and thalamus were activated by top-down controlled attention shifts and the ventromedial prefrontal cortex (VMPFC) was activated by to-be-ignored, but attention-catching salient changes in auditory input streams. VMPFC may be involved in the evaluation of environmental events causing the bottom-up triggered engagement of attention. Auditory working memory activated a brain network that largely overlapped with the one activated by top-down controlled attention. The present results also provide further evidence of the role of the cerebellum in cognitive processing: During auditory working memory tasks, both activity in the posterior cerebellum (the crus I/II) and reaction speed increased when the cognitive load increased. Based on the present results and earlier theories on the role of the cerebellum in cognitive processing, the function of the posterior cerebellum in cognitive tasks may be related to the optimization of response speed.

Cooperative game play with avatars and agents: Differences in brain activity and the experience of play

The current study sought to identify the impact of whether teammates in a cooperative videogame were controlled by other humans (avatars) or by the game (agents). The impact on player experience was explored through both subjective questionnaire measures and brain wave activity measurement (electroencephalography). Play with human teammates was associated with a greater sense of relatedness, but less competence and flow than play with other computer-controlled teammates. In terms of brain activity, play with human teammates was associated with greater activity in the alpha, theta and beta power bands than play with computer-controlled teammates. Overall, the results suggest that play with human teammates involves greater cognitive activity in terms of 'mentalising' than play with computer-controlled teammates. Additionally, the associations between subjective measures of player experience and brain activity are described. Limitations of the current study are identified and key directions for future research are discussed.

Encoding of marginal utility across time in the human brain.

Marginal utility theory prescribes the relationship between the objective property of the magnitude of rewards and their subjective value. Despite its pervasive influence, however, there is remarkably little direct empirical evidence for such a theory of value, let alone of its neurobiological basis. We show that human preferences in an intertemporal choice task are best described by a model that integrates marginally diminishing utility with temporal discounting. Using functional magnetic resonance imaging, we show that activity in the dorsal striatum encodes both the marginal utility of rewards, over and above that which can be described by their magnitude alone, and the discounting associated with increasing time. In addition, our data show that dorsal striatum may be involved in integrating subjective valuation systems inherent to time and magnitude, thereby providing an overall metric of value used to guide choice behavior. Furthermore, during choice, we show that anterior cingulate activity correlates with the degree of difficulty associated with dissonance between value and time. Our data support an integrative architecture for decision making, revealing the neural representation of distinct subcomponents of value that may contribute to impulsivity and decisiveness.

Frames, biases, and rational decision-making in the human brain.

Human choices are remarkably susceptible to the manner in which options are presented. This so-called "framing effect" represents a striking violation of standard economic accounts of human rationality, although its underlying neurobiology is not understood. We found that the framing effect was specifically associated with amygdala activity, suggesting a key role for an emotional system in mediating decision biases. Moreover, across individuals, orbital and medial prefrontal cortex activity predicted a reduced susceptibility to the framing effect. This finding highlights the importance of incorporating emotional processes within models of human choice and suggests how the brain may modulate the effect of these biasing influences to approximate rationality.

Detection of cathepsin S cysteine protease in human brain tumour microdialysates in vivo.

Microdialysis enables the chemistry of extracellular ?uid in body tissues to be measured. Extracellular proteases such as the cysteine protease, cathepsin S (CatS), are thought to facilitate astrocytoma invasion. Microdialysates obtained from human brain tumoursin vivo were subjected to cathepsin S activity and ELISA assays. Cathepsin S ELISA expression was detected in ?ve out of 10 tumour microdialysates, while activity was detected in ?ve out of 11 tumour microdialysates. Cathepsin S expression was also detected in microdialysate from the normal brain control although no activity was found in the same sample. While some re?nements to the technique are necessary, the authors demonstrate the feasibility and safety of microdialysis in human astrocytomasin vivo. Characterisation of the extracellular environment of brain tumoursin vivo using microdialysis may be a useful tool to identify the protease pro?le of brain tumours.